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Alan E. Lipton

Abstract

Geostationary satellite sounder radiances have typically been averaged over several individual fields of view before the radiances are used for retrieving thermodynamic profiles or for assimilation in weather prediction models. The purpose of the averaging is to compensate for data noise. Cloudy fields of view are excluded from averaging. In areas without a sufficient number of clear fields of view, complete profiles are not retrieved. Clouds thus cause gaps in sounder coverage. This note describes an automated method to select a set of averaging areas for a given field of sounder data, such that the gaps in coverage caused by clouds are as small and as few as possible. Test results are shown, indicating that the method can provide substantially better coverage than is obtained with a commonly used method.

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Alan E. Lipton

Abstract

Surface temperature retrieval in mountainous areas is complicated by the high variability of temperatures that can occur within a single satellite field of view. Temperatures depend in part on slope orientation relative to the sun, which can vary radically over very short distances. The surface temperature detected by a satellite is biased toward the temperatures of the sub-field-of-view terrain elements that most directly face the satellite. Numerical simulations were conducted to estimate the effects of satellite viewing geometry on surface temperature retrievals for a section of central Colorado. Surface temperatures were computed using a mesoscale model with a parameterization of subgrid variations in slope and aspect angles.

The simulations indicate that the slope-aspect effect can lead to local surface temperature variations up to 30°C for autumn conditions in the Colorado mountains. For realistic satellite viewing conditions, these variations can give rise to biases in retrieved surface temperatures of about 3°C. Relative biases between retrievals from two satellites with different viewing angles can be over 6°C, which could lead to confusion when merging datasets. The bias computations were limited by the resolution of the available terrain height data (∼90 m). The results suggest that the biases would be significantly larger if the data resolution was fine enough to represent every detail of the real Colorado terrain or if retrievals were made in mountain areas that have a larger proportion of steep slopes than the Colorado Rockies. The computed bias gradients across the Colorado domain were not large enough to significantly alter the forcing of the diurnal upslope-downslope circulations, according to simulations in which surface temperature retrievals with view-dependent biases were assimilated into time-continuous analyses. View-dependent retrieval biases may be relevant to climatological analysts that rely on remotely sensed data, given that bias-induced errors are systematic.

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Alan E. Lipton and Donald W. Hillger

Abstract

In retrieval of atmospheric temperature and moisture soundings from satellite infrared radiance measurements the raw data commonly used consist of dense fields of radiances interrupted by data-free gaps. This note reports an objective analysis procedure which was developed to specifically handle data fields of a discontinuous nature. The method is a correlation-weighted interpolation scheme and includes an oval-extension gap filling feature. Test cases demonstrate the ability of the program to fill gaps caused by instrument calibration periods and by data contamination due to clouds. The procedure is shown to produce much better results within a data-free region than does a similar method without the gap filling feature. An application of this method is also shown in a comparison of satellite-derived atmospheric parameters with conventional observations on a point-to-point basis. However, applications of the procedure are not limited to satellite data analysis, but could include analyses of aircraft data and data from ocean buoys.

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Alan E. Lipton and Thomas H. Vonder Haar

Abstract

Principal components have been widely used in regression retrieval of atmospheric parameters, but when applied to water vapor concentrations their use entails special problems. We discuss two of these problem and present results of retrieval experiments designed to alleviate them. The experiments employed High-resolution Infrared Radiation Sounder satellite data in conjunction with radiosonde observations. We found that mixing ratio is a less appropriate parameter for principal component-based retrieval than is a mean-saturation adjusted mixing ratio. Also, retrieval accuracy was vapor by identifying the optimum numbers of eigenvectors to use when transforming the water vapor profiles and the satellite brightness temperature, respectively, into their principal components. In our studies three eigenvectors were optimal for representation of water vapor, implying that HIRS-2 data are capable of retrieving at least third-order vertical resolution in water vapor profiles. In addition, we compared principal component-based retrieval with standard multiple regression and found that a hybrid of the two methods gave the greatest retrieval accuracy.

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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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