| 一种偏差订正方法在平昌冬奥会气象预报的应用 |
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| 引用本文： | 张玉涛,佟华,孙健.一种偏差订正方法在平昌冬奥会气象预报的应用[J].应用气象学报,2020,31(1):27-41. |
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| 作者姓名： | 张玉涛 佟华 孙健 |
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| 作者单位： | 1.国家气象中心, 北京 100081 |
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| 摘 要： | 为了提高GRAPES_3 km（Global/Regional Assimilation and Prediction System）模式在2018年平昌冬奥会气象服务中的预报能力，采用一阶自适应的卡尔曼滤波方法对GRAPES_3 km模式的2 m气温、2 m相对湿度和10 m风开展偏差订正。结果表明:偏差订正方法明显提高了地面要素的预报效果，其中2 m气温的均方根误差整体减小到2℃左右，站点订正改善率为10%~60%；10 m风速的均方根误差减小到2 m·s-1左右，站点订正改善率为10%~45%；2 m相对湿度减小到20%以下，站点订正改善率为0~20%。与韩国气象厅LDAPS（Local Data Assimilation and Prediction System）及美国宇航局NU-WRF（NASA-Unified WRF）模式相比，GRAPES_3 km模式的风速预报表现更为优异，各站点整体预报效果明显优于LDAPS和NU-WRF模式。偏差订正方法可有效改善模式在复杂地形条件下的预报能力，是提高精细化预报准确率的重要手段。
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| 关 键 词： | GRAPES_3 km模式 平昌冬奥会 ICE-POP 2018 偏差订正 |
| 收稿时间： | 2019-08-07 |
Application of a Bias Correction Method to Meteorological Forecast for the Pyeongchang Winter Olympic Games |
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| Affiliation: | 1.National Meteorological Center, Beijing 1000812.Numerical Weather Prediction Center of CMA, Beijing 100081 |
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| Abstract: | The 23rd Winter Olympics Games and the 13th Winter Paralympic Games are held in Pyeongchang, South Korea during 9-25 February 2018 and 8-18 March 2018. Supported by the WMO(World Meteorological Organization) WWRP(World Weather Research Project Group), ICE-POP 2018(International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games) is organized by KMA (Korea Meteorological Administration), which aims to improve the forecasting ability of convective scale numerical models for high-impact weather system under complex terrain and to support weather forecasting and meteorological services during the Winter Olympics through international cooperation. GRAPES_3 km, a high-resolution model independently developed by CMA (China Meteorological Administration), participated in this project and provided real-time forecasting products at the specific sites during the Winter Olympics Games. In order to improve the forecasting ability of GRAPES_3 km, a bias correction method named one-order adaptive Kalman filtering is applied, which compensate for the fact that the resolution of GRAPES_3 km is not sufficient to simulate the complex terrain of the Winter Olympic Games and GRAPES_3 km doesn't assimilate Korea's observations due to some objective reasons such as data transmission. 1-24-hour calibration products are provided twice a day, including 2 m temperature, 2 m relative humidity, 10 m wind speed, and 10 m wind direction on sixteen sites. The verification and evaluation are carried out in two aspects. First, it is to check whether the bias correction improves the accuracy of GRAPES_3 km, examined from the model's diurnal cycle, daily variation and the forecast ability of complex terrain. Second, to the performance of calibrated GRAPES_3 km during the Winter Olympic Games is and examined compared to LDAPS model from KMA and NU-WRF from NASA, which shows that the high-resolution GRAPES_3 km model has abilities to simulate the near-ground elements in this service and the bias correction technology makes model products better and effective. After bias correction, the root mean square error of model products is reduced to about 2℃ for the temperature, about 2 m·s-1 for the wind speed, and less than 20% for the relative humidity is reduced to. Compared with, NU-WRF and LDAPS models, the corrected GRAPES_3 km has the best wind speed forecast capability and root mean square error of the wind speed is significantly reduced. For the wind direction forecast of complex terrain, although all numerical models have limited capabilities, and their wind direction forecasting of all the stations are almost dominated by westerly during the Winter Games, the corrected GRAPES_3 km perform relatively well in some non-westerly dominated stations. However, GRAPES_3 km has no significant advantage in temperature and humidity compared with the other two models although they are improved more obviously than wind after the calibration. In addition, the bias correction can attenuate the diurnal variation characteristics of GRPAES_3 km, and to some extent, improve the simulation capability for complex terrain. In short, the application of the bias correction in the Pyeongchang Winter Olympic Games is an effective way for GRAPES_3 km. |
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