Alan E. Lipton

A Numerical Study of the Effect of GOES Sounder Cloud-Cleared Brightness Temperatures on the Prediction of Hurricane Felix

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.

Cloud Shading Retrieval and Assimilation in a Satellite-Model Coupled Mesoscale Analysis System

Abstract A retrieval-assimilation method has been developed as a quantitative means to exploit the information in satellite imagery regarding shading of the ground by clouds, as applied to mesoscale weather analysis. Cloud radiative parameters are retrieved from satellite visible image data and used, along with parameters computed by a numerical model, to control the models computation of downward tadiative fluxes at the ground. These fluxes, in turn, influence the analysis of ground surface temperatures under clouds. The method is part of a satellite-model coupled four-dimensional analysis system that merges information from visible image data in cloudy areas with infrared sounder data in clear areas, where retrievals of surface temperatures and water vapor concentrations are assimilated. The substantial impact of shading on boundary-layer development and mesoscale circulations was demonstrated in simulations, and the value of assimilating shading retrievals was demonstrated with a case study and with a...

Mesoscale Analysis by Numerical Modeling Coupled with Sounding Retrieval from Satellites

Abstract The development and evaluation of a system for time-continuous mesoscale analysis is presented, with a focus on retrieving water vapor concentrations and ground surface temperatures from VISSR Atmospheric Sounder (VAS) data. The analysis system is distinguished by an intimate coupling of retrieval and numerical modeling processes that avoids some of the problem researchers have encountered when satellite-retrieved parameters have been input to models. The system incorporates virtually all of the temporal, vertical and horizontal structure that can be resolved in VAS soundings while maintaining model-generated gradients. The two primary components of the system are a version of the CSU Regional Atmospheric Modeling System (RAMS) and an algorithm for retrieving meteorological parameters from VAS data. The analysis system was evaluated by means of simulations, with a domain that consisted of a vertical cross section through a broad mountain slope. The purposes were to determine the accuracy of coupl...

Satellite-Model Coupled Analysis of Convective Potential in Florida with VAS Water Vapor and Surface Temperature Data

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 systems ability to ass...

Coupled Assimilation of Geostationary Satellite Sounder Data into a Mesoscale Model Using the Bratseth Analysis Approach

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 a...

Assimilation of Satellite Imager Data and Surface Observations to Improve Analysis of Circulations Forced by Cloud Shading Contrasts

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.

Assimilation of Visible-Band Satellite Data for Mesoscale Forecasting in Cloudy Conditions

Abstract Assimilation of satellite data can enhance the ability of a mesoscale modeling system to produce accurate short-term forecasts of clouds and precipitation, but only if there is a mechanism for the satellite-derived information to propagate coherently from the analysis into the forecast period. In situations where stratiform cloud cover inhibits surface heating, assimilation of visible image data can be beneficial for analyses, but those data present particular challenges for application to numerical forecasts. To address the forecast problem, a method to adjust the humidity field and the radiative parameterization of a model was developed such that satellite retrievals of cloud properties have an impact that extends well into the forecast. The adjustment directs the model’s cloud diagnosis and radiation algorithms to produce results that agree with satellite retrievals valid at the forecast initiation time. Experiments showed a high level of fidelity between a short-term forecast made with this m...

Effects of Slope and Aspect Variations on Satellite Surface Temperature Retrievals and Mesoscale Analysis in Mountainous Terrain

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 te...

Preconvective Mesoscale Analysis over Irregular Terrain with a Satellite-Model Coupled System

Abstract Influences on the mesoscale distribution of summertime convective cloud development in the northeastern Colorado region are described using a new system for time-continuous mesoscale analysis. The analysis system is distinctive in that there is an intimate coupling between integration of a numerical model and retrieval of temperature and water vapor concentrations from VISSR Atmospheric Sounder (VAS) data. We present a case study to compare results of the coupled analysis method with those of related methods, focusing on the roles of variations in ground surface temperatures and water vapor concentrations. The horizontal and time variations represented in satellite-based (coupled) surface temperature analyses closely corresponded to information from conventional shelter temperature observations, but had much greater detail. In contrast, temperature based on energy balance computations tended to increase too quickly during the morning and were lacking in mesoscale feature. In the water vapor analy...

Retrieval of water vapor profiles via principal components: options and their implications

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 pri...