Quantitative precipitation estimation algorithm for C-band radar situated in complex topographical regions
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摘要: C波段雷达定量降水估计（QPE）精度受到很多因素的影响，主要包括：（1）雷达标定，（2）非气象回波的干扰，（3）降水物垂直空间变化，（4）地形或地物的严重遮挡，（5）Z-R关系的代表性，（6）雷达拼图的质量，（7）雷达观测回波衰减等。文中雷达定量降水估计算法基于陕西省C波段天气雷达展开，从雷达探测数据质量控制、地形遮挡、Z-R关系和雷达拼图等方面提高C波段天气雷达定量降水估计的精度，产生降水类型产品和1 h定量降水估计产品，产品空间分辨率为0.01°×0.01°，时间分辨率为6 min。通过对7次降水过程进行评估，结果表明：基于混合仰角反射率因子处理模块和降水类型分类模块进行雷达定量降水估计，得到的结果与地面雨量站观测降水接近，1 h累计降水量的统计评分指标均方根误差稳定在3 mm以下，相对误差稳定在50%左右，相对偏差保持在−30%以内，雷达定量降水估计产品的离散度和绝对偏差都较低，表明该算法得到的雷达定量降水估计稳定可靠。Abstract: The accuracy of C-band radar quantitative precipitation estimation (QPE) is affected by many factors, including the following: (1) Calibration of radar observations, (2) interference from non-meteorological echoes, (3) vertical spatial variation of precipitation, (4) severe radar beam blockage by terrain or ground objects, (5) Z-R relationship, (6) multi-radar mosaic method, (7) radar observation echo attenuation, etc. In this paper, the radar quantitative precipitation estimation is conducted based on the C-band weather radar in Shaanxi Province. It improves the accuracy of the C-band weather radar QPE from the aspects of radar quality control, terrain blockage, Z-R relationship and multi-radar mosaic, and produces precipitation type and 1 h QPE products. The spatial and temporal resolutions of the product are 0.01°×0.01° and 6 min, respectively. Through the evaluation of seven precipitation processes, the results show that radar QPE based on hybrid scan reflectivity processing module and precipitation type classification module is close to the precipitation observed by the ground gauge stations. The statistical indicators RMSE of hourly precipitation is stable and below 3 mm, RMAE is about 50% and remains stable, and RMB remains within −30%. The dispersion and absolute deviation of radar QPE products are both low, indicating the radar QPE obtained by this algorithm is stable and reliable.
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图 1 陕西省 （a） 雷达站、地面雨量站和地形空间分布及 （b） 各雷达有效探测范围
Figure 1. （a） Distribution of radars，surface rain gauge station，and topography in Shaanxi Province；（b） effective detection range of each radar in Shaanxi Province
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图 3 2019年4月28日03时24分西安雷达0.5°仰角反射率回波 （a. 质量控制前，b. 质量控制后）
Figure 3. Reflectivity of Xi'an radar （a） before and （b） after QC at 0.5° elevation at 03：24 UTC 28 April 2019
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图 4 （a） 雷达组合反射率和 （b） 降水类型分类结果 （CV、BB、ST分别代表对流性降水、0℃层亮带层状云降水和非0℃层亮带层状云降水）
Figure 4. （a） Composite reflectivity and （b） precipitation type （CV，BB，and ST stand for convective，bright band and stratiform，respectively）
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图 5 延安雷达 （a） 扫描平面内地形空间分布及雷达（b） 0.5°、（c） 1.45°仰角电磁波遮挡百分比空间分布和 （d） 雷达混合仰角
Figure 5. Distribution of （a） topography，electromagnetic wave shielding percentage at （b） 0.5° elevation and （c） 1.45° elevation，and （d） hybrid elevation angle of Yan'an radar
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图 6 Ku波段和C波段在雨区对降水粒子的反射特性 （a.
μ 取−1—4时DFR随D0 取值不同的变化；b. DFR随Ku波段降水粒子反射率不同产生的变化，黑色实线代表不同滴谱参数取平均后的结果，误差棒表示标准差；c. Ku波段和C波段反射率的散点分布）Figure 6. Comparison of Ku-band and C-band reflection characteristics of precipitation particles in rainy areas （a） The change of DFR with the value of when μ is from −1 to 4；（b） the relationship of DFR with different reflectivity of precipitation particles in Ku-band，the black solid line represents the relationship with average of different drop spectrum parameters，error bars indicate standard deviation；and （c） scatter plot of reflectivity of Ku-band and C-band radar
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图 7 不同降水类型中C波段雷达降水反演的Z-R关系 （适用于液态降水）（a. 0℃层亮带层状云降水，b. 非 0℃层亮带层状云降水，c. 对流性降水；黑色实线为拟合线）
Figure 7. The Z-R relationship of C-band radar precipitation for different precipitation types （applicable to liquid precipitation）（a. bright band，b. stratiform，and c. convective；The black solid line is the fitted line）
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图 8 2018年8月21日11时雷达拼图 （a. 雷达混合仰角反射率场，b. 降水类型分类场，c. 1 h雷达降水率场）
Figure 8. Multi-radar mosaic field of （a） reflectivity of hybrid elevation angle，（b） precipitation type，and （c） 1 h precipitation rate
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图 9 2019年5月26日14时—29日02时累计降水空间分布 （a. 地面雨量站累计降水观测，b. 雷达定量降水估计算法计算得到的累计降水；单位：mm）
Figure 9. Accumulated precipitation for the period from 14：00 UTC 26 May to 02：00 UTC 29 May 2019 from （a） surface gauge stations and （b） QPE algorithm described in this paper （unit：mm）
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图 10 2019年5月26日14时—29日02时1 h累计降水与地面雨量站观测降水散点对比
Figure 10. Scatterplots of 1 h precipitation from QPE algorithm described in this paper vs the surface gauge station observations from 14：00 UTC 26 May to 02：00 UTC 29 May 2019
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图 11 针对陕西7次降水过程，文中定量降水估计算法结果和地面雨量站降水观测对比统计评分指标 （a. 均方根误差， b. 相对误差， c. 相对偏差）
Figure 11. Statistical indicators of （a） RMSE，（b） RMAE，and （c） RMB for 7 precipitation processes in Shaanxi
表 1 2019年陕西7次降水个例
Table 1 The 7 precipitation cases in Shaanxi in 2019
个例 日期-时间 个例介绍 1 04-07 14:00—04-09 04:00 降水主要集中在陕西北部及南部地区，其中南部地区主要为对流性降水 2 04-26 01:00—04-28 09:00 飑线过程，自西北向东南移动，逐渐减弱成团状对流系统，降水主要集中在陕西中部及南部地区 3 05-05 15:00—05-08 22:00 降水主要集中在陕西中部及南部地区，其中中部地区有对流性降水过程 4 05-26 14:00—05-29 02:00 降水主要集中在陕西中部及南部地区，有对流性降水过程 5 06-26 14:00—06-28 14:00 全省范围内均有降水，其中南部地区主要为对流性降水 6 07-20 14:00—07-23 01:00 降水主要集中在陕西北部、中部和西南部地区，为对流性降水 7 07-28 14:00—07-31 08:00 全省范围内均有降水，其中北部和南部地区主要为对流性降水 总计 406 h 7次个例 
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