UCLA

Accurate weather forecast information has the potential to improve water resources management, energy, and agriculture. This study evaluates the accuracy of recently developed short-range (0- 18 hour) precipitation forecasts from the High-Resolution Rapid Refresh (HRRR) for selected extreme events over the US using NOAA’s Gauge-corrected Multi-Radar/Multi-Sensor (MRMS- GC) radar-gauge merged rainfall observations. This study also evaluates the accuracy of medium-range (1-15 day) precipitation forecasts from the Global Forecast System (GFS) over transboundary river basins in Africa using NASA’s Integrated Multi-satellitE Retrievals (IMERG) “Final Run” satellite-gauge merged rainfall observations. The assessment of HRRR on an hourly basis shows that there was a good agreement between the forecasted and observed precipitation in terms of temporal variability despite the forecasts tend to overestimate rainfall for hurricanes. Spatially, the forecasts were able to capture the general spatial pattern of hurricane driven events but failed to reproduce the characteristics of frontal storms. With regard to the effect of lead times, the 1-h lead forecasts have often lower accuracy than the other lead-time forecasts, while there was not much systematic difference in accuracy among the 2-h to 18-h lead-time forecasts. The evaluation of GFS reveals that the accuracy of forecasts varies a lot among different regions. GFS forecasts tend to overestimate precipitation in the wet climatic regimes but produce almost unbiased precipitation in dry regions. The GFS forecast accuracy decreases as the lead time increases, but the rate of decrement depends on the region. Aggregating the forecasts at temporal scales (1-day to 15-day) may increase or decrease the performance of GFS forecasts, depending on the region. We recommend exploring methods to increase the performance of short-range and medium-range forecasts, including post-processing techniques products before their application in water resources management.