Abstract
At present, numerical models, which have been used for forecasting services in northwestern China, have not been extensively evaluated. We used national automatic ground station data from summer 2016 to test and assess the forecast performance of the high-resolution global European Centre for Medium-Range Weather Forecast (ECMWF) model, the mesoscale Northwestern Mesoscale Numerical Prediction System (NW-MNPS), the global China Meteorological Administration T639 model, and the mesoscale Global/Regional Assimilation and Prediction System (GRAPES) model over northwestern China. The root mean square error (RMSE) of the 2-m temperature forecast by ECMWF was the lowest, while that by T639 was the highest. The distribution of RMSE for each model forecast was similar to that of the difference between the modeled and observed terrain. The RMSE of the 10-m wind speed forecast was lower for the global ECMWF and T639 models and higher for the regional NW-MNPS and GRAPES models. The 24-h precipitation forecast was generally higher than observed for each model, with NW-MNPS having the highest score for light rain and heavy storm rain, ECMWF for medium and heavy rain, and T639 for storm rain. None of the models could forecast small-scale and high-intensity precipitation, but they could forecast large-scale precipitation. Overall, ECMWF had the best stability and smallest prediction errors, followed by NW-MNPS, T639, and GRAPES.
Highlights
Numerical forecast products have become a mainstay of daily forecast services in modern meteorology (Chen and Xue, 2004; Yan et al, 2010), objective assessments remain an important part of ongoing performance improvements (Pan et al, 2014; Xue and Pan, 2016)
Objective and definitive test methods are commonly applied in most operational forecasts, including tests of precipitation forecasts, threat score (TS), equitable threat score (ETS), and false or missed alarm ratios
Researchers have developed other spatial testing methods, such as the Method for Object-Based Diagnostic Evaluation (MODE) (Davis et al, 2006a) and the intensityscale decomposition method (Casati et al, 2004; Csima and Ghelli, 2008; Casati, 2010), which allow forecasters to better understand the effects of model precipitation forecasts
Summary
Numerical forecast products have become a mainstay of daily forecast services in modern meteorology (Chen and Xue, 2004; Yan et al, 2010), objective assessments remain an important part of ongoing performance improvements (Pan et al, 2014; Xue and Pan, 2016). Assessment, and correction are important aspects of accuracy evaluations aimed at providing objective forecasting criteria for users (Chen and Sun, 2005; Pan et al, 2013, 2014). Testing and evaluating models by region improves the understanding of local forecast performance and enables model choice and results. The main aspect of numerical model development is improved resolution. This can enhance forecast capacity for small- and medium-scale weather phenomena, it does not necessarily
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
