Update Mar 28: Here is Luboš version replacing my much less pretty monochrome version showing the spatial decorrelation of the “Comiso” version of the data recently archived a couple of days ago by Steig. Figure 1. Spatial Correlation for Sample of “Comiso 2009” Antarctic Gridcells Jeff Id has compared this to corresponding surface stations at […]
“Noisy” covariance matrices have been discussed here on many occasions in a variety of contexts, largely because the underlying strategy of Mannian methods is to calculate the covariance of everything to everything else and then calculate verification stats using methods that ignore the data mining that effectively takes place with huge covariance matrices. Steig et […]
I’ve now ported my emulation of Schneider’s RegEM PTTLS to R and benchmarked it against Jeff’s Matlab as shown below. I caution readers that this is just an algorithm. There are other ways of doing regressions and infills. The apparent convergence to three PCs noted by Roman is still pending as a highly interesting phenomenon. […]
Standardization in Mannian algorithms is always a bit of an adventure. The bias towards bristlecones and HS-shaped series from the impact of Mann’s short segment standardization on his tree ring PCs has been widely publicized. Smerdon’s demonstration of defects in Rutherford et al 2005, Mann et al 2005 and Mann et al 2007 all relate […]
It seems that we are all “wild about Harry” recently, and no good kerfluffle would be complete without some pictures of the weather stations in question. It seems “Harry” got buried under snow. Why is this important? Well, as anyone skilled in cold weather survival can tell you, snow makes an excellent insulator and an […]
Yesterday, I noted that Steig had criticised previous developers of Antarctic gridded temperature data for not having “paid much attention” to West Antarctica (e.g. the NASA GISS trend map left the area blank due to lack of data meeting their quality standards) and reproached his predecessors (including, it seems, even Hansen) for “calculating with their […]
Image by mark van de wouw via Flickr For discussion of new study. by Steig (Mann) et al 2009. Data: Data sets used in this study include the READER and AWS data from the British Antarctic Survey. SI Tables 1 and 2 provide listings. They leave out station identifications (a practice that “peer” reviewers, even […]
In a recent CNN interview discussed at RC here, Joe D’Aleo said: Those global data sets are contaminated by the fact that two-thirds of the globe’s stations dropped out in 1990. Most of them rural and they performed no urban adjustment. And, Lou, you know, and the people in your studio know that if they […]
Both Luboš and David Stockwell have drawn attention today to the distribution of digits in Hansen’s GISS, suggesting that the distribution is, to borrow an expression, a fingerprint of anthropogenic impact on the calculations. I disagree with both Luboš and David and don’t see anything remarkable in the distribution of digits. I don’t disagree with […]
David Smith writes: This is a minor item but it illustrates NOAA/NCDC’s need for better software to flag outliers – NCDC’s US Climate at a Glance webpage uses preliminary temperature anomaly data to create a monthly anomaly map: The mauve arrow points to an oddity – a blazing hot spot around Greenwood, MS, with a […]
Climate Audit 