| Applications of AMSR-E Measurements for Tropical Cyclone Predictions Part Ⅰ： Retrieval of Sea Surface Temperature and Wind Speed |
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| 作者姓名： | Banghua YAN Fuzhong WENG |
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| 作者单位： | Banghua YAN and Fuzhong WENG NOAA Joint Center for Satellite Data Assimilation，Camp Springs，MD，USA NOAA/NESDIS/Center for Satellite Applications and Research，Camp Springs，MD，USA |
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| 基金项目： | This work is supported by NOAA Integrated Program Office through the Internal Government Studies funding.The views expressed in this publication are those of the authors and do not necessarily represent those of NOAA. |
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| 摘 要： | Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS） Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer （AMSRoE） onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSRoE measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square （RMS） errors for SST and SSW are about 1.8 K and 1.9 m s^- 1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds （e.g., its liquid water path is larger than 0.5 mm）, while they are 1.1 K for SST and 2.0 m s^-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.
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| 关 键 词： | 测量技术 云层 大气 海洋 风速 |
| 收稿时间： | 11 September 2006 |
Applications of AMSR-E measurements for tropical cyclone predictions Part I: Retrieval of Sea Surface Temperature and Wind speed |
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| Banghua YAN,Fuzhong WENG.Applications of AMSR-E measurements for tropical cyclone predictions Part I: Retrieval of Sea Surface Temperature and Wind speed[J].Advances in Atmospheric Sciences,2008,25(2):227-245. |
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| Authors: | Banghua Yan Fuzhong Weng |
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| Institution: | [1]NOAA Joint Center for Satellite Data Assimilation, Camp Springs, MD, USA [2]NOAA/NESDIS/Center for Satellite Applications and Research, Camp Springs, MD, USA |
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| Abstract: | Existing satellite microwave algorithms for retrieving Sea Surface Temperature (SST) and Wind (SSW) are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System (EOS) Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer (AMSR-E) onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSR-E measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square (RMS) errors for SST and SSW are about 1.8 K and 1.9 ms-1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds (e.g., its liquid water path is larger than 0.5 mm), while they are 1.1 K for SST and 2.0 m s-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields. |
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| Keywords: | Ocean surface temperature ocean surface wind AMSR-E hurricane vortex analysis |
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