The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System
The impact of model uncertainties on analyzed data is investigated using a global data assimilation system. This issue is explored in a 3D-Var system based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) system using two convective parameterization schemes, the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2011-01-01
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| Series: | Terrestrial, Atmospheric and Oceanic Sciences |
| Subjects: | |
| Online Access: |
http://tao.cgu.org.tw/images/attachments/v221p015.pdf
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| _version_ | 1811289909653143552 |
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| author | Song-You Hong Hyun Mee Kim Jung-Eun Kim Seung-On Hwang Hoon Park |
| author_facet | Song-You Hong Hyun Mee Kim Jung-Eun Kim Seung-On Hwang Hoon Park |
| author_sort | Song-You Hong |
| collection | DOAJ |
| description | The impact of model uncertainties on analyzed data is investigated using a global data assimilation system. This issue is explored in a 3D-Var system based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) system using two convective parameterization schemes, the Simplified Arakawa scheme and the Community Climate Model (CCM) scheme. Two sets of six-hourly analysis data are generated for the summer of 2004. The difference between the resulting analyses using different convective parameterization schemes is found to be significantly greater than that between two well-known analyzed data sets, the NCEP/National Center for Atmospheric Research (NCAR) reanalysis (RA1) and the NCEP/DOE reanalysis (RA2). This dependency is more pronounced in data-sparse areas like the East Asian region than in data-rich areas like the North American region. Our study indicates that predictabilities for short- to medium-range forecasts in the global forecast system are indirectly influenced by forecast model accuracy via the quality of the initial conditions. |
| first_indexed | 2024-04-13T04:02:25Z |
| format | Article |
| id | doaj.art-95882def5c0f41e1a30f6f579f35b5d9 |
| institution | Directory Open Access Journal |
| issn | 1017-0839 2311-7680 |
| language | English |
| last_indexed | 2024-04-13T04:02:25Z |
| publishDate | 2011-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Terrestrial, Atmospheric and Oceanic Sciences |
| spelling | doaj.art-95882def5c0f41e1a30f6f579f35b5d92022-12-22T03:03:26ZengSpringerTerrestrial, Atmospheric and Oceanic Sciences1017-08392311-76802011-01-0122101510.3319/TAO.2010.05.18.01(A)986The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation SystemSong-You HongHyun Mee KimJung-Eun KimSeung-On HwangHoon ParkThe impact of model uncertainties on analyzed data is investigated using a global data assimilation system. This issue is explored in a 3D-Var system based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) system using two convective parameterization schemes, the Simplified Arakawa scheme and the Community Climate Model (CCM) scheme. Two sets of six-hourly analysis data are generated for the summer of 2004. The difference between the resulting analyses using different convective parameterization schemes is found to be significantly greater than that between two well-known analyzed data sets, the NCEP/National Center for Atmospheric Research (NCAR) reanalysis (RA1) and the NCEP/DOE reanalysis (RA2). This dependency is more pronounced in data-sparse areas like the East Asian region than in data-rich areas like the North American region. Our study indicates that predictabilities for short- to medium-range forecasts in the global forecast system are indirectly influenced by forecast model accuracy via the quality of the initial conditions. http://tao.cgu.org.tw/images/attachments/v221p015.pdf Data assimilation systemConvective parameterization schemeModel physicsPredictability |
| spellingShingle | Song-You Hong Hyun Mee Kim Jung-Eun Kim Seung-On Hwang Hoon Park The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System Terrestrial, Atmospheric and Oceanic Sciences Data assimilation system Convective parameterization scheme Model physics Predictability |
| title | The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System |
| title_full | The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System |
| title_fullStr | The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System |
| title_full_unstemmed | The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System |
| title_short | The Impact of Model Uncertainties on Analyzed Data in a Global Data Assimilation System |
| title_sort | impact of model uncertainties on analyzed data in a global data assimilation system |
| topic | Data assimilation system Convective parameterization scheme Model physics Predictability |
| url |
http://tao.cgu.org.tw/images/attachments/v221p015.pdf
|
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