B038-0002
Mutually-exclusive Global Wetland, Lake, and Reservoir Methane Emissions Data Sets
Wednesday, 9 December 2020
Poster
Matthew S Johnson, NASA Ames Research Center, Moffett Field, CA, United States, Elaine Matthews, Bay Area Environmental Research Institute, Moffett Field, CA, United States, Vanessa B Genovese, CSU, Monterey Bay, Moffett Field, CA, United States, Jinyang Du, University of Montana, Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, Missoula, MT, United States, David Bastviken, Linköping University, Linköping, Sweden, Yoichi Paolo Shiga, Universities Space Research Association Moffett Field, Moffett Field, CA, United States and Alice Hsu, University of California, Berkeley, Berkeley, United States
Abstract:
Methane (CH4) is emitted from a variety of sources, both natural and anthropogenic, and is the second most important greenhouse gas contributing to climate change. Natural wetlands are the largest single contributor to annual global CH4 emissions and other inland water sources, such as lakes and reservoirs, produce CH4 but have received less attention on a global scale. These inland water emission sources are among the most uncertain components of the global CH4 cycle. These uncertainties stem from numerous issues, including the vast variability in these ecosystems and their sensitivity to meteorological and climate variations. Existing CH4 emission models display large differences in wetland spatial extent and include simplified, or lack all together, wetland-type classifications. Furthermore, lakes and reservoirs are commonly mixed with wetlands, but not identified as such, leading to double counting of wetland areas on a global scale. These uncertainties and caveats result in the critical need for source data that describe CH
4-relevant classes within
wetlands, lakes, and reservoirs (WLR), in addition to accurate and independent spatial distributions of each inland water source.
This study focused on the development of a suite of mutually-exclusive data sets of WLR including global distributions (0.25° × 0.25° spatial resolution) of areas, CH4-centric type classifications, and daily CH4 emission rates driven by remote-sensing freeze/thaw dynamics (hereafter WLR-CH4). This project thereby comprises separate emissions data for WLR, the first spatially-explicit global data set of lake and reservoir CH4 emissions, and wetland emissions comprising numerous different wetland-types. The focus of this presentation is to show the final results of the WLR-CH4 data set including global distributions of WLR areas and type classification, CH4 emissions, and initial evaluation through the inter-comparison with existing wetland CH4 models (e.g., WETCHIMP, WetCHARTs v1.0) and atmospheric observations in North America (using a top-down geostatistical atmospheric transport model). The presentation will include discussion of the novelty of this data set which could aid future modeling studies of WLR CH4 emissions and their contribution to the global CH4 cycle.
