Quality control(QC)is an essential procedure in scatterometer wind retrieval,which is used to distinguish good-quality data from poor-quality wind vector cells(WVCs)for the sake of wind applications.The current wind p...Quality control(QC)is an essential procedure in scatterometer wind retrieval,which is used to distinguish good-quality data from poor-quality wind vector cells(WVCs)for the sake of wind applications.The current wind processor of the China-France Oceanography Satellite(CFOSAT)scatterometer(CSCAT)adopts a maximum likelihood estimator(MLE)-based QC method to filter WVCs affected by geophysical noise,such as rainfall and wind variability.As the first Ku-band rotating fan-beam scatterometer,CSCAT can acquire up to 16 observations over a single WVC,giving abundant information with diverse incidence/azimuth angles,as such its MLE statistical characteristics may be different from the previous scatterometers.In this study,several QC indicators,including MLE,its spatially averaged value(MLE_(m)),and the singularity exponents(SE),are analyzed using the collocated Global Precipitation Mission rainfall data as well as buoy data,to compare their sensitivity to rainfall and wind quality.The results show that wind error characteristics of CSCAT under different QC methods are similar to those of other Ku-band scatterometers,i.e.,SE is more suitable than other parameters for the wind QC at outer-swath and nadir regions,while MLE_(m) is the best QC indicator for the sweet region WVCs.Specifically,SE is much more favorable than others at high wind speeds.By combining different indicators,an improved QC method is developed for CSCAT.The validation with the collocated buoy data shows that it accepts more WVCs,and in turn,improves the quality control of CSCAT wind data.展开更多
采用WRF(Weather Research and Forecasting)模式及其三维变分同化模块WRF-3DVar,开展了中法海洋卫星(China-France Oceanography SATellite,CFOSAT)散射计风场资料同化及数值预报试验研究,对比分析了同化常规观测资料及进一步同化CFOSA...采用WRF(Weather Research and Forecasting)模式及其三维变分同化模块WRF-3DVar,开展了中法海洋卫星(China-France Oceanography SATellite,CFOSAT)散射计风场资料同化及数值预报试验研究,对比分析了同化常规观测资料及进一步同化CFOSAT散射计风场资料后对台风“白鹿”预报效果的影响。结果表明:与不进行资料同化相比,同化常规观测资料使台风路径预报平均绝对误差(Mean Absolute Error,MAE)降低20 km以上,中心最低海平面气压平均绝对误差降低3%以上,但中心最大风速没有明显改善;同化CFOSAT卫星散射计风场资料后,台风路径和强度的预报效果得到进一步改善,与不进行资料同化相比,台风路径预报的平均绝对误差降低30 km以上,中心最低海平面气压平均绝对误差降低约7%,中心最大风速的预报平均绝对误差降低幅度超过20%。展开更多
基金The National Key Research and Development Program of China under contract Nos 2022YFC3104900 and 2022YFC3104902.
文摘Quality control(QC)is an essential procedure in scatterometer wind retrieval,which is used to distinguish good-quality data from poor-quality wind vector cells(WVCs)for the sake of wind applications.The current wind processor of the China-France Oceanography Satellite(CFOSAT)scatterometer(CSCAT)adopts a maximum likelihood estimator(MLE)-based QC method to filter WVCs affected by geophysical noise,such as rainfall and wind variability.As the first Ku-band rotating fan-beam scatterometer,CSCAT can acquire up to 16 observations over a single WVC,giving abundant information with diverse incidence/azimuth angles,as such its MLE statistical characteristics may be different from the previous scatterometers.In this study,several QC indicators,including MLE,its spatially averaged value(MLE_(m)),and the singularity exponents(SE),are analyzed using the collocated Global Precipitation Mission rainfall data as well as buoy data,to compare their sensitivity to rainfall and wind quality.The results show that wind error characteristics of CSCAT under different QC methods are similar to those of other Ku-band scatterometers,i.e.,SE is more suitable than other parameters for the wind QC at outer-swath and nadir regions,while MLE_(m) is the best QC indicator for the sweet region WVCs.Specifically,SE is much more favorable than others at high wind speeds.By combining different indicators,an improved QC method is developed for CSCAT.The validation with the collocated buoy data shows that it accepts more WVCs,and in turn,improves the quality control of CSCAT wind data.
文摘采用WRF(Weather Research and Forecasting)模式及其三维变分同化模块WRF-3DVar,开展了中法海洋卫星(China-France Oceanography SATellite,CFOSAT)散射计风场资料同化及数值预报试验研究,对比分析了同化常规观测资料及进一步同化CFOSAT散射计风场资料后对台风“白鹿”预报效果的影响。结果表明:与不进行资料同化相比,同化常规观测资料使台风路径预报平均绝对误差(Mean Absolute Error,MAE)降低20 km以上,中心最低海平面气压平均绝对误差降低3%以上,但中心最大风速没有明显改善;同化CFOSAT卫星散射计风场资料后,台风路径和强度的预报效果得到进一步改善,与不进行资料同化相比,台风路径预报的平均绝对误差降低30 km以上,中心最低海平面气压平均绝对误差降低约7%,中心最大风速的预报平均绝对误差降低幅度超过20%。
