Dr. Paul, R graphics guru, blessed us with his rendition of transparent contour maps drawn on a google earth image: Cool stuff. I’ll be taking his code and turning it into a function and sharing it back: here is the picture his code creates: That is just plain slick. While I was looking over his 
UPDATE: holy open source to the rescue. I posted a question yesterday on a idea peter had. Transaprency for overlaying light maps onto google maps. reminds me of the old Quake days. Well, I know John Carmack, John is an old friend of mine, but I’m no John Carmack. Neither am I Dr Paul Murrell. 
In part 1 and part 2 we went over the background of nightlights and the fundamental problem: Station inventory data had errors in it: In Hansen 2010, Hansen writes: “ Station location in the meteorological data records is provided with a resolution of 0.01 degrees of latitude and longitude, corresponding to a distance of about 1 
In part 1 we discussed UHI in a general way and introduced NASA’s use of nightlights to identify Rural, periurban and Urban stations. Very simply, the latitude and longitude data in the station inventory is used to look up at radiance value in the nightlights file. If that value is 10 or less, the site 
With the publication of Hansen2010 forthcoming it is critical to examine the subject afresh. The global temperature index product from NASA is known as GISSTEMP .GISSTEMP, like the temperature index from Hadley/CRU and NCDC attempts to estimate the average temperature of the globe using historical data archived in the GHCN ( Global Climate Historical Network) 
Kuwait International airport. Giss has it as nightlights =0, so do I. By looking at comparisons of nightlights with the station centered and a static google map with the station centered, there are mismatches between GISS and Me and between Nightlights and the world. Subtle shift here and there. Annoying. Also, you can see 
I am continuing the investigation of nightlights using some additional packages from Cran. Here we add Rgooglemaps to the mix. Rgooglemaps is a neat tool that gives you a simple ( needs better docs) interface to the static map server. Perhaps, I’ll modify the code to my likeing, so For now I use it as 
Update: Some are not aware that GISS has switched to using Nightlights in the ROW. According to their updates they have moved to nightlights for the ROW. The station inventories can be found here The station I examine below is listed like this in the new giss inventory 20551495001 TURPAN 42.92 91.00 24 384R -9MVDEno-9x-9HOT 
I’ve modified some routines so that we are always grabbing a roughly equal area regardless of the latitude. Basically, you do this: getLonScaleFactor <- function(lat){ kmAtEq <-111.3195 kmAtLat <- 111.41288*cos(lat*DEGREES.TO.RADIANS)-.09350*cos(3*lat*DEGREES.TO.RADIANS)+0.00012*cos(5*lat*DEGREES.TO.RADIANS) return(kmAtEq/kmAtLat) } # the above function returns a scale factor for km per degree @ a given latitude getExtent <-function(x,halfLength=.5,LonLat) { lonAdjust<-getLonScaleFactor(LonLat)*halfLength yMin <- max(ymin(x),LonLat 
Those who follow the discussions about UHI understand that “nightlights” plays a large role in defining whether or not a station is considered Rural or Urban. In the work of GISS nightlights are determined by looking at the DSMP product. The product is available in 30 arcsecond format. That’s .00833 degrees. The following issue arises. 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
