Observed Landscape Responsiveness to Climate Forcing

Climate variability and change shift environmental conditions on global land surfaces, creating uncertainties in predicting hydrologic flows, crop yields, and land carbon uptake. Land surfaces can present varying degrees of inertia to atmospheric forcing variability (e.g., precipitation). This study asks: are regions with the most variable environmental forcing necessarily the regions with the largest land surface variability? Specifically, it seeks to determine why land surfaces show varying responsiveness to environmental forcing. The degree to which and the mechanisms for how landscapes modulate the forcing are evaluated using a decade-long satellite observation record of Africa's diverse climates. Surface responsiveness is quantified using intra-seasonal energy flux variability, based on the observed diurnal temperature amplitude. We map the responsiveness and analyze the underlying mechanisms over intra-seasonal timescales (especially interstorms). We show that, at a location, land surface responsiveness is dependent on the soil moisture distribution and the nonlinear relationship between energy fluxes and soil moisture. Land surfaces with greater responsiveness to climate are those with soil moisture distributions that span the threshold between evaporation regimes and spend most of their time in the water-limited regime. Consequently, surface responsiveness mechanisms drive land surface variability beyond high climatic variability. Since we find these results to hold from intra-seasonal to interannual timescales, we expect that these responsive regions will be most vulnerable to long-term shifts in climate forcing. The quantification of these phenomena and determination of their geographic distributions based on observations can help assess land surface models used to evaluate hydrologic consequences of climate change.

Automated summary

Climate variability and change have uncertain effects on land surfaces, and this study uses satellite observations to evaluate the responsiveness of land surfaces to environmental forcing. The researchers find that soil moisture distribution and the nonlinear relationship with energy fluxes are important factors in determining land surface responsiveness. These findings are important for assessing hydrologic consequences of climate change.