Observed landscape responsiveness to climate forcing

Climate variability and change shift environmental conditions on global land surfaces, creating uncertainties in hydrologic flows, crop yields, and land carbon uptake. However, land surfaces 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 Africas diverse climates. This includes observations of land surface temperature from the MSG-2 Spinning Enhanced Visible and InfraRed Imager (SEVIRI) geostationary satellite as well as soil moisture from the Soil Moisture Active Passive (SMAP) satellite. Surface responsiveness is quantified using intra-seasonal energy flux variability, based on the observed diurnal temperature amplitude. We map the land surface 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 non-linear relationship between energy fluxes and soil moisture as well as the marginal distribution of soil moisture. Land surfaces with greater responsiveness to climate are those with soil moisture distributions that span the threshold between water and energy-limited evaporation regimes as well as spend most of their time in the water-limited regime. Since we find these results hold from intra-seasonal to interannual timescales, we expect that these responsive regions will be most vulnerable to long-term shifts in climate forcings. 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.