摘要
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.
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 instru- ment synchronously monitoring rain rate on the satellite platform of SAR, we have to derive the precipitation of the SAR ob- servation 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.
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)
