Hydrological Sciences Branch Seminar: Dr. Ana Pinheiro

Remote Sensing and Applications Division/NOAA NCDC
Land Surface Temperature (LST) is a proxy of the surface energy state and is routinely estimated from NASA's remote sensing satellites. Assimilation of LST into a land surface model should therefore improve estimates of land surface fluxes. Over the past 8 years we have developed LST products from AVHRR and MODIS platforms. Most recently we have been building a framework to assimilate these products into the Land Information System's (LIS) land surface models. Specifically, we implemented an Ensemble Kalman filter for the Community Land Model (CLM) within LIS. This process revealed several limitations in the retrieved LST products, our assimilation implementation and the CLM2.0 model physics. In this presentation we will describe some of the challenges encountered in our efforts. Further, we will investigate the sensitivity of the model estimates to LST accuracy and assimilation frequency. This project was developed in support of the Bureau of Reclamation's irrigation decision support tools, in New Mexico, and we use this area as our test bed.