VISSR atmospheric sounder /VAS/ simulation experiment for a severe storm environment
(Previously announced in STAR as N82-19774)
Engineering topics
Publications and source records attributed to Chesters, D..
(Previously announced in STAR as N82-19774)
Imagery available with the Goes satellite visible-IR spin-scan radiometer (VISSR) atmospheric sounders (VAS) are examined in terms of mid- and low-tropospheric moisture sensing and mesoscale soundings. The VAS can be operated in a Dwell Sounding mode (DS) involving preprogrammed scanning of a specific area using any number of combinations of 12 channels between 4-15 microns. A second, multi-spectral imaging mode (MSI) comprises operation of two IR channels simultaneously when time constraints are in effect. Case studies are presented to demonstrate the effectiveness of VAS imagery for characterizing mesoscale moisture conditions when identifying severe storms. The moisture patterns of the upper and lower troposphere are made visible, and a 6.7 micron channel image can be overlaid on a low level moisture field to delineate fields of potential instability.
Radiance fields were simulated for prethunderstorm environments in Oklahoma to demonstrate three points: (1) significant moisture gradients can be seen directly in images of the VISSIR Atmospheric Sounder (VAS) channels; (2) temperature and moisture profiles can be retrieved from VAS radiances with sufficient accuracy to be useful for mesoscale analysis of a severe storm environment; and (3) the quality of VAS mesoscale soundings improves with conditioning by local weather statistics. The results represent the optimum retrievability of mesoscale information from VAS radiance without the use of ancillary data. The simulations suggest that VAS data will yield the best soundings when a human being classifies the scene, picks relatively clear areas for retrieval, and applies a "local" statistical data base to resolve the ambiguities of satellite observations in favor of the most probable atmospheric structure.
The first orderly, calibrated radiances from the VAS-D instrument on the GOES-4 satellite are examined for: image quality, radiometric precision, radiation transfer verification at clear air radiosonde sites, regression retrieval accuracy, and mesoscale analysis features. Postlaunch problems involving calibration and data processing irregularities of scientific or operational significance are included. The radiances provide good visual and relative radiometric data for empirically conditioned retrievals of mesoscale temperature and moisture fields in clear air.
Three algorithms for calculating polychromatic atmospheric transmittance functions have been tested using a set of eleven distinct temperature profiles in order to compare transmittance accuracies achievable by the three methods. The comparison of rms errors demonstrates that the iterative method of McMillin and Fleming (1976) is the most accurate of the efficient algorithms currently available for gases with constant mixing ratios; its accuracy approaches that of the spectroscopic parameters and the computational approximations used in the ground-truth line-by-line calculations. The method of Arking et al. (1974), while less accurate, has the advantage of being perfectly general and easily adapted to cases where spectral bandwidths are varied
The key features of the sounding software laboratory being installed on the VAS Processor at NASA/GSFC are outlined. Emphasis is on the support data and personal guidance that a meteorological researcher must provide to attune a physically modeled VAS sounding to his experiment. The fundamental aim of the sounding-support effort is to provide a system which makes use of: radiation transfer models based upon laboratory data, analytic inversion schemes, human guidance for quality control, statistically conditioned retrieval methods, and current ancillary data.
Fourier analysis was used to remove periodic errors from a series of NIMBUS-5 electronically scanned microwave radiometer brightness temperatures. The observations were all taken from the midnight orbits over fixed sites in the Australian grasslands. The angular dependence of the data indicates calibration errors consisted of broad sidelobes and some miscalibration as a function of beam position. Even though an angular recalibration curve cannot be derived from the available data, the systematic errors can be removed with a spectral filter. The 7 day cycle in the drift of the orbit of NIMBUS-5, coupled to the look-angle biases, produces an error pattern with peaks in its power spectrum at the weekly harmonics. About plus or minus 4 K of error is removed by simply blocking the variations near two- and three-cycles-per-week.
Methods were developed for calculating radiative terms with relatively high accuracy but with sufficient speed, so that they can be used in numerical atmospheric models or in high volume processing of satellite measured radiances for remote sensing of atmospheric and surface parameters. Comparison with commonly used methods in both types of applications indicate improvements in calculating transmittances of factors between two and three, and in calculating radiances and cooling rates of factors between two and seven.