Yearly Archives: 2009

Recent study on decreasing US wind energy not as advertised

Wind speed trends over the contiguous USA by Pryor et al. (2009, in press, JGR) Some (read on to see who) would say that this particular wind farm energy reduction study is speculative, inconclusive, preliminary, and premature, and with the authors’ hesitant equivocation in press interviews, even they may agree with that particular straw man. […]

TAS vs TOS

My new script for scraping KNMI model makes it very convenient to look at model data without a lot of setup overhead. Up till now, I’d only downloaded air temperature data (tas) and I tested downloading SST data (tos). KNMI’s collection of tos data is unfortunately quite spotty and this information is not consistently available. […]

More on Retrieving KNMI Data

I’ve done a considerable upgrade to my function for retrieving model data from KNMI within R. This builds on the KNMI webpage but IMO is a considerable enhancement of it. I’ve made the script available here . The function read.knmi.models is built as an emulator of the radio buttons. Geert’s radio buttons (if I’m understanding […]

A Partial Victory for the R Philosophy

Obviously I think that R is a great language. But one of the reasons that it’s great is because it’s open source and because of the incredible energy and ingenuity of the packages contributed by the R Community for the use of others. In a real sense (as opposed to a realsense), this sort of […]

Cloud Super-Parameterization and Low Climate Sensitivity

“Superparameterization” is described by the Climate Process Team on Low-Latitude Cloud Feedbacks on Climate Sensitivity in an online meeting report (Bretherton, 2006) as: a recently developed form of global modeling in which the parameterized moist physics in each grid column of an AGCM is replaced by a small cloud-resolving model (CRM). It holds the promise […]

Why the difference?

Here is a puzzling comparison of two zonal averages from Phil Jones’ CRUTEM3 gridded land data. Red shows the average from 20S to 20N and black shows the average of the 20-30S band (both N and S). These are calculated from gridded data at http://hadobs.metoffice.com/crutem3/data/CRUTEM3.nc. I did this comparison because I noticed a difference between […]

Revisiting Detroit Lakes

Some long time Climate Audit readers may remember this famous picture of the USHCN climate station of record in Detroit Lakes, MN. This is what I wrote on July 26th, 2007 about it in: How Not to Measure Temperature, Part 25 This picture, taken by www.surfacestations.org volunteer Don Kostuch is the Detroit Lakes, MN USHCN climate […]

Banned at Sudbury Airport

At a friend’s request, I went up to northern Ontario this weekend to look at a gold prospect, which I might chat about some time. I got to trudge through bush for a few hours – exhausting work for city folk, drove a quad around empty logging roads (at a grandfatherly pace) – my sons […]

GISS Gridded and Zonal Data

Last week, I wanted to determine what GISS’ tropical land-and-ocean time series was. This did not prove as easy as it sounds. Nothing in GISS is intrinsically complicated – it;s all just averaging and smoothing and adjusting. But the code is written as though the whole thing were being done on a Commodore 64 with […]

UK Met Office: Refuse and Delete

A couple of week ago, I noticed that the UK Met Office website contained the following statement Q. Where can I get the raw observations? A. The raw sea-surface temperature observations used to create HadSST2 are taken from ICOADS (International Comprehensive Ocean Atmosphere Data Set). These can be found at icoads.noaa.gov/. To obtain the archive […]