A new 0.1° gridded daily sea surface temperature（SST） data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave（Wind Sat, AMSR-E, ASMR2 ...A new 0.1° gridded daily sea surface temperature（SST） data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave（Wind Sat, AMSR-E, ASMR2 and HY-2 A RM）and two infrared（MODIS and AVHRR） radiometers（RMs） based on the optimum interpolation（OI） method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error（RMSE） of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.展开更多
A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. ...A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976-1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.展开更多
Land data assimilation(DA)is an effective method to provide high-quality spatially and temporally continuous soil moisture datasets that are crucial in weather,climate,hydrological,and agricultural research.However,mo...Land data assimilation(DA)is an effective method to provide high-quality spatially and temporally continuous soil moisture datasets that are crucial in weather,climate,hydrological,and agricultural research.However,most existing land DA applications have used remote sensing observations,and are based on one-dimensional(1 D)analysis,which cannot be directly employed to reasonably assimilate the recently expanded in-situ soil moisture observations in China.In this paper,a two-dimensional(2 D)localized ensemble-based optimum interpolation(En OI)scheme for assimilating in-situ soil moisture observations from over 2200 stations into land surface models(LSMs)is introduced.This scheme uses historical LSM simulations as ensemble samples to provide soil moisture background error covariance,allowing the in-situ observation information to be propagated to surrounding pixels.It is also computationally efficient because no additional ensemble simulations are needed.A set of ensemble sampling and localization length scale sensitivity experiments are performed.The En OI performs best for in-situ soil moisture fusion over China with an ensemble sampling of hourly soil moisture from the previous 7 days and a localization length scale of 100 km.Following the evaluation,simulations for in-situ soil moisture fusion are also performed from May 2016 to September 2016.The En OI analysis is notably better than that without in-situ observation fusion,as the wet bias of 0.02 m3 m-3 is removed,the root-mean-square error(RMSE)is reduced by about 37%,and the correlation coefficient is increased by about 25%.Independent evaluation shows that the En OI analysis performs considerably better than that without fusion in terms of bias,and marginally better in terms of RMSE and correlation.展开更多
The commollly used objective analysis scheme(Scheme-A) for the analysis Of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics,specifically over convectiv...The commollly used objective analysis scheme(Scheme-A) for the analysis Of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics,specifically over convective regions.To overcome this deficiellcy, a new analysis SCheme in which divergent component is included in the statistical model of the wind forecast errors,has been proposed by Daley(1985).Following this scheme,a new set of correlahon functions of forecast errors for the indian region during monsoon season which are suitable for analysing the tropical wind are obtained.This analysis scheme(Scheme--B) as well as Scheme-A were used to make analyses for the period from 4 July to & July 1979(12 GMT) at 850,700 and 200 hpa levels over an area bounded by l.875'N to 39.375'N and 41.250'E to 108.750'E and subsequently divergent component,velocity potential are computed for both schemes.Results from both these schemes show that in the monsoon depression region the velocity potential and divergence have increased in the later case(Scheme-B).This suggests that the divergent component has been enhanced in Scheme-B and that the objechve of this study is realized to some extent.展开更多
基金The National Key Research and Development Program of China under contract No.2016YFA0600102the Basic Scientific Fund for National Public Research Institutes of China under contract No.2015T03the State Oceanic Administration's Second Remote Sensing Survey of East India Ocean Environmental Parameters under contract No.GASI-02-IND-YGST2-04
文摘A new 0.1° gridded daily sea surface temperature（SST） data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave（Wind Sat, AMSR-E, ASMR2 and HY-2 A RM）and two infrared（MODIS and AVHRR） radiometers（RMs） based on the optimum interpolation（OI） method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error（RMSE） of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.
文摘A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976-1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.
基金Supported by the China Meteorological Administration Special Public Welfare Research Fund(GYHY201506002)National Key Research and Development Program of China(2018YFC1506601)+1 种基金National Natural Science Foundation of China(91437220)National Innovation Project for Meteorological Science and Technology(CMAGGTD003-5)。
文摘Land data assimilation(DA)is an effective method to provide high-quality spatially and temporally continuous soil moisture datasets that are crucial in weather,climate,hydrological,and agricultural research.However,most existing land DA applications have used remote sensing observations,and are based on one-dimensional(1 D)analysis,which cannot be directly employed to reasonably assimilate the recently expanded in-situ soil moisture observations in China.In this paper,a two-dimensional(2 D)localized ensemble-based optimum interpolation(En OI)scheme for assimilating in-situ soil moisture observations from over 2200 stations into land surface models(LSMs)is introduced.This scheme uses historical LSM simulations as ensemble samples to provide soil moisture background error covariance,allowing the in-situ observation information to be propagated to surrounding pixels.It is also computationally efficient because no additional ensemble simulations are needed.A set of ensemble sampling and localization length scale sensitivity experiments are performed.The En OI performs best for in-situ soil moisture fusion over China with an ensemble sampling of hourly soil moisture from the previous 7 days and a localization length scale of 100 km.Following the evaluation,simulations for in-situ soil moisture fusion are also performed from May 2016 to September 2016.The En OI analysis is notably better than that without in-situ observation fusion,as the wet bias of 0.02 m3 m-3 is removed,the root-mean-square error(RMSE)is reduced by about 37%,and the correlation coefficient is increased by about 25%.Independent evaluation shows that the En OI analysis performs considerably better than that without fusion in terms of bias,and marginally better in terms of RMSE and correlation.
文摘The commollly used objective analysis scheme(Scheme-A) for the analysis Of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics,specifically over convective regions.To overcome this deficiellcy, a new analysis SCheme in which divergent component is included in the statistical model of the wind forecast errors,has been proposed by Daley(1985).Following this scheme,a new set of correlahon functions of forecast errors for the indian region during monsoon season which are suitable for analysing the tropical wind are obtained.This analysis scheme(Scheme--B) as well as Scheme-A were used to make analyses for the period from 4 July to & July 1979(12 GMT) at 850,700 and 200 hpa levels over an area bounded by l.875'N to 39.375'N and 41.250'E to 108.750'E and subsequently divergent component,velocity potential are computed for both schemes.Results from both these schemes show that in the monsoon depression region the velocity potential and divergence have increased in the later case(Scheme-B).This suggests that the divergent component has been enhanced in Scheme-B and that the objechve of this study is realized to some extent.
