With the ARPS (Advanced Regional Prediction System) Data Analysis System (ADAS) and its complex cloud analysis scheme, the reflectivity data from a Chinese CINRAD-SA Doppler radar are used to analyze 3D cloud and hydrometeor fields and in-cloud temperature and moisture. Forecast experiments starting from such initial conditions are performed for a northern China heavy rainfall event to examine ...

This study evaluated the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) forecast bias in different precipitation (light rain, moderate rain, heavy rain and very heavy rain) by comparing the ground-based observations in three countries. Then the correlations between GFS precipitation forecast errors and the aerosol loading are investigated extensively to examin...

Very short-period quantitative precipitation forecast (QPF) or nowcast schemes provide deterministic output that fails to convey explicit measures of the uncertainty in the forecast. Presented here is a forecast methodology based upon a Bayesian hierarchical model that produces a QPF product for a 1-h period along with an associated estimated forecast error field. The precipitation forecast qua...

During the strong 2015/16 El Niño, only normal to below-average precipitation fell across California in the late winter. This disagrees with both predictions by the ensemble mean of forecast models and expectations for strong El Niños. The authors examine one of the possible reasons why this event did not bring expected precipitation to California in the late winter. The maximum equatorial Paci...

Precipitation forecast verification is essential to the quality of a forecast. The Gaussian Mixture Model can be used to approximate the precipitation of several rain bands and provide a concise view of the data, which is especially useful for comparing forecast and observation data. The robustness of such comparison mainly depends on the consistency of and the correspondence between the extrac...

Cool season precipitation plays an important role in freshwater supply over the Southwest United States, which is marked by heterogeneous topographic and hydrologic scenarios. More accurate precipitation prediction is highly desirable for both the public and hydrological model users. Numerous studies indicate that ensemble forecasting provides more skillful weather forecasts than a single deter...

Quantifying the uncertainty of flood forecasts by ensemble methods is becoming increasingly important for operational purposes. The aim of this paper is to examine how the ensemble distribution of precipitation forecasts propagates in the catchment system, and to interpret the flood forecast probabilities relative to the forecast errors. We use the 622 km2 Kamp catchment in Austria as an exampl...

Probabilistic quantitative precipitation forecasts challenge meteorologists due to the wide variability of precipitation amounts over small areas and their dependence on conditions at multiple spatial and temporal scales. Ensembles of convection-allowing numerical weather prediction models offer a way to produce improved precipitation forecasts and estimates of the forecast uncertainty. Thesemo...

To test the accuracy of statistically downscaled precipitation estimates from numerical weather prediction models, a set of experiments to study what space and time scales are appropriate to obtain downscaled precipitation forecasts with maximum skill have been carried out. Fourteen-day forecasts from the 1998 version of the National Centers for Environmental Prediction (NCEP) Medium-Range Fore...

during the last several years, application of numerical weather prediction models in the country have become common in both research and operations, even though systematic verification of the models’ results using statistical methods has rarely been conducted (sodoudi et al. 2009). this paper aims at comparing the mm5 24-hour precipitation forecasts with the corresponding observations using sta...