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- Author or Editor: Clément Chouinard x
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Abstract
An algorithm is developed to derive hydrostatically balanced geopotentials at significant levels from radiosonde reports of significant-level temperatures and mandatory-level geopotentials and temperatures. It minimizes the square of the nonhydrostatic differences in a layer where at least one significant-level datum is reported and can be viewed as being a ID analysis step that returns an estimate of the departures from hydrostatic balance within the layer. The piecewise-polynomial interpolation of the minimization procedure is used to produce an expanded geopotential profile in any layer where significant-level data are reported, and the integrated minimization error can be used as a quality-control measure. The algorithm's performance has been evaluated using the global radiosonde dataset for a given synoptic time, and it is found that it produces equivalent layer-mean temperature errors that are generally smaller than radiosonde observational errors.
Abstract
An algorithm is developed to derive hydrostatically balanced geopotentials at significant levels from radiosonde reports of significant-level temperatures and mandatory-level geopotentials and temperatures. It minimizes the square of the nonhydrostatic differences in a layer where at least one significant-level datum is reported and can be viewed as being a ID analysis step that returns an estimate of the departures from hydrostatic balance within the layer. The piecewise-polynomial interpolation of the minimization procedure is used to produce an expanded geopotential profile in any layer where significant-level data are reported, and the integrated minimization error can be used as a quality-control measure. The algorithm's performance has been evaluated using the global radiosonde dataset for a given synoptic time, and it is found that it produces equivalent layer-mean temperature errors that are generally smaller than radiosonde observational errors.
Abstract
The first part of this paper presents the results of a study of the structure of the observed residuals, or differences, between radiosonde data and the short-range forecasts that are used as trial fields in an operational hemispheric data assimilation scheme. The study is based on fitting appropriate functional representations to horizontal correlations of observed height and wind residuals. Rather than represent the height residuals by the sum of a degenerate second-order autoregressive function and an additive constant to account for long-wave error, as in a previous study, we use a representation consisting of a sum of two degenerate third-order autoregressive functions of the form (1 + cr + c2r2 /3) exp(−cr), where r represents radial distance. For the wind residuals, we use the functional form that follows by geostrophy. In addition to examining the structure of the horizontal and vertical correlations, we also present other statistics relating to the performance of the data assimilation procedure, such as vertical profiles of the magnitude of the observed wind and height residuals for various regions.
In the second part of the paper, the results of the study are used as a basis for specifying interpolation statistics for the objective analysis. To evaluate the impact of the new interpolation statistics, various objective measures of analysis performance are examined and parallel 48-h forecasts are performed. It is found that significant improvements result when the new interpolation statistics are used in the data assimilation procedure.
Abstract
The first part of this paper presents the results of a study of the structure of the observed residuals, or differences, between radiosonde data and the short-range forecasts that are used as trial fields in an operational hemispheric data assimilation scheme. The study is based on fitting appropriate functional representations to horizontal correlations of observed height and wind residuals. Rather than represent the height residuals by the sum of a degenerate second-order autoregressive function and an additive constant to account for long-wave error, as in a previous study, we use a representation consisting of a sum of two degenerate third-order autoregressive functions of the form (1 + cr + c2r2 /3) exp(−cr), where r represents radial distance. For the wind residuals, we use the functional form that follows by geostrophy. In addition to examining the structure of the horizontal and vertical correlations, we also present other statistics relating to the performance of the data assimilation procedure, such as vertical profiles of the magnitude of the observed wind and height residuals for various regions.
In the second part of the paper, the results of the study are used as a basis for specifying interpolation statistics for the objective analysis. To evaluate the impact of the new interpolation statistics, various objective measures of analysis performance are examined and parallel 48-h forecasts are performed. It is found that significant improvements result when the new interpolation statistics are used in the data assimilation procedure.
Abstract
The improvement of analysis and data assimilation techniques can have a large impact, as shown here in the context of the Canadian global and regional data assimilation systems. Both of these systems utilize the same analysis component that was recently changed as follows: (a) a completely 3D algorithm replaced the previous split 3D scheme, which involved separate vertical and horizontal steps; (b) the assimilation of SATEM data was revised and is now done in terms of thicknesses over relatively thick layers; (c) an additional analysis level (at 925 hPa) was added and a derived temperature analysis replaced the former temperature analysis; (d) observation and forecast error statistics were revised; and (e) a correction procedure was introduced for certain types of radiosondes to offset the negative impact of solar and longwave radiation.
While many of these changes are interrelated, preventing a systematic evaluation of each in isolation, it is shown that the revised 3D algorithm eliminates a problem that sometimes occurred in areas of dense surface data, SATEM data have a large positive impact in the Southern Hemisphere, and the radiosonde bias-correction scheme very significantly reduces the geopotential height bias observed previously in the upper atmosphere over certain regions, such as western North America.
The overall evaluation of the analysis changes shows that in general the new analysis results in more accurate 6-h forecasts, with the largest improvements in the Tropics and especially in the Southern Hemisphere. In conjunction with these forecast gains, the evaluation of the general circulation statistics for August also show significant changes: the new analyses are more energetic, exhibiting a substantially stronger Hadley circulation and stronger zonal winds about Antarctica. The global forecasts from the revised analysis system consistently exhibit a significantly more rapid spinup of global precipitation as compared to the previous system.
Abstract
The improvement of analysis and data assimilation techniques can have a large impact, as shown here in the context of the Canadian global and regional data assimilation systems. Both of these systems utilize the same analysis component that was recently changed as follows: (a) a completely 3D algorithm replaced the previous split 3D scheme, which involved separate vertical and horizontal steps; (b) the assimilation of SATEM data was revised and is now done in terms of thicknesses over relatively thick layers; (c) an additional analysis level (at 925 hPa) was added and a derived temperature analysis replaced the former temperature analysis; (d) observation and forecast error statistics were revised; and (e) a correction procedure was introduced for certain types of radiosondes to offset the negative impact of solar and longwave radiation.
While many of these changes are interrelated, preventing a systematic evaluation of each in isolation, it is shown that the revised 3D algorithm eliminates a problem that sometimes occurred in areas of dense surface data, SATEM data have a large positive impact in the Southern Hemisphere, and the radiosonde bias-correction scheme very significantly reduces the geopotential height bias observed previously in the upper atmosphere over certain regions, such as western North America.
The overall evaluation of the analysis changes shows that in general the new analysis results in more accurate 6-h forecasts, with the largest improvements in the Tropics and especially in the Southern Hemisphere. In conjunction with these forecast gains, the evaluation of the general circulation statistics for August also show significant changes: the new analyses are more energetic, exhibiting a substantially stronger Hadley circulation and stronger zonal winds about Antarctica. The global forecasts from the revised analysis system consistently exhibit a significantly more rapid spinup of global precipitation as compared to the previous system.
Abstract
A global data assimilation system has been in operation at the Canadian Meteorological Centre (CMC) since March 1991 when it replaced the previous hemispheric system. This paper describes the system and presents an evaluation of its performance from several points of view, including the fit of the analyses and short-range forecasts to observations, the relative roles of various components of the system, the functioning of some specific subcomponents in a particular case, and the ability of the system to represent important as aspects of the mean monthly general circulation. This latter part of the evaluation includes comparisons with the corresponding statistics derived from the analyses of the National Meteorological Center.
The global data assimilation system is found to be functioning well, especially in extratropical regions with reasonable data coverage. Problems and weaknesses of the system are discussed.
Abstract
A global data assimilation system has been in operation at the Canadian Meteorological Centre (CMC) since March 1991 when it replaced the previous hemispheric system. This paper describes the system and presents an evaluation of its performance from several points of view, including the fit of the analyses and short-range forecasts to observations, the relative roles of various components of the system, the functioning of some specific subcomponents in a particular case, and the ability of the system to represent important as aspects of the mean monthly general circulation. This latter part of the evaluation includes comparisons with the corresponding statistics derived from the analyses of the National Meteorological Center.
The global data assimilation system is found to be functioning well, especially in extratropical regions with reasonable data coverage. Problems and weaknesses of the system are discussed.
Abstract
The Canadian regional data assimilation system is described. It is a spinup cycle designed to provide the regional finite-element forecast model with more detailed analyses in a dynamically consistent manner. Its operational performance is evaluated using performance statistics, and a case study is presented to highlight some of the benefits. These include analyses that better fit the data and more detailed and accurate forecasts, particularly for precipitation.
The system also benefits research applications. To illustrate this the authors describe the preparation of the first set of analysts for the international COMPARE (Comparison of Mesoscale Prediction and Research Experiments) Project. The scientific interest of this explosive marine cyclogenetic case is discussed, together with a useful methodology for determining the minimum domain size required by a regional model to avoid forecast contamination from lateral boundaries.
Abstract
The Canadian regional data assimilation system is described. It is a spinup cycle designed to provide the regional finite-element forecast model with more detailed analyses in a dynamically consistent manner. Its operational performance is evaluated using performance statistics, and a case study is presented to highlight some of the benefits. These include analyses that better fit the data and more detailed and accurate forecasts, particularly for precipitation.
The system also benefits research applications. To illustrate this the authors describe the preparation of the first set of analysts for the international COMPARE (Comparison of Mesoscale Prediction and Research Experiments) Project. The scientific interest of this explosive marine cyclogenetic case is discussed, together with a useful methodology for determining the minimum domain size required by a regional model to avoid forecast contamination from lateral boundaries.
