Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes
Abstract Numerous satellites utilized in numerical weather prediction are operating beyond their nominal lifetime, and their replacements are not yet operational. We investigate the impacts of a loss of U.S.‐based microwave and infrared satellite data and the addition of dropsonde data on forecast s...
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crwiley:10.1002/2017ea000350 2024-09-15T18:29:02+00:00 Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes English, Jason M. Kren, Andrew C. Peevey, Tanya R. National Oceanic and Atmospheric Administration Centre de Coopération Internationale en Recherche Agronomique pour le Développement 2018 http://dx.doi.org/10.1002/2017ea000350 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F2017EA000350 https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017EA000350 en eng Wiley http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ Earth and Space Science volume 5, issue 5, page 176-196 ISSN 2333-5084 2333-5084 journal-article 2018 crwiley https://doi.org/10.1002/2017ea000350 2024-08-27T04:30:53Z Abstract Numerous satellites utilized in numerical weather prediction are operating beyond their nominal lifetime, and their replacements are not yet operational. We investigate the impacts of a loss of U.S.‐based microwave and infrared satellite data and the addition of dropsonde data on forecast skill by conducting Observing System Simulation Experiments with the European Centre for Medium‐range Weather Forecasts T511 Nature Run and the National Center for Environmental Prediction Global Forecast System Model. Removing all U.S.‐based microwave and infrared satellite data increases Global Forecast System analysis error, global forecast error, and forecast error during the first 36 hr of three winter storms that impact the United States. Data from Suomi National Polar‐orbiting Partnership contributes roughly one third of the total satellite impacts. Assimilating “idealized” dropsondes (sampling over a large region of the Pacific/Arctic Oceans) significantly improves global forecasts and forecasts for all three storms. Assimilating targeted dropsonde flight paths using the Ensemble Transform Sensitivity method for 15 verification dates/locations for the three storms improves roughly 80% of forecasts relative to the control and 50% of forecasts relative to their corresponding experiments without dropsondes. However, removing satellite data degrades only 30% of targeted domain forecasts relative to the control. These results suggest that targeted dropsondes cannot compensate for a gap in satellite data regarding global average forecasts but may be able to compensate for specific targeted storms. However, as with any study of specific weather events, results are variable and more cases are needed to conclude whether targeted observations—as well as satellite data—can be expected to improve forecasts of specific weather events. Article in Journal/Newspaper Pacific Arctic Wiley Online Library Earth and Space Science 5 5 176 196 |
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Wiley Online Library |
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crwiley |
language |
English |
description |
Abstract Numerous satellites utilized in numerical weather prediction are operating beyond their nominal lifetime, and their replacements are not yet operational. We investigate the impacts of a loss of U.S.‐based microwave and infrared satellite data and the addition of dropsonde data on forecast skill by conducting Observing System Simulation Experiments with the European Centre for Medium‐range Weather Forecasts T511 Nature Run and the National Center for Environmental Prediction Global Forecast System Model. Removing all U.S.‐based microwave and infrared satellite data increases Global Forecast System analysis error, global forecast error, and forecast error during the first 36 hr of three winter storms that impact the United States. Data from Suomi National Polar‐orbiting Partnership contributes roughly one third of the total satellite impacts. Assimilating “idealized” dropsondes (sampling over a large region of the Pacific/Arctic Oceans) significantly improves global forecasts and forecasts for all three storms. Assimilating targeted dropsonde flight paths using the Ensemble Transform Sensitivity method for 15 verification dates/locations for the three storms improves roughly 80% of forecasts relative to the control and 50% of forecasts relative to their corresponding experiments without dropsondes. However, removing satellite data degrades only 30% of targeted domain forecasts relative to the control. These results suggest that targeted dropsondes cannot compensate for a gap in satellite data regarding global average forecasts but may be able to compensate for specific targeted storms. However, as with any study of specific weather events, results are variable and more cases are needed to conclude whether targeted observations—as well as satellite data—can be expected to improve forecasts of specific weather events. |
author2 |
National Oceanic and Atmospheric Administration Centre de Coopération Internationale en Recherche Agronomique pour le Développement |
format |
Article in Journal/Newspaper |
author |
English, Jason M. Kren, Andrew C. Peevey, Tanya R. |
spellingShingle |
English, Jason M. Kren, Andrew C. Peevey, Tanya R. Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
author_facet |
English, Jason M. Kren, Andrew C. Peevey, Tanya R. |
author_sort |
English, Jason M. |
title |
Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
title_short |
Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
title_full |
Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
title_fullStr |
Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
title_full_unstemmed |
Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes |
title_sort |
improving winter storm forecasts with observing system simulation experiments (osses). part 2: evaluating a satellite gap with idealized and targeted dropsondes |
publisher |
Wiley |
publishDate |
2018 |
url |
http://dx.doi.org/10.1002/2017ea000350 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F2017EA000350 https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017EA000350 |
genre |
Pacific Arctic |
genre_facet |
Pacific Arctic |
op_source |
Earth and Space Science volume 5, issue 5, page 176-196 ISSN 2333-5084 2333-5084 |
op_rights |
http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ |
op_doi |
https://doi.org/10.1002/2017ea000350 |
container_title |
Earth and Space Science |
container_volume |
5 |
container_issue |
5 |
container_start_page |
176 |
op_container_end_page |
196 |
_version_ |
1810470457429721088 |