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Xiaolei Zou, Qingnong Xiao, Alan E. Lipton, and George D. Modica

Abstract

The influence of Geostationary Operational Environmental Satellite (GOES) brightness temperature data on the numerical simulations of Hurricane Felix is investigated. Satellite data are included as an augmentation to a bogus data assimilation (BDA) procedure using a mesoscale adjoint modeling system. The assimilation of satellite data modified not only the environmental flow but also the structure of the initial vortex, which is located over a region devoid of satellite data. This modification resulted in a reduction of the 12-h forecast errors verified by radiosonde data. Despite the fact that the forecast using only the bogus surface low at the initial time was very good, track and intensity forecasts beyond 2 days of model integration were shown to be improved further by including satellite data in the initialization procedure. Differences in the prediction of Hurricane Felix with and without satellite data were also found in the prediction of the upper-level jet, the cold temperature trough ahead of the hurricane, the size of the hurricane eye, and the location of the maximum hydrometeor. Although the focus of this study is to assess the effect of the direct use of satellite brightness temperature data on hurricane prediction, it is also noted that the BDA experiment including only the bogus data shows a positive effect of the BDA vortex on the environmental flow during the forecast period, as verified by satellite observations.

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Jean-Luc Moncet, Gennady Uymin, Pan Liang, and Alan E. Lipton

Abstract

The optimal spectral sampling (OSS) method provides a fast and accurate way to model radiometric observations and their Jacobians (required for inversion problems) as a linear combination of monochromatic quantities. The method is flexible and versatile with respect to the treatment of variable constituents, and the method’s fidelity to reference line-by-line (LBL) calculations is tunable. The focus of this paper is on the modeling of radiances from hyperspectral infrared sounders in both clear and cloudy (scattering) atmospheres for application to retrieval and data assimilation. In earlier articles, the authors presented an approach that performed spectral sampling for each channel sequentially. This approach is particularly robust in terms of preserving fidelity to LBL models and yields ratios of monochromatic calculations per channel of approximately 1:1 for such hyperspectral sensors as the Infrared Atmospheric Sounding Interferometer (IASI) or the Atmospheric Infrared Sounder (AIRS) (when tuned for nominal 0.05-K accuracy). This paper describes the generalization of the OSS concept to minimize the total number of monochromatic points required to model a set of channels across individual spectral bands or across the entire domain of the measurements. Its application to principal components of radiance measurements is addressed. It is found that the optimal solution produced by the OSS method offers computational advantages over existing models based on principal components, but, more importantly, it has superior error characteristics.

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Frank H. Ruggiero, George D. Modica, and Alan E. Lipton

Abstract

An assimilation system that performs continuous assimilation of satellite imager data and intermittent assimilation of hourly surface observations is described. The system was applied to a case study of the southeast United States that was heavily influenced by the shading effect of an area of morning stratiform clouds. The results of analyses produced during the assimilation show improvement in the depiction of the modified surface heating effects beneath the cloudy region as well as in important convective precursors such as mass and moisture convergence and convective available potential energy in the cloudy and adjoining regions. Without assimilation of these data, the numerical model was less able to simulate these thermally forced circulations.

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Jean-Luc Moncet, Gennady Uymin, Alan E. Lipton, and Hilary E. Snell

Abstract

This paper describes a rapid and accurate technique for the numerical modeling of band transmittances and radiances in media with nonhomogeneous thermodynamic properties (i.e., temperature and pressure), containing a mixture of absorbing gases with variable concentrations. The optimal spectral sampling (OSS) method has been designed specifically for the modeling of radiances measured by sounding radiometers in the infrared and has been extended to the microwave; it is applicable also through the visible and ultraviolet spectrum. OSS is particularly well suited for remote sensing applications and for the assimilation of satellite observations in numerical weather prediction models. The novel OSS approach is an extension of the exponential sum fitting of transmittances technique in that channel-average radiative transfer is obtained from a weighted sum of monochromatic calculations. The fact that OSS is fundamentally a monochromatic method provides the ability to accurately treat surface reflectance and spectral variations of the Planck function and surface emissivity within the channel passband, given that the proper training is applied. In addition, the method is readily coupled to multiple scattering calculations, an important factor for treating cloudy radiances. The OSS method is directly applicable to nonpositive instrument line shapes such as unapodized or weakly apodized interferometric measurements. Among the advantages of the OSS method is that its numerical accuracy, with respect to a reference line-by-line model, is selectable, allowing the model to provide whatever balance of accuracy and computational speed is optimal for a particular application. Generally only a few monochromatic points are required to model channel radiances with a brightness temperature accuracy of 0.05 K, and computation of Jacobians in a monochromatic radiative transfer scheme is straightforward. These efficiencies yield execution speeds that compare favorably to those achieved with other existing, less accurate parameterizations.

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Alan E. Lipton, George D. Modica, Scot T. Heckman, and Arthur J. Jackson

Abstract

A system for time-continuous mesoscale weather analysis is applied to a study of convective cloud development in central Florida. The analysis system incorporates water vapor concentrations and surface temperatures retrieved from infrared VISSR (Visible–Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS) satellite data, with coupling between the retrieval process and time integration of a mesoscale model. Analyses prepared with variations of this coupled system are compared with a control numerical analysis prepared with only conventional meteorological observations and are validated against surface and upper-air data collected for the Convection and Precipitation/Electrification experiment. The coupled analyses assimilate six sets of VAS data over an 8-h period on 19 July 1991 and depict water vapor gradients at far greater horizontal resolution than is available from conventional observations and with an overall accuracy better than the control analysis. The coupled system's ability to assimilate multiple sets of VAS data, with meteorological continuity provided by the model, was important to the accuracy and the breadth of coverage of the water vapor analysis amid changing cloud cover conditions. The surface temperature information provided by the VAS was neither harmful nor very helpful to the mesoscale analysis for this case, owing to the combination of mediocre satellite viewing conditions and the apparent low importance of land surface temperature gradients to the meteorology of the day. Convective stability parameters computed from the coupled analysis data at 1000 local time corresponded closely with patterns of cloud development in the early afternoon.

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Frank H. Ruggiero, Keith D. Sashegyi, Alan E. Lipton, Rangarao V. Madala, and Sethu Raman

Abstract

A satellite–model coupled procedure for assimilating geostationary satellite sounder data was adapted to a mesoscale analysis and forecast system jointly developed by the Naval Research Laboratory and the Air Force Research Laboratory. The coupled procedure involves the use of the model output fields as the first guess for the thermodynamic retrievals. Atmospheric thermodynamic profiles and ground temperatures were retrieved from observed radiances of the VISSR Atmospheric Sounder (VAS) on board the Geostationary Operational Environmental Satellite. The successive corrections objective analysis scheme in the mesoscale analysis and forecast system was modified to consider the horizontal spatial correlation of the satellite data. The procedure was tested using a wintertime case from the 1986 Genesis of Atlantic Lows Experiment project. The retrievals generated by the coupled method were modestly improved relative to independent stand-alone retrievals. Coupled analyses and forecasts of temperature and moisture fields compared favorably to forecasts from a control run without the VAS assimilation.

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