The Use of the Deviation Angle Variance Technique on Geostationary Satellite Imagery to Estimate Tropical Cyclone Size ParametersSource: Weather and Forecasting:;2016:;volume( 031 ):;issue: 005::page 1625DOI: 10.1175/WAF-D-16-0056.1Publisher: American Meteorological Society
Abstract: his study extends past research based on the deviation angle variance (DAV) technique that utilizes digital brightness temperatures from longwave infrared satellite images to objectively measure the symmetry of a tropical cyclone (TC). In previous work, the single-pixel DAV values were used as an objective estimator of storm intensity while maps of the DAV values indicated areas where tropical cyclogenesis was occurring. In this study the spatial information in the DAV maps is utilized along with information from the Cooperative Institute for Research in the Atmosphere?s extended best-track archive and the Statistical Hurricane Intensity Prediction Scheme model to create multiple linear regression models of wind radii parameters for TCs in the North Atlantic basin. These models are used to estimate both symmetric, and by quadrant, 34-, 50-, and 64-kt wind radii (where 1 kt = 0.51 m s?1 1) on a half-hourly time scale. The symmetric model assumes azimuthal symmetry and has mean absolute errors of 38.5, 23.2, and 13.5 km (20.8, 12.5, and 7.3 n mi) for the 34-, 50-, and 64-kt wind radii, respectively, which are lower than results for most other techniques except for those based on AMSU. The asymmetric model independently estimates radii in each quadrant and produces mean absolute errors for the wind radii that are generally highest in the northwest quadrant and lowest in the southwest quadrant similar to other techniques. However, as a percentage of the average wind radii from aircraft reconnaissance, all quadrants have similar errors.
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contributor author | Dolling, Klaus | |
contributor author | Ritchie, Elizabeth A. | |
contributor author | Tyo, J. Scott | |
date accessioned | 2017-06-09T17:37:24Z | |
date available | 2017-06-09T17:37:24Z | |
date copyright | 2016/10/01 | |
date issued | 2016 | |
identifier issn | 0882-8156 | |
identifier other | ams-88242.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4232001 | |
description abstract | his study extends past research based on the deviation angle variance (DAV) technique that utilizes digital brightness temperatures from longwave infrared satellite images to objectively measure the symmetry of a tropical cyclone (TC). In previous work, the single-pixel DAV values were used as an objective estimator of storm intensity while maps of the DAV values indicated areas where tropical cyclogenesis was occurring. In this study the spatial information in the DAV maps is utilized along with information from the Cooperative Institute for Research in the Atmosphere?s extended best-track archive and the Statistical Hurricane Intensity Prediction Scheme model to create multiple linear regression models of wind radii parameters for TCs in the North Atlantic basin. These models are used to estimate both symmetric, and by quadrant, 34-, 50-, and 64-kt wind radii (where 1 kt = 0.51 m s?1 1) on a half-hourly time scale. The symmetric model assumes azimuthal symmetry and has mean absolute errors of 38.5, 23.2, and 13.5 km (20.8, 12.5, and 7.3 n mi) for the 34-, 50-, and 64-kt wind radii, respectively, which are lower than results for most other techniques except for those based on AMSU. The asymmetric model independently estimates radii in each quadrant and produces mean absolute errors for the wind radii that are generally highest in the northwest quadrant and lowest in the southwest quadrant similar to other techniques. However, as a percentage of the average wind radii from aircraft reconnaissance, all quadrants have similar errors. | |
publisher | American Meteorological Society | |
title | The Use of the Deviation Angle Variance Technique on Geostationary Satellite Imagery to Estimate Tropical Cyclone Size Parameters | |
type | Journal Paper | |
journal volume | 31 | |
journal issue | 5 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-16-0056.1 | |
journal fristpage | 1625 | |
journal lastpage | 1642 | |
tree | Weather and Forecasting:;2016:;volume( 031 ):;issue: 005 | |
contenttype | Fulltext |