The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). I...The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). In this study, we propose a new method, GRU_Z-ET, by introducing Z and ET as two independent variables into the GRU neural network to conduct the quantitative single-polarization radar precipitation estimation. The performance of GRU_Z-ET is compared with that of the other three methods in three heavy rainfall cases in China during 2018, namely, the traditional Z-R relationship(Z=300R1.4), the optimal Z-R relationship(Z=79R1.68) and the GRU neural network with only Z as the independent input variable(GRU_Z). The results indicate that the GRU_Z-ET performs the best, while the traditional Z-R relationship performs the worst. The performances of the rest two methods are similar.To further evaluate the performance of the GRU_Z-ET, 200 rainfall events with 21882 total samples during May–July of 2018 are used for statistical analysis. Results demonstrate that the spatial correlation coefficients, threat scores and probability of detection between the observed and estimated precipitation are the largest for the GRU_Z-ET and the smallest for the traditional Z-R relationship, and the root mean square error is just the opposite. In addition, these statistics of GRU_Z are similar to those of optimal Z-R relationship. Thus, it can be concluded that the performance of the GRU_ZET is the best in the four methods for the quantitative precipitation estimation.展开更多
为了解FY-4A卫星云顶高度(cloud top height,CTH)产品对陕南暖季降水云的反映状况,以陕南地区2020年暖季(5-10月)降水过程为例,对比分析FY-4A卫星CTH产品与汉中天气雷达回波顶高(echo top height,ET)产品对该地区降水云的探测资料。结...为了解FY-4A卫星云顶高度(cloud top height,CTH)产品对陕南暖季降水云的反映状况,以陕南地区2020年暖季(5-10月)降水过程为例,对比分析FY-4A卫星CTH产品与汉中天气雷达回波顶高(echo top height,ET)产品对该地区降水云的探测资料。结果表明:(1)在暖季21次降水过程中,卫星产品的云顶高度揭示了陕南地区降水云的空间变化,尤其在大巴山峡口附近,CTH值显著偏高的区域与陕南强降水的多发区相吻合。(2)以2020年暖季一次强降水过程为例,云顶高度探测表明卫星CTH的高值区通常与雷达ET的高值区相对应,说明卫星能够揭示陕南山区降水云体的时空变化,但在雷达ET高值区卫星CTH存在以填充值代替的现象,说明复杂地形区CTH填充值可能是潜在强降水区。(3)对比两种探测在降水云体发展中差异,结果显示在降水云初生和消亡阶段,两者绝对差值小于2 km的格点数与总格点数的占比都超过50%,说明CTH产品能有效捕捉降水云的初生和消亡变化。在降水云成熟阶段,两者平均差值超过4 km,卫星探测云体不确定性增加,较难反映降水云体特征。展开更多
利用2008—2017年5~8月天山南侧喀什地区气象台站观测记录、人工防雹作业点记录、灾害调查等资料,喀什探空站08时、20时探空资料,喀什雷达探测资料及其基数据反演产品,对冰雹的年分布、月分布及日变化特征进行了分析,归纳出冰雹云的雷...利用2008—2017年5~8月天山南侧喀什地区气象台站观测记录、人工防雹作业点记录、灾害调查等资料,喀什探空站08时、20时探空资料,喀什雷达探测资料及其基数据反演产品,对冰雹的年分布、月分布及日变化特征进行了分析,归纳出冰雹云的雷达回波特征及移动路径,依据百分位数方法确定了以0℃层高度、-20℃层高度、冻结层厚度、全总指数、杰弗逊指数、K指数、沙氏指数为代表的冰雹预报指标,以及以回波顶高及其与当日0℃层高度差、40~50 d BZ回波高度及其与当日0℃层高度差、组合反射率、垂直积分液态水含量为代表的雷达特征预警指标。展开更多
利用贵阳多普勒雷达资料及自动站观测资料对2012年7月16日影响贵州大部且持续时间长的短时强降水天气进行详细分析。研究表明:短时强降水出现开始阶段,雷达回波显示出强度为35 d Bz,且回波局地性强、回波顶高<8 km、垂直液态水含量&g...利用贵阳多普勒雷达资料及自动站观测资料对2012年7月16日影响贵州大部且持续时间长的短时强降水天气进行详细分析。研究表明:短时强降水出现开始阶段,雷达回波显示出强度为35 d Bz,且回波局地性强、回波顶高<8 km、垂直液态水含量>5 kg/m^2;短时强降水大面积发展阶段,回波发展迅速并不断合并成片,回波顶高达到10~12 km,且垂直液态水含量>1.8 kg/m^2,配合超低空急流形成大面积强度为40~45 d Bz的回波;短时强降水趋于结束阶段,片状回波逐渐减弱分散,但仍存在强度为40 d Bz、回波顶高8 km、垂直液态水含量>1.8 kg/m^2的小块状回波。展开更多
基金jointly supported by the National Science Foundation of China (Grant Nos. 42275007 and 41865003)Jiangxi Provincial Department of science and technology project (Grant No. 20171BBG70004)。
文摘The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). In this study, we propose a new method, GRU_Z-ET, by introducing Z and ET as two independent variables into the GRU neural network to conduct the quantitative single-polarization radar precipitation estimation. The performance of GRU_Z-ET is compared with that of the other three methods in three heavy rainfall cases in China during 2018, namely, the traditional Z-R relationship(Z=300R1.4), the optimal Z-R relationship(Z=79R1.68) and the GRU neural network with only Z as the independent input variable(GRU_Z). The results indicate that the GRU_Z-ET performs the best, while the traditional Z-R relationship performs the worst. The performances of the rest two methods are similar.To further evaluate the performance of the GRU_Z-ET, 200 rainfall events with 21882 total samples during May–July of 2018 are used for statistical analysis. Results demonstrate that the spatial correlation coefficients, threat scores and probability of detection between the observed and estimated precipitation are the largest for the GRU_Z-ET and the smallest for the traditional Z-R relationship, and the root mean square error is just the opposite. In addition, these statistics of GRU_Z are similar to those of optimal Z-R relationship. Thus, it can be concluded that the performance of the GRU_ZET is the best in the four methods for the quantitative precipitation estimation.
文摘为了解FY-4A卫星云顶高度(cloud top height,CTH)产品对陕南暖季降水云的反映状况,以陕南地区2020年暖季(5-10月)降水过程为例,对比分析FY-4A卫星CTH产品与汉中天气雷达回波顶高(echo top height,ET)产品对该地区降水云的探测资料。结果表明:(1)在暖季21次降水过程中,卫星产品的云顶高度揭示了陕南地区降水云的空间变化,尤其在大巴山峡口附近,CTH值显著偏高的区域与陕南强降水的多发区相吻合。(2)以2020年暖季一次强降水过程为例,云顶高度探测表明卫星CTH的高值区通常与雷达ET的高值区相对应,说明卫星能够揭示陕南山区降水云体的时空变化,但在雷达ET高值区卫星CTH存在以填充值代替的现象,说明复杂地形区CTH填充值可能是潜在强降水区。(3)对比两种探测在降水云体发展中差异,结果显示在降水云初生和消亡阶段,两者绝对差值小于2 km的格点数与总格点数的占比都超过50%,说明CTH产品能有效捕捉降水云的初生和消亡变化。在降水云成熟阶段,两者平均差值超过4 km,卫星探测云体不确定性增加,较难反映降水云体特征。
文摘利用2008—2017年5~8月天山南侧喀什地区气象台站观测记录、人工防雹作业点记录、灾害调查等资料,喀什探空站08时、20时探空资料,喀什雷达探测资料及其基数据反演产品,对冰雹的年分布、月分布及日变化特征进行了分析,归纳出冰雹云的雷达回波特征及移动路径,依据百分位数方法确定了以0℃层高度、-20℃层高度、冻结层厚度、全总指数、杰弗逊指数、K指数、沙氏指数为代表的冰雹预报指标,以及以回波顶高及其与当日0℃层高度差、40~50 d BZ回波高度及其与当日0℃层高度差、组合反射率、垂直积分液态水含量为代表的雷达特征预警指标。
文摘利用贵阳多普勒雷达资料及自动站观测资料对2012年7月16日影响贵州大部且持续时间长的短时强降水天气进行详细分析。研究表明:短时强降水出现开始阶段,雷达回波显示出强度为35 d Bz,且回波局地性强、回波顶高<8 km、垂直液态水含量>5 kg/m^2;短时强降水大面积发展阶段,回波发展迅速并不断合并成片,回波顶高达到10~12 km,且垂直液态水含量>1.8 kg/m^2,配合超低空急流形成大面积强度为40~45 d Bz的回波;短时强降水趋于结束阶段,片状回波逐渐减弱分散,但仍存在强度为40 d Bz、回波顶高8 km、垂直液态水含量>1.8 kg/m^2的小块状回波。
