Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AM...Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.展开更多
Two sets of assimilation experiments on a landfalling typhoon--Typhoon Dan （1999） over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that a...Two sets of assimilation experiments on a landfalling typhoon--Typhoon Dan （1999） over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation （3DVM） and the 4-dimensional variational data assimilation （4DVar）. Results show that： （1） both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3- dimensional variational data assimilation （3DVar） circle; （2） inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; （3） the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.展开更多
The linear regression and horizontally stepwise correction are conducted on the observational data from AMSU-A L1 B of NOAA polar orbit satellite to invert a 40-layers(from 1,000 h Pa to 0.1 h Pa) dataset of atmospher...The linear regression and horizontally stepwise correction are conducted on the observational data from AMSU-A L1 B of NOAA polar orbit satellite to invert a 40-layers(from 1,000 h Pa to 0.1 h Pa) dataset of atmospheric temperature with a horizontal resolution of 0.5°×0.5° after the correction of satellite antenna pattern and limb adjustment. Case study shows that the inversion data of temperature can reveal the detail structure of warm core in tropical cyclone. We choose two categories of tropical depressions(TDs) over the South China Sea, including the non-developing TDs and developing TDs. Both of them are developed downward from the middle and upper level to the lower level. Comparison between the evolutions of warm core in the two categories of TDs indicates that the warm core is developed downward from the middle and upper troposphere to the sea surface in all the downward-developing TDs. The difference is that in the group of further developing TDs, the warm core in the upper troposphere is intensified suddenly when it is extending to the sea surface. The warm core in the upper and lower troposphere is strengthened in a meantime. But the similar feature is not observed in the non-developing TDs. Then it may be helpful to judge the TD development by monitoring the change in its warm-core structure.展开更多
AMSU-A （Advanced Microwave Sounding Unit-A） measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction （NWP） models due to complicated ...AMSU-A （Advanced Microwave Sounding Unit-A） measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction （NWP） models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting （WRF） model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation （WRF-VAR） system, the surface parameters from the operational Microwave Surface and Precipitation Products System （MSPPS） are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error （RMSE） and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction （NCEP） global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.展开更多
Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A （AMSU-A） temperature sounding instruments onboard NOAA Polar- orbiting Operational Environmental Satellites （POES） have been extensiv...Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A （AMSU-A） temperature sounding instruments onboard NOAA Polar- orbiting Operational Environmental Satellites （POES） have been extensively used for studying atmospheric temperature trends over the past several decades. Inter- sensor biases, orbital drifts and diurnal variations of atmospheric and surface temperatures must be considered before using a merged long-term time series of AMSU-A measurements from NOAA- 15, - 18, - 19 and MetOp-A. We study the impacts of the orbital drift and orbital differences of local equator crossing times （LECTs） on temperature trends derivable from AMSU-A using near-nadir observa- tions from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998 - 2014 over the Amazon rainforest. The double difference method is firstly applied to estimation of inter-sensor biases between any two satellites during their overlapping time period. The inter-calibrated observations are then used to generate a monthly mean diurnal cycle of brightness temperature for each AMSU-A channel. A diurnal correction is finally applied each channel to obtain AMSU-A data valid at the same local time. Impacts of the inter-sensor bias correction and diurnal correction on the AMSU-A derived long-term atmospheric temperature trends are separately quantified and compared with those derived from original data. It is shown that the orbital drift and differences of LECT among different POESs induce a large uncertainty in AMSU-A derived long-term warming/cooling trends. After applying an inter-sensor bias correction and a diurnal correction, the warming trends at different local times, which are approximately the same, are smaller by half than the trends derived without applying these corrections.展开更多
卫星微波垂直探测器的辐射观测资料在数值预报中的同化应用使得数值预报水平有了巨大的飞跃。微波资料的质量控制是保证观测资料成功同化的关键所在。文章提出一种基于AMSU-A(Advanced Microwave Sounding Unit-A)辐射亮温资料梯度信息...卫星微波垂直探测器的辐射观测资料在数值预报中的同化应用使得数值预报水平有了巨大的飞跃。微波资料的质量控制是保证观测资料成功同化的关键所在。文章提出一种基于AMSU-A(Advanced Microwave Sounding Unit-A)辐射亮温资料梯度信息的新质量控制方法,将亮温梯度距平值明显较大的资料作为被降水污染或因为其他原因出现的"坏"的资料。利用中尺度非静力WRF(Weather Research and Forecasting)模式和区域三维变分同化,针对"海鸥"(2008)和"圆规"(2010)2个个例,对比旧质量控制中的降水检测和阈值检测方法,评估该方法用于AMSU-A资料同化时对台风数值模拟的情况。研究表明,旧质量控制方法将会使一些"坏"的微波观测资料同化进入模式,降低模式分析场的质量,进而导致同化结果有较大误差。相对于旧方法获得的分析场,利用基于亮温梯度信息的质量控制方法可使更多"坏"的观测剔除,同化后模式初始时刻的位势高度场和风场更接近于真实情况。与传统AMSU-A辐射资料的同化相比,新质量控制方案使2个台风路径数值模拟的偏差有明显的减小:"海鸥"个例中,模拟台风路径误差的最大改善比为12,路径误差改善约540km;"圆规"个例的最大改善比为13,模拟路径误差减小118km。展开更多
借助快速辐射传输模式RTTOV v10(Radiative Transfer for TOVS)及其地表微波发射率模块,针对江淮区域晴天和雨天2类不同天气状况,采用理想试验手段,利用集合平方根滤波(En SRF)方法同化AMSU-A对地敏感第1通道的模拟亮温资料,探究改善中...借助快速辐射传输模式RTTOV v10(Radiative Transfer for TOVS)及其地表微波发射率模块,针对江淮区域晴天和雨天2类不同天气状况,采用理想试验手段,利用集合平方根滤波(En SRF)方法同化AMSU-A对地敏感第1通道的模拟亮温资料,探究改善中尺度模式WRF(Weather Research and Forecasting)初始场的可行性。结果表明:晴天时,同化对位温、水汽混合比及水平风速u和v整体上均有不同程度的改善,但不同高度改善程度有所差异,相对而言水平风场的改进程度最大,位温最小;有降水时,4个要素场整体改进程度与晴天时类似,但分析场误差的水平空间分布与晴天时不同。展开更多
基金This study was supported by the Hunan Provincial Natural Science Foundation of China[grant number 2021JC0009]the Natural Science Foundation of China[grant number U2142212]the National Key R&D Program of China[grant number 2022YFC3004200].
文摘采用支持向量机(SVM,Support Vector Machine)方法,对AMSU-A进行了临边调整试验。利用全球廓线数据集和快速辐射传输模式计算的理想亮温资料,以及AMSU-A全球实际亮温资料的分析表明,临边效应增大了窗区通道边缘视场的亮温,减小了5～14通道边缘视场亮温。临边效应对于各通道影响明显,且随着视角的增大而增大。通过理想试验分析表明,与多元线性回归方法相比,支持向量机方法对于窗区通道调整效果改进较多,对于通道5～14,同样优于多元线性回归方法。除窗区通道1、2、15边缘少数视场外,各视场调整均方根(RMS,Root Mean Square)误差在AMSU-A仪器噪声范围之内。对实际资料的试验表明,支持向量机方法调整效果同样优于多元线性回归方法。
文摘Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.
文摘Two sets of assimilation experiments on a landfalling typhoon--Typhoon Dan （1999） over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation （3DVM） and the 4-dimensional variational data assimilation （4DVar）. Results show that： （1） both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3- dimensional variational data assimilation （3DVar） circle; （2） inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; （3） the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.
基金National Natural Science Foundation of China(40875026,91015011)Project for Natural Science Foundation Teams of Guangdong Province(8351030101000002)Specialized Program for Social Welfare Industries(Meteorological Sector)(GYHY201106036)
文摘The linear regression and horizontally stepwise correction are conducted on the observational data from AMSU-A L1 B of NOAA polar orbit satellite to invert a 40-layers(from 1,000 h Pa to 0.1 h Pa) dataset of atmospheric temperature with a horizontal resolution of 0.5°×0.5° after the correction of satellite antenna pattern and limb adjustment. Case study shows that the inversion data of temperature can reveal the detail structure of warm core in tropical cyclone. We choose two categories of tropical depressions(TDs) over the South China Sea, including the non-developing TDs and developing TDs. Both of them are developed downward from the middle and upper level to the lower level. Comparison between the evolutions of warm core in the two categories of TDs indicates that the warm core is developed downward from the middle and upper troposphere to the sea surface in all the downward-developing TDs. The difference is that in the group of further developing TDs, the warm core in the upper troposphere is intensified suddenly when it is extending to the sea surface. The warm core in the upper and lower troposphere is strengthened in a meantime. But the similar feature is not observed in the non-developing TDs. Then it may be helpful to judge the TD development by monitoring the change in its warm-core structure.
基金Supported by the National Key Basic Research and Development (973) Program of China (2010CB950802 and 2010CB428602)the National Natural Science Foundation of China (40605011)
文摘AMSU-A （Advanced Microwave Sounding Unit-A） measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction （NWP） models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting （WRF） model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation （WRF-VAR） system, the surface parameters from the operational Microwave Surface and Precipitation Products System （MSPPS） are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error （RMSE） and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction （NCEP） global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.
基金The work was supported by JPSS Proving Ground and Risk Reduction （PGRR） program （Project No. NA11OAR4320199）, the National Natural Science Foundation of China （Grant No. 41505086） and National Oceanic and Atmospheric Administration （NOAA） under Grant NA14NES4320003.
文摘Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A （AMSU-A） temperature sounding instruments onboard NOAA Polar- orbiting Operational Environmental Satellites （POES） have been extensively used for studying atmospheric temperature trends over the past several decades. Inter- sensor biases, orbital drifts and diurnal variations of atmospheric and surface temperatures must be considered before using a merged long-term time series of AMSU-A measurements from NOAA- 15, - 18, - 19 and MetOp-A. We study the impacts of the orbital drift and orbital differences of local equator crossing times （LECTs） on temperature trends derivable from AMSU-A using near-nadir observa- tions from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998 - 2014 over the Amazon rainforest. The double difference method is firstly applied to estimation of inter-sensor biases between any two satellites during their overlapping time period. The inter-calibrated observations are then used to generate a monthly mean diurnal cycle of brightness temperature for each AMSU-A channel. A diurnal correction is finally applied each channel to obtain AMSU-A data valid at the same local time. Impacts of the inter-sensor bias correction and diurnal correction on the AMSU-A derived long-term atmospheric temperature trends are separately quantified and compared with those derived from original data. It is shown that the orbital drift and differences of LECT among different POESs induce a large uncertainty in AMSU-A derived long-term warming/cooling trends. After applying an inter-sensor bias correction and a diurnal correction, the warming trends at different local times, which are approximately the same, are smaller by half than the trends derived without applying these corrections.
文摘卫星微波垂直探测器的辐射观测资料在数值预报中的同化应用使得数值预报水平有了巨大的飞跃。微波资料的质量控制是保证观测资料成功同化的关键所在。文章提出一种基于AMSU-A(Advanced Microwave Sounding Unit-A)辐射亮温资料梯度信息的新质量控制方法,将亮温梯度距平值明显较大的资料作为被降水污染或因为其他原因出现的"坏"的资料。利用中尺度非静力WRF(Weather Research and Forecasting)模式和区域三维变分同化,针对"海鸥"(2008)和"圆规"(2010)2个个例,对比旧质量控制中的降水检测和阈值检测方法,评估该方法用于AMSU-A资料同化时对台风数值模拟的情况。研究表明,旧质量控制方法将会使一些"坏"的微波观测资料同化进入模式,降低模式分析场的质量,进而导致同化结果有较大误差。相对于旧方法获得的分析场,利用基于亮温梯度信息的质量控制方法可使更多"坏"的观测剔除,同化后模式初始时刻的位势高度场和风场更接近于真实情况。与传统AMSU-A辐射资料的同化相比,新质量控制方案使2个台风路径数值模拟的偏差有明显的减小:"海鸥"个例中,模拟台风路径误差的最大改善比为12,路径误差改善约540km;"圆规"个例的最大改善比为13,模拟路径误差减小118km。
文摘借助快速辐射传输模式RTTOV v10(Radiative Transfer for TOVS)及其地表微波发射率模块,针对江淮区域晴天和雨天2类不同天气状况,采用理想试验手段,利用集合平方根滤波(En SRF)方法同化AMSU-A对地敏感第1通道的模拟亮温资料,探究改善中尺度模式WRF(Weather Research and Forecasting)初始场的可行性。结果表明:晴天时,同化对位温、水汽混合比及水平风速u和v整体上均有不同程度的改善,但不同高度改善程度有所差异,相对而言水平风场的改进程度最大,位温最小;有降水时,4个要素场整体改进程度与晴天时类似,但分析场误差的水平空间分布与晴天时不同。
