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| Titel |
Three-dimensional visualization of ensemble weather forecasts – Part 2: Forecasting warm conveyor belt situations for aircraft-based field campaigns |
| VerfasserIn |
M. Rautenhaus, C. M. Grams, A. Schäfler, R. Westermann |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 7 ; Nr. 8, no. 7 (2015-07-31), S.2355-2377 |
| Datensatznummer |
250116469
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2355-2015.pdf |
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| Zusammenfassung |
| We present the application of interactive three-dimensional (3-D) visualization of ensemble weather predictions to forecasting warm conveyor belt
situations during aircraft-based atmospheric research campaigns. Motivated by forecast requirements of the T-NAWDEX-Falcon 2012 (THORPEX – North Atlantic Waveguide and Downstream Impact Experiment)
campaign, a method to predict 3-D probabilities of the spatial occurrence of warm conveyor belts (WCBs) has been developed.
Probabilities are derived from Lagrangian particle trajectories computed on the forecast wind fields of the European Centre for Medium Range Weather Forecasts (ECMWF) ensemble
prediction system. Integration of the method into the 3-D ensemble visualization tool Met.3D, introduced in the first part of
this study, facilitates interactive visualization of WCB features and derived probabilities in the context of the ECMWF ensemble
forecast. We investigate the sensitivity of the method with respect to trajectory seeding and grid spacing of the forecast
wind field. Furthermore, we propose a visual analysis method to quantitatively analyse the contribution of ensemble members to
a probability region and, thus, to assist the forecaster in interpreting the obtained probabilities. A case study, revisiting
a forecast case from T-NAWDEX-Falcon, illustrates the practical application of Met.3D and demonstrates the use of 3-D and
uncertainty visualization for weather forecasting and for planning flight routes in the medium forecast range (3 to
7
days before take-off). |
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