Dear colleagues, we would like to draw your attention to our AGU session: Mapping and scaling surface-atmosphere biogeochemical, water, and energy fluxes We invite contributions that improve our understanding of surface-atmosphere exchange attribution and scaling, and especially encourage studies that use hierarchies of observations, as well as approaches that explore processes at model sub-grid scales. The full session description can be found below and here <https://agu.confex.com/agu/fm16/preliminaryview.cgi/Session12972>. Invited and confirmed speakers - Ken Davis (Pennsylvania State University) - Kusum Naithani (University of Arkansas) Abstract submission To submit an abstract, please visit the AGU abstract submission site <https://agu.confex.com/agu/fm16/preliminaryview.cgi/Session12972>, deadline is August 3. In previous years this developed into a well-attended session, and with your contribution we hope for a similar success this year.
Please feel free to contact us with any questions! Stefan, Ankur, Cove and Andy. Full session description Session title: Mapping and scaling surface-atmosphere biogeochemical, water, and energy fluxes <https://agu.confex.com/agu/fm16/preliminaryview.cgi/Session12972> ID: 12972 (Biogeosciences) Organizers: Stefan Metzger (NEON), Ankur Desai (U Wisconsin), Cove Sturtevant (NEON), Andy Fox (NEON) Our understanding of energy, water and greenhouse gas cycling between the earth’s surface and its atmosphere is grounded in in-situ observations. Eddy-covariance provides one of the most direct methods for this purpose, and its widespread use across tower flux networks such as AmeriFlux, ICOS and NEON in addition to aircraft applications enables insights from local to global scales. However, eddy-covariance relies on simplifications of the mass balance concept, and suffers from biases such as limited and varying spatial representativeness, and energy balance non-closure. This session focuses on the complementary strengths of in-situ, remotely sensed and ancillary information for determining unbiased surface-atmosphere exchange at scales suitable for model-data fusion. We welcome contributions that quantify, map, or aggregate spatio-temporal patterns across scales, thus improving conceptual and quantitative understanding. Especially encouraged are studies using spatio-temporal hierarchies of observations, and data-driven and mechanistic approaches that explore processes at model sub-grid scales (< 100 km2). ------------------------------------------------- Ankur R Desai N.P. Smith Professor of Climate Science Dept of Atmospheric and Oceanic Sciences University of Wisconsin - Madison http://flux.aos.wisc.edu <http://flux.aos.wisc.edu/> [email protected] <mailto:[email protected]>
