THE OVERARCHING GOAL OF THIS PROPOSAL IS TO IMPROVE THE CAPABILITY OF LAND-ATMOSPHERE MODELING WITH THE NASA UNIFIED WEATHER RESEARCH AND FORECASTING MODEL (NU-WRF) USING STRONGLY COUPLED DATA ASSIMILATION. STRONGLY COUPLED DATA ASSIMILATION CAN ESTIMATE CROSS-MODEL ERROR COVARIANCE THUS IT ENABLES THE CORRECTION OF LAND SURFACE AND ATMOSPHERIC VARIABLES SIMULTANEOUSLY AND RESULTS IN IMPROVED LAND-ATMOSPHERE COUPLING WITH CONSISTENCY BETWEEN LAND AND ATMOSPHERE. PREVIOUS STUDIES FROM THE PI S GROUP HAVE PROVED THAT A STRONGLY COUPLED LAND-ATMOSPHERE OUTPERFORMS THE TRADITIONAL WEAKLY COUPLED METHOD IN NUMERICAL WEATHER PREDICTION. THIS PROJECT PLANS TO: IMPLEMENT STRONGLY COUPLED LAND-ATMOSPHERE DATA ASSIMILATION WITH NU-WRF AND MAKE IT PART OF THE NASA NU-WRF DATA ASSIMILATION OPTIONS FOR THE RESEARCH COMMUNITY ALONG WITH THE NASA LAND INFORMATION SYSTEM (LIS). EXAMINE THE INFLUENCE OF STRONGLY COUPLED LAND-ATMOSPHERE DATA ASSIMILATION ON ACCURATE NUMERICAL SIMULATIONS OF EXTREME WEATHER SYSTEMS. UNDERSTAND THE IMPACT OF COUPLED LAND-ATMOSPHERE DATA ASSIMILATION ON IMPROVED REPRESENTATION OF NEAR-SURFACE AND BOUNDARY LAYER ATMOSPHERIC CONDITIONS. STUDY THE PROCESSES ASSOCIATED WITH LAND-ATMOSPHERIC INTERACTION AND THE EVOLUTION OF ATMOSPHERIC BOUNDARY LAYER STRUCTURES DURING EXTREME WEATHER EVENTS.