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february 2011 troy s scratchpad troy s scratchpad february 23 2011 population growth and uhi another look using the noaa population data filed under uncategorized troyca 6 54 pm update 2 24 i realized i should explicitly state that all charts below are for the 1970 2000 period a few months ago i plugged noaa population data into my pairwise comparison of stations that i had previously performed with the nghis census data looking for a uhi signal one of the questions i ve had on the backburner since then is why this noaa population data did not seem to show a uhi signal particularly in the tob dataset comparable to that of the nhgis data for the 1970 2000 time period it seemed that the noaa data given that it s presented in 1 km cells should better represent the population at a station than the place designation i used for my nghis station assignments this is some further analysis into the issue i m using the ushcnv2 tob avg dataset and my intermediate data and code can be retrieved from http dl dropbox com u 9160367 climate 2 23 11postuhi zip first of all i ll note that because i ve been updating my comparison method since that original post this analysis now restricts the difference in station change years from crs to mmts to 5 years which does seem to eliminate some of the noise even with this restriction i still do not get much of anything in the way of a signal however one thing i noticed when doing a different analysis was that quite a few stations which experienced the largest increase in log population growth tended to be the most rural and those stations with the lowest absolute population growth it s been suggested that the most uhi might occur at the early stages of urbanization but even if this were the case i was skeptical that 1 this pristine slightly urbanized transition could accurately be reflected using population as a proxy as opposed to land changes and 2 that the noaa is precise enough to assume that the data going from 0 25 to 0 75 persons per km should have the same weight as going from 10 to 30 persons per km furthermore the main difference between the nghis and noaa data was that nhgis gave absolute population numbers for a place whereas the noaa gives population per km and thus much lower numbers whose differences will be amplified using log diffs as a quick fix then for population i decided to use log popdensity x instead of simply log popdensity where i varied x here are some results x 10 x 25 x 50 this is far from optimized but you can see in each scenario we seem to get a much stronger signal this seems to suggest that we have to put a lower limit on when this log population relationship to uhi exists or at least when it is reflected in the data another area of investigation is related to the fact that nhgis place reflects a larger area than the 1 km radius we ve used for noaa population data expanding the radius to include for a station might increase our signal in that 1 it is quite possible that an increase of population more than 1 km would still affect that station and 2 it does not require the same locational precision from the noaa population data population radius 5km x 25 population radius 10km x 25 i think this further investigation suggests that indeed the noaa data seems to show an even stronger signal than my nhgis population runs in some future posts i should look into different time periods after all the noaa pop data goes back to 1930 as well as examining pairs specifically that are in the same group of absolute population density 10 100 100 etc perhaps there is more of a linear relationship when going from 0 to 25 persons km rather than a log relationship comments 1 pages about radiation budget and climate sensitivity recent comments briana on comment on the phase relation between atmospheric carbon dioxide and global temperature christine barr on how well do the ipcc s statements about the 2 c target for rcp4 5 and rcp6 0 scenarios reflect the evidence alyce on comment on the phase relation between atmospheric carbon dioxide and global temperature window on estimating sensitivity from 0 2000m ohc and surface temperatures the case against a u s carbon tax us china news on on forcing enhancement efficacy and kummer and dessler 2014 millionnaire on cmip3 multi model mean vs individual runs in 20th century hindcast no the greenhouse effect does not justify your pet idea on on forcing enhancement efficacy and kummer and dessler 2014 warming has not stopped surface temperatures reflect multiple forcing factors the environmental centurythe environmental century on could the multiple regression approach detect a recent pause in global warming blogroll air vent amac bart verheggen blackboard lucia chad herman climate audit climate charts graphs k o day hyp testing andrew ttca isaac held judith curry moyhu nick stokes open mind tamino realclimate science of doom steven mosher whiteboard ron broberg zeke hausfather recent posts combining recent instrumental sensitivity estimates with paleo sensitivity estimates cmip5 processing on github with another comparison of observed temperatures to cmip5 model runs estimating ecs bias from local feedbacks and observed warming patterns example with gfdl cm3 on forcing enhancement efficacy and kummer and dessler 2014 effective vs equilibrium sensitivity uncertainty in projections resulting from the cmip5 ohu efficacy range in a two layer model search search for archive october 2014 september 2014 june 2014 may 2014 march 2014 february 2014 october 2013 september 2013 august 2013 july 2013 may 2013 april 2013 february 2013 january 2013 december 2012 november 2012 october 2012 september 2012 august 2012 july 2012 may 2012 april 2012 march 2012 february 2012 january 2012 december 2011 november 2011 october 2011 september 2011 august 2011 july 2011 june 2011 may 2011 april 2011 march 2011 february 2011 january 2011 december 2010 november 2010 august 2010 create a free website or blog at wordpress com 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