Chinese climate scientists tactfully tell the IPCC that surface air temperature (SAT) trends over north China include a large component of urban warming

Ren et al 2008 measure urban warming in a north China grid box 33 to 43 degrees North and 108 to 120 degrees East by comparing temperature trends in groups of stations of different population size for the period 1961-2000. For a concise summary of the Ren et al 2008 paper, Urbanization Effects on Observed Surface Air Temperature Trends in North China
Ren et al 2008 grid cell north China
Their results are summarised in their Table 3 copied here and they conclude from this, assuming no urban warming in their Rural series which warms at 0.18 degrees per decade that urban warming in their various station groups is as shown in their Table 4 below.
Ren et al Tables 3 and 4
In view of the importance of IPCC global warming underpinning carbon reduction policies being considered by many nations, it seemed vital to compare the Ren et al trends against those for the Hadley Centre CRUT3 land only data which has provided the mainstay for IPCC warming claims over nearly 20 years. Ren et al did not compare their trends with any global gridded datsets.

Taking the Hadley Centre CRUT3 data for Ren et al’s north China grid box from the KNMI Climate Explorer website we find a warming trend of 0.31 degrees per decade over the 40 years 1961 to 2000. When compared to the Ren et al numbers in Table 3 we can see this warming trend is near the top of the range and indeed indicates urban warming of 0.13 per decade or equivalent to a rate of 1.3 degrees per century.
So, more evidence that IPCC data contains serious UHI contamination.

Quickly comparing the Hadley Centre CRUT3 land only data 1979-2008 for the north China grid box with the NASA MSU LT data from University of Alabama at Huntsville, all data downloaded from the KNMI Climate Explorer.
We find that CRUT3 warms at 0.57 degrees per decade, while the lower troposphere warms at 0.27, suggesting urban warming of 0.3 per decade. This comparison indicates that urban warming in north China has increased after 2000.

Ren, G., Zhou, Y., Chu, Z., Zhou, J., Zhang, A., Guo, J. and Liu, X. 2008. Urbanization effects on observed surface air temperature trends in north China. Journal of Climate 21: 1333-1348.

11 thoughts on “Chinese climate scientists tactfully tell the IPCC that surface air temperature (SAT) trends over north China include a large component of urban warming”

  1. The world is about to change its economy based on known false data, and incorrect interpretation of it. The IPCC uses computer models which have failed to predict recent trends. Yet others have identified a 60 year cycle using solar magnetism, wind and ocean currents etc (Mazzarella) which accurately match these trensds. However, it seems it’s more important for the models to match the politics rather than the science.

    Now we find that even the raw data is in doubt.

  2. Hm, I notice that this area has large positive trend biases in the paper:
    McKitrick, R. R., and P. J. Michaels, 2007. Quantifying the influence of anthropogenic surface processes inhomogeneities on gridded global climate data. Journal of Geophysical Research, 112, D24S09, doi:10.1029/2007JD008465.
    Just look at the map:

  3. Was not sure exactly what the map portrayed.
    I just downloaded their pre-print Andrew.
    Some light reading.
    If anybody can produce a global map of 5 degree grid points showing the difference in anomalies, HadCRUT3 minus UAH MSU LT for 30 years 1979-2008 please get in touch.

  4. WSH: The image shows the difference between the original trends in the data and the trends after correcting for spurious effects detected as correlations with socioeconomic variables- They detect a spurious warming trend of about 50% in the land surface data! There are red, orange and yellow cells in the approximate location of the Urbanization effect that Ren et al. found, indicating that that non-climatic factors have indeed caused excess warming trend in that region to be detected (essentially, this confirms Ren et al.’s findings). The actual trend is considerably less!

  5. Thanks Andrew. Have you seen the 2008 Jones et al paper ?

    I have some more comparisons to publish later but there is a stunning backing away from Jones et al 1990 claims that UHI effect did not exceed 0.05 degrees, that’s per century, not per decade !! Now he accepts 0.1 per decade, about a 20 times backdown. The IPCC have quoted that 0.05 per century figure ever since 1990 and still do.

  6. Wow! That’s a heck of a turn around! Definitely going to have to look at this one in depth. Thanks.

  7. Try Google Earth, go to Lijiang in west China at about 27 deg N 100 deg E, view from altitude of 300 km or so. I’ve been there on the ground a few times. Look for Tiger Leaping Gorge, steeper & deeper than the Grand Canyon. Look further west and in 120 km width you meet the Yangtse, Mekong, Salween and Irrawaddy Rivers flowing N-S, with mountain ranges to elevations of 3,800 m or more between them. The eastern downturn of the Himalayas. The population density in these mountains would be about 1 lost yak per 100 sq km. Frequency of weather stations? Not so large. Viewing/shadowing problems, albedo problems for a satellite? I guess they are still working on it. Yet we can write scientifically about 0.1 degree changes? Twaddle.

    Still, the scenery is way better than Switzerland.

  8. Like the USA huh … their surface stations are no better sited than ours.

    Worse, actually. Esp. when it comes to tracking Station History.

  9. Isnt there a simple way of resolving whether UHI is adequately adjusted in these datasets, (no one denies UHI exists)?
    Just compare the warming trend of rural stations, with the UHI adjusted urban stations. (I know there are not as many rural stations but there ought to be enough for this exercise, at the very least in the USA).
    Has that been done? If so what were the results. If it hasnt been done, why not?
    I’m just a layman, but why wouldnt that resolve the issue at least approximately?

  10. Gidday Bill, Can you point out for me where it is described that city station data is adjusted for the UHI in any of the CRUT series datasets ?
    Warwick Hughes

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