A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones
نویسندگان
چکیده
Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW) measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE) wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008) to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division’s H*Wind surface analyses and with the corresponding SeaWinds Project’s L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1) with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms. OPEN ACCESS Remote Sens. 2014, 6 4134
منابع مشابه
Passive Microwave Remote Sensing of Tropical Cyclones
Passive microwave radiometers have a strong heritage of instruments: the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI), the Advanced Microwave Scanning Radiometer–Earth Observing (AMSR-E) and the Special Sensor Microwave Imager/Sounder (SSMI/S). These instruments measure vertically and horizontally polarized brightness temperatures ...
متن کاملSeawinds Improved Ocean Vector Wind Retrievals in Hurricanes
The most pressing issue for the Ku-band scatterometer is associated with the measurement of ocean surface winds in tropical cyclones in the presence of precipitation, which can significantly degrade the wind vector retrieval. Furthermore, at high wind speeds (> 32 m/s), the measurements suffer from radar backscatter saturation effects. Since the spatial resolution of satellite scatterometer and...
متن کاملImproved Hurricane Wind Speed Algorithm for the SeaWinds Satellite Scatterometer
Abszracl-Satellite microwave scatterometer wind retrievals, given in the standard product (e.g., QuikSCAT LZB), badly underestimate the peak wind speed in tropical cyclones. One important reason is that the effects of precipitation on the normalized radar cross section sigma-0 are neglected in the processing algorithms. This paper presents results of a first attempt to provide sigma-0 correctio...
متن کاملImpact of ERS Scatterometer Winds in ECMWF’s Assimilation System
The impact of ERS scatterometer winds on the European Centre for Medium-Range Weather Forecasts (ECMWF) three-dimensional variational (3D-Var) and four-dimensional variational (4D-Var) assimilation systems is investigated. ERS scatterometer winds are found to be of consistent high quality in comparison to other surface wind observations. Both 3D-Var and 4D-Var systems assimilate the data well a...
متن کاملCombined Active/Passive Hurricane Wind Retrieval Algorithm for the Seawinds Scatterometer
Because of their high wind gradient structures, tropical cyclones (TC’s) present a major challenge to space-borne scatterometer measurements of ocean surface wind vectors. Frequently spiral bands of strong rains accompany the high winds, and this precipitation attenuates the ocean backscatter due to wind. Also scattering by the rain volume increases the backscatter measured by the scatterometer...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 6 شماره
صفحات -
تاریخ انتشار 2014