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- Author or Editor: Cheng-Zhi Zou x
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Abstract
A technique that uses satellite-based surface wind and temperature soundings for deriving three-dimensional atmospheric wind fields is developed for climate studies over the middle- and high-latitude oceans. In this technique, the thermal wind derived from the satellite soundings is added to the surface wind to obtain a first-guess, nonmass-conserved atmospheric wind profile. Then a Lagrange multiplier in a variational formalism is used to force the first-guess wind to conserve mass. Two mass conservation schemes are proposed. One is to use the meridional mass transport conservation equation as a constraint to derive the meridional wind first, and then the vertically integrated mass conservation equation is used to infer the zonal wind. The zonal and meridional winds are obtained separately in this approach. The second scheme is to use the vertically integrated mass conservation equation as a constraint to retrieve the zonal and meridional winds simultaneously from the first-guess field.
Temperature soundings from the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A dataset and a Special Sensor Microwave Imager (SSM/I) satellite-based surface wind field are used to derive the wind fields. The two mass conservation schemes yield two different wind fields. They are compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses and radiosonde observations over the Southern Ocean. The general circulation structure of both wind fields is similar to the reanalysis winds. However, the annual-mean bias of the first method is small in both the zonal and meridional winds compared to radiosonde observations, while the zonal wind bias of the second method is as large as −4 m s−1. The main reason for the difference is that the second method requires that the Lagrange multiplier be zero on the latitudinal boundaries. This forces the retrieved zonal wind to approach the first-guess zonal wind. In contrast, the first method does not require latitudinal boundary conditions, allowing a larger correction to the first-guess zonal wind.
Abstract
A technique that uses satellite-based surface wind and temperature soundings for deriving three-dimensional atmospheric wind fields is developed for climate studies over the middle- and high-latitude oceans. In this technique, the thermal wind derived from the satellite soundings is added to the surface wind to obtain a first-guess, nonmass-conserved atmospheric wind profile. Then a Lagrange multiplier in a variational formalism is used to force the first-guess wind to conserve mass. Two mass conservation schemes are proposed. One is to use the meridional mass transport conservation equation as a constraint to derive the meridional wind first, and then the vertically integrated mass conservation equation is used to infer the zonal wind. The zonal and meridional winds are obtained separately in this approach. The second scheme is to use the vertically integrated mass conservation equation as a constraint to retrieve the zonal and meridional winds simultaneously from the first-guess field.
Temperature soundings from the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A dataset and a Special Sensor Microwave Imager (SSM/I) satellite-based surface wind field are used to derive the wind fields. The two mass conservation schemes yield two different wind fields. They are compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses and radiosonde observations over the Southern Ocean. The general circulation structure of both wind fields is similar to the reanalysis winds. However, the annual-mean bias of the first method is small in both the zonal and meridional winds compared to radiosonde observations, while the zonal wind bias of the second method is as large as −4 m s−1. The main reason for the difference is that the second method requires that the Lagrange multiplier be zero on the latitudinal boundaries. This forces the retrieved zonal wind to approach the first-guess zonal wind. In contrast, the first method does not require latitudinal boundary conditions, allowing a larger correction to the first-guess zonal wind.
Abstract
Moisture fields from the NCEP–DOE reanalysis-2 (R-2) and Television Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A are validated using the Special Sensor Microwave Imager (SSM/I) retrievals over the Southern Ocean. It is shown that the spatial distributions of the annual mean statistics of the total precipitable water are similar among SSM/I, R-2, and TOVS Pathfinder A for both the eddy and mean components. However, transient statistics show that the R-2 total precipitable water agrees with SSM/I with a correlation of 0.77 over the Southern Ocean while the TOVS Pathfinder A moisture is almost uncorrelated with the SSM/I data.
Total moisture transport convergence for 1988 over the Antarctic continent is further examined using the R-2 wind and moisture data as well as the moisture retrievals from TOVS Pathfinder A. To gain a better understanding of transient and mean processes on moisture transport, the total moisture transport was decomposed into mean and eddy components. The results suggest that a mass conservation correction is necessary for the mean component, but can safely be ignored for the eddy component. With the mass conservation correction, the mean moisture transport is about the same for both the R-2 estimate alone and the estimate based on the mixed TOVS Pathfinder A moisture–R-2 wind. The computed eddy and total moisture transport convergence over Antarctica for the R-2 data agrees within 10%–15% with previous surface-data-based estimates as well as estimates from other model analyses. However, the eddy component of the mixed TOVS moisture with R-2 wind is about 60%–70% lower than the R-2 result. These differences occur because the eddy moisture amplitude of the TOVS Pathfinder A is nearly 40% lower than the R-2 data and also because the TOVS moisture has a much lower correlation with the R-2 winds. These results reflect the difficulties with the TOVS sensor in quantifying synoptic moisture transients resulting from conditional sampling problems.
Abstract
Moisture fields from the NCEP–DOE reanalysis-2 (R-2) and Television Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A are validated using the Special Sensor Microwave Imager (SSM/I) retrievals over the Southern Ocean. It is shown that the spatial distributions of the annual mean statistics of the total precipitable water are similar among SSM/I, R-2, and TOVS Pathfinder A for both the eddy and mean components. However, transient statistics show that the R-2 total precipitable water agrees with SSM/I with a correlation of 0.77 over the Southern Ocean while the TOVS Pathfinder A moisture is almost uncorrelated with the SSM/I data.
Total moisture transport convergence for 1988 over the Antarctic continent is further examined using the R-2 wind and moisture data as well as the moisture retrievals from TOVS Pathfinder A. To gain a better understanding of transient and mean processes on moisture transport, the total moisture transport was decomposed into mean and eddy components. The results suggest that a mass conservation correction is necessary for the mean component, but can safely be ignored for the eddy component. With the mass conservation correction, the mean moisture transport is about the same for both the R-2 estimate alone and the estimate based on the mixed TOVS Pathfinder A moisture–R-2 wind. The computed eddy and total moisture transport convergence over Antarctica for the R-2 data agrees within 10%–15% with previous surface-data-based estimates as well as estimates from other model analyses. However, the eddy component of the mixed TOVS moisture with R-2 wind is about 60%–70% lower than the R-2 result. These differences occur because the eddy moisture amplitude of the TOVS Pathfinder A is nearly 40% lower than the R-2 data and also because the TOVS moisture has a much lower correlation with the R-2 winds. These results reflect the difficulties with the TOVS sensor in quantifying synoptic moisture transients resulting from conditional sampling problems.
