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作 者:Xiaohua XU Yadi LI Jia LUO
机构地区:[1]School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China [2]Collaborative Innovation Center for Geospatial Technology,129 Luoyu Road,Wuhan 430079,China [3]Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,129 Luoyu Road,Wuhan 430079,China
出 处:《Advances in Atmospheric Sciences》2023年第6期1058-1072,共15页大气科学进展(英文版)
基 金:supported by the National Natural Science Foundation of China (Grant Nos. 42174017, 42074027, 41774033, and 41774032)。
摘 要:Using the global navigation satellite system(GNSS) and radio occultation(RO) refractivity data from the Constellation Observing System for Meteorology Ionosphere and Climate-2(COSMIC-2) mission from January 2020 to December 2021, the spatial and temporal variability of Marine Boundary Layer Heights(MBLHs) over the tropical and subtropical oceans are investigated. The MBLH detection method is based on the wavelet covariance transform(WCT)algorithm, while the distinctness(DT) parameter, which reflects the significance of the maximum WCT function values, is introduced. For the refractivity profiles with indistinct maximum WCT function values, the available surrounding ROderived MBLHs are used as auxiliary information, which helps to improve the objectiveness of the inversion process. The RO-derived MBLHs are validated with the MBLHs derived from the collocated high-vertical-resolution radiosonde observations, and the seasonal distributions of the RO-derived MBLHs are presented. Further comparisons of the magnitudes and the distributions of the RO-derived MBLHs with those derived from two model datasets, the European Centre for Medium-Range Weather Forecasts(ECMWF) analyses and the National Centers for Environmental Prediction(NCEP) Aviation(AVN) 12-hour forecast data, reveal that although high correlations exist between the RO-derived and the model-derived MBLHs, the model-derived ones are generally lower than the RO-derived ones in most parts of the tropics and sub-tropic ocean areas during different seasons, which should be partially attributed to the limited vertical resolutions of the model datasets. The correlation analyses between the MBLHs and near-surface wind speeds demonstrate that over the Pacific Ocean, near-surface wind speed is an important factor that influences the variations of the MBLHs.
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