为研究COSMIC(constellation observing system for meteorology,ionosphere and climate)掩星反演湿温廓线的质量,需对数据误差特性进行量化研究。首先采用线性插值的方法,以时间窗3 h、水平距离300 km为匹配准则,对0.2~30 km各高度层...为研究COSMIC(constellation observing system for meteorology,ionosphere and climate)掩星反演湿温廓线的质量,需对数据误差特性进行量化研究。首先采用线性插值的方法,以时间窗3 h、水平距离300 km为匹配准则,对0.2~30 km各高度层温度的平均偏差和标准差进行统计分析,研究随海拔高、季节和纬度带变化的温度平均偏差特性。然后采用2016年的全球探空数据集分析全球区域的COSMIC湿温廓线质量,以及北温带COSMIC湿温廓线质量随季节变化的特点,探究不同纬度带地区COSMIC掩星湿温廓线质量随纬度变化的特点。结果表明,全球范围内温度平均偏差为-0.16 K,掩星数据和探空站资料精度相当;季节变化的统计量F=0.999 6>0.05,该因素对COSMIC湿温廓线质量影响不显著;纬度带变化的统计量F=0.024 4<0.05,该因素对COSMIC湿温廓线质量有显著影响,尤其是热带地区受水汽影响较大,温度平均偏差处于峰值,偏差高于0.25 K,南温带地区次之。展开更多
It is important to be able to characterize the thermal conditions over the equatorial Indian Ocean for both weather forecasting and climate prediction. This study compared the equatorial eastern Indian Ocean (EEIO) te...It is important to be able to characterize the thermal conditions over the equatorial Indian Ocean for both weather forecasting and climate prediction. This study compared the equatorial eastern Indian Ocean (EEIO) temperature and relative humidity profiles from three reanalysis products (JRA-55, MERRA2, and FGOALS-f2) with shipboard global positioning system (GPS) sounding measurements obtained during the Eastern Indian Ocean Open Cruise in spring 2018. The FGOALS-f2 reanalysis product is based on the initialization module of a sub-seasonal to seasonal prediction system with a nudging-based data assimilation method. The results indicated that:(1) both JRA-55 and MERRA2 were reliable in characterizing the temperature profile from 850 to 600 hPa, with a maximum deviation of about <0.5℃. Both datasets showed a large negative deviation below 825 hPa, with a maximum bias of about 2℃ at 1000 hPa and 1.5℃ at 900 hPa, respectively.(2) JRA-55 showed good performance in characterizing the relative humidity profile above 850 hPa, with a maximum deviation of < 8%, while it showed much wetter conditions below 850 hPa. MERRA2 overestimated the relative humidity in the middle to lower troposphere, with a maximum deviation of about 15% at 925 hPa.(3) The FGOALS-f2 reanalysis product more accurately reproduced the temperature profile in the marine atmospheric boundary layer over the EEIO than that in JRA-55 and MERRA2, but showed much wetter conditions than the GPS sounding observations, with a maximum deviation of up to 20% at 600 hPa. Future applications of GPS sounding datasets are discussed.展开更多
文摘为研究COSMIC(constellation observing system for meteorology,ionosphere and climate)掩星反演湿温廓线的质量,需对数据误差特性进行量化研究。首先采用线性插值的方法,以时间窗3 h、水平距离300 km为匹配准则,对0.2~30 km各高度层温度的平均偏差和标准差进行统计分析,研究随海拔高、季节和纬度带变化的温度平均偏差特性。然后采用2016年的全球探空数据集分析全球区域的COSMIC湿温廓线质量,以及北温带COSMIC湿温廓线质量随季节变化的特点,探究不同纬度带地区COSMIC掩星湿温廓线质量随纬度变化的特点。结果表明,全球范围内温度平均偏差为-0.16 K,掩星数据和探空站资料精度相当;季节变化的统计量F=0.999 6>0.05,该因素对COSMIC湿温廓线质量影响不显著;纬度带变化的统计量F=0.024 4<0.05,该因素对COSMIC湿温廓线质量有显著影响,尤其是热带地区受水汽影响较大,温度平均偏差处于峰值,偏差高于0.25 K,南温带地区次之。
基金supported by funds from the National Key Research and Development Program Global Change and Mitigation Project [grant number 2017YFA0604004]the National Natural Science Foundation of China [grant numbers41675100,91737306 and U1811464]provided by the SCSIO under the project ‘Scientific investigation of the Eastern Indian Ocean in 2018’,funded by the NSFC(NORC2018-10)
文摘It is important to be able to characterize the thermal conditions over the equatorial Indian Ocean for both weather forecasting and climate prediction. This study compared the equatorial eastern Indian Ocean (EEIO) temperature and relative humidity profiles from three reanalysis products (JRA-55, MERRA2, and FGOALS-f2) with shipboard global positioning system (GPS) sounding measurements obtained during the Eastern Indian Ocean Open Cruise in spring 2018. The FGOALS-f2 reanalysis product is based on the initialization module of a sub-seasonal to seasonal prediction system with a nudging-based data assimilation method. The results indicated that:(1) both JRA-55 and MERRA2 were reliable in characterizing the temperature profile from 850 to 600 hPa, with a maximum deviation of about <0.5℃. Both datasets showed a large negative deviation below 825 hPa, with a maximum bias of about 2℃ at 1000 hPa and 1.5℃ at 900 hPa, respectively.(2) JRA-55 showed good performance in characterizing the relative humidity profile above 850 hPa, with a maximum deviation of < 8%, while it showed much wetter conditions below 850 hPa. MERRA2 overestimated the relative humidity in the middle to lower troposphere, with a maximum deviation of about 15% at 925 hPa.(3) The FGOALS-f2 reanalysis product more accurately reproduced the temperature profile in the marine atmospheric boundary layer over the EEIO than that in JRA-55 and MERRA2, but showed much wetter conditions than the GPS sounding observations, with a maximum deviation of up to 20% at 600 hPa. Future applications of GPS sounding datasets are discussed.
