The Promise of Microwave Remote Sensing for Understanding Dryland Carbon-Water Dynamics
Steven A. Kannenberg1,2* (email@example.com), William R. L. Anderegg3,4, Mallory L. Barnes5, Alan K. Knapp2
1Department of Biology, West Virginia University, Morgantown, WV; 2Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO; 3School of Biological Sciences, University of Utah, Salt Lake City, UT; 4Wilkes Center for Climate Science and Policy, University of Utah, Salt Lake City, UT; 5O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN
Dryland ecosystems occupy ~40% of Earth’s land surface and exert an outsized role in shaping global carbon and water cycling. Unfortunately, dryland ecosystems are notoriously difficult to study at broad scales, due to their large spatial and temporal heterogeneity. As such, fundamental ecological questions remain unresolved in drylands. For example, what is the role of atmospheric drivers versus soil moisture in controlling carbon-water fluxes? And which soil moisture pools (shallow versus deep) matter the most for ecosystem function? To assess these questions, researchers synthesized gross primary productivity (GPP) and evapotranspiration (ET) data from all eddy covariance towers located in American drylands, most of which contained soil moisture depth profiles. Researchers found that GPP and ET were most sensitive to fluctuations in shallow soil moisture and varied only slightly in response to other drivers such as vapor pressure deficit, temperature, and light. Researchers then assessed the ability of land surface models to properly capture this dynamic by comparing the soil moisture sensitivity of in situ ecosystem fluxes to output from 15 CMIP6 models. The team found that these models significantly underestimated the sensitivity of GPP to soil moisture fluctuations and overestimated the sensitivity of ET. Finally, the team evaluated the degree to which six different l-band and x-band microwave remote sensing products could accurately capture fluctuations in GPP and ET and found that they were tightly linked to ecosystem fluxes on a daily timescale. The significant ability of these products to capture dryland fluxes at a high frequency was due to the fact that they generally tracked soil moisture dynamics. The results indicate that microwave remote sensing products show great promise for capturing the dynamics of dryland ecosystem function and suggest that assimilation of these data into existing land surface models may improve simulations of dryland fluxes.