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Retrospective high-resolution SWE analysis using MERRA, Landsat and data assimilation: An exercise o

Friday, November 20, 2015, 12:00PM - 1:00PM


Gonzalo Cortés

UCLA PhD candidate; incoming INSTAAR postdoc


SEEC room C120

4001 Discovery Drive

Please join the Molotch Lab group for a noon seminar with guest speaker, an incoming postdoctoral fellow from UCLA. Feel free to bring your lunch.

Full title

Retrospective high-resolution SWE analysis using MERRA, Landsat and data assimilation: An exercise over the South American Andes


The extratropical Andes are an important source of water storage for the countries of Chile and Argentina. The high elevation and mediterranean climatology allows for the existence of a seasonal snow reservoir that spans latitudes from 20°S to 40°S. This reservoir melts during the spring and summer months, resulting in a secure water supply for a semi-arid region with a significant agricultural development. An accurate characterization of the dynamics of this snowpack would represent a significant value to water planners, however this is a difficult task since the snow data over the region is scarce or non-existent. The Andes Snow Reanalysis aims to integrate present and future remote sensing measurements with model estimates via data assimilation. The integration results in relatively high-resolution (180 m) daily ensemble SWE fields that are conditioned by the Landsat Snow Covered Area depletion record and by model and forcing uncertainty. The methodology constitutes an example of how Bayesian principles can be applied to integrate data from different tools including models, atmospheric reanalyses and remote sensing into one common estimation framework. The resulting estimate of snowpack states represents the theoretical optimal combination between different uncertain datasets.