Biasing the Surface Land Temperature Record with Big Cities

Willis Eschenbach has been doing some great digging into the UN IPCC AR4 surface land temperature record.  He notes that the UN IPCC AR4 says:

Additional warming occurs in cities and urban areas (often referred to as the urban heat island effect), but is confined in spatial extent, and its effects are allowed for both by excluding as many of the affected sites as possible from the global temperature data and by increasing the error range.

He checked into this:

To check this claim, I took the list of temperature stations used by CRU (which I had to use an FOI to get), and checked them against the GISS list. The GISS list categorizes stations as “Urban” or “Rural”. It also uses satellite photos to categorize the amount of light that shows at night, with big cities being brightest. It puts them into three categories, A, B, and C. C is the brightest.

It turns out that there are over 500 cities in the CRU database that the GISS database categorizes as “Urban C”, the brightest of cities. These include, among many others:

AUCKLAND, NEW ZEALAND
BANGKOK METROPOLIS, THAILAND
BARCELONA, SPAIN
BEIJING, CHINA
BRASILIA, BRAZIL
BRISBANE, AUSTRALIA
BUENOS AIRES, ARGENTINA
CHRISTCHURCH, NEW ZEALAND
DHAKA, BANGLADESH
FLORENCE, ITALY
GLASGOW, UK
GUATEMALA CITY, GUATEMALA
HANNOVER, GERMANY
INCHON, KOREA
KHARTOUM, SUDAN
KYOTO, JAPAN
LISBON, PORTUGAL
LUXOR, EGYPT
MARRAKECH, MOROCCO
MOMBASA, KENYA
MOSKVA, RUSSIAN FEDERA
MOSUL, IRAQ
NAGASAKI, JAPAN
NAGOYA, JAPAN
NICE, FRANCE
OSAKA, JAPAN
PRETORIA, SOUTH AFRICA
RIYADH, SAUDI ARABIA
SAO PAULO, BRAZIL
SEOUL, KOREA
SHANGHAI, CHINA
SINGAPORE, SINGAPORE
STOCKHOLM, SWEDEN
TEGUCIGALPA, HONDURAS
TOKYO, JAPAN
VALENCIA, SPAIN
VOLGOGRAD, USSR

So the CRU is using Tokyo? Beijing? Seoul? Shanghai? Moscow? Their claim is entirely false. In other words, once again the good folk of the CRU are blowing smoke. I can understand why it took me a Freedom of Information request to get the station list.

It is utter nonsense to include data from weather stations in large, medium, or even small cities to produce a record of temperature which might address whether there are human effects of note on the global climate.  Indeed, if you want to bias the results in that direction, the best way to do it is to drop rural weather stations and leave a large number of city stations in your database of temperatures.  This has clearly been done in the U.S. and, according to the Institute of Economic Analysis in Moscow, in Russia.  This list makes it very clear that such warming as has not been added simply by changing recent measurements upward and dropping the measurements of earlier decades, has been strongly biased in an upward direction by using data from many cities and dropping many rural stations.  The only useful data is from rural stations in actual fact.  That this is occurring is a very blatant scientific fraud.