A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tr...A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg^(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.展开更多
Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphe...Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphere can be de-rived from Advanced Microwave Sounding Unit （AMSU） and Advanced Technology Microwave Sounder （ATMS） through either regression-based or variational retrieval algorithms. This study investigates the dependency of TC warm core structure on emission and scattering processes in the forward operator used for radiance computations in temperature retrievals. In particular, the precipitation scattering at ATMS high-frequency channels can significantly change the retrieval outcomes. The simulation results in this study reveal that the brightness temperatures at 183 GHz could be depressed by 30-50 K under cloud ice water path of 1.5 mm, and thus, the temperature structure in hur-ricane atmosphere could be distorted if the ice cloud scattering was inaccurately characterized in the retrieval system. It is found that for Hurricanes Irma, Maria, and Harvey that occurred in 2017, their warm core anomalies retrieved from ATMS temperature sounding channels 4 15 were more reasonable and realistic, compared with the retrievals from all other channel combinations and earlier hurricane simulation results.展开更多
风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期...风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期间FY-4A加密观测(15分钟间隔)的GIIRS数据开展晴空和部分云区的三维水平风场算法研究,重点研究如何联合同一卫星平台的多光谱成像仪(AGRI)改进GIIRS部分云视场区的三维风场反演结果。利用ERA5独立测试集、CRA40再分析和空投探空数据开展对晴空和云区的三维风场反演结果的检验,基于该个例的反演结果表明:(1)基于GIIRS亮温信息反演得到对流层水平风场,在晴空区均方根误差小于1.5 m s^(-1),方向绝对差基本在15°左右,在部分云视场区,均方根误差为1.5~1.7 m s^(-1),方向绝对差基本在20°左右。与光流法相比,基于GIIRS亮温的直接反演表现出更好的优势,其均方根误差和方向绝对差明显小于光流法的结果。(2)按云量和云顶高度分类后,表现出云量越多、云顶高度越高则RMSE(Root Mean Square Error)越大。在部分云视场区,进一步在反演模型输入中加入来自同平台上成像仪(AGRI)云量和云高信息后,RMSE有所减小,表明更高空间分辨率的AGRI产品可以改进GIIRS部分云覆盖区的风场反演精度。(3)基于GIIRS亮温信息反演的风廓线与CRA40再分析、空投探测风廓线有较好的一致性,表明利用静止卫星红外高光谱大气探测仪观测亮温反演风场的合理性和可行性。展开更多
基金Supported by the National Basic Research and Development(973)Program(2015CB452805)National Key Research and Development Program of China(2018YFC1506500)
文摘A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg^(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.
基金Supported by the National Natural Science Foundation of China(91337218 and 41475103)China Meteorological Administration Special Public Welfare Research Fund(GYHY201406008)
文摘Accurate information on atmospheric temperature of tropical cyclones （TCs） is important for monitoring and pre- diction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphere can be de-rived from Advanced Microwave Sounding Unit （AMSU） and Advanced Technology Microwave Sounder （ATMS） through either regression-based or variational retrieval algorithms. This study investigates the dependency of TC warm core structure on emission and scattering processes in the forward operator used for radiance computations in temperature retrievals. In particular, the precipitation scattering at ATMS high-frequency channels can significantly change the retrieval outcomes. The simulation results in this study reveal that the brightness temperatures at 183 GHz could be depressed by 30-50 K under cloud ice water path of 1.5 mm, and thus, the temperature structure in hur-ricane atmosphere could be distorted if the ice cloud scattering was inaccurately characterized in the retrieval system. It is found that for Hurricanes Irma, Maria, and Harvey that occurred in 2017, their warm core anomalies retrieved from ATMS temperature sounding channels 4 15 were more reasonable and realistic, compared with the retrievals from all other channel combinations and earlier hurricane simulation results.
文摘风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期间FY-4A加密观测(15分钟间隔)的GIIRS数据开展晴空和部分云区的三维水平风场算法研究,重点研究如何联合同一卫星平台的多光谱成像仪(AGRI)改进GIIRS部分云视场区的三维风场反演结果。利用ERA5独立测试集、CRA40再分析和空投探空数据开展对晴空和云区的三维风场反演结果的检验,基于该个例的反演结果表明:(1)基于GIIRS亮温信息反演得到对流层水平风场,在晴空区均方根误差小于1.5 m s^(-1),方向绝对差基本在15°左右,在部分云视场区,均方根误差为1.5~1.7 m s^(-1),方向绝对差基本在20°左右。与光流法相比,基于GIIRS亮温的直接反演表现出更好的优势,其均方根误差和方向绝对差明显小于光流法的结果。(2)按云量和云顶高度分类后,表现出云量越多、云顶高度越高则RMSE(Root Mean Square Error)越大。在部分云视场区,进一步在反演模型输入中加入来自同平台上成像仪(AGRI)云量和云高信息后,RMSE有所减小,表明更高空间分辨率的AGRI产品可以改进GIIRS部分云覆盖区的风场反演精度。(3)基于GIIRS亮温信息反演的风廓线与CRA40再分析、空投探测风廓线有较好的一致性,表明利用静止卫星红外高光谱大气探测仪观测亮温反演风场的合理性和可行性。
