The Value of a Variable Resolution Approach to Numerical Weather Prediction

2010 ◽  
Vol 138 (4) ◽  
pp. 1026-1042 ◽  
Author(s):  
Roberto Buizza

Abstract It is shown that a numerical weather prediction system with variable resolution, higher in the early forecast range and lower afterward, provides more skilful forecasts than a system with constant resolution. Results indicate that the advantage can be detected also beyond the time when the resolution is truncated (truncation time). Forecasts generated with a T399 spectral truncation up to forecast day 3 and a T255 truncation from day 3 to day 8 (VAR3) are compared with forecasts generated with a constant T319 truncation. First, forecasts are verified in an idealized model error (IME) scenario against higher resolution, T799 simulations. In this scenario, VAR3 outperforms the T319 system beyond the day-3 truncation time for the entire 8-day forecast range, with differences statistically significant at the 5% level. Second, forecasts are verified in a realistic scenario against T799 analyses. In this case, although the advantage of VAR3 can still be detected beyond day 3, it is less evident and not statistically significant. Forecast error spectra indicate that using a higher-resolution model during the first forecast days improves the forecasts of the large scales, thus helping to maintain the advantage of the variable resolution system beyond the truncation time. VAR3 and T319 ensembles are also compared with forecasts with a T255, T399, and T799 constant resolution. The predictability “gain” of all ensemble configurations is measured with respect to the reference constant T255 configuration. Results show that, in the realistic scenario, VAR3 gives gains 50%–75% higher than T319 and 50%–75% lower than T799.

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyo-Jong Song

Abstract Numerical weather prediction provides essential information of societal influence. Advances in the initial condition estimation have led to the improvement of the prediction skill. The process to produce the better initial condition (analysis) with the combination of short-range forecast and observation over the globe requires information about uncertainty of the forecast results to decide how much observation is reflected to the analysis and how far the observation information should be propagated. Forecast ensemble represents the error of the short-range forecast at the instance. The influence of observation propagating along with forecast ensemble correlation needs to be restricted by localized correlation function because of less reliability of sample correlation. So far, solitary radius of influence is usually used since there has not been an understanding about the realism of multiple scales in the forecast uncertainty. In this study, it is explicitly shown that multiple scales exist in short-range forecast error and any single-scale localization approach could not resolve this situation. A combination of Gaussian correlation functions of various scales is designed, which more weighs observation itself near the data point and makes ensemble perturbation, far from the observation position, more participate in decision of the analysis. Its outstanding performance supports the existence of multi-scale correlation in forecast uncertainty.


2019 ◽  
Vol 145 (725) ◽  
pp. 3432-3454 ◽  
Author(s):  
Heather Lawrence ◽  
Niels Bormann ◽  
Irina Sandu ◽  
Jonathan Day ◽  
Jacky Farnan ◽  
...  

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 205
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll

The direct radiative effect of aerosols is taken into account in many limited-area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We studied the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single-column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA simple broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud–radiation–aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and the vertical distribution of the aerosol species. In such cases, regional weather models should use external real-time aerosol data for radiation parametrizations. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust.


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