Surface temperature over land is estimated from GOES-10/12 sounder retrievals in near real-time at CIMSS.  These estimates approximate the radiometric temperature and emissivity where sky conditions are clear.  Previous work by Diak et al. (1995), Rabin et al. (2000), and others have shown the utility of daytime heating rates of radiometric temperature in estimating daytime sensible heat flux.  The heating rate is obtained by differencing the temperature near its peak in the afternoon from that near sunrise.  (Ideally, the temperature difference should be based on fixed solar times at all locations.  However, for simplicity, 21 -12 UTC has been used.  The results appear to be relatively insensitive to varying the beginning and ending times by as much as 2-3 hours). Using the difference in temperature rather than an average daytime temperature reduces some of the possible errors associated with the temperature estimate from satellite. 

The measured heating rates are also inversely related to surface wetness as follows: 

1) The amount of surface heating is reduced over wet surfaces and locations with active vegetation and adequate root zone moisture.

2) Surface heating increases with drier surfaces where surface evaporation and evapotransporation from vegetation is limited. 

Hence, the measured heating rates may be used to assess the surface wetness.  In a previous study based on data from 1999-2201, heating rates were compared to soil moisture anomalies (from the NOAA Climate Prediction Center) and Vegetation Health (obtained from Felix Kogan at NOAA/NESDIS).  In general, many of the soil moisture anomalies could be detected in the analysis of heating rates from satellite on a monthly time scale. See this link for more details.  It appears that the infrared heating rates may have an advantage over available microwave estimates (from SSM/I) in being able to distinguish varying degrees of dryness. (The microwave observations are mainly sensitive to very wet surfaces).

Two products are shown here:

Absolute Heating Rates.  These images derived from GOES data are color enhanced to emphasis the surface wetness in an absolute sense.  The smaller rates are indicated in green (wet) and the largest rates in yellow and white (dry). In the mean, the images may be related to an absolute measure of soil moisture from the contoured maps of the Climate Prediction Center.  The soil moisture is based on precipitation and temperature data by NCDC climate divisions and a one-layer hydrological model ( Huang et al., 1996).  Precipitation measurements are from the cooperative surface network and other observations.  Hence, the satellite product should be expected to contain more detail (because of its 10 km resolution).  Differences with the modeled soil moisture may also occur due to the model residence time of soil moisture and effects of vegetation not included in the hydrologic model.

Heating Rate Anomalies.  These are deviations of the absolute heating rate from monthly mean heating rate from the 3-year mean  (1999-2001).  Smaller than average heating rates are indicated in green (anomalously wet), larger than average rates in cyan (anomalously dry).  The maps of heating rate anomalies can be compared with soil moisture anomalies from the Climate Prediction Center.  These are based on departures from the 1971-2000 year mean.

    References:

    Diak, G.R., R.M. Rabin, K.P. Gallo, C.M. Neale, 1995: Regional-scale comparisons of NDVI, soil moisture indices from surface and microwave data and surface energy budgets evaluated from satellite and in-situ data. Remote Sensing Reviews, 12, 355-382.

    Huang, J., H. van den Dool, K.P. Georgakakos, 1996: Analysis of model-calculated soil moisture over the United States (1931-93) and application to long-range temperature forecasts. Journal of Climate, 9, No. 6,

    Kogan, F.N., 1997:  Global drought watch from space. Bulletin of the American Meteorological Society, 78, 621-636.

    Rabin, R.M., B. Burns, C. Collimore, G. R. Diak, W. Raymond, 2000: Relating remotely-sensed vegetation and soil moisture indices to surface energy fluxes in vicinity of an atmospheric dryline. Remote Sensing Reviews, 18, 53-82.