26, June, 2005, This site exposes the errors and distortions in temperature records used by the IPCC as evidence of "global warming", scroll down past Australian maps for those pages. Radical new development as US Congressional committee demands to see source data behind "Global Warming" claims. Coolwire 11 reviews facts behind the Oxford University based Climateprediction.net climate modelling project which uses thousands of PC's around the world to run a Hadley Centre (UK Met Office) General Climate Model.
  BoM predictive (max & min) temperature "Outlook" maps go to Coolwire 8  For '02-04 rainfall "Outlooks", which seem just as flawed, go drought page  See further below for Temperature trends in the old USSR.  Coolwire 10 exposes urban warming effects in Alaskan temperature data Coolwire index  While here check out my other science web sites

Page Links  For more links scroll down on left and right Scroll down for "USSR High Magnitude Climate Warming Anomalies 1901-1996"

To contact me ----- sanur2007 at sign warwickhughes.com

Infra-red NASA satellite image of Illinois, Indiana & Ohio. City 
>heat islands are clearly visible. This heat – from buildings, asphalt, cars etc. – has nothing to do with the so-called greenhouse effect. Yet the IPCC uses temperature records from these cities and many others to give a spurious impression that greenhouse warming is already happening. To see an example of how the urban heat pictured above feeds into "global warming", follow the explanation to the right.

Page Links

The left sidebar gives links to all pages on the site. Pages are designed to be quick loading. Where there are too many images to load at once, they 
are accessed by text links direct to pictures.

Growth of the UHI
In Helmut E. Landsberg's book, The Urban Climate, he gives an example of the new urban area of Columbia, Maryland, where construction started in 1968. By 1974 when population had grown to 20,000 the maximum UHI was measured. at 7 degrees Celsius.

 A fraudulent notion based on corrupted data *
The central contention of these pages is that for over a decade the IPCC has published global temperature trends distorted by purely local warmth from Urban Heat Islands (UHI's). These spurious trends have been promoted as “smoking gun” evidence of greenhouse warming. The data were generated by Dr. P.D. Jones and others (1986, 91 & 94), mainly from the Climatic Research Unit (CRU) of the University of East Anglia at Norwich in the UK. The CRU and the IPCC claim that our atmosphere has warmed by ~0.6 to 0.8  degrees Celsius since the late 19th Century, and ascribe most of this to an enhanced greenhouse effect. 

Ever since the beginning of the greenhouse scare, astute observers have suspected that urban heat was responsible for a large slice of the purported warming. The IPCC has stonewalled, telling policymakers that the urban heat island issue has "...been taken account of." This site proves the contrary. There is simply no systematic compensation for urban warming in the Jones dataset. Occasionally there is a slight adjustment in a record for a site change or other anomaly but the majority of records are used “raw”. This applies even to large cities with large, documented heat islands – e.g. Los Angeles, Chicago, Sydney, Johannesburg etc. etc. In recent years, two independent remote sensing methods – nightlight pictures and infrared heat imaging – have clarified the extent of urban heat islands. Their evidence is incontrovertible. Nightlight images show that the bulk of CRU’s records come from lit areas of the surface. Infrared imaging shows that many are from cities with huge heat islands – enough to raise the annual average temperature by 2-3 degrees Celsius compared to the surrounding countryside.

The problem should have been obvious all along. The UHI was first identified in London 200 years ago, and many studies have shown that it can raise the temperature even in small towns. But political correctness, a desire not to "rock the boat", the corrupting influence of "greenhouse funding" on the science and sheer wishful thinking have made the urban heat island a tabu subject in the greenhouse debate. This site breaks that tabu. It turns the spotlight on individual city records included in the CRU dataset, and also examines the CRU results for various "grid cells" across the globe. It leaves no doubt that the CRU temperature graphs are contaminated with pervasive and substantial urban heat which has nothing to do with greenhouse gases. Satellite images of night lights have been published by NASA and give a good indication of the location of urban areas over the entire earth. Taking the same midwest USA area as the Infra Red image above, this is a small preview of how the Jones / IPCC temperature stations are dominantly located in urban regions.
The IPCC tell policymakers that the urban heat island issue has "...been taken account of.." Sure, we can see that, their data is collected mainly from UHI areas. Follow the Earthlights link for larger images of the USA with Jones stations located.   See "City reviews"  link at left for UHI contamination in Chicago compared to more rural neighboring stations.  Below is a classic example of century long growth in  small town UHI contamination from the region shown above: 

The graphic shows the Jones 1994  record for Peoria, Illinois, compared with the average of four nearby rural stations from the US HCN for the 1910-1995 period for which the most complete data is available.   In 1910 Peoria is the cooler, but as its population grows it works its way up and finishes  warmer than the four rurals. The trend lines generated in MS Excel demonstrate that in this case the inclusion of a small town, pop. 114,000 inserts ~0.6 degrees Celsius per century of  urban warming into the IPCC / CRU / Jones compilation of "global warming".  This is the "urban contamination" sceptics talk about. 
Peoria (Jones 1994) compared to the average of Minonk, Galva, Rushville, La Harpe.

A few more quick comments on the Peoria graph and mid west region of USA. [1]  Corrected Peoria data from NCDC and GISS follows closely the rural trend above, so Dr Jones is in a minority of one by using the UHI affected Peoria. [2]  In the 5 degree grid cell containing Chicago, that is between 85 and 90 degrees west and 40 to 45 degrees north, Jones 94 uses no rural stations. Dr Jones claims to be measuring regional temperature trends by using data from Chicago (+6 million), Milwaukee (1.4 million), Grand Rapids (600,000), Madison (324,000), Fort Wayne, Green Bay, Peoria, Rockford, South Bend, and Urbana all between 100,000 and 200,000 population. The list of twelve stations is rounded off by Muskegon Air Port (listed as 40,000 population by the GHCN and nearby Grand Haven at 12,000. 

* Refers to thermometer based measures of global temperature changes over the last 150 or so years as promoted by the IPCC.

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Moscow / Kyoto Special

Over the next few months the Russian government is debating whether or not to ratify Kyoto. A situation rife with many ironies.  How will the Moscow mandarins sell Kyoto to its far flung people who every year of their lives battle winter hardships that few of us have any experience of.  How will the "sell" go.  Could this line work, "Comrades, the Europeans are taxing ther people in order to save you from warmer winters.  They want us to join them in the Kyoto treaty."   Can you hear the silence echoing from the icicles around a hall in Siberia.  But we know the issue will not be decided on the common sense of the Russian people and their scientists but on what the Europe politicians can deliver in booty to the Kremlin bosses.

As if there is not enough irony in the above for one story.  We have the situation that looking at the global distribution of "warming anomalies" going to make up IPCC "Global Warming", it is clear the the "noisy" temperature data in the old USSR gave Dr Jones and his Norwich Climate Research Unit their best hunting grounds to generate high magnitude warming anomalies.  Unfortunately for the citizens of those far flung regions the only way to enjoy warmer winters is to live in an urban heat island (UHI) and/or have access to the fuel you need at a price you can afford.  Kyoto will not affect UHI's but will make your life harder with higher energy prices more likely.  The article below sets out chapter and verse how the Jones / IPCC high magnitude warming anomalies have been generated and how a more realistic survey of those data would see much less warming hence much less global warming.  You read it first here.

USSR High Magnitude Climate Warming Anomalies 1901-1996


Station temperature records are examined in nine five-by-five degree grid cells in the former USSR claimed by Karl 1998 to have warmed by circa 2 degrees over the period 1901-1996.  Karl’s results, derived from updated Jones 1994 grid point data, are compared with temperature records from the Jones 1994 global update, the V2 GHCN and the NASA GISS website.  In no grid cells are rural station records found to justify the warming claimed in Karl 1998.  In three grid cells, stations with warming trends close to the Karl 1998 anomaly magnitudes are found, but in all three cases cities are the source of the apparent warming, which is not apparent at nearby small town or rural stations.  The other six grid boxes contain either stations not warming at the rate suggested in Karl 1998, or very incomplete data for the 1901-1996 period.  Station-by-station comparisons in all grid boxes show significant trend differences between Jones 1994 and GHCN/GISS data.


The veracity of the surface temperature record will continue to be questioned as long as the aggregates used include urban sites, and as long as there is significant departure from lower troposphere temperature trends measured by radiosondes and satellites.

In recent years it has become apparent that a sizeable share of century-long "global warming" was in the region of the former USSR.  This paper examines at the level of individual weather station records the evidence for the claim in Karl 1998 of circa 2 degrees warming during 1901-1996 in nine grid boxes in Siberia and eastern Kazahkstan.   Figure 1 shows the warming over this period from the updated Jones 1994 global dataset as used by Karl 1998 in his contribution to the IPCC publication "The Regional Impacts of Climate Change".

Figure 1

The boxes shaded grey in Figure 2 were shown in Karl 1998 as warming by 2 degrees over the indicated period.  In this and subsequent figures, crosses indicate Jones 1994 stations,  while square diamonds show the Version 2 GHCN stations of Peterson and Vose 1997.  The boxes form four zones, reviews of which can be accessed through the following links:

Tarko Sale, Khanty-Mansi Region of Siberia

Far Eastern Siberia, Sea of Ohotsk

Lake Baikal Region

Eastern Kazahkstan - Lake Balkhash

Figure 2

Notes on Data Sources/Temperature Records

The Version 2 Global Historical Climate Network (GHCN) station data (Peterson and Vose 1997)  provide the mainstay for this study.  These data come from ~7000 stations worldwide, but GHCN mean adjusted data are based on a smaller sample which excludes poorer quality data.

There are 312 stations from the old USSR in the GHCN.   It should be noted that the GHCN contains duplicate data for many station names.  This is often because separate nearby localities in cities have been archived together.  The duplicates are numbered in the GHCN data files starting from 0 (the GHCN preferred version).  Version 0 has always been used here.  This detail is mentioned because as will be seen in this review, other surveys  have accessed different data sources resulting in disparate data choices for the same station.   As an example of this, Figure 3, downloaded  from the GISS website, shows that 7 sets of widely divergent data are available for Irkutsk.

Figure 3

The Jones 1994 updated data contains just over 3500 stations, more than twice the Jones et al 1991 compilation.  In the area of the old USSR, 298 stations are shown, almost as many as in the GHCN.

The NASA GISS website provides a third source of  global temperature records.  By selecting points on a global map it is possible to view graphs (see Fig. 3) from a range of data types and also to download a table of the station data.  GISS data is more processed than the GHCN and has fewer gaps, but the trends are usually similar to the GHCN.  The term “gissGHCN” used on chart legends refers to GISS data termed “GHCN Adjusted”.  This is the only GISS data used in this study.


This study focuses on whether there is any evidence for the claimed warming from rural stations where data can be demonstrated to be substantially homogenous with neighbouring stations.  It is interesting that two recent papers by compilers of global temperature databases, Peterson et al 1999 and Hansen et al 1999, which discuss the V2 GHCN and GISS data respectively, insist that global trends are little affected whether one uses rural station data only or mixed city/rural data.  This is not so in these USSR high warming grid boxes, where cities clearly warm more than rural stations.

The present study also shows that, to a surprisingly large extent, the issue of whether or not the claimed warming is present in these grid boxes depends on which set of station data the reader chooses to rely on.  The Jones 1994 data, which also forms the basis for many IPCC presentations,  generally warms more than GHCN/GISS data for equivalent stations.  The differences between the two sets of data are significant and suggest that at least one is seriously flawed.

Many USSR stations have significant missing data which reduces the confidence that can be placed in trends.

Summary of Findings

In not one grid box, in any of the datasets, could this survey find in homogenous rural records the 1901-1996 warming magnitudes featured in Karl 1998.

In 80% of comparisons the Jones 1994 trends were warmer than GHCN or GISS.  The GHCN and GISS trends are generally in fair agreement considering the sparse station density and frequent gaps in data.

In some cases, strong warming trends were based on data from fast-growing cities such as Irkutsk.  In view of the well-documented urban heat island effect in such localities and the easily demonstrable warming compared to nearby rural sites, the use of such data to contribute to global climatic trends lacks credibility.

Data gaps early in the 1901-1996 period, and the increased likelihood of outlier data in pre-1935 records which are hard to check, may have imparted other non-climatic effects on trends. In particular,  Jones habit of often shortening data has inserted warming into a trend.

Despite the central control of the soviet system, the continuity of meteorological recordings over the period is far from impressive.  It also appears that economic and social re-adjustments during the 1990's have precluded significant improvement in record-keeping over this huge land-mass, despite the sharper focus on climate issues since 1988.   Given the substantial contribution of “Soviet warming” to “global warming” shown in Fig 1,   it is vital  to reassess all of the Soviet station-by-station records.


Goddard Institute for Space Studies (GISS), (2000) Surface Temperature: Station Data.    http://www.giss.nasa.gov/data/update/gistemp/station_data

Hansen, JR, Lebedeff S, (1987) Global trends of measured surface temperature. J. Geophysical Research   92:13,345-13,372

Hansen J, Ruedy R, Glascoe, J, Sato, M, (1999) GISS analysis of surface temperature change J. Geophys. Res.  104: 30997-31022.

Jones PD , Raper SCB, Bradley RS, Diaz HF, Kelly PM, Wigley TML. (1986) Northern Hemisphere surface air   temperature variations 1851-1984. J. Clim Appl Met. 25:161-179

Jones PD , Raper SCB, Cherry BSG, Goodess CM,  Wigley TML, Santer B, Kelly PM,  Bradley RS, Diaz HF, . (1991) An Updated Global Grid Point Surface Air Temperature Anomaly Data Set: 1851-1990. Carbon Dioxide Research Program, Environmental Sciences Division, US Department of Energy.

Jones PD, (1994) Hemispheric surface air temperature variations: a reanalysis and an update to 1993.  J Clim 7:1794-1802

Karl TR (1998) Annexe A; Regional trends and variations of temperature and precipitation in The regional impacts  of climate change, Watson RT, Zinyowera MC, Moss RH (Eds) Cambridge University Press Cambridge

Peterson TC, Vose RS (1997) An overview of the Global Historical Climatology Network temperature database. Bull    Amer Met Society 78: 2837-2849

Peterson et al (1999)  Global rural temperature trends. Geophysical Research Letters. Vol 26., No. 3,  328332.

© 2000, 2001, 2002 2003 Warwick Hughes

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