But burying their heads in denial over
UHI contamination problems — this only makes them look anti-scientific.
Also, are we certain that
UHI contamination does not affect the models?
This was an ingenious method of detecting
the UHI contamination indirectly, rather than examining the individual records and locations.
If you're now agreeing that it doesn't matter then, terrific, we all agree:
UHI contamination is a serious problem.
Of course Hinkel et al show that very clearly, but even a team player has shown that the assumption of rural sites being free of
any UHI contamination is very questionable.
But eventually cities will grow and
UHI contamination will creep into the record.
Narrowing of Diurnals, narrowing of varience in Tmin, is a first order sign of of
UHI contamination.
How much
UHI contamination remains in the global mean temperatures has been tested in papers such as Parker (2005, 2006) which found there was no effective difference in global trends if one segregates the data between windy and calm days.
Not exact matches
If we look at the trends since records began, noting that there are longitudinal problems (changes in locations of weather stations, +
UHI effects) and
contamination by human analysts (data trickery), the trends seem cyclical in periods of around 60 years.
Tagged Chris de Freitas, economic
contamination, Gavin Schmidt, Patrick Michaels, Ross McKitrick, surface temperature,
UHI
But that doesn't seem consistent with the idea of «improving» the data quality at each station and removing
contamination like
UHI, TOBS, and sawtooth drift - correction patterns.
As a starting point, I think sat - temps are high enough in the atmosphere to eliminate or minimalize
UHI «
contamination», but IMO it's not impossible that
UHI could produce plumes of localized warm areas above / downwind of large developed regions at sat - temp elevations, but I don't know for sure.