Quantitative precipitation forecasting (QPF) is the most important and significant challenge of weather forecasting. Advances in computing and observational technology combined with theoretical advances regarding the chaotic nature of the atmosphere offer the possibility of significant improvement in QPF. To achieve these improvements, this report recommends research focusing on 1) improving the accuracy and temporal and spatial resolution of the rainfall observing system; 2) performing process and climatological studies using the modernized observing system; 3) designing new data-gathering strategies for numerical model initialization; and 4) defining a probabilistic framework for precipitation forecasting and verification. Advances on the QPF problem will require development of advanced ensemble techniques that account for forecast uncertainty, stemming from sampling error and differences in model physics and numerics and development of statistical techniques for using observational data to verify probabilistic QPF in a way that is consistent with the chaotic nature of the precipitation process.
|Original language||English (US)|
|Number of pages||15|
|Journal||Bulletin of the American Meteorological Society|
|State||Published - Jan 1 1998|
All Science Journal Classification (ASJC) codes
- Atmospheric Science