WRF model forecasts and their use for hydroclimate monitoring over southern South America

OMAR V. MÜLLER; MIGUEL A. LOVINO; ERNESTO H. BERBERY

Vienna

Congreso; European Geosciences Union General Assembly 2017; 2017

European Geosciencies Union

Weather forecasting and monitoring systems based on regional models arebecoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive andmonitoring capabilities of a system based on WRF model simulations at15 km grid spacing over a domain that encompasses La Plata Basin(LPB) in southern South America, where agriculture and waterresources are essential. The model?s skill up to a lead-time of 7days is evaluated with daily precipitation and 2m temperature in-situobservations. Results show high prediction performance with 7 dayslead-time throughout the domain and particularly over LPB, whereabout 70% of rain and no-rain days are correctly predicted. Thescores tend to be better over humid climates than overarid-to-semiarid climates. Compared to the arid-semiarid climate, thehumid climate has a higher probability of detection and less false alarms. The ranges of the skill scores are similar to those foundover the United States, suggesting that proper choice ofparameterizations lead to no loss of performance of the model. Dailymean, minimum and maximum forecast temperatures are highly correlatedwith observations up to 7 day lead time. The best performance is fordaily mean temperature, followed by minimum temperature and aslightly weaker performance for maximum temperature over aridregions. The usefulness of WRF products for hydroclimate monitoringwas tested for an unprecedented drought in southern Brazil and for aslightly above normal precipitation season in northeastern Argentina.In both cases the model products reproduce the observed precipitationconditions with consistent impacts on soil moisture,evapotranspiration and runoff. This evaluation validates the model?susefulness to fore-cast weather up to one week and to monitor climateconditions in real time. The scores suggest that the forecast lead-time can be extended into week two, while bias correction methods can reduce part of the systematic errors.