Abstract
Station by station temperature records are examined for nine by five degree gridded data points in the old USSR that are indicated to be warming at circa 2 degrees for the 1901-1996 period in Fig 1 from Karl 1998. The warming anomalies are derived from updated Jones 1994 grid point data. Temperature records have been searched from the Jones 1994 global update, the V2 GHCN and the NASA GISS web site. In no cases are the Karl 1998 warming anomalies apparent in rural stations. Only three grid points relate to stations with warming trends close to the Karl 1998 anomaly magnitudes and in all three cases cities are the source while small town or rural stations nearby contradict the warming trends. The remaining six grid boxes have no obvious warming data source or have very incomplete data over the 1901-1996 period. Station by station comparisons in all grid boxes show significant trend differences between Jones 1994 data on the one hand and GHCN & GISS data on the other.
Introduction
The veracity of the surface temperature record will continue to be questioned while the station by station composition includes 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 significant focus of century long "global warming" has been the general region of the old USSR.
This paper will examine the station by station evidence for claimed warming of circa 2 degrees 1901-1996 Karl 1998, in several five degree grid boxes in Siberia, and eastern Kazahkstan. Figure 1 shows the warming over the 1901 to 1996 period from the Jones 1994 global dataset as used by Karl 1998 in his paper in the IPCC book "The Regional Impacts of Climate Change".
Figure 1
Figure 2 covers much of the old USSR and shaded grey are the 2 degrees warming grid boxes where station by station analysis below will examine the evidence behind this high amplitude Soviet warming that constitutes a significant proportion of global warming. In Figure 2 and following maps crosses mark locations of Jones 1994 stations, while the Version 2 GHCN stations of Peterson and Vose 1997 are marked with square diamonds.
Reviews of the four grey shaded areas can be accessed through links further down this page.
Figure 2
In order to justify the claimed warming for these grid boxes, this study is looking for mutually supporting warming trends from rural stations where data can be demonstrated to be substantially homogenous with neighbours.
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 believe in. Usually the Jones 1994 trends contain more warming than the GHCN or GISS data. They both can not be correct. It is interesting that two recent papers by compilers of global temperature databases, Peterson et al 1999 and Hansen et al 1999, writing about the V2 GHCN and GISS data respectively, emphasize that global trends are little affected by using rural station data as opposed to mixed city / rural data. This is not so in these USSR high warming grid boxes.
These sation by station reviews at the very peaks of "global warming" are revealing a very different situation. Not only do cities warm more than rural stations but the Jones 1994 data generally warms more than GHCN / GISS data for equivalent stations.
Notes on Data Sources / Temperature Records
The Version 2 Global Historical Climate Network (GHCN) station data derived from ~7000 stations world wide, Peterson and Vose 1997, provides the mainstay for this study. Using their mean adjusted data available stations are fewer than this due to rejection of poor data. There are 312 stations from the old USSR in the GHCN. It should be noted that the GHCN often contains duplicate data for many stations, particularly city records where separate nearby localities may have been archived together. These duplicates are numbered from 0 (which is the GHCN preferred version) in the GHCN data files and it is that data option which has always been used here. This detail is mentioned because as will be seen in this review, other surveys have accessed different data sources which has resulted in disparate data choices available for the same station. As an example of this, Figure 3, downloaded from the GISS web site 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 there are 298 stations available, almost equal to GHCN.
Another source of global temperature records can be found on the NASA GISS web site at 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 trends are usually similar to GHCN. Where the term gissGHCN is used on chart legends it refers to the data from GISS termed GHCN Adjusted, which is the source of all the GISS data quoted in these reviews.
Many USSR stations have significant missing data which reduces the confidence that can be placed in trends.
Below are links to illustrated station by station data reviews for the four regions.
Tarko Sale, Khanty-Mansi Region of Siberia
Far Eastern Siberia, Sea of Ohotsk
Eastern Kazahkstan - Lake Balkhash
Summary of Findings
It has to be puzzling that in not one grid box, in any of the datasets could this survey find in rural records the 1901-1996 warming magnitudes featured in Karl 1998.
In 80% of comparisons the Jones 1994 trends are warmer than GHCN or GISS.
The use of strong warming trends from fast growing cities such as Irkutsk is quite simply totally lacking in credibility and it is up to the climate fraternity to ignore datsets with such obvious shortcomings.
The GHCN and GISS trends are generally in fair agreement considering the sparse station density and frequent gaps in data.
The effect of data gaps early in the 1901-1996 period and the possibility of outlier data in those hard to check years before 1935 can have a non-climatic effect on trends.
Looking at the issue of overall data quality as manifested by
record gaps, it is clear that despite the central control of the soviet
system, the continuity of meteorological recordings lapsed in many
instances. Although the greater global awareness of climate issues
after 1988 may have had some effect in the post soviet system, it is also
likely that economic and social re-adjustments during the 1990's would
not contribute to better record keeping over this very large land mass.
The Karl 1998 anomaly map Fig 1 demonstrates that "global warming"
is heavily influenced by "soviet warming", which makes it vital
to reassess all of these station by station records.
References
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.
© Warwick Hughes, 2000
www.ozemail.com.au/~hughesw7