为了探究云区卫星微波资料的同化应用,利用中国风云三号D星(Fengyun-3D,FY-3D)微波温度计二型(microwave temperature sounder-2,MWTS2)和微波湿度计二型(microwave humidity sounder-2,MWHS2)资料,基于人工神经网络算法研制了云区温湿...为了探究云区卫星微波资料的同化应用,利用中国风云三号D星(Fengyun-3D,FY-3D)微波温度计二型(microwave temperature sounder-2,MWTS2)和微波湿度计二型(microwave humidity sounder-2,MWHS2)资料,基于人工神经网络算法研制了云区温湿廓线反演模型,建立了云区资料的间接同化方案。于2019年6月开展晴空和云区同化试验,评估加入云区MWTS2和MWHS2资料对区域模式预报的影响。试验结果表明:MWTS2和MWHS2资料的同化对温湿度预报场有改善,主要体现在模式中高层均方根误差和平均偏差的减小,云区同化的改善幅度比晴空同化更大;同化MWTS2和MWHS2资料对于提高降水预报技巧有积极影响,云区同化对降水预报的改善主要体现在同化后的12~24 h,较晴空同化更明显。针对强降水个例分析表明,MWTS2和MWHS2资料对温度场、湿度场、水汽通量散度场的调整有利于降水预报的改善,而云区同化能够直接对天气系统的初始场进行调整,降水的位置与强度预报效果更好。展开更多
In order to evaluate the impact of assimilating FY-3C satellite Microwave Humidity Sounder(MWHS2)data on rainfall forecasts in the new-generation Rapid-refresh Multi-scale Analysis and Prediction System–Short Term(RM...In order to evaluate the impact of assimilating FY-3C satellite Microwave Humidity Sounder(MWHS2)data on rainfall forecasts in the new-generation Rapid-refresh Multi-scale Analysis and Prediction System–Short Term(RMAPS-ST)operational system,which is developed by the Institute of Urban Meteorology of the China Meteorological Administration,four experiments were carried out in this study:(i)Coldstart(no observations assimilated);(ii)CON(assimilation of conventional observations);(iii)FY3(assimilation of FY-3C MWHS2 only);and(iv)FY3+CON(simultaneous assimilation of FY-3C MWHS2 and conventional observations).A precipitation process that took place in central-eastern China during 4–6 June 2019 was selected as a case study.When the authors assimilated the FY-3C MWHS2 data in the RMAPS-ST operational system,data quality control and bias correction were performed so that the O-B(observation minus background)values of the five humidity channels of MWHS2 became closer to a normal distribution,and the data basically satisfied the unbiased assumption.The results showed that,in this case,the predictions of both precipitation location and intensity were improved in the FY3+CON experiment compared with the other three experiments.Meanwhile,the prediction of atmospheric parameters for the mesoscale field was also improved,and the RMSE of the specific humidity forecast at the 850–400 hPa height was reduced.This study implies that FY-3C MWHS2 data can be successfully assimilated in a regional numerical model and has the potential to improve the forecasting of rainfall.展开更多
All-sky (i.e., clear, cloudy, and precipitating conditions) assimilation of microwave observations shows potentially positive impacts on the improvement of the forecasts of cloud-associated weather processes. In this ...All-sky (i.e., clear, cloudy, and precipitating conditions) assimilation of microwave observations shows potentially positive impacts on the improvement of the forecasts of cloud-associated weather processes. In this study, a typical mei-yu heavy precipitation event that occurred in 2017 was investigated, and the Weather Research and Forecasting data assimilation (WRFDA) as well as its 3D-Var assimilation scheme (excluding cloud and precipitation control variables) were applied to assimilate the Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) observations under clear- sky (excluding the observations that are strongly affected by ice clouds and precipitation) and all-sky conditions. Three experiments including a control experiment without assimilating any observations, clear-sky, and all-sky experiments with only FY-3C/MWHS-2 observations assimilated were carried out. The results show that the all-sky assimilation approach that provides more cloud and precipitation information and increased more than 10% of the satellite data usage than the clear-sky experiment. Meanwhile, as compared with the control experiment, the all-sky assimilation reduced nearly 0.5% of the root mean square errors in the humidity fields, leading to more accurate forecast performances regarding the distribution and intensity of heavy rainfall;but it exhibited a neutral to negative impacts on the wind and temperature. Although the system used to conduct all-sky assimilation is only able to adjust control variables for moisture-, wind-, and temperature- related variables in the presence of cloud and does not benefit directly from cloud or precipitation information, the positive effects on heavy rainfall forecasts achieved in this study indicate a potential future benefit regarding disaster prevention and mitigation.展开更多
This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard Fengyun-3C (FY-3C). For algorithm development, sc...This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard Fengyun-3C (FY-3C). For algorithm development, scattering- induced TB depressions (ΔTBs) of MWHS-2 at channels between 89 and 190 GHz were collocated to rain rates derived from measurements of the Global Precipitation Measurement’s Dual-frequency Precipitation Radar (DPR) for the year 2017. ΔTBs were calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel. These ΔTBs were then related to rain rates from DPR using (1) multilinear regression (MLR);the other two algorithms, (2) range searches (RS) and (3) nearest neighbor searches (NNS), are based on k-dimensional trees. While all three algorithms produce instantaneous rain rates, the RS algorithm also provides the probability of precipitation and can be understood in a Bayesian framework. Different combinations of MWHS-2 channels were evaluated using MLR and results suggest that adding 118 GHz improves retrieval performance. The optimal combination of channels excludes high-peaking channels but includes 118 GHz channels peaking in the mid and high troposphere. MWHS-2 observations from another year were used for validation purposes. The annual mean 2.5° × 2.5° gridded rain rates from the three algorithms are consistent with those from the Global Precipitation Climatology Project (GPCP) and DPR. Their correlation coefficients with GPCP are 0.96 and their biases are less than 5%. The correlation coefficients with DPR are slightly lower and the maximum bias is ~8%, partly due to the lower sampling density of DPR compared to that of MWHS-2.展开更多
基金Supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(grant no.2019QZKK0105)the National Key Research and Development Program of China(2018YFC1506603).
文摘In order to evaluate the impact of assimilating FY-3C satellite Microwave Humidity Sounder(MWHS2)data on rainfall forecasts in the new-generation Rapid-refresh Multi-scale Analysis and Prediction System–Short Term(RMAPS-ST)operational system,which is developed by the Institute of Urban Meteorology of the China Meteorological Administration,four experiments were carried out in this study:(i)Coldstart(no observations assimilated);(ii)CON(assimilation of conventional observations);(iii)FY3(assimilation of FY-3C MWHS2 only);and(iv)FY3+CON(simultaneous assimilation of FY-3C MWHS2 and conventional observations).A precipitation process that took place in central-eastern China during 4–6 June 2019 was selected as a case study.When the authors assimilated the FY-3C MWHS2 data in the RMAPS-ST operational system,data quality control and bias correction were performed so that the O-B(observation minus background)values of the five humidity channels of MWHS2 became closer to a normal distribution,and the data basically satisfied the unbiased assumption.The results showed that,in this case,the predictions of both precipitation location and intensity were improved in the FY3+CON experiment compared with the other three experiments.Meanwhile,the prediction of atmospheric parameters for the mesoscale field was also improved,and the RMSE of the specific humidity forecast at the 850–400 hPa height was reduced.This study implies that FY-3C MWHS2 data can be successfully assimilated in a regional numerical model and has the potential to improve the forecasting of rainfall.
基金the National Natural Science Funds of China(Grant No.41875039)the Fengyun-3 meteorological satellite ground application system projectthe development of the application software for southwest regional road traffic using the Fengyun-3 satellite remote sensing monitoring service(Grant No.ZQC-J19193)are also appreciated to support this research。
文摘All-sky (i.e., clear, cloudy, and precipitating conditions) assimilation of microwave observations shows potentially positive impacts on the improvement of the forecasts of cloud-associated weather processes. In this study, a typical mei-yu heavy precipitation event that occurred in 2017 was investigated, and the Weather Research and Forecasting data assimilation (WRFDA) as well as its 3D-Var assimilation scheme (excluding cloud and precipitation control variables) were applied to assimilate the Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) observations under clear- sky (excluding the observations that are strongly affected by ice clouds and precipitation) and all-sky conditions. Three experiments including a control experiment without assimilating any observations, clear-sky, and all-sky experiments with only FY-3C/MWHS-2 observations assimilated were carried out. The results show that the all-sky assimilation approach that provides more cloud and precipitation information and increased more than 10% of the satellite data usage than the clear-sky experiment. Meanwhile, as compared with the control experiment, the all-sky assimilation reduced nearly 0.5% of the root mean square errors in the humidity fields, leading to more accurate forecast performances regarding the distribution and intensity of heavy rainfall;but it exhibited a neutral to negative impacts on the wind and temperature. Although the system used to conduct all-sky assimilation is only able to adjust control variables for moisture-, wind-, and temperature- related variables in the presence of cloud and does not benefit directly from cloud or precipitation information, the positive effects on heavy rainfall forecasts achieved in this study indicate a potential future benefit regarding disaster prevention and mitigation.
基金This work was supported by a NASA grant(Grant No.NNX17AJ09G)to Vanderbilt University.
文摘This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard Fengyun-3C (FY-3C). For algorithm development, scattering- induced TB depressions (ΔTBs) of MWHS-2 at channels between 89 and 190 GHz were collocated to rain rates derived from measurements of the Global Precipitation Measurement’s Dual-frequency Precipitation Radar (DPR) for the year 2017. ΔTBs were calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel. These ΔTBs were then related to rain rates from DPR using (1) multilinear regression (MLR);the other two algorithms, (2) range searches (RS) and (3) nearest neighbor searches (NNS), are based on k-dimensional trees. While all three algorithms produce instantaneous rain rates, the RS algorithm also provides the probability of precipitation and can be understood in a Bayesian framework. Different combinations of MWHS-2 channels were evaluated using MLR and results suggest that adding 118 GHz improves retrieval performance. The optimal combination of channels excludes high-peaking channels but includes 118 GHz channels peaking in the mid and high troposphere. MWHS-2 observations from another year were used for validation purposes. The annual mean 2.5° × 2.5° gridded rain rates from the three algorithms are consistent with those from the Global Precipitation Climatology Project (GPCP) and DPR. Their correlation coefficients with GPCP are 0.96 and their biases are less than 5%. The correlation coefficients with DPR are slightly lower and the maximum bias is ~8%, partly due to the lower sampling density of DPR compared to that of MWHS-2.
