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Verification of Rainfall Forecasts for the South Central Climate Region of Vietnam | ||
| فیزیک زمین و فضا | ||
| مقاله 19، دوره 46، شماره 4، بهمن 1399، صفحه 247-258 اصل مقاله (1.01 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2020.300651.1007208 | ||
| نویسندگان | ||
| Van Thang Nguyen1؛ Mai Van Khiem2؛ Hoang-Minh Nguyen* 2؛ Vu Van Thang1 | ||
| 1Ph.D., Vietnam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam | ||
| 2Associate Professor, National Center for Hydro-Meteorological Forecasting, Viet Nam Meteorological and Hydrological Administration, Hanoi, Vietnam | ||
| چکیده | ||
| This study aims to investigate the performance of the Weather Research and Forecasting (WRF) model for rainfall forecasts in the South Central climate region of Vietnam. The investigation was carried out by analyzing the accuracy of the model outputs at station sites and the spatial structure of rain events for different rainfall thresholds over the whole year and in the flood and dry seasons. The traditional (standard) method was utilized to analyze the accuracy of the WRF model in predicting precipitation point-by-point, whereas the Contiguous Rain Area (CRA) method was applied to analyze the spatial structure of rain events. The results showed that rainfall forecasts by the WRF model for the South Central region had certain limitations because the model scores and measured error criteria were not close to their perfect values. The proportion of hit forecasts decreased from 30 % with the traditional verification method to 10% with the spatial structure verification method. The pattern error was a main contributor to the total error at 53%, followed by the intensity error at 34%. The location error accounted for the lowest percentage contribution to the total error, at only 13%. The performance of this model could lead to substantial errors in weather and streamflow predictions for the south-central region and may lead to a lack of forecast effectiveness for mitigating the damage from natural disasters. Thus, improvements in the performance of the Numerical Weather Prediction (NWP) model for the studied area are necessary. | ||
| کلیدواژه‌ها | ||
| QPF؛ WRF model؛ traditional and spatial structure verification؛ South Central؛ Vietnam | ||
| عنوان مقاله [English] | ||
| Verification of Rainfall Forecasts for the South Central Climate Region of Vietnam | ||
| نویسندگان [English] | ||
| Van Thang Nguyen1؛ Mai Van Khiem2؛ Hoang-Minh Nguyen2؛ Vu Van Thang1 | ||
| 1Ph.D., Vietnam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam | ||
| 2Associate Professor, National Center for Hydro-Meteorological Forecasting, Viet Nam Meteorological and Hydrological Administration, Hanoi, Vietnam | ||
| چکیده [English] | ||
| This study aims to investigate the performance of the Weather Research and Forecasting (WRF) model for rainfall forecasts in the South Central climate region of Vietnam. The investigation was carried out by analyzing the accuracy of the model outputs at station sites and the spatial structure of rain events for different rainfall thresholds over the whole year and in the flood and dry seasons. The traditional (standard) method was utilized to analyze the accuracy of the WRF model in predicting precipitation point-by-point, whereas the Contiguous Rain Area (CRA) method was applied to analyze the spatial structure of rain events. The results showed that rainfall forecasts by the WRF model for the South Central region had certain limitations because the model scores and measured error criteria were not close to their perfect values. The proportion of hit forecasts decreased from 30 % with the traditional verification method to 10% with the spatial structure verification method. The pattern error was a main contributor to the total error at 53%, followed by the intensity error at 34%. The location error accounted for the lowest percentage contribution to the total error, at only 13%. The performance of this model could lead to substantial errors in weather and streamflow predictions for the south-central region and may lead to a lack of forecast effectiveness for mitigating the damage from natural disasters. Thus, improvements in the performance of the Numerical Weather Prediction (NWP) model for the studied area are necessary. | ||
| کلیدواژه‌ها [English] | ||
| QPF, WRF model, traditional and spatial structure verification, South Central, Vietnam | ||
| مراجع | ||
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Bytheway, J. L. and Kummerow, C. D., 2015, Toward an object-based assessment of high-resolution forecasts of long-lived convective precipitation in the central U.S. J. Adv. Model. Earth Syst., 7, 1248–1264. Casati, B., Wilson, L. J., Stephenson, D. B., Ghelli, A., Pocernich, M., Damrath, U., Ebert, E. E., Brown B. G. and Mason, S, 2008, Forecast verification: current status and future directions. Meteorol. Appl., 15, 3–18. Chen, Y., Ebert, E. E., Davidson, N. E. and Walsh, K. J. E., 2018, Application of contiguous rain area (CRA) methods to tropical cyclone rainfall forecast verification. Earth Space Sci., 5, 736–752. Diomede, T., Marsigli, C., Nerozzi, F., Papetti, P. and Paccagnella, T., 2008, Coupling high-resolution precipitation forecasts and discharge predictions to evaluate the impact of spatial uncertainty in numerical weather prediction model outputs. Meteor. Atmos. Phys., 102, 37–62. Hu, Q., Li, Z., Wang, L., Huang, Y., Wang, Y. and Li, L., 2019, Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging. J. Water., 11, 1– 30. Ebert, E. E. and McBride, J. L., 2000, Verification of precipitation in weather systems: Determination of systematic errors. J. Hydrol., 239, 179–202. Ebert, E. E., Wilson, L., Weigel, A., Mittermaier, M., Nurmi, P., Gill, P., G¨ober, M., Joslyn, S., Brown, B. and Fowlerh, T., 2013, Progress and challenges in forecast verification. Meteorol. Appl., 20, 130–139. Gofa, F., Boucouvala, D., Louka, P. and Flocas, H. A., 2018, Spatial verification approaches as a tool to evaluate the performance of high resolution precipitation forecasts. Atmos. Res., 208, 78–87. Nguyen, H. M. and Bae, D. H., 2019, An approach for improving the capability of a coupled meteorological and hydrological model for rainfall and flood forecasts. J. Hydrol., 577, 1–15. Ran, Q., Fu, W., Liu, Y., Li, T., Shi, K. and Sivakumar, B., 2018, Evaluation of Quantitative Precipitation Predictions by ECMWF, CMA, and UKMO for Flood Forecasting: Application to Two Basins in China. Nat. Hazards Rev., 19(2), 1–13. Robert, N., 2008, Assessing the spatial and temporal variation in the skill of precipitation forecasts from an NWP model. Meteorol. Appl., 15, 163–169. Song, H. J., Lim, B. H. and Joo, S. W., 2019, Evaluation of Rainfall Forecasts with Heavy Rain Types in the High-Resolution Unified Model over South Korea. Wea. Forecasting, 34, 1277–1293. Weusthoff, T., Ament, F., Arpagaus, A. and Rotach, M. W., 2010, Assessing the benefits of convection-permitting models by neighborhood verification: examples from MAP D-PHASE. Mon. Wea. Rev., 138, 3418–3433. Wilks, D. S., 2006, Statistical Methods in Atmospheric Science. 2nd edn. Academic Press: Burlington, MA, pp 627. | ||
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