Update 26/4: The feedback should really be calculated by the ratio DT1/DT2 = 1-g0F. Applying this for the full period of CRUTEM4 data 1900-2005 the value derived for F= -1.5+/- 0.8 Wm-2K-1.
I have been studying differences in climate data between those areas of the world with very low atmospheric water vapour (Deserts and Polar regions) and those areas with very high water vapour content (Tropical Wet regions). The data set consists of all 5500 station data corresponding to CRUTEM4 kindly provided by the UK Met office. Each station has then been classified by climatology using it’s geographic location and a lat,lon grid based on the Köppen-Geiger climate classification .
We define ARID stations as all those situated in Deserts or Polar regions i.e. those in areas with precipitation ‘W’ or climate ‘E’ in . These areas have the lowest atmospheric water content on Earth. The WET stations instead are defined as those within Tropical fully humid areas – ‘Af” in . These include tropical rain-forests and have the highest atmospheric water vapour content on Earth. In a previous post I already showed that the temperature anomalies in the Sahara rose faster than a similar area in S. Asia, so I wanted to extend this study globally using the latest CRUTEM4 data. I therefore calculated the global anomalies for both sets of stations ARID and WET using the same algorithm as used for CRUTEM4. The results are shown in Figure 1.
There is a clear trend in the data that ARID stations cool faster and warm faster than WET stations. They seemingly react stronger to external forcing. The WET humid stations respond less than both the ARID stations and the global average. The location of the stations are shown in Figure 2 which is taken from reference . The ARID stations are the yellow desert areas and the light blue polar areas. The WET stations are located in the red zones – Amazon, central Africa and SE. Asia.
We will assume that there are external forcings on the climate both anthropogenic and natural which are reflected in temperature anomalies. If we label the forcing DS and the consequent change in temperature anomaly as DT.
DT1 = g1*DS for ARID and DT2 = g2*DS for WET. We then divide the last 110 years of data into 3 main time periods to measure DT1 and DT2, and assume that DS is a universal global external forcing ( for example due to CO2 )
|1900 – 1940:||0.4+- 0.05||0.18+-0.05||-0.22+-0.07|
|1940 – 1970:||-0.11+-0.05||-0.03+- 0.05||0.08+-0.07|
|1970 – 2005:||0.83+-0.05||0.60+- 0.05||-0.23+-0.07|
Critics may argue that heat inertia effects due to nearby oceans are causing tropical climates react slower than desert regions. However, the IPCC argues that feedbacks from increased water evaporation will lead to enhanced warming. This is not observed in those regions most affected by water vapour. In fact the opposite seems to be the case implying negative feedback. If we make the assumption that there have been 3 separate forcings for the 3 time periods above and that there is no other difference other than humidity, then we can estimate the water feedback F. Taking F=0 for ARID stations:
(DT2-DT1) = F*DS ; where DT1 = g0*DS and DT2 = (g0+F)*DS
F/g0 for the 3 periods : -0.5+-0.1 , -0.7+-0.1 , -0.3+-0.1
Average Feedback parameter = -0.5 (+- 0.1)*g0 which taking G0 = the Stefan-Boltzman value 4*sigma*T^3 = 3.75W/m2K-1.
Water Feedback = – 1.8 +- 0.2 W/m2K-1
Remarkably this is the same value as that derived from a simple argument regarding the Faint Sun paradox see here. It has been pointed out by Richard Lindzen  that much of the Earth’s heat is transported bodily through evaporation and convection to the upper atmosphere where IR opacity is low and can then escape to space. Therefore water feedback effects depend on the water vapor content of the upper atmosphere more than that at the surface. Increased evaporation, convection and rain out could even dry out the upper atmosphere. This could be a possible mechanism for negative feedbacks. Such effects would be much smaller in ARID areas with little or no evaporation.
1. Rubel, F., and M. Kottek, 2010: Observed and projected climate shifts 1901-2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorol. Z., 19, 135-141. DOI: 10.1127/0941-2948/2010/0430. http://koeppen-geiger.vu-wien.ac.at/
2. Richard Lindzen, Some uncertainties with respect to water vapor’s role in climate sensitivity. Proceedings NASA workshop on the role of Water Vapor in Climate Processes.