Rain is one of the main sources of error in dual-frequency altimeter Jason-1 wind measurement. In this study, a new radar altimeter backscatter model is proposed and validated to eliminate rain effects. The model take...Rain is one of the main sources of error in dual-frequency altimeter Jason-1 wind measurement. In this study, a new radar altimeter backscatter model is proposed and validated to eliminate rain effects. The model takes into account attenuation, volume backscattering, and sea surface perturbation by raindrops under rain conditions. A match-up dataset is built to evaluate rain effects, in combination with the Jason-1 normalized radar cross section, precipitation radar data from the Tropical Rainfall Measuring Mission, and sea surface wind reanalysis data from the European Centre for Medium-Range Weather Forecasts. The results show that rain-induced surface perturbation backscatter increases with rain rate at Ku-band, but their correlation at C-band is poor. In addition, rain surface perturbation and attenuation have major effects on radar altimeter wind measurements. Finally, a rain correction model for Jason-1 winds is developed and validation results prove its ability to reduce rain-induced inaccuracies in wind retrievals.展开更多
The traditional method of Synthetic Aperture Radar(SAR)wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds,w...The traditional method of Synthetic Aperture Radar(SAR)wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds,where this relation is called the geophysical model function(GMF).However,the accuracy rapidly decreases due to the impact of rainfall on the measurement of SAR and the saturation of backscattered intensity under the condition of tropical cyclone.Because of no available instrument synchronously monitoring rain rate on the satellite platform of SAR,we have to derive the precipitation of the SAR observation time from non-simultaneous passive microwave observations of rain in combination with geostationary IR images,and then use the model of rain correction to remove the impact of rain on SAR wind field measurements.For the saturation of radar backscatter cross section in high wind speed conditions,we develop an approach to estimate tropical cyclone parameters and wind fields based on the improved Holland model and the SAR image features of tropical cyclone.To retrieve the low-to-moderate wind speed,the wind direction of tropical cyclone is estimated from the SAR image using wavelet analysis.And then the maximum wind speed and the central pressure of tropical cyclone are calculated by a least square minimization of the difference between the improved Holland model and the low-to-moderate wind speed retrieved from SAR.In addition,wind fields are estimated from the improved Holland model using the above-mentioned parameters of tropical cyclone as input.To evaluate the accuracy of our approach,the SAR images of typhoon Aere,typhoon Khanun,and hurricane Ophelia are used to estimate tropical cyclone parameters and wind fields,which are compared with the best track data and reanalyzed wind fields of the Joint Typhoon Warning Center(JTWC)and the Hurricane Research Division(HRD).The results indicate that the tropical cyclone center,maximum wind speed,and central pressure are generally consistent with the best track data,and wind fields agree well with reanalyzed data from HRD.展开更多
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences (No.Y0S04300KB)the Major Program for the Research Equipment of Chinese Academy of Sciences (No.YZ200946)
文摘Rain is one of the main sources of error in dual-frequency altimeter Jason-1 wind measurement. In this study, a new radar altimeter backscatter model is proposed and validated to eliminate rain effects. The model takes into account attenuation, volume backscattering, and sea surface perturbation by raindrops under rain conditions. A match-up dataset is built to evaluate rain effects, in combination with the Jason-1 normalized radar cross section, precipitation radar data from the Tropical Rainfall Measuring Mission, and sea surface wind reanalysis data from the European Centre for Medium-Range Weather Forecasts. The results show that rain-induced surface perturbation backscatter increases with rain rate at Ku-band, but their correlation at C-band is poor. In addition, rain surface perturbation and attenuation have major effects on radar altimeter wind measurements. Finally, a rain correction model for Jason-1 winds is developed and validation results prove its ability to reduce rain-induced inaccuracies in wind retrievals.
基金supported by the National Natural Science Foundation of China(Grant Nos.41201350&41228007)the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.Y0S04300KB)
文摘The traditional method of Synthetic Aperture Radar(SAR)wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds,where this relation is called the geophysical model function(GMF).However,the accuracy rapidly decreases due to the impact of rainfall on the measurement of SAR and the saturation of backscattered intensity under the condition of tropical cyclone.Because of no available instrument synchronously monitoring rain rate on the satellite platform of SAR,we have to derive the precipitation of the SAR observation time from non-simultaneous passive microwave observations of rain in combination with geostationary IR images,and then use the model of rain correction to remove the impact of rain on SAR wind field measurements.For the saturation of radar backscatter cross section in high wind speed conditions,we develop an approach to estimate tropical cyclone parameters and wind fields based on the improved Holland model and the SAR image features of tropical cyclone.To retrieve the low-to-moderate wind speed,the wind direction of tropical cyclone is estimated from the SAR image using wavelet analysis.And then the maximum wind speed and the central pressure of tropical cyclone are calculated by a least square minimization of the difference between the improved Holland model and the low-to-moderate wind speed retrieved from SAR.In addition,wind fields are estimated from the improved Holland model using the above-mentioned parameters of tropical cyclone as input.To evaluate the accuracy of our approach,the SAR images of typhoon Aere,typhoon Khanun,and hurricane Ophelia are used to estimate tropical cyclone parameters and wind fields,which are compared with the best track data and reanalyzed wind fields of the Joint Typhoon Warning Center(JTWC)and the Hurricane Research Division(HRD).The results indicate that the tropical cyclone center,maximum wind speed,and central pressure are generally consistent with the best track data,and wind fields agree well with reanalyzed data from HRD.
