基于WRF的机场中尺度预报模式对乌鲁木齐机场地面气象要素预报效果的评估分析
Evaluation and Analysis of WRF Model for Forecasting Effect of Ground Meteorological Elements in Urumqi Airport

DOI: 10.12677/CCRL.2021.102013, PP. 102-113

Keywords: 乌鲁木齐机场，WRF模式，气象要素，质量评估
Urumqi Airport, WRF Model, Meteorological Elements, Quality Assessment

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Abstract:

对乌鲁木齐国际机场中尺度预报模式WRF在2016~2019年预报的风速、温度、海平面气压、相对湿度等要素进行评估，评估过程中采用最近点插值法将嵌套2区(d02区)和嵌套3区(d03区)分别插值到乌鲁木齐机场站点，将插值结果与机场实况资料进行对比分析。结果表明：1) 从全年误差度量情况来看，模式对海平面气压预报效果最好，温度和湿度次之，对风速的预报能力相对薄弱，d03-00预报结果最优。2) 从月际变化来看，模式预报对温度和修正海平面气压的变化趋势和数值大小预报能力较强，春、夏、秋季对相对湿度的预报较实况偏高，对春冬季的相对湿度预报效果优于夏秋季，对风速的预报效果稍差。其中d03-00预报偏差最小，d02-12整体偏差最大。3) 从日变化来看，各预报结果对海平面气压的模拟效果较好，以d03为最优；对风速预报结果的平均偏差和均方根误差较小，但相关性较差，以d03为优；对温度、湿度的预报值误差随时间变化有明显的波动，其中以d02-12、d03-12最优。
The Urumqi Airport mesoscale forecasting model WRF was used to evaluate the forecasted wind speed, temperature, sea level pressure, relative humidity and other factors for 2016~2019, and the nearest point interpolation method was used to interpolate d02 and d03 to the Urumqi airport station respectively. And the forecast results are compared with the site data. The results show: 1) The changes of the four meteorological elements have obviously seasonal characteristics. There is a positive correlation between temperature and wind speed, relative humidity and sea level pressure; there is a significantly negative correlation between temperature and relative humidity, temperature and sea level pressure. 2) From the perspective of the error measurement throughout the year, the model has the best effect on sea level pressure forecast, followed by temperature and humidity, and relatively weak forecasting ability of wind speed, the d03-00 is the best. 3) From the perspective of inter-monthly changes, the model forecast has a strong ability to predict the change trend and numerical magnitude of temperature and corrected sea level pressure, and the forecast effect of wind speed is slightly worse. The forecast deviation of d03-00 is the smallest. 4) From the perspective of daily changes, the prediction results of sea level pressure are better, and d03 is the best. The average deviation and root mean square error of the wind speed forecast results are small, but the correlation is poor, and d03 is the best. The errors in the predicted values of temperature and humidity have obvious fluctuations with time, d02-12 and d03-12 are the best.

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