Satellite-Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

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Abstract

Land surface energetic partitioning between latent, sensible, and ground heat fluxes determines climate and influences the terrestrial segment of land-atmosphere coupling. Soil moisture, among other variables, has a direct influence on this partitioning. Dry surfaces characterize a water-limited regime where evapotranspiration and soil moisture are coupled. This coupling is subdued for wet surfaces, or an energy-limited regime. This framework is commonly evaluated using the evaporative fraction–-soil moisture relationship. However, this relationship is explicitly or implicitly prescribed in land surface models. These impositions, in turn, confound model-based evaluations of energetic partitioning-–soil moisture relationships. In this study, we use satellite-based observations of surface temperature diurnal amplitude (directly related to available energy partitioning) and soil moisture, free of model impositions, to estimate characteristics of surface energetic partitioning–-soil moisture relationships during 10–-20-day surface drying periods across Africa. We specifically estimate the spatial patterns of water-limited energy flux sensitivity to soil moisture (m) and the soil moisture threshold separating water and energy-limited regimes (θ*). We also assess how time evolution of other factors (e.g., solar radiation, vapor pressure deficit, surface albedo, and wind speed) can confound the energetic partitioning–-soil moisture relationship. We find higher m in drier regions and interestingly similar spatial θ* distributions across biomes. Vapor pressure deficit and insolation increases during drying tend to increase m. Only vapor pressure deficit increases in the Sahelian grasslands systematically decrease θ*. Ultimately, soil and atmospheric moisture availability together play the largest role in land surface energy partitioning with minimal consistent influences of time evolution of other forcings.

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Feldman, A. F., Short Gianotti, D. J., Trigo, I. F., Salvucci, G. D., & Entekhabi, D. (2019). Satellite-Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables. Water Resources Research, 55(12), 10657–10677. https://doi.org/10.1029/2019WR025874

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