Cyclones with strong winds can make the Southern Ocean and the Antarctic a dangerous environment.Accurate weather forecasts are essential for safe shipping in the Southern Ocean and observational and logistical operat...Cyclones with strong winds can make the Southern Ocean and the Antarctic a dangerous environment.Accurate weather forecasts are essential for safe shipping in the Southern Ocean and observational and logistical operations at Antarctic research stations.This study investigated the impact of additional radiosonde observations from Research Vessel"Shirase"over the Southern Ocean and Dome Fuji Station in Antarctica on reanalysis data and forecast experiments using an ensemble data assimilation system comprising the Atmospheric General Circulation Model for the Earth Simulator and the Local Ensemble Transform Kalman Filter Experimental Ensemble Reanalysis,version 2.A 63-member ensemble forecast experiment was conducted focusing on an unusually strong Antarctic cyclonic event.Reanalysis data with(observing system experiment)and without(control)additional radiosonde data were used as initial values.The observing system experiment correctly captured the central pressure of the cyclone,which led to the reliable prediction of the strong winds and moisture transport near the coast.Conversely,the control experiment predicted lower wind speeds because it failed to forecast the central pressure of the cyclone adequately.Differences were found in cyclone predictions of operational forecast systems with and without assimilation of radiosonde observations from Dome Fuji Station.展开更多
Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logist...Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP.Atmospheric soundings applying unmanned aerial vehicles(UAVs)have a large potential to supplement conventional radiosonde sounding observations.Here,we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting(Polar WRF)model.Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation.In any case,the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature,wind speed,and humidity at the observation site for most of the time.Further,the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site.All experiments succeeded in capturing the main features of the evolution of near-surface variables,but the effects of data assimilation varied between different cases.Due to the limited vertical extent of the UAV observations,the impact of their assimilation was limited to the lowermost 1?2-km layer,and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed.展开更多
The quality controlled（RAW） and homogenized（ADJ） radiosonde temperatures within 850-30 hPa collected at 118 stations in China are compared,on a monthly mean basis,with the temperatures extracted from 8 reanalysis ...The quality controlled（RAW） and homogenized（ADJ） radiosonde temperatures within 850-30 hPa collected at 118 stations in China are compared,on a monthly mean basis,with the temperatures extracted from 8 reanalysis datasets（REA） including NCEP-1,NCEP-2,ERA-40（ECMWF 45-yr Reanalysis）,ERAInterim,JRA-55（Japanese 55-yr Reanalysis）,20CR（20th Century Reanalysis）,MERRA（Modern Era Retrospective-Analysis）,and CFSR（Climate Forecast System Reanalysis）.Average differences,correlations,standard deviations,and linear trends among RAW,ADJ,and REA for the period 1981-2010 are analyzed.The results reveal significant inhomogeneity in the time series of RAW radiosonde temperature in China;an overall negative adjustment was thus employed to obtain the ADJ temperatures,and the effect of the negative adjustment is the most significant within 200-100 hPa.Such a homogenization process has removed the system errors in RAW,possibly caused by radiosonde instrument changes and observation system upgrades.Hence,the correlation is higher between ADJ and REA than that between RAW and REA.The mean difference between ADJ and REA is about 1℃ during 1981-2010,while REA are mostly cooler in the troposphere and warmer in the stratosphere than ADJ;nonetheless,they have a significant high and positive correlation and their annual variability is notably consistent.Furthermore,the linear trends in REA and ADJ both demonstrate warming in the lower-mid troposphere and cooling in the mid stratosphere,with large uncertainties found in the upper troposphere and lower stratosphere.In general,ERA-Interim,JRA-55,and MERRA are more consistent with ADJ than other reanalysis datasets.展开更多
The discontinuities in historical Chinese radiosonde datasets are attributed to artificial errors. In order to reflect more realistically basic conditions of the atmosphere over China and provide more reasonable radio...The discontinuities in historical Chinese radiosonde datasets are attributed to artificial errors. In order to reflect more realistically basic conditions of the atmosphere over China and provide more reasonable radiosonde data as input to climate change analysis and to atmospheric reanalysis data assimilation systems, this paper proposes a scheme to identify breakpoints and adjust biases in daily radiosonde observations. The ongoing ECMWF Re Analysis-Interim(ERA-Interim) 12-h forecasts are used as reference series in the scheme, complemented by the ECMWF Twentieth Century Reanalysis(ERA-20 C). A series of breakpoint identification schemes are developed and combined with metadata to detect breakpoints. The Quantile-Matching(QM) method is applied to test and adjust daily radiosonde data on 12 mandatory pressure levels collected at 80 sounding stations during 1979–2013. The adjusted temperatures on mandatory levels are interpolated to significant levels for temperature adjustment on these levels. The adjustment scheme not only solves the data discontinuity problem caused by changes in observational instruments and bias correction methods, but also solves the discontinuity problem in the 1200 minus 0000 UTC temperature time series on mandatory levels at individual sounding stations. Before the adjustment, obvious discontinuities can be found in the deviation field between the raw radiosonde data and ERA-Interim reanalysis with relatively large deviations before 2001. The deviation discontinuity is mainly attributed to the nationwide upgrade of the radiosonde system in China around 2001. After the adjustment, the time series of deviations becomes more continuous. In addition, compared with the adjusted temperature data on mandatory levels over 80 radiosonde stations in China contained in the Radiosonde Observation Correction Using Reanalyses(RAOBCORE) 1.5, the dataset adjusted by the method proposed in the present study exhibits higher quality than RAOBCORE 1.5, while discontinuities still exist in the time series of temperature at 0000, 1200, and 1200 minus 0000 UTC in RAOBCORE 1.5.展开更多
基金a Japan Society for the Promotion of Science(JSPS)Overseas Research Fellowship,JSPS Grants-in-Aid for Scientific Research(KAKENHI)(Grant Nos.19K14802 and 18H05053)。
文摘Cyclones with strong winds can make the Southern Ocean and the Antarctic a dangerous environment.Accurate weather forecasts are essential for safe shipping in the Southern Ocean and observational and logistical operations at Antarctic research stations.This study investigated the impact of additional radiosonde observations from Research Vessel"Shirase"over the Southern Ocean and Dome Fuji Station in Antarctica on reanalysis data and forecast experiments using an ensemble data assimilation system comprising the Atmospheric General Circulation Model for the Earth Simulator and the Local Ensemble Transform Kalman Filter Experimental Ensemble Reanalysis,version 2.A 63-member ensemble forecast experiment was conducted focusing on an unusually strong Antarctic cyclonic event.Reanalysis data with(observing system experiment)and without(control)additional radiosonde data were used as initial values.The observing system experiment correctly captured the central pressure of the cyclone,which led to the reliable prediction of the strong winds and moisture transport near the coast.Conversely,the control experiment predicted lower wind speeds because it failed to forecast the central pressure of the cyclone adequately.Differences were found in cyclone predictions of operational forecast systems with and without assimilation of radiosonde observations from Dome Fuji Station.
基金the China National Key R&D Program of China(Grant No.2016YFC1402705)the Academy of Finland(contract:304345).
文摘Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP.Atmospheric soundings applying unmanned aerial vehicles(UAVs)have a large potential to supplement conventional radiosonde sounding observations.Here,we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting(Polar WRF)model.Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation.In any case,the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature,wind speed,and humidity at the observation site for most of the time.Further,the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site.All experiments succeeded in capturing the main features of the evolution of near-surface variables,but the effects of data assimilation varied between different cases.Due to the limited vertical extent of the UAV observations,the impact of their assimilation was limited to the lowermost 1?2-km layer,and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430201)Climate Change Special Fund of the China Meteorological Administration(CCSF201330)China Meteorological Administration Special Public Welfare Research Fund(GYHY201406017)
文摘The quality controlled（RAW） and homogenized（ADJ） radiosonde temperatures within 850-30 hPa collected at 118 stations in China are compared,on a monthly mean basis,with the temperatures extracted from 8 reanalysis datasets（REA） including NCEP-1,NCEP-2,ERA-40（ECMWF 45-yr Reanalysis）,ERAInterim,JRA-55（Japanese 55-yr Reanalysis）,20CR（20th Century Reanalysis）,MERRA（Modern Era Retrospective-Analysis）,and CFSR（Climate Forecast System Reanalysis）.Average differences,correlations,standard deviations,and linear trends among RAW,ADJ,and REA for the period 1981-2010 are analyzed.The results reveal significant inhomogeneity in the time series of RAW radiosonde temperature in China;an overall negative adjustment was thus employed to obtain the ADJ temperatures,and the effect of the negative adjustment is the most significant within 200-100 hPa.Such a homogenization process has removed the system errors in RAW,possibly caused by radiosonde instrument changes and observation system upgrades.Hence,the correlation is higher between ADJ and REA than that between RAW and REA.The mean difference between ADJ and REA is about 1℃ during 1981-2010,while REA are mostly cooler in the troposphere and warmer in the stratosphere than ADJ;nonetheless,they have a significant high and positive correlation and their annual variability is notably consistent.Furthermore,the linear trends in REA and ADJ both demonstrate warming in the lower-mid troposphere and cooling in the mid stratosphere,with large uncertainties found in the upper troposphere and lower stratosphere.In general,ERA-Interim,JRA-55,and MERRA are more consistent with ADJ than other reanalysis datasets.
基金Supported by the National Innovation Project for Meteorological Science and Technology (CMAGGTD003-5)China Meteorological Administration Special Public Welfare Research Fund (GYHY201506002)National Key Research and Development Program of China (2017YFC1501801)。
文摘The discontinuities in historical Chinese radiosonde datasets are attributed to artificial errors. In order to reflect more realistically basic conditions of the atmosphere over China and provide more reasonable radiosonde data as input to climate change analysis and to atmospheric reanalysis data assimilation systems, this paper proposes a scheme to identify breakpoints and adjust biases in daily radiosonde observations. The ongoing ECMWF Re Analysis-Interim(ERA-Interim) 12-h forecasts are used as reference series in the scheme, complemented by the ECMWF Twentieth Century Reanalysis(ERA-20 C). A series of breakpoint identification schemes are developed and combined with metadata to detect breakpoints. The Quantile-Matching(QM) method is applied to test and adjust daily radiosonde data on 12 mandatory pressure levels collected at 80 sounding stations during 1979–2013. The adjusted temperatures on mandatory levels are interpolated to significant levels for temperature adjustment on these levels. The adjustment scheme not only solves the data discontinuity problem caused by changes in observational instruments and bias correction methods, but also solves the discontinuity problem in the 1200 minus 0000 UTC temperature time series on mandatory levels at individual sounding stations. Before the adjustment, obvious discontinuities can be found in the deviation field between the raw radiosonde data and ERA-Interim reanalysis with relatively large deviations before 2001. The deviation discontinuity is mainly attributed to the nationwide upgrade of the radiosonde system in China around 2001. After the adjustment, the time series of deviations becomes more continuous. In addition, compared with the adjusted temperature data on mandatory levels over 80 radiosonde stations in China contained in the Radiosonde Observation Correction Using Reanalyses(RAOBCORE) 1.5, the dataset adjusted by the method proposed in the present study exhibits higher quality than RAOBCORE 1.5, while discontinuities still exist in the time series of temperature at 0000, 1200, and 1200 minus 0000 UTC in RAOBCORE 1.5.
