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 De...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.展开更多
This paper presents the design of an observation operator for assimilation of global navigation satellite system（GNSS） radio occultation（RO） refractivity and the related operational implementation strategy in the ...This paper presents the design of an observation operator for assimilation of global navigation satellite system（GNSS） radio occultation（RO） refractivity and the related operational implementation strategy in the global GRAPES variational data assimilation system.A preliminary assessment of the RO data assimilation effect is performed.The results show that the RO data are one of the most important observation types in GRAPES,as they have a significant positive impact on the analysis and forecast at all ranges,especially in the Southern Hemisphere and the global stratosphere where in-situ measurements are lacking.The GRAPES model error cannot be controlled in the Southern Hemisphere without RO data being assimilated.In addition,it is found that the RO data play a key role in the stable running of the GRAPES global assimilation and forecast system.Even in a relatively simple global data assimilation experiment,in which only the conventional and RO data are assimilated,the system is able to run for more than nine months without drift compared with NCEP analyses.The analysis skills in both the Northern and Southern Hemispheres are still relatively comparable even after nine-month integration,especially in the stratosphere where the number of conventional observations decreases and RO observations with a uniform global coverage dominate gradually.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 42174017, 42074027, 41774033, and 41774032)。
文摘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.
基金Supported by the National Natural Science Foundation of China(41075081)China Meteorological Administration Special Public Welfare Research Fund(GYHY201106008 and GYHY201206007)
文摘This paper presents the design of an observation operator for assimilation of global navigation satellite system（GNSS） radio occultation（RO） refractivity and the related operational implementation strategy in the global GRAPES variational data assimilation system.A preliminary assessment of the RO data assimilation effect is performed.The results show that the RO data are one of the most important observation types in GRAPES,as they have a significant positive impact on the analysis and forecast at all ranges,especially in the Southern Hemisphere and the global stratosphere where in-situ measurements are lacking.The GRAPES model error cannot be controlled in the Southern Hemisphere without RO data being assimilated.In addition,it is found that the RO data play a key role in the stable running of the GRAPES global assimilation and forecast system.Even in a relatively simple global data assimilation experiment,in which only the conventional and RO data are assimilated,the system is able to run for more than nine months without drift compared with NCEP analyses.The analysis skills in both the Northern and Southern Hemispheres are still relatively comparable even after nine-month integration,especially in the stratosphere where the number of conventional observations decreases and RO observations with a uniform global coverage dominate gradually.
