Scale-Dependent Uncertainties in Global QPFs and QPEs from NWP Model and Satellite Fields

Abstract

Global precipitation forecasts from numerical weather prediction (NWP) models can be verified using the near-global coverage of satellite precipitation retrievals. However, inaccuracies in satellite precipitation analyses complicate the interpretation of forecast errors that result from verification of an NWP model against satellite observations. In this study, assessments of both a global quantitative precipitation estimate (QPE) from a satellite precipitation product and corresponding global quantitative precipitation forecast (QPF) from a global NWP model are conducted using available global land-based gauge data. A scale decomposition technique is devised, coupled with seasonal and spatial classifications, to evaluate these inaccuracies. The results are then analyzed in context with various physical precipitation systems, including heavy monsoonal rains, light Mediterranean winter rains, and North American convective-related and midlatitude cyclone-related precipitation.In general, global model results tend to consistently overforecast rainfall, whereas satellite measurements present a mixed pattern, underestimating many large-scale precipitation systems while overestimating many convective-scale precipitation systems. Both global model QPF and satellite-retrieved QPE showed better correlation scores in large-scale precipitation systems when verified with gauge measurements. In this case, model-based QPF tends to outperform satellite-retrieved QPE. At convective scales, there are significant drops in both model QPF and satellite QPE correlation scores, but satellite QPE performs slightly better than model QPF. These general results also showed regional and seasonal variation. For example, in tropical monsoon systems, satellite QPE tended to outperform model-based QPF at both scales. Overall, the results suggest potential improvements for both satellite estimates and weather forecast systems, in particular as applied to global precipitation forecasts.

Spatial verification using wavelet transforms: a review

“…To the best of our knowledge, there is no spatial verification score or refined methodology based on 2D CWT. However, Lu et al (); Wang and Lu () use 2D CWT as a diagnostic tool in the evaluation of precipitation and wind fields. Lu et al () apply a 2D CWT with an isotropic halo wavelet to global QPFs and satellite observations to extract distributions for two spatial scales (200 and 1000 km).…”

Intercomparison of High-Resolution Precipitation Products over Northwest Europe

“…The global atmospheric models provide precipitation estimates based on a physically consistent environment that, despite many modeling uncertainties, can outperform products constructed from individual observation types (Ebert et al 2007;Lu et al 2010). However, NWP models occupy a unique position since they incorporate a large volume of diverse, mostly satellite-based observations that may also include cloudand precipitation-affected regions.…”

Gridded daily Indian monsoon rainfall for 14 seasons: Merged TRMM and IMD gauge analyzed values

“…This bias fluctuates from year to year. Satellite rainfall estimates show regional and seasonal variations in biases also (Lu et al 2010). Region specific biases have to be corrected by inclusion of said conventional observations (Mitra et al 2003(Mitra et al , 2009.…”