{"501531":{"#nid":"501531","#data":{"type":"event","title":"PhD Dissertation Defense by Liao-Fan Lin","body":[{"value":"\u003Cp\u003EAdvisor: Dr. Rafael L. Bras (CEE)\u003C\/p\u003E\u003Cp\u003ECommittee Members:\u003C\/p\u003E\u003Cp\u003EDr. Aris P. Georgakakos (CEE), Dr. Jingfeng Wang (CEE), Dr. Emanuele Di Lorenzo (EAS), and\u003Cbr \/\u003EDr. Alejandro N. Flores (Boise State U.)\u003C\/p\u003E\u003Cp\u003EAbstract:\u003Cbr \/\u003EEnvironmental monitoring of Earth from space has provided invaluable information for understanding of the\u0026nbsp;land-atmosphere water and energy exchanges. However, the use of satellite observations in hydrologic applications is\u0026nbsp;often limited by coarse space-time resolutions. This study aims to develop a data assimilation system that integrates\u003Cbr \/\u003Eremotely-sensed precipitation and soil moisture observations into physically-based models to produce fine-scale\u0026nbsp;precipitation, soil moisture, and other relevant hydrometeorological variables. This is particularly useful with the\u0026nbsp;active Global Precipitation Measurement and Soil Moisture Active Passive missions. The system consists of two\u0026nbsp;major components: (1) a framework for dynamic downscaling of satellite precipitation products using the Weather\u003Cbr \/\u003EResearch and Forecasting (WRF) model with four-dimensional variational data assimilation (4D-Var) and (2) a\u0026nbsp;variational data assimilation system using spatio-temporally varying background error covariance for directly\u0026nbsp;assimilating satellite soil moisture data into the Noah land surface model coupled with the WRF model. The WRF\u0026nbsp;4D-Var system can effectively assimilate and downscale six-hour precipitation products of a spatial resolution of\u0026nbsp;about 20 km (i.e., those derived from the National Centers for Environmental Prediction Stage IV data and the\u0026nbsp;Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset) to hourly precipitation with a spatial resolution of less\u0026nbsp;than 10 km. The system is able to assimilate and downscale daily soil moisture products at a gridded 36-km\u0026nbsp;resolution obtained from the Soil Moisture and Ocean Salinity (SMOS) mission to produce hourly 4-by-4-km surface\u0026nbsp;soil moisture forecasts with a reduction of mean absolute error by 35% on average. The results from the system with\u003Cbr \/\u003Ecoupled components show that assimilation of the TRMM 3B42 precipitation improves the quality of both\u0026nbsp;downscaled precipitation and soil moisture analyses, while the effect of SMOS soil moisture data assimilation is\u0026nbsp;largely on the soil moisture analyses. The downscaled WRF precipitation with and without assimilation of TRMM\u0026nbsp;precipitation was preliminarily tested with a spatially distributed simulation of streamflow using the TIN (Triangular\u0026nbsp;Irregular Network)-based Real-time Integrated Basin Simulator (tRIBS).\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Data Assimilation and Dynamical Downscaling of Remotely-Sensed Precipitation and Soil Moisture from Space"}],"uid":"27690","created_gmt":"2016-02-17 10:58:04","changed_gmt":"2016-10-08 02:16:30","author":"Jacquelyn Strickland","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-03-04T11:30:00-05:00","event_time_end":"2016-03-04T13:30:00-05:00","event_time_end_last":"2016-03-04T13:30:00-05:00","gmt_time_start":"2016-03-04 16:30:00","gmt_time_end":"2016-03-04 18:30:00","gmt_time_end_last":"2016-03-04 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"119191","name":"PhD Dissertation Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}