SATELLITE PRECIPITATION PRODUCTS (SPPS) THOUGH ADVANCING IN ACCURACY AND RESOLUTION ARE SUSCEPTIBLE TO SYSTEMATIC BIAS AND RANDOM ERROR. THE PROPOSED WORK WILL ADDRESS SPP ERROR CHARACTERIZATION FOR DATA-LIMITED REGIONS PRECIPITATION ENSEMBLE GENERATION AND LANDSLIDE HAZARD APPLICATIONS. INSTEAD OF RELYING ON GROUND-BASED REFERENCE DATA (I.E. RAIN GAGES) TO ESTIMATE MODEL PARAMETERS LIKE MOST SPP ERROR MODELS DO THIS PROJECT WILL ANALYZE RELATIONSHIPS BETWEEN REGIONAL VARIABLES (INCLUDING CLIMATE ELEVATION LAND COVER AND HYDROCLIMATE) AND ERROR MODEL PARAMETERS TO CREATE A REGIONALIZATION FRAMEWORK. THEN THE CENSORED SHIFTED GAMMA DISTRIBUTION (CSGD) ERROR MODEL WILL BE APPLIED USING ONLY REGIONAL VARIABLES EXTENDING SPP ERROR CHARACTERIZATION TO AREAS THAT LACK GROUND REFERENCE DATA. THIS PROJECT WILL SIGNIFICANTLY EXPAND ON THE CSGD ERROR MODEL TO DEVELOP A METHOD FOR GENERATING LARGE PRECIPITATION ENSEMBLES REPRESENTING RANGES OF POSSIBLE RAINFALL. ENSEMBLE RAINFALL VALUES WILL BE RANDOMLY GENERATED FROM ERROR DISTRIBUTIONS CONDITIONED ON SPP OBSERVATIONS. PRECIPITATION ENSEMBLES WILL BE USED AS INPUT TO TEST THE LANDSLIDE HAZARD ASSESSMENT FOR SITUATIONAL AWARENESS (LHASA) MODEL WHICH DOESN T CURRENTLY ACCOUNT FOR SPP ERRORS AS A PROBABILISTIC MONITORING SYSTEM FOR LANDSLIDE HAZARD. THESE PROBABILISTIC HAZARD ASSESSMENTS WILL ALSO EXPLORE THE CHALLENGES OF PRESENTING PROBABILISTIC RISKS TO PUBLIC AUDIENCES. THE PROPOSED WORK ADVANCES UNDERSTANDING OF PRECIPITATION S ROLE IN EARTH S WATER AND ENERGY CYCLES AND IS ESSENTIAL TO ENVIRONMENTAL MODELING APPLICATIONS IN DATA-LIMITED REGIONS. ACCOUNTING FOR SPP ERROR IN LHASA WILL PROVIDE MORE USEFUL HAZARD ASSESSMENTS TO THOSE LIVING IN LANDSLIDE-PRONE REGIONS AROUND THE WORLD WHILE THE ENSEMBLE GENERATION METHOD WILL BE BROADLY USEFUL IN ENVIRONMENTAL MODELING AND MONITORING APPLICATIONS.