I also did another estimate of the SSTs from the Keigwin 1996 paper graph shown above for century long periods and used that estimate to rank the SSTs and the Besonen extreme events for calculating a Spearman Rank correlation and the probability of r being zero.

The re-estimation of the SSTs lead to the same results as previously reported above: When testing the hypothesis that Spearman Rank r was not zero, it could not be rejected with a p = 0.40.

The correlations of the SST average for the months of August, September and October in the MDR (10 to 20 N and 20 to 80 W) to the annual SSTs for StatS (32 to 36 N and 62 to 66 W) were calculated for a 1, 10 and 20 year averages. I wanted to determine whether the correlation progressively improved by averaging over larger increments of time.

1 year R^2 = 0.39; 10 year R^2 = 0.77 and 20 year R^2 = 0.80.

Since I only had approximately 150 years of data I could not determine directly the correlation for century long averaged SSTs for MDR versus StatS.

I used StatS on an annual basis according to CA here http://www.climateaudit.org/?p=898 were we have:

“The reference to Deuser 1987 in Keigwin (Science 1996) was as follows”:

For isotope analysis, I chose the planktonic foraminfera G ruber (white variety 150 to 230 microns) The white variety of this species lives year-round in the upper 25 m of the northern Sargasso Sea and has a relatively constant annual mass flux and shell flux (18- W.G. Deuser, 1987. J Foraminiferal Res 17, 14.). Thus of all planktonic foraminifera in this location this species is most appropriate for reconstructing annual average SSTs (18).

The SSTs were taken from the link:

http://nomads.ncdc.noaa.gov/#climatencdc

using the Smith-Reynolds Extended Reconstructed SST’s.

The Keigwin core samples had variable time intervals but averaged approximately 60 years for temperature proxy readings from 76 years before present to 3100 years before present. The paper they were taken from was written in 1996.

The data listing core depth, calibrated YrBP and d18O G. rubber are in this link here

I am sure others here could do better renditions of back of the envelop analyses with these data, but in Besonen et al. (2008) it appeared that the authors were trying too hard to indicate an SST to extreme events correlation. I have no idea how much one could count on the validity of the Keigwin d18O as a proxy for temperature and for that matter what would increase the tendencies for the occurrence of extreme events (TCs migrating up to MA). Would theory predict that a century with a higher average SST in the MDR for the ASO months have a greater tendency to form extreme events or could a century with a lower average SST but a larger standard deviation, and perhaps a few seasons with higher SSTs, create more extreme events? I guess it would depend on how constant SST variability is over time periods of a century.

Anyway I was able to relocate the link for calculating SST time series by entering in the grid locations and time periods so something was accomplished.

It could be argued that this paper found significant evidence of increased hurricane activity in the Medieaval Period, so it must have been very warm.

1. The evidence of couplets in the varve sediment in Lower Mystic Lake (LML) for defining annual/seasonal events seems reasonable to me. Once the annual resolution is demonstrated it is reasonable to go on to look for evidence of extreme events, such as hurricanes, on an annual basis.

2. The correlation of outlier status varve thicknesses with a characteristic graded bed with hurricane events in the Boston area seems rather well established even without a calculation of statistical significance. The authors point to these outlier conditions as being distinguishable from heavy rainfall and snow melt events by way of the varve having a graded bed property and have outlier thicknesses as determined by the program CLIM-X-DETECT – which differences the MA mean from the annual mean.

The explanation of how the hurricanes produce distinguishable varves by uprooting trees and disturbing other vegetation seems a bit unclear to this layperson and could be helped by some independent evidence for this phenomenon. One has to take the authors’ word that the heavy snowmelt and rainfall events do not correlate with outlier varve appearances. On the face of it the correlation of outlier varves to hurricanes in the period 1630-1870 appears excellent as noted in this paper excerpt:

We confined our analysis to the period prior to 1870 given the significant anthropogenic interference and altered sedimentation dynamics as discussed above. [11] No relationship was noted with the freshets or extratropical systems. However, we did note a very strong correspondence with known historical hurricanes—10 of the 11 prominent graded beds deposited between 1630 and 1870 fall during years in which hurricanes are known to have struck the Boston area [Ludlum, 1963].

It is a bit disconcerting that these 10 of 11 “prominent” graded beds do not correspond to the number of outlier varves for the period using any of the three limits of outlier. The lower outlier limit gives 14 , the middle gives 8 and the higher gives 7 extreme events.

The following excerpt from Besonen et al. (2008) explains the selection/calibration process in more detail. The 1707 and 1736 years are without hurricanes but have outlier varves and are not graded. Thusly the authors show further evidence of the graded character being connected to the hurricane produced outlier varves. At the same time the authors note a year (1649) without a hurricane but with a graded varve that was excluded because of the outlier thickness being insufficient to meet their criterion. They also comment that 3 hurricane years were eliminated with graded varves that did meet their outlier thickness criterion.

Also when one looks at the number hurricanes that the authors’ source (Early American Hurricanes 1492-1870 by David M Ludlum) one finds under the state of MA for the period used above 31 hurricanes from which to select. I’ll need to look at Ludlum’s details to determine how the authors selected the ones they did – or whether they merely fail to mention the hurricane years that did not meet their varve outlier status or graded condition. At this point one can really only conclude that the author’s have produced a criteria for extreme events that can be associated rather uniquely with hurricanes and should be consistent over time in selecting an extreme event with a limited range for perhaps category 2 and 3 hurricanes.

We examined the LML record using a range of TDVs from med +2.0 rstd up to med +5.0 rstd in increments of 0.5 rstd. Using the 1630–1870 portion of the historical records as a guideline, we determined the best compromise between over-/under-sensitivity was provided by a TDV of med +3.5 rstd. At this value, nine of the varves were identified as extreme events based on thickness alone. Two of the events (1707 and 1736) are varves which do not contain a graded bed, and are simply thicker than usual, for unknown reasons. However, the remaining seven events (1635, 1706, 1727, 1770, 1804, 1850, and 1869) are all varves that contain a graded bed, and correspond to a year in which a hurricane is known to have struck the Boston area [Ludlum, 1963]. We note that this choice of TDV is conservative as it was large enough to exclude the only varve with a prominent graded bed that does not correspond with a known hurricane year (1649). However, it did so at the expense of excluding three other varves that do include graded beds, and also correspond with hurricane years (1849, 1858, and 1861).

In summary, using guidance provided by the historical portion of the record, we recognize hurricane-related events in the LML varve thickness time series based on two conditions: 1.) the varve must reach or exceed a thickness TDV defined by med +3.5 rstd, and 2.) the varve must also contain a graded bed. Using these criteria, 36 hurricane related events (7 historic, 29 prehistoric) were recognized the LML record from 1011–1870.

3. The connection of extreme events to SST is pointed to in the paper in rather general and approximate terms. We can make the case that the distribution of extreme events as tabulated by the authors does not appear to have any statistical significance above what would be expected by chance for the 100 year periods per RomanM’s analyses posted earlier in this thread. That is, however, not to say that a correlation between SST in the NATL TC Main Development Region (MDR) and extreme events does not exist. The extreme events could be affected by the SST changes that are, in turn, occurring on a random basis.

To check for a correlation between the Besonen et al. (2008) extreme events and SST, I took the available SSTs graphed for the Sargasso Sea dO18 reconstruction at 40 to 70W and 25 to 35N here

http://www.climateaudit.org/?p=2202

as a proxy for the SSTs in the NATL TC MDR which is approximately designated at 20 to 80W and 10 to 20N and ranked them for the periods listed in the Besonen paper along with a ranking of the extreme events. I then calculated a Spearman rank correlation from these rankings. The correlation, r, was 0.18 and testing the hypothesis that the correlation was not greater than zero could not be rejected with a p = 0.62. The table below gives the Sargasso SSTs estimated from the graph for the various centennial periods along with the extreme events. The O18 Sargasso Sea graph is also shown below.

This correlation test amounts to a back of the envelop calculation and certainly does not account for any differences that might arise between the MDR and Sargasso Sea or the SSTs from the proxy being related to those months of the TC season in NATL or for that matter the accuracy of the O18 proxy. Since, however, the authors referenced this (and other) proxies I thought it might be fair game. Even more important in hurricanes making it as far north as MA might be the historical SSTs closer to the MA shoreline, but there was no mention of that in the Besonen paper.