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- Author or Editor: Dewey E. Harms x
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Four-dimensional data-assimilation methods, along with the most commonly used objective analysis and initialization techniques, are examined from a historical perspective. Operational techniques, including intermittent data assimilation and Newtonian nudging, and next-generation methods (Kalman–Bucy filtering and the adjoint method) are briefly described. Several methods are compared, with primary emphasis being placed on recent papers dealing with the operational assimilation techniques. Ongoing and future research is outlined, and some important implications of this research are discussed.
Four-dimensional data-assimilation methods, along with the most commonly used objective analysis and initialization techniques, are examined from a historical perspective. Operational techniques, including intermittent data assimilation and Newtonian nudging, and next-generation methods (Kalman–Bucy filtering and the adjoint method) are briefly described. Several methods are compared, with primary emphasis being placed on recent papers dealing with the operational assimilation techniques. Ongoing and future research is outlined, and some important implications of this research are discussed.
Abstract
Diabatic forcing has been incorporated into a nonlinear normal-mode initialization scheme to provide more realistic initial conditions and to alleviate the problem of the spinup time of the Naval Research Laboratory Limited-Area Numerical Weather Prediction Model. Latent heating profiles are computed from the observed rainfall and from the model-generated convective rainfall at locations where there were no observations. The latent heating is distributed in the vertical according to the cumulus convective parameterization scheme (Kuo scheme) of the model. The results of a case study from the Genesis of Atlantic Lows Experiment indicated that model spinup of forecast rainfall can be reduced when diabatic initialization with merging of heat and/or rain is used.
Abstract
Diabatic forcing has been incorporated into a nonlinear normal-mode initialization scheme to provide more realistic initial conditions and to alleviate the problem of the spinup time of the Naval Research Laboratory Limited-Area Numerical Weather Prediction Model. Latent heating profiles are computed from the observed rainfall and from the model-generated convective rainfall at locations where there were no observations. The latent heating is distributed in the vertical according to the cumulus convective parameterization scheme (Kuo scheme) of the model. The results of a case study from the Genesis of Atlantic Lows Experiment indicated that model spinup of forecast rainfall can be reduced when diabatic initialization with merging of heat and/or rain is used.
Abstract
The successive correction scheme of Bratseth, which converges to optimum interpolation, is applied for the numerical analysis of data collected during the Genesis of Atlantic Lows Experiment. A first guess for the analysis is provided by a 12-h forecast produced by integrating a limited-area model from a prior coarse operational analysis. Initially, univariate analyses of the mass and wind fields are produced. To achieve the coupling of the mass and wind fields, additional iterations on the geopotential are performed by extrapolating the geopotential to grid points, using improving estimates of the geostrophic wind. This improved geostrophic wind is then used to update the geostrophic component of the initial univariate wind analysis. Use of a background forecast produces much improved mesoscale structures in the analysis. Enhanced gradients of the geopotential and larger wind shears are the result of the coupling of the mass and wind fields, particularly in regions of lower data density. Application of the vertical mode initialization scheme of Bourke and McGregor is used to diagnose the divergent component of the mesoscale circulations produced with the analysis scheme.
Abstract
The successive correction scheme of Bratseth, which converges to optimum interpolation, is applied for the numerical analysis of data collected during the Genesis of Atlantic Lows Experiment. A first guess for the analysis is provided by a 12-h forecast produced by integrating a limited-area model from a prior coarse operational analysis. Initially, univariate analyses of the mass and wind fields are produced. To achieve the coupling of the mass and wind fields, additional iterations on the geopotential are performed by extrapolating the geopotential to grid points, using improving estimates of the geostrophic wind. This improved geostrophic wind is then used to update the geostrophic component of the initial univariate wind analysis. Use of a background forecast produces much improved mesoscale structures in the analysis. Enhanced gradients of the geopotential and larger wind shears are the result of the coupling of the mass and wind fields, particularly in regions of lower data density. Application of the vertical mode initialization scheme of Bourke and McGregor is used to diagnose the divergent component of the mesoscale circulations produced with the analysis scheme.
Abstract
This paper presents an objective and subjective verification of a high-resolution configuration of the Regional Atmospheric Modeling System (RAMS) over east-central Florida during the 1999 and 2000 summer months. Centered on the Cape Canaveral Air Force Station (CCAFS), the innermost nested grid of RAMS has a horizontal grid spacing of 1.25 km, thereby providing forecasts capable of modeling finescale phenomena such as ocean and river breezes, and convection. The RAMS is run operationally at CCAFS within the Eastern Range Dispersion Assessment System (ERDAS), in order to provide emergency response guidance during space operations. ERDAS uses RAMS wind and temperature fields for input into ERDAS diffusion algorithms; therefore, the accuracy of dispersion predictions is highly dependent on the accuracy of RAMS forecasts. The most substantial error in RAMS over east-central Florida is a surface-based cold temperature bias, primarily during the daylight hours. At the Shuttle Landing Facility, the RAMS point error statistics are not substantially different than the National Centers for Environment Prediction Eta Model; however, an objective evaluation consisting of only point error statistics cannot adequately determine the added value of a high-resolution model configuration. Thus, results from a subjective evaluation of the RAMS forecast sea breeze and thunderstorm initiation on the 1.25-km grid are also presented. According to the subjective verification of the Florida east coast sea breeze, the RAMS categorical and skill scores exceeded that of the Eta Model predictions in most instances. The RAMS skill scores in predicting thunderstorm initiation are much lower than the sea-breeze evaluation scores, likely resulting from the lack of a sophisticated data assimilation scheme in the current operational configuration.
Abstract
This paper presents an objective and subjective verification of a high-resolution configuration of the Regional Atmospheric Modeling System (RAMS) over east-central Florida during the 1999 and 2000 summer months. Centered on the Cape Canaveral Air Force Station (CCAFS), the innermost nested grid of RAMS has a horizontal grid spacing of 1.25 km, thereby providing forecasts capable of modeling finescale phenomena such as ocean and river breezes, and convection. The RAMS is run operationally at CCAFS within the Eastern Range Dispersion Assessment System (ERDAS), in order to provide emergency response guidance during space operations. ERDAS uses RAMS wind and temperature fields for input into ERDAS diffusion algorithms; therefore, the accuracy of dispersion predictions is highly dependent on the accuracy of RAMS forecasts. The most substantial error in RAMS over east-central Florida is a surface-based cold temperature bias, primarily during the daylight hours. At the Shuttle Landing Facility, the RAMS point error statistics are not substantially different than the National Centers for Environment Prediction Eta Model; however, an objective evaluation consisting of only point error statistics cannot adequately determine the added value of a high-resolution model configuration. Thus, results from a subjective evaluation of the RAMS forecast sea breeze and thunderstorm initiation on the 1.25-km grid are also presented. According to the subjective verification of the Florida east coast sea breeze, the RAMS categorical and skill scores exceeded that of the Eta Model predictions in most instances. The RAMS skill scores in predicting thunderstorm initiation are much lower than the sea-breeze evaluation scores, likely resulting from the lack of a sophisticated data assimilation scheme in the current operational configuration.
