Fine-Resolution 4DVAR Data Assimilation for the Great Plains Tornado Outbreak of 3 May 1999Source: Weather and Forecasting:;2002:;volume( 017 ):;issue: 003::page 506Author:Zupanski, Dusanka
,
Zupanski, Milija
,
Rogers, Eric
,
Parrish, David F.
,
DiMego, Geoffrey J.
DOI: 10.1175/1520-0434(2002)017<0506:FRDAFT>2.0.CO;2Publisher: American Meteorological Society
Abstract: The National Centers for Environmental Prediction fine-resolution four-dimensional variational (4DVAR) data assimilation system is used to study the Great Plains tornado outbreak of 3 May 1999. It was found that the 4DVAR method was able to capture very well the important precursors for the tornadic activity, such as upper- and low-level jet streaks, wind shear, humidity field, surface CAPE, and so on. It was also demonstrated that, in this particular synoptic case, characterized by fast-changing mesoscale systems, the model error adjustment played a substantial role. The experimental results suggest that the common practice of neglecting the model error in data assimilation systems may not be justified in synoptic situations similar to this one.
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contributor author | Zupanski, Dusanka | |
contributor author | Zupanski, Milija | |
contributor author | Rogers, Eric | |
contributor author | Parrish, David F. | |
contributor author | DiMego, Geoffrey J. | |
date accessioned | 2017-06-09T15:01:31Z | |
date available | 2017-06-09T15:01:31Z | |
date copyright | 2002/06/01 | |
date issued | 2002 | |
identifier issn | 0882-8156 | |
identifier other | ams-3243.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4169990 | |
description abstract | The National Centers for Environmental Prediction fine-resolution four-dimensional variational (4DVAR) data assimilation system is used to study the Great Plains tornado outbreak of 3 May 1999. It was found that the 4DVAR method was able to capture very well the important precursors for the tornadic activity, such as upper- and low-level jet streaks, wind shear, humidity field, surface CAPE, and so on. It was also demonstrated that, in this particular synoptic case, characterized by fast-changing mesoscale systems, the model error adjustment played a substantial role. The experimental results suggest that the common practice of neglecting the model error in data assimilation systems may not be justified in synoptic situations similar to this one. | |
publisher | American Meteorological Society | |
title | Fine-Resolution 4DVAR Data Assimilation for the Great Plains Tornado Outbreak of 3 May 1999 | |
type | Journal Paper | |
journal volume | 17 | |
journal issue | 3 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/1520-0434(2002)017<0506:FRDAFT>2.0.CO;2 | |
journal fristpage | 506 | |
journal lastpage | 525 | |
tree | Weather and Forecasting:;2002:;volume( 017 ):;issue: 003 | |
contenttype | Fulltext |