Diurnal energy cycles and net water vapor fluxes in mountain watersheds
Abstract ID: 3.11774 | Accepted as Talk | Talk/Oral | TBA | TBA
Ethan Gutmann (0)
Lundquist, Jessica (2), Kirshbaum, Daniel (3), Hogan, Danny (2), Schwat, Eli (2), Adler, Bianca (4)
Ethan Gutmann ((0) NSF National Center for Atmospheric Research, 3090 Center Green Dr, 80301, Boulder, Colorado, US)
Lundquist, Jessica (2), Kirshbaum, Daniel (3), Hogan, Danny (2), Schwat, Eli (2), Adler, Bianca (4)
(0) NSF National Center for Atmospheric Research, 3090 Center Green Dr, 80301, Boulder, Colorado, US
(1) NSF National Center for Atmospheric Research
(2) University of Washington
(3) McGill University
(4) NOAA Physical Sciences Laboratory
(2) University of Washington
(3) McGill University
(4) NOAA Physical Sciences Laboratory
Mountain meteorology and hydrology are difficult to model due to fine spatial scales and strong land-atmosphere feedbacks. Mountain topography organizes both atmospheric motions and hydrologic processes affecting both mountain hydrology and weather predictions. Here we use data from the SAIL, SPLASH, and SOS field campaigns to study mountain valley winds and water vapor fluxes in the East River Basin. We will combine these observations with satellite data and high-resolution snow and atmospheric modeling to quantify feedbacks between surface fluxes, winds, and cloud cover. Surface stations along a transect in the East River basin are used to measure valley-scale flows over different catchment areas and their interaction with local and basin scale snow cover. Initial results show that daytime upvalley circulation patterns vary with snow cover presence, and that there is a strong non-linear feedback between valley wind strength and surface sublimation fluxes due to the importance of blowing snow. Winter surface fluxes are linked to wind speed, snow shear strength, and available energy, controlling mid-winter sublimation. This has important implications for the parameterization of mountains in atmospheric and macroscale hydrology models. This research will lead to enhanced mountain hydroclimate models while highlighting biases in existing high-resolution atmospheric simulations, especially regarding cloud and snow cover feedbacks in high alpine terrain.
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