Quantifying land-atmosphere interaction with satellite remote sensing: Current capabilities, findings, and limits

The impact of atmospheric forcing (precipitation, radiation) on the land surface state may be readily observed via surface water, surface soil moisture, and regional vegetation composition. Conversely, the influence of the land surface state on the initiation, development, and triggering of convective precipitation, is a much more subtle signal, but with important implications for “hydrologic intensification” that may occur under a changing climate. Improving our ability to identify, understand, and properly parameterize the many mechanisms that comprise land-atmosphere interaction or “coupling” is recognized by the World Climate Research Programme (WCRP) Global Energy and Water Cycle Experiment (GEWEX) as a key step towards improving short to medium-range forecast skill.

In the past, coupling research has been based on the analysis of model outputs. Alan Betts developed many of the coupling diagnostics using ERA-40. Randy Koster identified soil moisture ‘hot spots' for seasonal prediction. And inter-model variability has been explored in-depth by the Global Land-Atmosphere Coupling Experiment (GLACE) led by Paul Dirmeyer. Today, a more than 30-year record of surface states (soil temperature, soil moisture, and vegetation) and fluxes (water vapor and radiation) are available from satellite remote sensing (RS), making feasible observation-based analyses.

We provide a global map of the spatial distribution of land-atmosphere coupling as derived from satellite remote sensing, which we inter-compare with model-predicted coupling patterns from the GLACE. Contributing RS data products include those from the: GEWEX Surface Radiation Budget (SRB) Experiment, International Satellite Cloud Climatology Project (ISCCP), Atmospheric InfraRed Sounder (AIRS), TIROS Operational Vertical Sounder (TOVS), Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR), Advanced Microwave Scanning Radiometer - EOS (AMSR-E), TRMM Microwave Imager (TMI), and Scanning Multichannel Microwave Radiometer (SSMR). Then, centered over the southern Great Plains- the North American ‘hot spot' for coupling- we address the following questions: (1) Are the accuracies and characteristics of RS data products (often less than 2x daily and ~ 40km) sufficient for the purpose of quantifying coupling?; (2) Compared to in-situ metrics that focus on the diurnal evolution of the planetary boundary layer, how similar are the coupling strengths and patterns derived via remote-sensing?; and (3) Can we develop a new remote sensing-based multi-metric decision tree for quantifying coupling? For the baseline in our comparisons, we use the soil moisture – cloud base height correlation of Alan Betts and the humidity index – convective triggering potential regime classification of Kirsten Findell and Elfatih Eltahir. The accuracies of both the data and metrics are evaluated using ground meteorological observations, such as those from the Oklahoma Mesonet.