Climate Audit

Judith Curry

Reply to Dave Dardinger (on the Emanuel thread:)

The issue of greenhouse warming and increasing hurricane activity is a hypothesis (see our BAMS article that was discussed on a previous thread). I have argued that the greenhouse warming argument is the best available explanation for the increase in global hurricane intensity and the increase in total number of North Atlantic tropical cyclones (the magnitude of the increase associated with the greenhouse warming is the main issue of contention, rather than the existence of the increase).

For a hypothesis to be elevated to a theory, it must pass 3 tests (discussed in the BAMS article):
1. Survive scrutiny and debate, including attacks by skeptics.
2. Be the best existing explanation (physical and statistical) for the particular phenomenon.
3. Demonstrate predictive capability.

As concluded in the BAMS article, this hypothesis is not yet ready to be elevated to a theory owing to uncertainties in the data and the need for further observations with continued warming to assess whether this hypothesis has any predictive value. Statistical analysis is a key element, but not the only element. The short data records and uncertainties (which are very difficult to quantify) are a substantial challenge to our field. The data issues in combination with the complexity of the climate system make this an extremely challenging scientific problem.

In the past year and a half, there have been many papers published on this topic (most of which are referenced by the Holland/Webster paper). However analyses made this far have not been sufficiently convincing to reject any of the subhypotheses in the causal chain that we propose that links an increase in hurricane intensity and global warming.

Dave’s analogy re the hammer and nail is apt. Until the Emanuel and Webster et al. papers were published, the main hammer around was the natural variability one. Now we have a new hammer on the scene. As stated in my BAMS article:

” Investigative scientists bring prior experience, understanding and prejudices to their investigation. Amongst a group of investigators, if these priors are so different that the investigators genuinely reach divergent conclusions from the available sparse data, then none of the hypotheses can be raised to the status of a theory.”

So we are talking about a hypothesis here, that has not yet been elevated to a theory.

Steve McIntyre

Davis 1976 is online here . bender, you’re right about this – it’s annoying to see these sorts of “trade” references rather than proper statistical authorities, although at least they didn’t cite themselves as statistical authorities a la Wahl and Ammann.

bender

To finish #1:
There’s a BIG difference between p lt 0.05 and p lt 0.0001. Ask Martin Juckes.

(Why does neither “&lt” nor the lt symbol work anymore?)

Judith Curry

Bender,

I’ve emailed a data set to Steve M. No guarantees that this is exactly what Holland used, I am on travel and don’t have full access to my data sets. Also, a reminder that a few months ago there was a hurricane data compilation thread where these data were assembled.

With regards to the SST/TC correlations. There is a negative correlation associated with El Nino; this needs to be filtered out in some way to examine the correlation associated with the longer time scales. The optimum way to do this while still maintaining statistical significance has perhaps not yet been accomplished, have a go at it.

John A

Here’s Holland and Webster (2006) Figure 1:

Figure 1. Tropical cyclone occurrence (blue points indicate annual totals and the black line is a 9-y running mean) in the North Atlantic together with East Atlantic SST anomalies for the hurricane season (red line) from 1855-2005. TC1, 2 and 3 refer to climate regimes discussed in the text.

Forgive me for a naive interpretation of this, but if there’s an opportunity here for a spurious correlation then other scientists have not put that chance down.

Dave B

Dr Curry, you wrote:

“There is a negative correlation associated with El Nino; this needs to be filtered out in some way to examine the correlation associated with the longer time scales. The optimum way to do this while still maintaining statistical significance has perhaps not yet been accomplished, have a go at it.”

please forgive me as a statistical layperson, but shouldn’t one first “filter out” the negative correlation with el nino, THEN determine whether one still has statistical significance? rather than presume one will “still maintain statistical significance”?

thank you for considering this.

Steve McIntyre

#9. bender – I’ve browsed through Davis (1976). ON a first pass, it sure seems like a strange choice of statistical authority for what they are doing. IT would definitely be worthwhile reconciling what Davis 1976 actually recommended against what H&W actually did.

Gerald Machnee

Re #2 & @11
**I have argued that the greenhouse warming argument is the best available explanation for the increase in global hurricane intensity and the increase in total number of North Atlantic tropical cyclones (the magnitude of the increase associated with the greenhouse warming is the main issue of contention, rather than the existence of the increase).**
I have 4 questions:
1) Did the SST in the North Atlantic increase or decrease from 2005 to 2006?
2) What was the change in temperature?
3) Was the change caused by AGW?
4) What is the proof?

Judith Curry

Jae, in the context of the causal chain that we pose, there are two separate links:

1. increased SST causes increased global hurricane intensity and increased number of NATL tropical cyclones

2. the increase in SST since 1970 is predominantly attributed to greenhouse warming (climate model simulations).

Looking at the entire SST record since 1854 (which is in the xcel spreadsheet i sent to steve), the SST variations over that time period can be attributed to a combination of solar forcing, aerosol forcing, greenhouse forcing, and natural internal variability such as the AMO. So there is no automatic attribution of all warming to greenhouse gases. The proportion of warming since 1970 attributable to greenhouse gases can be debated, but no credible scientist suggests that there is NO temperature increase from the increases in greenhouse gases.

The Holland/Webster paper addresses link #1. It does not explicitly address link #2, although they refer to other papers that address this link

jae

OK, Dr. Curry; can’t disagree with that. Thanks for the clarification.

Judith Curry

Bender, I agree with your statement in #18. In the BAMS article, i discussed the values gap between the scientist and the policy maker. Alarmism doesn’t help the situation at all, but it isn’t as bad as completely ignoring the issue either. How to appropriately frame the scientific issues in a way that addresses what people really care about in a way that is scientifically credible is the challenge. The middlemen between the scientists and public (the media, bloggers, congressional committees) have not been helping. what is needed is clarification of values (economic and moral issues) surrounding this topic, and some precautionary planning to assess what the options are and the costs. Then, where opportunity meets value, we can develop some sensible policies.

in case you didn’t catch it, integrityofscience posted some talks on this subject at AGU, addressing these issues from a scientists point of view (I liked these talks better than the talks on dealing with the media) see http://scienceblogs.com/integrityofscience/

Steve Bloom

Re #20: Sorry, Dane, but professional geologists working for the fossil fuel industry aren’t credible scientists. One, they are not qualified (fuds and pubs are rare), two, on the rare occasions any of them do publish (outside of trade pubs) it seems to be under questionable circumstances (and with often ludicrous “science”) such as with those two Russian characters from USC, and three, they made a collective laughingstock of themselves when they gave that award to Crichton. But by all means try to prove me wrong: Do some research and publish on the SST-global warming connection. Heck, just do an “audit” of the papers that demonstrate the relationship and post it here. BTW, nobody is under the illusion that the fossil fuel industry and its employees don’t understand the debate.

bender

You might find it annoying; however it is not Dr Curry’s personal verdict, but prevailing professional/expert opinion. Like it or not it is a fact that proponents of A=0 have little or no credibility among the scientific community at large. Agnosticism, ok, somewhat acceptable. A LT 50% Ok, maybe. But A=0, untenable. If you dissent with expert-opinion-at-large, spell out your case.

I’m tempted to admonish: don’t shoot the messenger. Except, of course, that’s sort of how alarmism works: the most direct way to stop the spread of the alarming message is to terminate the transmission process at the source. (Alternatively, you could damp the impact of the message at the receiving end by making sure the receiver is able to put the alarmist message in proper context. Pretty challenging though.)

bender

Re #21
Again, a subsample of 20 CA skeptics pegs A at 20%, not 0%, as many warmers would like to assert.

bender

Has anyone had any luck working out the properties of this bizarre test?

First things first. Has anyone had any luck identifying the actual test extracted from Davis (1976)? We have to identify it before we can characterize it.

TAC

Following up on #23 and the statement that “the standard trend tests will be hugely biased in the direction of finding significance” (unless corrected), it seems that, without the correction for serial correlation, the probability of rejecting H0 when we have 156 observations of white noise is about 50 percent.

J. Curry

to the skeptics: it is pretty difficult to argue ZERO increase in surface temperature for 30% or 100% increase in a major greenhouse gas like CO2. You may not agree with climate model attribution studies for the 20th century, or their projections for the 21st century, but to say ZERO increase is pretty indefensible. Among the most extreme AGW skeptics (that actually publish on these topics), Bill Gray anticipates 0.3C increase for doubling CO2. A more moderate skeptic (Lindzen) anticipates a 1C increase (which is just shy of the 1.5C increase that comprises the IPCC lower limit on their range of expected increase). The real debate (scientific and policy) is 1C (do we care?) vs 5C (yeah we definitely care). Do the 20% CA skeptics say ZERO increase from doubling CO2, or do they say yes some increase but we have no idea how much and we aren’t convinced by the allegedly “alarmist” values of order 3C or greater?

J. Curry

re #18 Bender, I agree. (here is another try to get my “flagged” message through). In my BAMS article, we discussed the values gap between scientists and policy makers. which is worse, alarmism or ignoring the issue all together? hard to decide which is worse, the are both wrong, but those seem to be the choices we are presented with. How to appropriately frame the scientific issues in a way that addresses what people really care about in a way that is scientifically credible is the challenge. The middlemen (the media, bloggers, aadvocay groups) have not been helping.

What we need (instead of alarmism vs ignoring) is clarification of values (economic and moral issues) surrounding this topic, and some precautionary planning to assess the options and their costs and benefits. We can then develop some sensible policies where opportunity meets values. Instead, we fight this silly war over the science that is admittedly uncertain.

in case you didn’t catch it, integrityofscience (won’t try to post the link, that may be why this message has been censored?) posted some talks on this subject at AGU, addressing these issues from the perspective of scientists

J. Curry

John S: not faith, but a hypothesis. Better observations are needed (reanalysis of existing data, a few more years in the time series), continued examination of our theories, and continued improvement to our models will eventually resolve this issue. Much work to be done. But the hypothesis of greenhouse warming contributing to an increase in hurricane activity is presently supported by the observations, the theory, and models. They all agree on the sign of the relationship. They disagree on the magnitude of the relationship, and whether any increase can actually be detected in a significant way with the data that we do have. So again, the issue is not so much whether we would expect global hurricane intensity to increase with greenhouse warming, but how large the increase might be. The intriguing thing about the North Atlantic data set is that the quality and quantity of the data may be sufficient to quantify this relationship in a credible way, that is the focus of activity right now. The correlation of SST and tropical cyclone counts is a key link, the statistics of this needs to be sorted out. I’m sure Holland’s analysis (and Emanuel’s) is not the last word on this. I look forward to CA’s take on this (i’ve also asked Carlos Hoyos for his opinion on how to address this)

jae

Dr. Curry: I hope you have read (and studied) this paper. It appears to me that anyone who posits highly significant amounts of warming from GHGs has to be able to “tackle” the basic logic and physical explanations presented therein. Modelers should especially pay attention to it, since it offers a much better approach than computer modeling for estimating the effects of GHGs (IMO, of course).

Dane

Bender and Dr. Curry,

Most people ie scientific skeptics in geologic and environmental consulting don’t have time to post on CA, or even know CA exists for that matter. Just because benders little survey says 0%, means nothing to me. It is also irrelevent that we do not publish in the field for the purpose of this discussion. What is important is our detailed knowlege of earth processes, not just climate science, that allow us to understand the current data and compare it to older examples from the geologic record. When one does this, one finds Co2 levels were much higher in the past, yet climate continued to fluctuate radically from warm to cold. Lag times in ice cores is another problem I have with correlating Co2 content in the atmosphere and tempurature averages on earth. They don’t match. Apparently this doesn’t bother bender or Dr Curry, but as an environmentalist and concerned scientist, it sure bothers me.

I also am bothered by the lack of time and precision in the limited real world data we do have. As a consultant who deals with government regulatory agencies on a regualr basis, as well as a former regulator myself, I am also fully aware that data can be “Massaged”, smoothed, whatever you want to call it, statistically manipulated, to give one the result one desires.

Bender please find me one article showing proof of a link between Co2 concentrations in earths atmosphere and earths temperature? No models please, real data. The ice cores have all been shot down, what else do you have?

I understand the earth is a complex adaptive system, NOT a greenhouse. I also see potential benifits in earth becoming warmer, many more benifits than from a colder earth. I think we all can agree that the climate WILL NOT stay the same, regardless of what we do. Dr. Curry, am I to believe that you would like the earths climate to just stay the same? You know perfectly well that will never happen. That is the feeling I get from proponents of AGW.

welikerocks

#34 Dr. Curry,
Thanks for your reply.

the physics of radiative transfer indicate the direct forcing for doubling CO2 is 0.4C increase in surface temperature.

I understand all the models. And I understand that is still one. It is Earth simulated in a lab. That is, physics with a lid on it and not a real world.

And I believe most people everywhere are willing and ready any time to change engines and fuels for reasons besides the climate- so your “What we need (instead of alarmism vs ignoring) is clarification of values (economic and moral issues) surrounding this topic” isnt what I think we need here from a scientist. Truth, fact-and politics out of the lab and heads of scientists who run in circles of acadamia and “the media” is what we need.

Can you get sued for being wrong as working scientists do in the real world?

bender

Re #37
“bender’s little survey” (n=20) said A ~ 20% ± 10% (standard error), much like Lindzen. The purpose of this survey was not to establish any kind of consensus, dear friend. It was merely to point out that A=0 is not the “skeptic position” (if there is such a thing). It was a counterpoint to some turkey who was suggesting that was the skeptic position.

No models please

Why not? Do you dismiss all models as a matter of principle? It’s one thing to argue that models X,Y,Z are flawed. Quite another to dismiss them all as a matter of principle. You aren’t that twisted, are you?

Ken Fritsch

Jim Kossin presented the linked presentation at the AMS Environmental Science Seminar Series October 20, 2006 where as I recall Holland also reviewed his paper under discussion here. I was curious whether Kossin’s paper is in publication/review at this point and how it is being received.

It would apparently put much of the previously uncorrected tropical cyclone data outside the NATL and Eastern Pacific into question as it shows the mean intensity of storms diverging from that reported the further one goes back into time.

Summary:

The trends in the Atlantic and East Pacific intensity records are well supported by our new record. Upward in the Atlantic. Downward in the East Pacific. No upward trends were found in the West Pacific, Northern and Southern Indian, and South Pacific oceans. The vast majority (85%) of global hurricane activity takes place in these basins. Similar warming trends are found everywhere in the tropics. Why is the Atlantic behaving so differently? If the data are not good enough to accurately measure long-term hurricane behavior, then our path to understanding how hurricanes will change in a warming world must be through better physical understanding. This is our present research challenge.

Click to access Kossin102006.pdf

Landsea papers on the quality of tropical cyclone data were reviewed on CA in the thread below.

http://www.climateaudit.org/?p=864

jae

Dane: You have friends here, you know….You seem to misunderstand this site. Read some of the threads.

Dane

Bender,

Why attack and call me twisted? What do you gain from that? In my scientific experience models. although useful tools in many situations, are usually flawed and unreliable at best. They are by no means the standard in good science. As a geoscientist I want to see REAL data, why do you have a problem with that? If Co2 was such a major player in global climate (as say Malinkavitch cycles are), you would think that it would leave its signature somewhere on earth, where we can find it and study it. In 1991, models predicted we would loose 10,000 troops in Gulf War 1, they were WAY off. Those were excellent models I might add that were perfected in WW2 and again in ground combat operations in Vietnam. Am I foolish enough to belive that something even more complex than modern human ground combat, like Global climate for example, is better understood?

A better question is why do you have so much faith in the models?

Dr. Curry,

I quote “The physics of relating atmospheric composition and radiative transfer is very well understood”. I know this. My point is that those physics are for a model, not the real working earth, which you must agree is far more complex than any model humans have yet developed.

I quote again “You can’t make major changes to the atmospheric greenhouse gases and expect climate to remain unchanged”. actually you can if those gases aren’t as important as you think they are on a real working planet. Again you assume the earth is a greenhouse, I don’t.

You think there is a real risk in the next century or two from GHG, I don’t. I look at all the data, and think people who live in areas that may be affected by future warming will have time to adapt (which will create jobs), and that the risk is exaggerated greatly by both acedemia and especially the mainstream media. It is literally in the news EVERY DAY! article, news peices on local TV, TV shows, jokes, sitcoms etc, the propoganda is endless and the reality is we don’t even know if its happening, then we don’t even know if it will be a bad thing. Again, picture the Littte Ice Age, did Co2 conc. drop? Or during the Medieval Warm period did Co2 increase? What was better for humanity? I would argue warm is far better than cold. Panic about 100 to 200 years from now does nobody any good at all unless your trading futures or in carbon credits. And last, please admit you hurricane data is sparse at best in intensity, distribution, and numbers over the past 150 years. You must realize you are looking at a snapshot of time as far as the real earth goes, geologically speaking. To think you can make policy based on the weak evidence you have is scary, to the point of extremism. Do I think we should continue to study the issue? Of course, it should remain well funded, if for nothing else than to gain the knowledge of how the earth works. Do I want off Oil as our main energy source? Yes, but not due to some fallacy about Co2 and fossil fuels warming the planet. The science so far is weak in my opinion, almost criminal when it comes to the media propaganda and blitz we have seen over the last 10 years ( I began to seriously study the issue in the early to mid 1990’s).

Jim Edwards

#40, 42

Dr. Curry:

I agree wholeheartedly that we shouldn’t be forced into choosing between two antithetical positions for acting on GW – “ignoring” and “alarming.”

I hope that you would also agree that passing zero laws / enacting zero regulation Re: CO2 and other GHGs while funding vigorous research is not the same as “ignoring” GW as a potential problem – when thinking people can agree that there is no compelling evidence demonstrating A in AGW is not just likely more than zero, but actually a demonstrably significant and disturbing factor in climate change.

As long as you and your colleagues are receiving grants of taxpayer dollars, and continue to investigate, the problem is not being “ignored.”

J. Curry

Ken, re Jim Kossin’s work, apparently this has not yet been published (although I believe that papers have been submitted). Hence his work hasn’t quite received the scrutiny yet that it will receive once it has been published. There are two reasons i like his study:
1) he uses an objective analysis technique that does subjectively depend on the analyst (in the way that the Dvorak technique does)
2) he seems personally objective and unbiased on the subject of hurricane trends

His paper seems to demonstrate that the NATL and EPAC intensity data sets that have been used in studies such as Webster et al. are reliable (i.e. his analysis agrees with the standard data sets). However, in the other ocean basins, his analysis disagrees with the conventional analyses. Since his algorithm was trained on the NATL dataset, it is unclear how accurate this algorithm will be in different regions characterized by storms that are on average larger and more intense. The community is currently focused on sorting out the discrepancies in the WPAC data set; WPAC has 40% of the global TCs, and played an important role in both the Emanuel and Webster et al. papers. In addtion to the JTWC dataset (used by Emanuel and Webster), and Kossin’s analysis, several other WPAC data sets are also out there (from Hong Kong and Taiwan), all of them disagreeing with each other (there was a recent EOS article on this). There is some hope that the aircraft reconnaissance flights in the WPAC during 1983-1987 can be used to sort out these discrepancies (note Kossin and JTWC show large disagreements during 1983-1987). Also, Kossin did not explicitly calculate PDI or NCAT45, so exactly what the discrepancy in his dataset with that used by Webster and Emanuel remains unclear.

Bottom line: there have been numerous claims (e.g. landsea and gray) that the global TC data base is no good. I view Kossin’s work to be the first important word on this subject. However, it is far from the last word. The discrepancies among the different data sets need to be sorted out, the accuracy of Kossin’s method needs to be assessed in the different regions, and Kossin’s analysis needs to be extended to the period prior to 1983. Until this is sorted out, the community is focusing on the NATL data (and people should also start looking at EPAC more closely as well.)

p.s. one statistical issue. it seems that he calculated the trends using the 5 year averages, I doubt that the trends from old and new analyses calculated this way are significantly different from each other?

nanny_govt_sucks

…the reality is we don’t even know if its happening, then we don’t even know if it will be a bad thing. … I would argue warm is far better than cold.

Absolutely.

There is much evidence that the planet is benefiting from recent warming. Greening, and poleward-expanded habitats for animals is certainly a good thing when compared to the opposite. Isn’t it possible that just maybe this planet is currently too cold and dry?

And has anyone ever stopped to consider what the concentration of CO2 SHOULD be? It is said that plants virtually starve at 200ppm, and studies show that the vast majority thrive best at around 1000-1200ppm. Shouldn’t we consider that what is best for plants is best for the animals (including humans) that eat those plants?

David Smith

Re #44 One problem I have with HW is the quality of the older data. This is an old problem and covered in detail in the past at CA. It’s hard for me to build up much enthusiasm for the HW analysis when I’m bothered by the data on which it is founded.

To beat this horse once again, I want to add a new ocular exercise, with regards to holes in the data. This will take a minute because I have not consolidated these:

Glance at 1931 , 1932 , 1933 , 1934 , 1935 , 1936 , 1937 , 1938 , 1939 , 1940 , and on to 1945. I think the visual impression is that there are few storms east of 55W. What was happening between 55W and Africa? It’s like a void existed, with few exceptions.

Now, glance at 1995 , 1996 , 1997 , 1998 , 1999 , 2000 , 2001 , 2002 , 2003 , 2004 and 2005 .

The activity east of 55W is widespread.

I would say what has changed (today vs 1930s/40s) is data collection in these remote parts of the ocean, thanks to reconnaissance and especially satellite. In my opinion, some weaker storms in the east Atlantic were missed and some peak strengths were missed. HW may say “regime change” with hotter SST and more activity in the east Atlantic. I think it’s a data collection problem.

welikerocks

J. Curry,

Then certain elements of the media, bloggers and certain advocacy groups (and geologists) attack them for destroying the U.S. economy

And geolgoists? I knew it. I just said in another thread how since the get go, the climatolgists had to discredit the field of geology for their A in AGW.

Scientific research does not translate into policy (which is clear since we have had alot of science but no policy to deal with the issue, at least at the federal issue). Policy is a complex interplay of uncertain science, technologies, economics, politics, and values. Whether there are policy decisions to ignore AGW or to do something about it, surely it is best that at least some scientists engage with the decision makers so the risks of the different policy options are undersood.

I live in California. Need I say more? I am being taxed and policied, fined and regulated, and my children are taught AGW as fact in their school books.

Skeptics need to be skeptical of their skepticism, to insure that you are not overreacting emotionally to attitudes of a few people

No. I am making a opinion, like everyone else here, on the data, the temperature reconstructions and the statisically flawed models THEN not liking the attitude of the scientists who promote these things. I am not as shallow as you assume. I don’t care who the scientist is or what the science is about-only the data matters.

Bender, I think you should lay off Dane and visa versa. You both are misunderstanding each other. Dane said models are useful tools and of course jae needs his models, but the difference is solar scientists aren’t running around proclaiming they know everything by what they see in models. I see a major difference in wording and presentation of ideas here. Climatologists and the powers that be are taking the climate, which does bother, affect, change and run human lives, and they are using these play by play snap shots, or models to control things politically. It’s brilliant propaganda, because every single senerio fits somebody’s fear or grudge or concern doesn’t it? In the meantime, we’ve had record low temperatures where I live and nary a peep in the media about it as unusal. My plants I have had for years and years are freezing. Doesn’t fit the agenda I suppose.

Ken Fritsch

David that was a great review and now I have some puzzlements to post.

Holland and Webster indicate that they used July to September SSTs in the Eastern Atlantic (5N-25N,55W-20W) for correlation with NATL cyclones (that is what the labeled graphs indicated as they reference the Eastern Atlantic). They also give Goldenberg and Shapiro (1996) as a reference for the MDR, the main development region for tropical storms, who in turn would appear to indicate that as bounded by (10N-20N,80W-20W) in the link below and as shown in the graphic below.

Emanuel 2005 used SSTs for (6N-18N,60W-20W) for the month of September only for his correlations of PDI with SST.

My question to you, David, or anyone else willing to take it on: What is the sensitivity of the cyclone activity/intensity to SST to the SST bounds selected and the months of SST data used?

http://iri.columbia.edu/climate/ENSO/globalimpact/TC/Atlantic/windshear.html

bender

I want to see REAL data, why do you have a problem with that?

“Why?” Because, unfortunately, there’s a limit as to what you can learn from statistical analysis of the limited available data. All theings being equal, I agree: data are always preferable to models. Unfortunately good data do not come cheaply or quickly enough. Hence the value of modeling. It’s not either/or. Both need to be pursued simultaneously in proportion to their benefit:cost.

Rocks says “lay off” so I will. I like rocks.

Tim Ball

#55
Thanks David for drawing attention to the data and the changes in coverage, measurement devices and techniques, as well as analysis changes. I raised these issue in #12, as well as the problems of complete prediction failure for 2006 based on the same data sets, but all this was avoided by focussing on definitions of theory and hypothesis. The definitions provided did not resolve the problems I identified with the original definition in #14, but they roiled the water sufficiently to appear like an answer. I am not impressed by attempts to qualify the reliability of the data, especially when there is any subjectivity. Something about silk purses and sows ears.

Ken Fritsch

It is possible to get the press to comprehend scientific points, but it takes time and effort. As scientists and engineers we have not done a very good job of providing resources to the press so that they can get the story right. We need to do a better job of this I find it unlikely that the press corps is going to solve its problem any time soon.

The problem with the press, and the media in general, is that they judge in order to sell their product they have to jolt the public. This is evident from the differences between what one takes away from story headings and story content. It is not confined to scientific articles either. The process has been dumbed down because that is what sells to the current public. There is also the cases of the biases of the writers getting involved. The journalist and/or from whomever they get their orders, I think, know very well what they are doing.

If a scientist judges that the they have been misquoted or misinterpreted, the paper would normally be more than happy to afford them space for doing so and particularly so a competitor in the media. The split personality of a scientist/policy advocate may not be sufficiently disturbed to set an embellishment straight.

David Smith

Judith, first I want to thank you for spending time here today. You help the conversation greatly.

Let me touch on another data problem: here are Otto (2004) , Nicole (2004) and Gamma . The green portion of the tracks are where they were of minimal tropical storm (40 MPH) strength.

(I’d also post the recent 10’th tropical storm of 2006, the one found while reviewing satellite photos, but Unisys has not posted it yet. It lasted all of 18 hours.)

How dinky can a storm get? What are the chances of a ship encountering one like these in olden days and recognizing that it’s a “storm” and not a depression or active wave or squall and reporting it?

These are small, weak storms, mostly at sea. I call them “junk storms” because they junk up the records and are of no significance. Yet they are part of the modern record, especially in the last 10 years. I’ve never catalogued them but my impression is that junk storms like these are not part of the pre-reconaissance record and aren’t common in the early satellite era.

I’ve counted about two junk storms a year since the late 1990s. It’s difficult for me to understand their use in long-term data comparisons.

Willis Eschenbach

Dear Dr. Curry:

First, I applaud your willingness to explain, clarify, and defend your ideas on this site. It is very valuable, and I read your posts quite carefully.

Next, some comments. You say:

The number of NATL tropical cyclones (when filtered for el nino and other short term variability) does show a correlation with SST. Webster has done the calculation for 5 year running means, and the correlation between NATL SST and TC counts from 1910-2005 gives a correlation of 0.78 that is significant using the Mann Kendall statistic (this is a curry/webster paper that is in press, to be published around June 07).

If Steve M, Bender, or Willis can provide any further insights into the statistical significance of this relationship, I would certainly be interested in pondering it and would certainly forward to Holland/Webster.

As has been shown numerous times on this site, and as is widely known, many standard statistical tests (including the Mann-Kendall statistic) are worse than useless for auto-correlated datasets. I say worse than useless, because they show statistical significance where none exists.

Even on white noise, a 5-year running average introduces strong autocorrelation, with a corresponding reduction in degrees of freedom. For a 5 year running average of white noise, N = 101 as in H/W, lag 1 corr = ~ 0.8, effective N = ~ 8.

But using an average of already autocorrelated datasets such as SST is much worse. The 1910-2005 ACR region has inherent lag 1 autocorrelation = 0.56. The lag-1 autocorrelation of a 5-year running average of the ACR temperature is 0.92, with an effective N of only 2 … in other words, any statistical tests such as the Mann-Kendall statistic on such averages are useless.

Second, you ask:

With regards to the SST/TC correlations. There is a negative correlation associated with El Nino; this needs to be filtered out in some way to examine the correlation associated with the longer time scales. The optimum way to do this while still maintaining statistical significance has perhaps not yet been accomplished, have a go at it.

I must admit to being totally astounded by this statement. The methods for adjusting for confounding variables are a well known sub-discipline of statistics, and are taught at the undergraduate level. Perhaps I have misunderstood your question?

If not, the most obvious one is to establish some sort of statistical relationship (linear, power, log-linear, log-log, etc.) between the El Nino and the hurricane datasets. Use the Durbin-Watson statistic of the residuals to distinguish between possible models and select the best one. Then regress the El Nino data on the hurricane dataset using the selected relationship, and subtract out the regression from the hurricane dataset.

w.

J. Curry

Willis, I have no involvement in the H/W paper. I am prepared to accept that it is possible that the statistical analysis in the paper was not optimal. I would be interested in seeing an alternative analysis, and assessing whether what H/W did adversely effects the conclusions drawn from the data set. I will be very surprised if there is no correlation between these two time series. I look forward to any analysis that you, bender, or steve m might do. I will consider your arguments and ask Carlos Hoyos for his opinion since I am not a statistician. I will make sure that I provide Holland with any useful input. The insights that I can provide are on the data and the physics.

J. Curry

Brooks and Ken, the whole issue with the media makes me want to tear my hair out. Re the hurricane and global warming story, one science journalist has taken it on himself to delve deeply into this, and has written a book (due to be published summer 07) called “storm world” , here is the book description from amazon:

One of the leading science journalists and commentators working today, Chris Mooney delves into a red-hot debate in meteorology: whether the increasing ferocity of hurricanes is connected to global warming. In the wake of Katrina, Mooney follows the careers of leading scientists on either side of the argument through the 2006 hurricane season, tracing how the media, special interests, politics, and the weather itself have skewed and amplified what was already a fraught scientific debate. As Mooney puts it: “Scientists, like hurricanes, do extraordinary things at high wind speeds.” Mooney”¢’‚¬?a native of New Orleans”¢’‚¬?has written a fascinating and urgently compelling book that calls into question the great inconvenient truth of our day: Are we responsible for making hurricanes even bigger monsters than they already are?

I have no idea what to expect (although the statement about extraordinary things at high wind speeds makes me a bit nervous). But with all the work that Mooney, a very serious science journalist, put into this, this has to be the best shot at making sense of the implications of this issue. We’ll see.

bender

Re #73
This thread is about the HW manuscript. Let’s try to focus on that. Recapitulations are silly, as the course of discussion is a matter of record.

Re #76

I will be very surprised if there is no correlation between these two time series.

It’s not the magnitude of the correlation coefficient that is the real concern, but its significance level. A correlation can be high but non-significant if there are not many degrees of freedom available for the hypothesis test. AS Wilis points out, this appears to be the case. A more precise analysis will follow, I’m sure.

If I may, Dr. Curry … I think this is the complaint people have about climate science: it’s not about a mere lack of statistical rigor. It’s more fundamental than that. It’s about a perceived generalized failure to be self-critial, in the Feynmanian sense of how science ought best to proceed.

It’s the drive toward self-criticism that should motivate the sceintist to seek robust statistics, not what a reviewer or an Editor demands. Some get the sense that this is lacking, and frankly I’m inclined to agree. I think there is a reason climatologists tend to hold the statisticians off at arms length: they don’t want to hear the bad news. I’m prepared to change my view on this, but it would take a pretty solid rebuttal.

bender

Re #77

Sad, but true. Climate research is NOT like controlled laboratory experiments where you can take detailed measurements and carefully determine and constrain the accuracy and precision of these measurements.

And that is precisely why cautious interpretation is necessary … if you want to maintain scientific credibility.

[I am not a climatologist, but I am sympathetic, because the very same problems plague the field of ecology. I wish it were not so difficult to determine the probability of species extinctions under climate change. Alas, it is nigh impossible except for the very, very best-studied systems. (Polar bears not being one of them.)]

bender

Re #83
This is your answer as to why Gore gets a standing O at AGU. Not because the room was full of believers, but because scientists are generally tired of being marginalized by an elected leadership that doesn’t seem to want to listen.

Paul Biggs

Judith Curry should be commended for being involved in the climate debate – far too few working climate scientists are involved in communicating their informed views to the public and wider scientific community. That said, CO2 driven warming/cooling is not the only theory available to explain climate change accross all time scales, including the past few decades. Published/working scientist Nir Shaviv, not funded by big oil or big tofu, gives an objective overview here:

http://www.sciencebits.com/CO2orSolar

Climate sensitivity:

http://www.sciencebits.com/OnClimateSensitivity

Click to access 2004JA010866.pdf

http://www.sciencebits.com/IPCCbias

Much published/working climate scientist Roger Pielke Sr is a good source for papers on land use change being at least as big a human climate influence as CO2, and poor siting of temperature stations which contribute to the flawed ‘global average surface temperature’ metric.

TAC

Judith, I would be interested in hearing Hoyos’s response to Willis’s comment (#74). What concerns me here, and elsewhere, is that the statistical methods often employed in climate science seem inappropriate given the widely recognized characteristics of climate processes. For example, no one argues with your statement (#45) that “climate varies on many time scales, associated with external forcing and natural internal variability,” yet you glance at H&W and see use of a statistical test — which is a proof by contradiction — assuming that climate data (adjusted in peculiar ways) correspond to an AR(1) process. Needless to say, statistical significance is meaningless if the null hypothesis fails to represent the “untreated” system.

To be absolutely clear, here’s a silly example: Let H0 be: “All cars are blue and there’s no trend in hurricanes.” Now we go out and observe a red car, which means we reject H0 and conclude ( 😉 ) that there is a trend in hurricanes. QED.

Is this even remotely relevant? I think it is. Modify H0 by replacing “All cars are blue” with an equally bogus statement like “Natural variability is white noise (or even AR(1)).” QED.

Does it matter? As I noted in #27 and #32, the type 1 error rate — the true probability of incorrectly concluding that there is a significant trend based on a nominal 5% test — can easily go above 50 percent.

J. Curry

Willis, Bender, TAC,

I absolutely agree that rigor in statistical analysis is desired. There are two factors that contribute to a perceived lack of rigor in statistical analysis used by climate scientists. The first one (which you will accept as obvious) is that many climate researchers have at best rudimentary training in statistical analysis. The second one (which you need to ponder) is that statistical analysis alone (and obsessing about the details of confidence intervals) doesn’t get our field very far. It is the combination of statistics and physics that move the field forward. When we a have a physical reason for expecting a relationship to be significant (theories and laws, even), then details of statistical significance are less relevant. Simply because we have a data record of insufficient length or accuracy for statistical significance, this does not mean that we should not proceed forward with exploring or using the relationship. Then there is an interplay between the two factors, where climate scientists don’t take the issue of statistical significance as seriously as they should in situations where it is truly important.

For the issue at hand, e.g. the correlation of SST and NATL TC counts, we don’t have a physical explanation and the issue of statistical significance is relatively important. Hence, I look forward to the results of your analysis. Even if the correlation turns out not to be statistically significant, scientists will use the relationship to further explore the scientific issues and to test to see if the relationship has any predictive capability.

welikerocks

There are more papers on Atalntic hurricanes listed here on a page of the AGU website.

First on the list is a paper by a Holland also, but I don’t think it’s the same person.

“A decomposition of the North Atlantic hurricane energy dissipation index and the mechanisms contributing to its increase since 1970”

* Holland, C L (cholland@utig.ig.utexas.edu) , University of Texas, Institute for Geophysics, 4412 Spicewood Springs Rd, #600, Austin, TX 78759, United States
Scott, R B (rscott@utig.ig.utexas.edu) , University of Texas, Institute for Geophysics, 4412 Spicewood Springs Rd, #600, Austin, TX 78759, United States

J. Curry

David and Ken, the issue of the SST averaging region is an important one. Peter Webster made a presentation at AGU (I think Steve M mentioned it somewhere) about the changing character of the tropical warm pools (not just temperature increase but area increase/change). It may also be that the MDR region changes with time. For the longer time periods, given the low resolution of the observations, it may be best to look at the SST of the entire tropical atlantic.

UC

#90

The second one (which you need to ponder) is that statistical analysis alone (and obsessing about the details of confidence intervals) doesn’t get our field very far.

You are right, need to ponder this. Specially that obsessing about the details of confidence intervals part. Something related to MBH99? We won’t get far in climate science if we do it right? How far the field must go?

Jeff Weffer

Judith Curry brought up the negative correlation with the ENSO.

I think if a person looks closely into this, you will find a strong correlation of the ENSO with TSs in the Atlantic which overrides the Atlantic SSTs. You might also find that average global temperature changes are closely correlated with the ENSO as well. You might also find that the ENSO shows no correlation whatsoever with CO2 levels in the atmosphere.

1997-98, near-record El Nino, high TS counts, highest global temperature.

2005, weak La Nina, record TS counts, lower global temperature (taking into account the slanting of the data by Hansen).

2006, stronger El Nino (still going strong), near record low TSs, lower global temperature (World Meteorological Association beats Hansen to the punch this year and declares 2006 as the sixth highest year – Hansen would have made it the highest if he would have got to the media sooner.)

The problem is that the ENSO varies throughout the year while the Atlantic TSs are limited to a specific season which makes the statistical analysis complicated. Since most climate researchers are concerned with proving/slanting the AGW case and are not particularly good statisticians, they have botched up the link.

http://www.cdc.noaa.gov/people/klaus.wolter/MEI/

http://en.wikipedia.org/wiki/Image:NOAA_ACE_index_1950-2004_RGB.svg

bender

Rocks et al, the “war on science” is real, although I agree the label is hyperbolous. Fact is a large number of government science programs were terminated prematurely and/or downsized in order to pay for the “war on terror”. The negative correlation is direct, and that’s where the hyperbolous phrase comes from. Ask any scientist about their grant writing experiences in the 2001-2002 period; they will tell you the same story. And since then, look at the (relative) stagnation in American universities, compared to the demographic renewal going in in every other developed country in the world. Broad brush at the national scale, and every thing looks fine … on the surface. But go talk to the profs on campus and they will generally agree with Dr Curry: the universities have been neglected and are overdue. It’s not just AGW climate scientists we’re talking about, but all departments, all parts of the spectrum. It’s sad. We used to be the best of the best. But it’s been slipping away.

Back to stats …

fFreddy

Re #91, J. Curry
And please don’t refer me to this Mooney fellow. His reaction to the Wegman report concluded :

And make no mistake: Despite the new fireworks, that big picture remains unaltered. Whether the “hockey stick” is right, wrong, or irrelevant, the underlying message on global warming is that we’re causing it. Period. End of story.

So he either doesn’t understand the issues, or else doesn’t care. So I doubt that he is worth taking seriously.

jae

59: Dr. Curry, I agree with you, in general. I guess I was reacting to some of the plans for high taxes on fossil fuels, which I disagree with. That’s a ploy to make alternate forms of energy SEEM to be economically feasible. Such taxes are inflationary and can wreak havoc on the economy. And they put much more burden on the poor than on the wealthy. And I doubt that they would not have any measureable effect on CO2 levels, especially if China and India did not participate. And what will all this tax money be used for? I’m with Bjorn Lomborg’s views in the Skeptical Environmentalist.

EP

There are two wars on terror: the one against Islamists and the second against spurious scientific results that try to alarm people.

The US seems quite capable of winning Noble prizes in science; contrast with the UK’s decline. And this is a nation whose main parties are vying for the crown of “Greenest of all.”

Al Fin

Dr. Curry is quite game in holding up her end of the discussion on climate modeling and the physics of climate. She risks losing all credibility when she wanders onto the field of political debate and Bush-bashing.

Please stick to the topic at hand, Dr. Curry, and maintain the respect you deserve.

EP

Regardless of scientists’ political views on Bush, funding or the colour of Janet Jackson’s nipple where does this paper leave the debate on AGW? Do relatively short term trends in warming an cyclone frequency mean we should change our economic policies?

bender

Re #108 And does USC not create great technologies that fuel the capitalist enterprise?

J. Curry

Looks like I unleashed a monster with the war on science thing.

One comment on a statement by TAC:

“I accept your explanation that some scientists have felt “provoked” by a perceived government “war on science.” But does this justify a scientist exaggerating claims or publishing invalid results? I hope we can agree that the answer is no.”

The answer of course is no. But when ideologues take over the skeptical arguments, using the strategies of the defense lawyer out to defend a guilty client, then an unfortunate chain of events (unfortunate for the science) may take place. Although I suspect that I will regret throwing this idea out there, I think that hockey stick war was inflated by ideologues, provoking a circle the wagon response by the scientists and necessitating unusual strategies by M&M (I regard Steve M as a bonafide scientific skeptic and not an ideologue). I.e. the hockey stick war is almost a predictable result of the war on science (I wonder what Chris Mooney would do with this idea). And I state this as someone who has no stake in the hockey stick wars either way and as someone who accepts the the assessment of the NRC committee.

So this is the real danger of the war on science. The government should not suppress or alter scientific research (if you want some examples from the climate field, see Rick Piltz’s site http://www.climatesciencewatch.org/
If the government wants to devalue or ignore the science (after considering the various assessments and uncertainties) in their policy making (i.e. for economic, political, or whatever reasons), just say so (and preferably why), without trying to distort or suppress the science to justify ignoring it. Distorting and suppressing the science has some very serious backlash effects on the scientific process.

J. Curry

EP, here is our answer as to what we we should do about the North Atlantic hurricane threat. You can link to the entire statement at Kerry Emanuel’s web page http://wind.mit.edu/~emanuel/Hurricane_threat.htm. This statement (discussed in the New York Times), and involved 10 scientists from both sides of the debate (including Landsea, Mayfield, Emanuel, Webster, Holland).

Here is the text of the statement:

As the Atlantic hurricane season gets underway, the possible influence of climate change on hurricane activity is receiving renewed attention. While the debate on this issue is of considerable scientific and societal interest and concern, it should in no event detract from the main hurricane problem facing the United States: the ever-growing concentration of population and wealth in vulnerable coastal regions. These demographic trends are setting us up for rapidly increasing human and economic losses from hurricane disasters, especially in this era of heightened activity. Scores of scientists and engineers had warned of the threat to New Orleans long before climate change was seriously considered, and a Katrina-like storm or worse was (and is) inevitable even in a stable climate.

Rapidly escalating hurricane damage in recent decades owes much to government policies that serve to subsidize risk. State regulation of insurance is captive to political pressures that hold down premiums in risky coastal areas at the expense of higher premiums in less risky places. Federal flood insurance programs likewise undercharge property owners in vulnerable areas. Federal disaster policies, while providing obvious humanitarian benefits, also serve to promote risky behavior in the long run.

We are optimistic that continued research will eventually resolve much of the current controversy over the effect of climate change on hurricanes. But the more urgent problem of our lemming-like march to the sea requires immediate and sustained attention. We call upon leaders of government and industry to undertake a comprehensive evaluation of building practices, and insurance, land use, and disaster relief policies that currently serve to promote an ever-increasing vulnerability to hurricanes.

Ken Fritsch

Re: #114

I had already copied that statement to an earlier CA comment –as I thought it was excellent advice. At the time I commented that

Federal disaster policies, while providing obvious humanitarian benefits, also serve to promote risky behavior in the long run.

was a pleasantly surprising statement to me as it goes to the nature of unintended consequences of the “good intentions” of government.

jae

90: Dr Curry said:

Simply because we have a data record of insufficient length or accuracy for statistical significance, this does not mean that we should not proceed forward with exploring or using the relationship.

Of course not, but you certainly should not be misleading people by publishing definite conclusions with this information. The weaknesses should be clearly stated.

Paul Penrose

Dr. Curry,
First let me thank you for the frank and continued discussion on this topic. I really appreciate you spending your limited and valuable time helping us to understand these issues.

In message #90 you seem to be saying that if you have a really good physical understanding of something, that you can basically ignore failing stastical scores when analyzing the data and vice versa. Please correct me if I’ve missinterpreted what you’ve said. I, however, see these two items, the physical understanding and the data analysis, as two sides of the same coin. If you think you have good understanding of the underlying physical processes but the correlations in your data are not stastically significant, then I think you have to question whether you really have a good understanding of the physics. The converse is also true in that good correlation could be spurious and uncertainty is high if you don’t understand the underlying physics. In either case I don’t think a good scientist should be coming to any conclusions, let alone making them public.

Only when both are in general agreement should any conclusions be drawn. Obsession in only one area or the other is counter-productive, and if one can’t do justice to both on one’s own, then a colaboration should be sought with an expert in the other area. Failure to do so is, in my opinion, one of the major weaknesses of climatology today.

John Norris

re #110

Point taken, you used the term “neglect”, I colored it further with “starving”, my poor attempt at sarcasm.

By the way I agree with you 100% on your standing O observation. They feel they are getting ignored and shorted on funding. I have a different opinion.

Also by the way, I did not cherry pick my data, I just quickly looked for a science funding stat most relevant to this HW paper thread. NSF apparently funded the HW paper, see page 24. If I read it correctly NSF annually funds 10,000 awards with a median average of $100,000. Most I suspect not towards climate science, but obviously some. As you said NSF is just one program, but obviously not a small program. Do you think the US taxpayer is getting their moneys worth out of funding Mann and this HW paper?

J Edwards

Re: #110

Excellent observations bender. Another point to note is the declining “share” of R&D under government funding. Like Ken, my libertarian tendencies are to keep government out of most things, but I realize that is a double-edged sword in some areas of R&D, and might be perceived to some as being antithetical toward science, as opposed to merely ambivalent. The IntegrityofScience website that Dr Curry linked to, has a presentation by Dr Gleick which includes a slide (#20) that shows the declining market share of Government-funded R&D compared to the waxing share represent by corporate R&D (URL: http://www.pacinst.org/topics/integrity_of_science/AGU_IntegrityofScience_Gleick.pdf).

EP

That should read “cyclone” above 😉

John Norris

re #110, 124

Dr Gleick’s slides are excellent.

From this link it looks to me as the government share decrease in total R&D is mostly due to a large increase in private industry R&D, at least up to 2004.

R&D Chart

Brooks Hurd

Re: 113,

Ken,

Mooney, like so many other agenda driven people, wants to use the media as a club to beat the other side into submission. My reading of his statement is that he sees the media as providing balanced and thus unfair coverage of the views that he opposes.

This is same sort of argument that one frequently hears that it is unfair to have Fox News and talk radio. These are the folks who believe that when the US Constitution mentions “Freedom of Speach” in the Bill of Rights, it only applies to them and to those who share their opinions.

Consequently, I can imagine that the theme of Mooney’s book will be.

bender

Re #118
Dr Webster was burned by the ol’ less-than-sign problem. Care to finish that comment, Dr Webster? Very, very interesting. (Thanks for commenting at CA.)

bender

Dr. Curry said:

I doubt this was selected to confound people from figuring out what he actually did.

Dave B in #134 agrees … and so do I.

That is not the point however. The point is in #9. Please, can someone tell me which equation in Davis (1976) HW are invoking as a correction method? Has #9 got it?

You see why Steve M is a fan of transparency and accountability when it comes to statistical methods? Then it doesn’t matter if the method is “arcane” or “standard” – it is what it is. We can debate its suitability once we know what the heck it is.

Ken Fritsch

Re: #136

Damn!!

Nordic

RE#129: Looking at that chart one would conclude that the war on science (research funding) was waged and lost by the elder President Bush, the Clinton administration kicked the can on down the road, followed by capitulation by the latest Bush administration.

One might guess that the decrease in research funding during the GHW Bush administration might have something to do with the cold war ending and subsequent “Peace Dividend” that came with the downsizing of the military.

I think the growth in private-sector research is more interesting. If one can’t find NSF funding to explore the linkage between rising SSTs and cyclone intensity maybe Munich RE would be interested in funding a little research to help them understand why they made such a bundle this year.

fFreddy

try anything once …

J. Curry

The so called war on science is NOT about research funding. It is about suppressing and distorting science. For recent examples related to climate, see Rick Piltz’s site Climate Science Watch http://www.climatesciencewatch.org/, his earlier posts are most relevant.

David Smith

Re #118 Dr Webster, I am honored by your reply and I appreciate the article references.

My concept has been that easterly waves have an axis which extends well northward into the tropical Atlantic, away from the “cloud puffs” of the ITCZ, and that the location of greatest wind-shift is sometimes, perhpas often, often located away from the “cloud puff”, sometimes in a rather dry region. That’s the crux of my speculation – perhaps there are times/seasons/regimes when the two (moisture and what I’d call (perhaps incorrectly) vorticity) are better aligned.

My concept of the ITCZ has been that of a mean moisture axis, with surface convergence, through which easterly waves (and their associated storms) travel.

I appreciate your response to the question, and will do homework!

fFreddy

Re #144, J. Curry
Note to anyone following Dr Curry’s link : you will need to delete the comma from the end of the URL.

Dr Curry, I tried putting Wegman in the search box at that site and got no results. A quick flick through the first page doesn’t seem to show any scientific stuff, just advocacy stuff.
Why do you regard this as a credible source ?

Paul Penrose

Re #125:

The fact that the Government and Coporate lines in that graph are almost mirror images should tell you something. The fact of the matter is that Government spending on science has remained relatively stable since 1964, once inflation is taken into account. The only reason for the apparent drop in Government spending in that graph is because Coporate R&D spending has increased considerably over the 20 or 30 years. This is a good thing. I work in an industry that did not even exist in 1964, but because of large R&D investments since about 1970 has saved many lives and continues to save lives every day.

Now I won’t argue that the selection of what gets funded may have changed since 1964, or that now large and expensive projects tend to be funded in favor of larger numbers of smaller projects; I just don’t know. However we are not cutting funding to science in the US, it is actually increasing if you count Coporate R&D, and despite what some may think, Coporate science is not evil. It has produced many break-throughs beneficial to society, often in cooperation with various universities around the world.

Jim Edwards

Is the portion of Fed Science budget related to biomedical research broken out ?

Pres. Nixon began the much ridiculed “War on Cancer” over 30 years ago – much federal funding was directed there, to the supposed detriment to physics and climatological research funding.

Much of the recent private research has been to expand upon the fruits of Nixon’s War on Cancer programs.

If Federal biomedical research is correspondingly decreasing, presumably that would provide relative increases for the physical and earth sciences.

Roger Pielke, Jr.

Dave-

Thanks. I’m not at all surprised that it has been raised here (it does seems like a point that would be obvious to check in the data, as Judy Curry notes above in this thread). The point comes up all of the time in discussions of our normalized loss data, which shows no long-term trends (see, e.g., my exchange with Kerry Emanuel Dec, 2005, Nature). I am nonetheless very surprised that this aspect of the NATL TC data hasn’t yet been explicitly discussed in the peer-reviewed literature even as papers are published using data relatively uncritically on historical storm counts.

But this seems to be changing, and not just with my short and simple draft — I know of another paper in the works (completely independent of mine), with a different slant on the same sort of issue.

TAC

#141 Roger, thanks for posting Sarewitz’s review of Mooney’s “war on science”. Sarewitz reports:

As an unapologetic critic of the Bush administration, I was eager to read a penetrating political analysis of how the current regime has sought to wring partisan advantage from the complex and difficult relationship between politics and science. Alas, what I found was a tiresome polemic masquerading as a defense of scientific purity.

Having some familiarity with Sarewitz’s writings (“Frontiers of Illusion” and “Prediction,” among others), I am confident that his assessment is accurate.

Paul Linsay

#144, J. Curry,

The so called war on science is NOT about research funding. It is about suppressing and distorting science.

When you talk about suppressing science do you mean Jim Hansen refusing to appear at a Congressional hearing because “deniers” like Spencer and Christy will be there?

When you talk about distorting science do you mean the paper under discussion here which uses some mediocre data and unjustified smoothing to make its point? How about the hockey stick? What about the refusal to accept the satellite temperature measurements and the insistence on using the ground stations?

Think of the refusal to accept AGW and its imagined future catastrophes as a correct application of the precautionary principle. Since the science is so uncertain it would be foolish to make large social and economic changes just because some subset of the scientific community believes deep in its heart that disaster looms a century from now. A subset which happens to have good political and oratorical skills so that its viewpoint is broadcast, broadcast to the detriment of others who have sincere and deep doubts about the validity of the basic science.

bender

All these funding trend data are fine. However the facts remain: (1) the war on terror is costly, (2) universities and the natural and earth sciences are paying for that choice.

On top of the move toward expensive “Big S” science programs, you have basic physical science programs being “watered down” to include more social and economic dimensions, thus leaving less for basic earth observation and experimentation.

It’s somewhat irrelevant how the left chooses to define an alleged capital W “War on Science”. I’m talking about a little w war of attrition against scientific programs. It is a demonstrable fact that science programs were cancelled when the decision was made to fund the war on terror. You can view it the way welikerocks does: “it’s one of the sacrifices we need to make”. But you can’t deny it.

Spin it any way you like; you might influence public opinion, but you are not going to change perceptions on campus with such superficial analyses. Sorry to have to bring you this unpalatable message.

jae

quick to form conclusions about Chris Mooney and the Republican War on Science tbased upon a few posts that make accusations of bush bashing and RP Jrs cherry picking of a single book review from the hundreds that you can find on the web.

Huh? I sure haven’t formed any conclusions, yet. IMO, it’s good to see the various views that are presented here.

Tim Ball

#146
The factor not being mentioned here, but important in the transition from an easterly wave to an enclosed system, is coriolis force (CF) and angular momentum. Below 10° of latitude CF is insufficent to trigger the circular system associated with tropical depressions, tropical storms, and then hurricanes. The greater the latitudinal shift the more angular momentum changes and influences the pattern and force of the system. If the easterly waves are forming further north in the eastern North Atlantic because of a shift in the Intertropical Convergence Zone (ITCZ) then it is likely more closed systems will develop. It is also important to consider that there are two Hadley Cells with the point of contact between them being the ITCZ. This contact zone will vary in width depending on several dynamic factors and thus extend or narrow the zone. This is then important with regard to latitude of part or all of the ITCZ and formation and transition of easterly waves. It is also important because of the land/ocean pattern on the coast of Africa at the critical latitudes.

J. Curry

Here is my hypothesis regarding the lack of an increase in U.S. landfalling tropical cyclones:

1. AGW is contributing to an increase in the number and intensity of NATL TCs

2. The AMO also contributes to the number and intensity of NATL TCs, and it also plays a dominant influence on the tracks of NATL TCs on decadal time scales (this may arise from gradients in the SST that influence atmospheric circulation , or possibly some other mechanism). In an active AMO phase, more TCs make U.S. landfall.

3. Lets combine AGW and AMO and see what happens to U.S. landfalling TCs.
(at this point it may be useful to reference figures 1 and 4rin my congressional testimony

Click to access GT%20-%20Curry%20Testimony.pdf

The number of U.S. landfalling tropical storms in the past 10 years exceeds (slightly) the previous peaks in the AMO (ca 1950, 1880). Oceanographers tell us we are probably 15-20 years away from the current peak in the AMO. So already we have slightly exceeded the previous peak in U.S. landfalls, and we have say 15 years to go before reaching the peak of the current cycle.

The point is, trying to fit a trend line through this very cyclical data for the U.S. landfalls doesn’t get you anywhere. However, when you interpret the time series in the context of physical understanding of the AMO, if you compare successive AMO cycles, it can be argued that we are already seeing a slight signal in the U.S. landfalls that is associated with the increased number of tropical cyclones (relative to where we are at in the AMO cycle). This argument was presented in my testimony. No, nothing statistically significant here. But this is a good example of using physical arguments to interpret what is going on to pose a hypothesis about what is going on, and predicting that we will soon be seeing a signficant signal.

Several issues here. Some scientists such as Kerry Emanuel think that the AMO doesn’t influence the tropical atlantic and the tropical cyclones. I think it does. Actually, the scariest scenario for the north atlantic is if you combine AGW with the rising AMO.

Ken Fritsch

On top of the move toward expensive “Big S” science programs, you have basic physical science programs being “watered down” to include more social and economic dimensions, thus leaving less for basic earth observation and experimentation.

I think that you are looking at a cultural issue here that might be more related to university policy than directly to politics. As for me personally, I think the government spends too much on wars and R&D.

Such assumptions and stereotypical behaviour (by everyone except Bender who has responded on this) reduce the credibility of this site as a place for bonafide scientific skeptics.

We all have our individual “politics” and policy advocacies and that includes you and me. We voice them peripherally here and without the degree of justification that we expect from scientific pronouncements and conclusions that are the main topic of discussion. I personally get tired of attempts to label those with whom we disagree and make it part of the science argument. I am fully capable of hearing all sides of the arguments, whether they be politically or scientifically based, considering potentially biasing of those doing the arguing and then deciding for myself what I find closest to the truth.

I personally think that Mooney makes some good points about politics and science, I just think that he fails to see the general problem of the mixing of science and government. Even those that advocate for more government involvement in science or any other endeavor surely do not reject the reality of the price that ultimately needs to be paid for that involvement. Mooney was aghast at Representative Barton’s involvement with science and naively forgets that it if you want to be independent of such controls then do not put your hand out for taxpayer money. We are not yet to the point of having scientist kings.

Roger Pielke, Jr.

Hi Judy-

You write, “The number of U.S. landfalling tropical storms in the past 10 years exceeds (slightly) the previous peaks in the AMO (ca 1950, 1880).” Here are landfalling hurricanes by decade:

1880s – 23
1950s – 19
1997-2006 – 23

Maybe you meant 1996-2005. Another interesting “decade”:

1908-1917 – 26

Near as I can tell 1917 is about the bottom of the supposed AMO cycle:
http://www.aoml.noaa.gov/phod/amo_fig.php

I’m no climate scientist, but I don’t think that the data on landfalls supports your physically-based explanation.

jae

The mood on campus that Bender mentions is very understandable. The universities have become bastions of liberalism, following the myth that liberal people are more intelligent and caring than conservative people. So naturally they find as much fault in the present administration as possible.

J. Curry

Jae: re my take on 2006 NATL TC season, I would say I agree with Jeff Masters

J. Curry

Roger, you should ask your colleagues Landsea and Mayfield, as far as i can tell they think that the AMO controls U.S. lanfalling TCs.

peter Webster

Tim,
Thanks for the comment. Rotation has EVERYTHING to do with the ITCZ location, that there are waves at all and that some of them turn into hurricanes. My field (tropical meterology and oceanography) has languished for a long time because we have considered the of too simpl as observed e systems: systems that have no variation in the zonal direction (I mentioned the importance of this before) and systems that exist in strong cross-equatoprial pressure gradient forces (CEPG). This opens up a new class of dynamics and they are important. The CEPGs are set up by the warm water to the north of the equator (NH summer) and the colder water to the south. The CEPG is increased in the african region by the sahara and its very low surface pressure. This CEPG drives air from the southern hemipshere to the northern hemipshere. If there were no rotation one would finish up with a constant Hadley Circulation and really not much fun! Up to here we agree.
But the problem is that if you look at data you will find that the Hadley Circulation is anything but steady. The are strong day-by-day variations and the Hadley circulation (like the ITCZ) is a statistical artifact. If you are really interested I can provide you with some diagrams from a paper we are about to submit in a couple of weeks (proprietary). But here is what happens. The CEPG drives air across the equator. Because the earth is rotating, it brings across air from the SH with the worng signed vorticity. To correct this “inertial instability” (sorry, you have to read Tomas and Webster 1997) the Hadely ciruclation speeds up generating the opposite signed vorticity. This produces waves that propagate westward. The location of the mean ITCZ is were this correction takes place.
These are the reasons why the ITCZ, the ascending branch of the Hadley circulation is located where it is and niot at say, 30N. This is the reason why waves propagate across the atlantic in the 5-15 N band. So it is rotation , but with the caveat that the CEPG causes an instability in this rotating system. Hurricanes form 10-20N in the NATL becasue that is where the source of the waves is, where the SST is warmest and etc.
I think all of this hangs together and I don’t think we are speaking at odds. Its just a matter of explaining how rotation works.
One intersting observation is that the mean ITCZ in regions where the CEPG is substantial lies equatorward of the warmest SST. If there were no rotation or if it were not important then the ascending air should be over the warmest SST and the lowest pressure.This rarely occurs! To me this is intriguing and proof in the eating of the pudding. Tomas and webster (1997).

Peter W

J. Curry

Sorry to see the thread degrade so badly, starting with my simple mention that someone was writing a book about hurricanes and global warming. Too much noise, greatly amplified by RP Jr., and I am finished posting here (for the same reason i stopped posting a few months ago as a result of degradation of the Gray thread.) I’ll check back occasionally to see if bender or willis comes up with anything useful on the SST-TC correlation. Again, be skeptical of your skepticism.

bender

Dr Curry,
Before you go, have a look at Willis’s comment(s) on Quenouille’s method (use search tool at top right). He asked if it was a legitimate method for correcting for autocorrelation. Looks good to me, but maybe Dr Hoyos would have an opinion.

Roger Pielke, Jr.

Is it just my impression, or is it actually the case that every time I try to engage Judy Curry on substance (with data, papers, evidence, here or on our site) she packs up and leaves, usually saying something critical about “noise” or somesuch?

EP

Does anyone have a model to explain why the cyclone frequency for the 25 degree band about the equator dipped between 1950 and 2000?

Steve McIntyre

#185. TAC, I agree 1000% with your question which was unanswered in an earlier post. I see nothing in Davis 1976 that supports the test of Holland and Webster. The following comment in Davis 1976 is almost opposing:

Thus if a 6-month filter were applied to the data the correlation scale of SST could be expected to approach one year and any less than perfect correlation could not be regarded as significant.

jae

Anyway, is there no feedback on Roger Pielke’s paper? I think it is very relevant to the TC discussion. Where is the AGW “signal” here? Where is the SST signal here? Does warming have anything to do with hurricanes? It should, IMO, but Roger’s paper makes me wonder. Does chaos rule?

Ken Fritsch

[snip – Steve:  Ken,  I don’t disagree with your comments but please lay off on this for a while.]

Willis Eschenbach

Dr. Curry, I’m sorry you feel that the discussion has degenerated. Me, I treat the trolls and such that are on every blog like I treat the spam in my email … I just ignore it.

In any case, I’ve taken a look at the Hunter-Webster paper. Despite the autocorrelation, the relationship between the number of named storms and the SST is in fact significant (p=0.03, 5 year trailing average). However, claims of correlations on averaged values must be treated with some skepticism. As two series are averaged, the correlation increases. The only meaningful number is the correlation between the datasets themselves. Sea temperature only explains about a quarter of the variance in Atlantic hurricane numbers (r^2=0.27).

However, what all of that ignores is the measurement and sampling errors. This is all too common in the climate science field, I fear.

The HadSST2 sea surface temperature dataset provides these errors, so I have used it for the SST. Here are the data and errors for the July-September temperatures:

As we would expect, the M&S errors in the SST database are quite large in the earlier years and smaller in the more recent time. Note that we can’t tell whether the 2005 temperature was warmer than the 1940s or not, since their 95% CI’s overlap. Also, note the marked cooling in 2006.

I have assumed that the standard error in the “Named Storms” is ±0 post 1970, +1/-0 in 1945, and +3/-0 in 1910, with a linear transition between the values. When we include these errors, the phase diagram they use to show the 3 “regimes” (Hunter-Webster (Figure 1) looks like this:

I have placed a half-oval (thin black lines) around the area in which there is 95% confidence that each point might be found. This is not a rectangular box, since the errors add in quadrature. It is a half-oval rather than a full oval since our hurricane negative error is 0. If two half-ovals overlap, we cannot say that the data points are statistically different.

As you can see, because of the large size of the errors, the “regimes” claimed by Hudson-Webster are not statistically distinct. As bender has correctly stressed, data without error estimates (including M&S errors) is simply not science.

Finally, it is worth looking at the “regimes” without the 5-year filtering done by H/W. Here is that plot:

Regimes?

Also, note that rather than continuing on an up and away increase, in fact 2006 has come back into the middle of the fold … go figure.

w.

bender

Now, with Willis’s figures as a backdrop, I would like to reiterate my initial remark from the previous thread:

Figure 4 (of HW) is comical. The hypothesis here is that a step function fits the hurricane proportion data better than a smooth oscillatory function. Where is the hypothesis test? How were the parameters of the step function chosen? Where are the methods?

The idea that the climate system is switching states according to this step function is the essence of the phase diagram. Willis’s enhanced phase diagram illustrates why the idea of switching among disrete state is pure fancy: the error is enormous. Cute (hey, who doesn’t like Lorenz’ butterfly attractor?), but fanciful.

Moreover this underlines my statement in #80 about a lack of self-criticism in climate science. They systematically neglect error because they are more interested in hypothesis confirmation than hypothesis refutation. Seems statistics just get in the way.

bender

Since HW try to make the connection between discrete state-switching & the multistable Lorenz attractor, I may as well ask my naive question about time-scale compatibility of the two works. I had always assumed Lorenz (1963) was interested in the problem of weather prediction, and that his attractor was supposed to be relevant to short-run thermodynamics. Whereas HW are looking at the possibility of superdecadal changes in climatic regimes. Am I wrong? Are HW inappropriately conflating time scales, or am I just overinterpreting the connection between their phase diagram and Lorenz’s? Apologies to the authors if I’ve misrepresented their work.

Bob K

Here is a breakout of all wind speed readings from the unisys hurricane database
for the Atlantic basin. The file I used is tracks.atl that ends with 2005.
It appears that as time goes on, more low readings are being included.
There appears to have been a shift in observational techniques around 1950
and again around 1980.
I don’t know how this affects the statistical reliability, but thought it might
have a bearing on the lower percentage of US landfalling storms. Might it be
appropriate to only use obsevations above a certain wind speed threshhold?
Say 30-35kts. Those are certainly the ones most likely to be recorded over long
periods of time.

10kt, 15kt, 20kt, 25kt, 30kt, 35kt, 40kt, 45kt, 50kt, 55kt, more, total
1851-60, 0, 0, 0, 0, 0, 0, 69, 0, 147, 0, 685, 901
1861-70, 0, 0, 0, 0, 0, 0, 54, 0, 140, 0, 827, 1021
1871-80, 0, 0, 0, 0, 52, 0, 367, 0, 396, 0, 1252, 2067
1881-90, 0, 0, 0, 4, 56, 167, 291, 143, 349, 67, 1268, 2345
1891-00, 0, 0, 2, 47, 94, 326, 332, 223, 405, 116, 1463, 3008
1901-10, 0, 0, 4, 74, 288, 498, 269, 181, 190, 86, 873, 2463
1911-20, 0, 3, 29, 44, 114, 225, 153, 142, 98, 80, 667, 1555
1921-30, 0, 2, 13, 33, 55, 370, 191, 116, 97, 56, 861, 1794
1931-40, 0, 18, 51, 72, 78, 732, 418, 173, 149, 113, 971, 2775
1941-50, 0, 18, 26, 105, 80, 360, 295, 230, 188, 109, 1094, 2505
1951-60, 0, 27, 10, 301, 178, 327, 180, 229, 191, 103, 1241, 2787
1961-70, 0, 11, 27, 475, 502, 193, 171, 178, 170, 137, 1419, 3283
1971-80, 0, 20, 90, 342, 478, 210, 240, 218, 160, 136, 886, 2780
1981-90 21, 47, 81, 302, 418, 281, 247, 244, 188, 178, 816, 2823
1991-00, 6, 21, 164, 251, 475, 329, 308, 315, 264, 171, 1334, 3638
2001-05, 34, 29, 139, 273, 378, 293, 212, 250, 221, 166, 816, 2811
total, 61, 196, 636, 2323, 3246, 4311, 3797, 2642, 3353, 1518, 16473, 38556

Here’s mean wind speed for all readings and also for speeds of 30kt or more.
All, 30kt+
1851-60, 71.6, 71.6
1861-70, 71.7, 71.7
1871-80, 62.7, 62.7
1881-90, 61.2, 61.3
1891-00, 61.4, 62
1901-10, 52.1, 53
1911-20, 57.8, 59.6
1921-30, 61.2, 62.2
1931-40, 53.1, 54.8
1941-50, 58.6, 60.9
1951-60, 58.5, 63.2
1961-70, 55.1, 60.8
1971-80, 49.2, 54.1
1981-90, 48.4, 53.3
1991-00, 52.7, 56.9
2001-05, 50.6, 56.5
total, 56.3, 59.3

Hmmm. Doesn’t seem to format well.
The data could be saved as a .csv file and put in a spreadsheet for better viewing.

David Smith

RE #194 willis, one of the questions still in my mind has to do with the choice of SST region. If your Figure 1 used 25-5N and 90-20W, would that make a significant difference in your results?

Beyond statistics, Dr Webster if you’re around, a question related to the climate regime concept: any general thoughts on the structure of the tropical Atlantic atmosphere in the current regime? Has something shifted, is something moving faster/slower, is something less stable, etc? I’m interested in what I’d call the “mechanics” of the atmosphere in the new new regime.

One piece of (limited) data I noticed is this sea level pressure plot . This covers much of the Western tropical Atlantic. What I note is the apparent sharp drop circa 1995. It makes me wonder if Atlantic pressure patterns shifted at that time. I’m trying to develop a mental picture of what’s different.

Thanks

Roger Pielke, Jr.

All, a few replies-

Re: #193 Ken- Two replies. In my short paper see Figure 1 which shows the number of landfalls over time. What needs to be explained is the remarkable consistency of landfalls, especially if there are in fact big things going on in the Atlantic. In the discussion I present some very simple statistical analysis on the probability of various periods seeing different landfall rates assuming that the rate in the earlier period holds in the second.

Re: #194 Willis- Very interesting! A small name correction- It is Holland/Webster;-)

Re: 195 Parminator- I did not look at pre-1950 SSTs. Certainly would be worth a look, for completeness if nothing else.

Re: 196 Bender- I agree with your point here, but I’d phrase it a bit differently. Within the community there are those who offer criticism in the best of the scientific tradition, but it is often dismissed as “nose”, “denial”, or an “attack.” The community’s pathology lies is in the fact that such dismissals usually win the day (for a range of reasons, a few political, but many cultural and professional).

Roger Pielke, Jr.

Steve- Thanks, link doesn’t work ..

Ron Cram

re: 177

Dr. Pielke,

Great post there on 177. Thanks for explaining the facts on his resignation.

David Smith

Re #203 TAC, my (classical/quaint/antiquated/layman) view is that there should be some connection between SST and the number of storms in the Atlantic.

There is something of a “magic temperature” (26C, give or take a bit) below which it is difficult for a tropical storm to form. For storms to form, the surface water needs to be 26C or higher. As the Atlantic warms over time, the area that is +26C expands, and lasts longer, so that seedlings have a greater opportunity to turn into storms.

This is especially important in the middle tropical Atlantic, where the seedlings (easterly waves) progress westward. The sooner they encounter +26C water, the sooner they can strengthen. This is important, because they often encounter unfavorable conditions when they enter the eastern Caribbean: they need to “get healthy” before entering the Caribbean/ Central Atlantic so that they have a better chance of survival.

So, the “classical” view is that warmer water should lead to some increase in the number of Atlantic storms, and probably has, but it may be hard to discern in the poor-quality data.

However, there are mysteries (at least to me). The global number of storms is remarkably constant at about 90 per year : why is that? Sea surface temperatures have risen but the global number of storms has been more-or-less constant. Perhaps it’s related to some aspect of energy release, perhaps it is upper-atmospherics. perhaps there are offsetting factors. My classical view would expect some increase in global storms as SST increases, but that does not seem to have happened (based on the admittedly weak global historical data).

On the question of intensity, the classical view is that there should be some (modest) increase in intensity as tropical SST increase. As SST rise the warmth goes deeper into the ocean (which reduces the cooling due to ocean mixing during a raging storm), the surrounding surface air should be more humid, evaporation is enhanced, the seedlings get an “earlier start”, there’s a greater delta-T between the surface and upper air, and so forth. But, for a 0.5C increase, I would expect the increase to be modest and probably hard to detect.

Directionally, I think that the Curry/Websters and the Landsea/Grays agree with each other – the difference is over magnitude.

(They may also differ on the importance of any natural oscillations, which this HW paper addresses but which has not been discussed here (so far at least).)

Jeff Weffer

This is much like the tree ring problem.

Tropical Storms are affected by a large number of variables – SSTs, ENSO wind shear, jet streams, dust from the Sahara, High and Low Pressure systems around it, Solar?, atmospheric water vapour – you name it.

Much like tree rings, trying to tie tropical storms to global warming is going to be a difficult case because tropical storms themselves are multivariate. Besides that, the data sets we have are incomplete and not long enough.

All of these studies are trying to tease out a very weak signal and, in so doing, the statistics used are always reaching and questionable.

Go back to the original tropical storm models (Bill Gray’s for instance), which include all these variables.

Dane

[snip- Steve: Dane, take this to another thread please]

Jean S

Willis, Judith, Roger and others interested in these storm data:

IMHO, there is a fundamental problem with the statistical approach of all of the storm papers (at least the ones I’ve seen referred here). That is, the underlying data set is count data, and furthermore, the level of measurement (if the storms are given in categories like “named strom” and hurricanes in Saffir-Simpson categories as they should IMO as the early wind speed measurements are inaccurate) is ordinal. Hence the standard linear statistics may not be approriate here.

IMO, something like Generalized Linear Models (multivariate Poisson regression, Multinomial,…) should be used for analyzing the relationship between, e.g., SST and hurricane counts. However, I do not think standard GLM is appropriate due to apparent autocorrelation, but there exist extensions to time series. The standard references include

Cameron & Trivedi: Regression Analysis of Count Data, Cambridge University Press, 1998

Harry Joe: Multivariate Models and Dependence Concepts, Chapman & Hall, 1997.

Also the following recent paper looks very interesting:

R. Zhu & H. Joe: Modelling Count Data Time Series with Markov Processes Based on Binomial Thinning, Journal of Time Series Analysis Volume 27 Issue 5 Page 725 – September 2006.

Abstract. We obtain new models and results for count data time series based on binomial thinning. Count data time series may have non-stationarity from trends or covariates, so we propose an extension of stationary time series based on binomial thinning such that the univariate marginal distributions are always in the same parametric family, such as negative binomial. We propose a recursive algorithm to calculate the probability mass functions for the innovation random variable associated with binomial thinning. This simplifies numerical calculations and estimation for the classes of time series models that we consider. An application with real data is used to illustrate the models.

Ken Fritsch

Re: #197

For those interested in statistically robust trends in landfalling hurricanes, recall this was discussed some months ago. Use search tool at top right to locate relevant comments. Graphics are currently missing from those threads, but maybe they’ll be back soon?

Thanks, Bender, for the reminder. The discussions appear to point to the same interpretation as RPJ used in his draft paper, but without definitive statistical analysis.

Re: #204

In the discussion I present some very simple statistical analysis on the probability of various periods seeing different landfall rates assuming that the rate in the earlier period holds in the second.

Thanks RPJ for the reply. I want back to the paper for a closer read and did see the probability measures assuming a binomial distribution.

Overall I think I agree with the “over 26 degree centigrade” theory of which David Smith reminded me and additionally that the effect of SST on TC activity and intensity could well be sufficiently small to make finding the signal difficult.

I also recall a paper reviewed here earlier that used delayed or anticipatory SSTs on the track or as near as measurements were available to the TC track to relate SST to PDI or ACE and found no significant correlation. I need to search for that author’s name as I think I would recognize it if I saw it.

In the Holland/Webster paper, the authors seemed to me to be in a hurry to make the policy statement of connecting AGW to significantly more TCs without deference to countervailing evidence that scientists would normally be expected to make. My view may be the result of a layperson not understanding all the nuances involved. It is also frustrating not to be able to hear their comments and replies to some of the seeming weaknesses in their paper noted here, Dr. Curry’s efforts notwithstanding. It is too easy without those replies or an opportunity to make them to talk amongst ourselves as though their results/conclusion have been refuted.

Ken Fritsch

Re: #221

Yes Patrick Michaels — I would have remembered the name. Thanks David. I think he was ranked way down on the Curry list for AGW advocacy by climatologists.

TC win speed reaches a threshold at 28.25 degrees C for SST and platueas there with SST being defined in anticipation of the storm and as a maximum. The authors conclude that the relationship found would tend to contradict what Webster and Emanuel found and predict no significant increase on TC counts or category 4 and 5 hurricanes but that with 2 or 3 degree increases the portion of higher category storms could increase.

I have noted that this paper was not referenced in the Holland/Webster paper under discussion here.

David Smith

Re #222 If I remember correctly, Michaels wrote a book some years ago in which he said that Earth would indeed warm due to CO2, CH4, etc at about the no-feedback rate (1 to 1.5C for 2x). But, the consequences would not be severe. Needless to say, he’s been shunned.

Sounds like Michaels is a lukewarmer, like me

Willis Eschenbach

Jean S., as always, a very interesting post. Your point is well taken, the data is not well described by a Gaussian distribution. Here is a comparison of three distributions and the hurricane data (1851-2006).

As you can see, the data is best described by a Gamma distribution, shape = 5.1, scale = 1.6 … about which I have reams of ignorance. Perhaps you could comment on the statistics of Gamma distributions …

w.

Roger Pielke, Jr.

#225, #224

The use of various distributions, especially Poisson, to describe various aspects of hurricane/TC frequencies has been well-explored in the literature, especially in the work of Jim Elsner. See, e.g.,

http://ams.allenpress.com/perlserv/?request=get-pdf&doi=10.1175%2F1520-0442%281999%29012%3C0427%3AFINAHF%3E2.0.CO%3B2

Willis Eschenbach

TAC, thanks for your comment. You say that the Poisson is a discrete distribution, which it is. However, the cumulative distribution changes slowly, and I have sampled it at 28 points (corresponding to the 28 maximum hurricane count), so it looks smooth, although you can see slight kinks in the tight turns.

Also, the difference between the Gaussian and the data is one hurricane, and occurs at about the average number of hurricanes (~9). This may or may not be significant, but the difference in the statistics of their expected error, effects of autocorrelation, and the like may be.

In any case, I’m not sure if the Poisson distribution is more likely than the Gamma distribution. Poisson fit improves if the data is detrended, but the Gamma distribution still beats it. Gamma is generally used for Mean Time Between Failure (MTBF) analysis, and hurricanes can certainly be considered as a “failure” of the normal heat redistribution modes of the tropical ocean … dunno.

w.

Willis Eschenbach

TAC, your point is taken, poisson is a discrete function, and I have connected the dots.

w.

Steve McIntyre

#23 OK, Chris, you’ve plugged your book – if you wish to advertise here, I’d be happy to discuss. Everyone else – please keep this thread on statistical issues.

McCall

Correction: spewpersons

Willis Eschenbach

Man, Davis 1976 is twisting my head. I can’t make out their paper. In equation (2) they say

S = 1 – average(p-phat^2)/average(p^2)

Shouldn’t that be

S = 1 – average(p-phat)^2/average(p^2)

??

I still haven’t figured out how they are deciding if their results are significant given autocorrelation …

w.

J. Curry

Willis, I haven’t had sufficient time to go through all this. The big issue in moving the science forward is how we can combine physics and statistics to make sense of what is going on. Stating that H/W’s attempt to consider the low frequency correlation between SST and TC is not statistically significant may very well be correct. The challenge is then to try to devise some sort of analysis that has some hope of being statistically significant that can tease out the hypothesized low frequency link between SST and TC. If the data quality and length simply won’t allow this (to clarify whether a significant link exists or not), then scientists will then explore theory and models to try to understand this link, and will also test to see if the relationship has any predictive value. Note in terms of predictive value, this low frequency relationship might be potentially useful in predicting averate TC activity 20 years from now with an SST increase of 0.5C (25 years from now we will be able to verify this prediction and we will also have 25 more years of data and potentially more accurate historical data base). So, in the context of how science works, demonstrating that one analysis is not statistically significant isn’t sufficient to reject the hypothesis that there is a low frequency correlation between NATL SST and TC counts.

I am not defending the H/W paper, I am just trying to clarify how science works when you don’t have sufficient accuracy/length of data. The hypothesis of the low frequency TC-SST link is an interesting one, even if the statistical link is not sufficiently established by H/W. By the same token, Pat Micheal’s idea about thresholds of SST for increasing TC intensity was also very interesting, but would not meet your statistical significance test either. These hypotheses, supported by the data that we do have, provide fuel for further scientific progress, and should be part of the published scientific literature.

(and we don’t need to diverge here to talk about what policy makers do or don’t do with the science, we’ve already covered that territory).

p.s. on the status of the H/W paper. It is accepted for publication, but it is part of a special issue that is awaiting completion of other papers. I understand that some revisions are being contemplated. If this thread can provide constructive input on how better to analyze the data or otherwise interpret the data, I’m sure it will receive careful consideration.

bender

Re #236
-I hadn’t noticed that error. Thanks for catching it.
-Agreed: Davis (1976) is a confusing paper.

Re #238

If this thread can provide constructive input on how better to analyze the data or otherwise interpret the data, I’m sure it will receive careful consideration.

Find a proper citation from the statistics literature on correcting for autocorrelation. Or clarify what exactly was extracted from Davis (1976).

It is accepted for publication

Really?! I wonder who the reviewers were?

UC

#238

So, in the context of how science works, demonstrating that one analysis is not statistically significant isn’t sufficient to reject the hypothesis that there is a low frequency correlation between NATL SST and TC counts.

What would be needed to reject that hypothesis? I’m bit worried about ‘low frequency correlation’. In general, for given sample, correlation is a non-monotonic function of running-mean window length.

I am just trying to clarify how science works when you don’t have sufficient accuracy/length of data

I see, i.e. the effect is of a magnitude that remains close to the limit of detectability, or many measurements are necessary because of the very low statistical significance of the results.

Willis Eschenbach

Judith, thank you for your comment, which contains many interesting insights. However, in it, you say:

So, in the context of how science works, demonstrating that one analysis is not statistically significant isn’t sufficient to reject the hypothesis that there is a low frequency correlation between NATL SST and TC counts.

Ummm … respectfully, that’s absolutely not how science works. It is not anyone’s responsibility to reject the hypothesis that there is a low frequency correlation between SST and TC counts.

On the contrary, it is the responsibility of those who assert the low-frequency hypothesis (e.g. H/W) to show that we can reject the null hypothesis, which is that there is no low-frequency correlation between TC and SST.

To do so, they need to show that the relationship is statistically significant at some level above random chance (typically p less than 0.05), which they have not done.

Again, thank you for your participation in this discussion.

w.

Dave Dardinger

re: #245,

I can’t see how you could expect either the regular or inverse null hypothesis to be rejected in his example.

If there is truly a trend, it may be too weak to be able to reject the null hypothesis that there is no trend. But in that case, clearly the inverse null, that there is a trend, could not be rejected.

And if there is truely no trend, then obviously the null hypothesis that there is no trend couldn’t be rejected. But it’s not clear that the inverse, that there is a trend, must be rejected. Here the problem is that we don’t have a WFH (Well Formed Hypothesis). Surely a well formed hypothesis must have some sort of number attached. I.e. that there is a trend greater than 5% increase per year (or decade or whatever). Obviously if there is a trend but it’s .0005% per year, you couldn’t reject the hypothesis that it’s there without a great amount of data or a great precision of measurement.

John S

Re #245, #246 et al.

See my comment at #35.

The data are so noisy and the power of our tests sufficiently low (at least those tests so far used) that the assumption of H0 determines the outcome. When you have assumptions determining the result it is not really empirical science – faith may be too pejorative a word for some in this context – but whatever it is, it is not empirical science because it is not falsifiable. (I will allow for assumptions to determine results in the queen of sciences but otherwise you better have a really good explanation.)

Ken Fritsch

I used the 800px/600px code???

Willis Eschenbach

Judith, you say:

We should be trying to provide a range of future projections of TC activity that can be used in risk management. If we simply say the data isn’t good enough to do anything with, we should ignore the whole subject, and close our eyes and cross our fingers and hope for the best, we might be in for some very unpleasant surprises in coming decades.

I do not see the connection between poor data on the one hand and ignoring the subject, closing our eyes, and hoping for the best on the other hand. One does not imply the other. At times, the best and most useful sentence in the world is “we don’t know”. Let me see if I can summarize the situation as I see it, one of the beauties of this blog is that plenty of people will let me know if any of these are wrong.

“‚⠠ Global climate is a tera-watt scale heat engine, with an energy source at about 345 W/m2 and an energy sink at about 0°K.

“‚⠠ Thunderstorms, squall lines, frontal systems, tropical cyclones, and hurricanes are all local heat engines which move heat from the surface to the upper atmosphere. As such, they are driven by some form of àƒ⣃ ‹’€ ”‚¬⟔, the temperature difference between the surface and the upper atmosphere. They form a parasitic loss to the global heat engine.

“‚⠠ In a warming world, this àƒ⣃ ‹’€ ”‚¬⟔ will increase. However, and this is a very important point, it will not increase as fast as àƒ⣃ ‹’€ ”‚¬⟓, the change in the surface temperature. This is because both the atmosphere and the surface are warming.

“‚⠠ In a warming world, the sum total of parasitic heat loss through all possible mechanisms (e.g. local climate heat engines as above, ordinary convection, evapotranspiration, hydrometeors, wind driven evaporation, Hadley cell circulation, ENSO events, atmospheric turbulence, mobile polar highs, changes in vegetation, etc.) will increase.

“‚⠠ We have very little information on how this increased parasitic heat loss will be apportioned among the various mechanisms. Nor is there any reason to assume that the various proportions will be the same year-to-year.

“‚⠠ Near as we can tell, the world has been warming over the last century, yet globally the number of hurricanes hasn’t changed much. The number of hurricanes in the Atlantic has increased. We don’t know why either of those might be the case.

“‚⠠ While theoretical calculations indicate stronger hurricanes in a warmer world, observations find less of an effect than predicted. We don’t know why.

“‚⠠ Near as we can tell, there is only a very weak correlation between landfalling named storms and hurricanes and sea surface temperature in the Atlantic. (ACR temp vs landfalling named storms 1851-2006, r^2 = 0.07, p=0.03. ACR vs landfalling hurricanes, r^2 = 0.03, p=0.05. Maximum 50-year trailing correlation r^2 = 0.14)

Now, should this confusing situation mean that we should “close our eyes and cross our fingers and hope for the best”? By no means. But it doesn’t mean that we should pretend to know more than we do. Given our current knowledge, we cannot “provide a range of future projections of TC activity that can be used in risk management” in anything more than the most general sense:

1. If the world warms in the future, we will likely see a slight increase in Atlantic hurricanes. On average, they will be slightly stronger. On average, there will be very little change in landfalling cyclones or hurricanes.

2. If the world cools in the future, we will likely see a slight decrease in Atlantic hurricanes. On average, they will be slightly weaker. On average, there will be very little change in landfalling cyclones or hurricanes.

3. For a “range of future predictions”, see 2005-2006.

But this doesn’t mean a lot, because In either case, ALL THE NORMAL PRECAUTIONS APPLY. Don’t build in flood-prone areas, or if you do, take the normal precautions. Don’t build in hurricane prone areas, or if you do, take the normal precautions. Don’t build in areas exposed to extreme winds, and if you do, take the normal precautions.

The mathematics for occasional extreme events are curious. Suppose I live in an area where a hurricane strikes occasionally. Being a prudent person, I figure out the highest wind I expect to encounter over the next hundred years, add a safety margin, and build to those specifications. I figure the house may be hit by a hurricane say six times in a hundred years. I know that there is a statistically small chance, let’s call it 5%, that sometime in the next hundred years a bigger wind may come along and, like the wolf in the story of the Three Little Pigs, “blow my house down”.

Now, there is only an extremely weak correlation between sea temperature and land-falling hurricanes or cyclones in the Atlantic, with less than 10% of the variation explained by SST. Suppose somehow we could see into the future and we knew for a fact that the world would warm by a degree over the next century. Now, instead of expecting six hurricanes over a hundred years, I expect 6.15 hurricanes, and instead of having a 5% chance that my house will blow down, it’s now a 7% chance …

What difference will it make?

This is a much wider question than just hurricanes, because all of the doomsday evils foretold by the climate alarmists are with us today. Droughts? We have extra, no shortage there. Floods? Check with Bangladesh, they might have some to spare. Hurricanes? See 2005. Rising see levels? Go talk to Holland. Disease? Chat with some Africans. Hot spells? Yep, aplenty.

Will any given one of these increase in the future? Quite possibly, but the ugly truth is, we don’t know.

Should we just “hope for the best”? Nonsense. Should we worry about the year 2100? We don’t have enough knowledge to do that, and besides, we have pressing problems and limited money.

The best thing we can do about future climate problems, our best defense, is to deal with the current climate problems. The more we know about solving current droughts, the better we will be able to deal with future droughts … and the same is true about hurricanes, floods, and all of the vagaries of weather.

w.

welikerocks

Willis,

Thank you for your excellent post. “you rock!” which means the same thing. You have a gift of diplomacy some of us lack, among other gifts. 😉 It is nice to read something calm and reasonable for the New Year.

Dane, my husband thanks you as well (he’s off on a Pacific Coast Hwy trip with daughter-ending in Santa Barbara, CA. There are epic winter waves going off and she got in the line up; and caught a wave at Rincon with an 8ft swell; just like her dad did in the olden days yesterday-Yay! a dose of joy provided by the same dynamic planet ) 🙂

#253 Agreed.
The past is history, the future is a mystery, all we have is right now. Happy New Year!

Ken Fritsch

Re: #252

While theoretical calculations indicate stronger hurricanes in a warmer world, observations find less of an effect than predicted. We don’t know why.

Willis nice summary in this comment, however, I was of the view that the theoretical calculations and models would predict a sufficiently small change in wind speeds to make it virtually undetected at this point and that some researchers in the field, such as Emanuel and Mann, believe that they can show a significantly larger effect than the predicted one.

Steve McIntyre

Florida has been clobbered in the last 11 years, with about half of the U.S. landfalls. in 2004, apparently 20% of all homes in florida were damaged from the landfalling hurricanes. The concentration of population and wealth in particularly in florida and the gulf coast, combined with increasing TC activity in the coming decades (AMO, AGW, or both), adds up to huge vulnerability.

No one’s arguing this point. What’s this got to do with statistics?

J. Curry

Margo, your analysis is very interesting. This is a good example of one of those consistency tests I mentioned before (but one i hadn’t thought of). Several issues (perhaps fodder for further analysis)

1. If TCs are undercounted, I would expect something like this
1944-1960: perhaps some small undercounting, but maybe just random errors where some TCs were missed and some tropical depressions were misclassified as TCs (perhaps undercounting of 0.5 TC
1910-1944: some undercounting, probably with more in 1910 than 1944 (say 1 TC average undercount)
1870-1910: more undercounting (say 1-2)
before 1870: undercounting by 2-3
Maybe try chopping this into 3 periods, with a cutoff say 1910

2. The average SST for your two periods is different (avg SST is higher 1944-2004). the “true” relationship between TC and SST may not be linear, there may be thresholds (or “regimes”). To test strictly for undercounting, it may be best to lop off some of the recent years, enough to make the two periods have the same mean SST. Then check to see if the difference in intercepts is significantly different

Margo

Judy,

1. I am absolutely astonished someone (like you), who has been dealing with this storm data so long had not thought to do a t-test to compare the difference in the mean value of storms predicted at some constant temperature SST. Applying T-tests to determine confidence in the slope and intercept is the sort of thing undergraduates in engineering are expected to do in laboratory courses.

2. I am aware the data for pre-1945 and post-1945 have different mean in storm counts. I set up the t-test with this in mind and performed what I believe is the appropriate comparison. (Had I made the mistake of comparing the two means, I would have come up with a confidence interval that is truly minuscule!)

3. Your speculation that quadratic terms may be important is “interesting”. You could, test for the quadratic term. It is straight forward and can be done with EXCEL. If you do, I suggest you begin by simply fitting a quadratic to the full data set. Then remember to test the coefficients on the quadratic term to learn whether they are statistically significant. Then come back and tell me what you find. 😉 (Note: I’ve already done this.)

4. In light of the fact that the hypothesis that there is “no change” is categorically excluded by a simple t-test, I should think those who wish to insist there is no change (which seem to include you or Holland and Webster ) have an uphill battle here. However, if you wish, you may of course, chop the data into any size chunks you wish. (Afterwards, you can try to explain why it makes sense to chop up a very noisy signal into smaller and smaller bits– and in some cases a batch of with as few as 16-17 data pairs.)

5. It is not a question of “if”. Unless there is a change in physics, storms were undercounted. If you wish to tease out precisely how many were undercounted in each of various eras, knock yourself out. Meanwhile, this impacts the conclusions in the Holland and Webster paper which include somethng like 7 figures with data going back as far as 1855.

Margo

Armand,

You may be correct about tone. I didn’t mean to be snippy. If Judy is suggesting she will have her research team and frequent collaborators to consider these sorts checks, I would highly recommend that. I apologize for failing to interpret her comments in the manner she intended.

However, if should they attempt to do these analyses, I would caution that trying to come up with “corrections” using the short 16 sample period between 1944 and 1960 as the benchmark would be dubious. I would also point out that trying to tease out any information about the quadratic term will result in the conclusion that the quadratic term is not significant either statistically or in magnitude. (Besides that, she’ll also find that if she really wants to keep the quadratic term, it suggests the bias is worse than suggested by a simple linear analysis.)

Willis Eschenbach

Judith, as always, an excellent post. As you point out, the main issue is not changes in cyclones/hurricanes (C/H), it is changes in landfalling cyclones/hurricanes, because of the damage that they cause.

Whether you are a proponent of AGW or AMO or a combination of the two, all agree that we are headed for several decades of elevated TC activity, at least as bad as the 1950’s (or possibly worse if AGW is a factor). Prior to the 1980’s, the gulf coast was relatively undeveloped, largely owing to the hurricane issue. The hurricane lull of the 1970’s and 1980’s encouraged the coastal development. The development really took off in the 1980s, after hurricane frederic (a big one), which is politically significant since it was the first hurricane that received federal disaster aid (it also occurred a few months after FEMA was formed). The combination of the disaster relief plus 15 prior years of low hurricane activity, gave the green light for big coastal development. At this point, the government (federal and state) is subsidizing coastal development in hurricane prone areas through flood and disaster insurance, regulation and subsidization of insurance, etc. We are paying the bill through our taxes and higher insurance rates. So the issue of elevated hurricane activity projected for the next few decades (and likely beyond) does have serious economic consequences.

What I don’t understand is your claim that landfalling C/H increase with temperature. While there is a clear relationship between C/H and temperature in the Atlantic, there is no such relationship between landfalling C/H and temperature. According to your data, the relationship is (all references in this post are to landfalling C/H.

ACR Temp/Landfalling tropical cyclones

1851-2006 r^2 = 0.07, trend = 0.05 TCs/°C, p = 0.05
1851-1944 r^2 = 0.08, trend = 0.06 TCs/°C, p = 0.04
1945-2006 r^2 = 0.07, trend = 0.05 TCs/°C, p = 0.13

ACR Temp/Landfalling hurricanes

1851-2006 r^2 = 0.03, trend = 0.05 TCs/°C, p = 0.05
1851-1944 r^2 = 0.05, trend = 0.05 TCs/°C, p = 0.05
1945-2006 r^2 = 0.06, trend = 0.06 TCs/°C, p = 0.14

This is an increase of 1/20th of a landfalling cyclone/hurricane for each 1° rise in ACR temperature. Note also that the relationship is no longer statistically significant in the recent era when we have better data.

Finally, while there is relationship between the AMO and landfalling C/H, it is not statistically significant (p greater than 0.1 1856-2006, greater than 0.5 1945-2006). However, since we need to make decisions based on uncertainty, let’s ignore that. The trend between the AMO and TCs is 4.6 TCs/°C, and the trend between the AMO and hurricanes is 2.6 hurricanes/°C. Currently, the AMO is at about +0.2, which translates to 0.9 extra TC/year and 0.5 extra hurricane per year.

Thus, I am totally at a loss why this small increase is even an issue at all. You keep saying that if the temperature goes up, so will the number of landfalling C/H, but there is no such trend in the data. Also, the AMO is probably within a year or so of peaking, but even if it is not, the change is likely to be small.

If I were asked about the possible C/H numbers in the coming years, I’d say “somewhere between the numbers for 2005 and 2006, with a most probable value about a quarter of the way up, call it 6 landfalling TCs and 3 landfalling hurricanes. I don’t think that the data supports a more detailed forecast than that. And if I were in charge of planning for Florida, I’d plan for another year like 2005 … might not happen, but you’d have to plan for it. Doesn’t seem like science can help us much in this case, history is a better guide.

Many thanks, best of the coming year to you,

w.

Willis Eschenbach

Re 262, Steve B., thanks for the insightful comment. You say:

Willis, don’t forget that rising SSTs alone will allow cat 4/5 hurricanes to range much farther up the East Coast. Long-term, this oft-forgot problem has (IMHO) the largest practical implications; e.g., worst-case scenarios such as a cat 5 strike on Chesapeake Bay or a cat 4 strike on New York Harbor. On the West Coast, major hurricane strikes into the L.A. area might become possible.

An interesting question. I suspect that I can put some numbers on this. Let me see … back in a while …

OK, thanks for waiting, it took three hours. Here’s a graph. I don’t have sea temps under the hurricanes, so I have compared wind speed with average sea temperature by latitude, by taking the latitude of each 6 hour observation and comparing it to the average sea temperature for that latitude. This represents all hurricanes, 1851-2006.

Now, the question is, if the sea temperature at 40°N rises, will there be more cat 4/5 hurricanes? As you can see, at the average temperature of NYC, cat 4 hurricanes are rare, and cat 5 nonexistent. Remember, each blue dot represents only 6 hours.

There’s another way to look at it. We can graph the winds by latitude, and then take the slope of the latitude/temperature line and adjust the latitude of New York to see what the equivalent latitude would be. At the latitude of New York, the ocean temperature is rising about 1.2°C for each degree of latitude you go south. Here’s the chart:

Again, we find that there’s not much change. A 1° change in temperature only makes NYC the equivalent of about 1° further south, so there’s no real difference in terms of risk.

So the conclusion is, although hurricanes do go north, the stronger ones require warmer water, and the slope of the temperature vs latitude line is steep enough to make even a 1° temperature rise not very significant in the northern latitudes. In other words, it is not true that “rising SSTs alone will allow cat 4/5 hurricanes to range much farther up the East Coast”. At the latitude of NYC it will only change the range by about one degree of latitude per degree of warming.

My appreciation for raising an interesting issue,

w.

Steve Bloom

Re #269: Willis, how did you figure those SST numbers? I ask that because for these example we would be interested in SSTs running northeasterly from the Gulf Stream into NYC and Chesapeake Bay. Also, perhaps I’m not reading the graphs right but it looks as if you’ve lumped NYC and Chesapeake Bay together.

David Smith

Data on SST versus storm strength, using the SST beneath each storm, is given in Figures 3 and 4 here .

Figure 4 pretty well shows that, to achieve category 4, a SST of 28C is needed.

Summertime ocean off of Virginia runs about 23C, I believe. Here is a global SST chart for September, 1996, which was the best I can find at the moment and it should be similar to today.

So, about 5C of warming would be necessary for a credible threat of cat 4 storms to exist.

The Gulf Stream is clearly shown offshore, with warmer water. It’s possible that a category 4 storm could stay strong until leaving the Gulf Stream, and if it moves quickly it may not spin down much before getting to Cheasapeake Bay, but it will definitely weaken.

The key is how fast the storm moves.

Judith Curry

Willis and David, I agree that anything greater than cat 3 striking NYC or vicinity is pretty unlikely in the current or slightly warmer climate. At cat 3 would be pretty catastrophic tho.

Steve Sadlov

RE: “On the West Coast, major hurricane strikes into the L.A. area might become possible.”

No way. Not possible with current ocean basin shapes and current tectonic plate configurations. Meaning, you can’t fight the ocean currents that result from large slow convection cells interacting with the Coriolis Force interacting with land masses. The California Current will remain a cold current, there will not be tropical waters off of any place north of mid Baja.

Steve Bloom

Re #277: You’re likely right about the California Current, but bear in mind that LA was hit by a weakish storm (probable TS) in the 1930s and an out-and-out hurricane in the 1830s. Tropical storms can survive over colder water for considerable distances, or else Canada wouldn’t have to worry about them.

Willis Eschenbach

Steve B, sorry, I missed this one. You ask:

Re #269: Willis, how did you figure those SST numbers? I ask that because for these example we would be interested in SSTs running northeasterly from the Gulf Stream into NYC and Chesapeake Bay. Also, perhaps I’m not reading the graphs right but it looks as if you’ve lumped NYC and Chesapeake Bay together.

The SST numbers are the zonal averages for July-Sept for 80°-50°W, from 0 to 55°N in 5° increments.

Chesapeake Bay stretches from about 37 – 39N (Washington, DC is 38.5), NYC is about 40N. They were close enough for the purposes of my analysis that I just put in NYC, you can see where Chesapeake Bay is on the graphs. At that latitude, one degree N/S translates to about 1°C water temp.

All the best,

w.

UC

#27, TAC:

Having said that, I have a hard time understanding why one would begin by taking a lag-9 moving average “¢’‚¬? which would typically introduce correlation out to lag 9 “¢’‚¬? and then try to fix things by using a correction for serial correlation (AR(1), or lag 1). Without the correction, the standard trend tests will be hugely biased in the direction of finding significance when it isn’t there. So the question is: Does the “correction for serial correlation” take care of this problem? It might, I suppose. Without seeing any equations, it is hard to say.

Maybe it is some kind of optimal smoothing in Mann’s way. In MannGRL04 he warns against false conclusions based on unobjective statistical smoothing approaches. Maybe 9-year moving average is objective non-statistical smoothing approach.

#194, Willis

However, claims of correlations on averaged values must be treated with some skepticism. As two series are averaged, the correlation increases. The only meaningful number is the correlation between the datasets themselves. Sea temperature only explains about a quarter of the variance in Atlantic hurricane numbers (r^2=0.27).

And r^2 is 0.60 after 9-year averaging, I presume. The correlation is indeed higher for the lower frequencies.. Hmmm.. Was there a correction for serial correlation somewhere?

Steve Sadlov

RE: “Canada wouldn’t have to worry about them.”

Apples and oranges – (Maritime) Canada is affected by the Gulf Stream and eddies thereof. Compare summer SSTs between British Columbia and Nova Scotia.

Margo

Steve:

The Slutsky effect is also well understood by those working in signal processing, instrument development fluid dynamics, and heat and mass transfer. To avoid introducing the anamolies associated with linear averaging, analysits presented with noisy data usually transform data into the frequency domain, filter out the high frequencies and then perform the inverse transform.

This must be done with careful attention not to filter out physics or signal of interest.

bender

Re DFT: like this?
http://www.climateaudit.org/?p=825

David Smith

bender, I see the words “Bayesian” and “hurricane” in several titles on this list . Caution: it is from the reviled FSU Seminoles website.

bender

Re: #291
FSU junk science. (Kidding!)

Over dispersion in coastal hurricane counts does a decent job fitting truncated possion distributions to hurricane counts.

P.S. Congrats LSU. Impressive win over stinky ND.

Brooks Hurd

Re: 294 & 293
Watching the game on Monday with another Buckeye. I hope that OSU has not forgotten how to play like Michican did against USC. Did some of the Wolverines get stuck in DIA’s snow?

LSU’s win over the Irish was decisive!