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The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0
The Ensemble Mars Atmosphere Reanalysis System (EMARS) dataset version 1.0 contains hourly gridded atmospheric variables for the planet Mars, spanning Mars Year (MY) 24 through 33 (1999 through 2017). A reanalysis represents the best estimate of the state of the atmosphere by combining observations...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919928/ https://www.ncbi.nlm.nih.gov/pubmed/31894192 http://dx.doi.org/10.1002/gdj3.77 |
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author | Greybush, Steven J. Kalnay, Eugenia Wilson, R. John Hoffman, Ross N. Nehrkorn, Thomas Leidner, Mark Eluszkiewicz, Janusz Gillespie, Hartzel E. Wespetal, Matthew Zhao, Yongjing Hoffman, Matthew Dudas, Patrick McConnochie, Timothy Kleinböhl, Armin Kass, David McCleese, Daniel Miyoshi, Takemasa |
author_facet | Greybush, Steven J. Kalnay, Eugenia Wilson, R. John Hoffman, Ross N. Nehrkorn, Thomas Leidner, Mark Eluszkiewicz, Janusz Gillespie, Hartzel E. Wespetal, Matthew Zhao, Yongjing Hoffman, Matthew Dudas, Patrick McConnochie, Timothy Kleinböhl, Armin Kass, David McCleese, Daniel Miyoshi, Takemasa |
author_sort | Greybush, Steven J. |
collection | PubMed |
description | The Ensemble Mars Atmosphere Reanalysis System (EMARS) dataset version 1.0 contains hourly gridded atmospheric variables for the planet Mars, spanning Mars Year (MY) 24 through 33 (1999 through 2017). A reanalysis represents the best estimate of the state of the atmosphere by combining observations that are sparse in space and time with a dynamical model and weighting them by their uncertainties. EMARS uses the Local Ensemble Transform Kalman Filter (LETKF) for data assimilation with the GFDL/NASA Mars Global Climate Model (MGCM). Observations that are assimilated include the Thermal Emission Spectrometer (TES) and Mars Climate Sounder (MCS) temperature retrievals. The dataset includes gridded fields of temperature, wind, surface pressure, as well as dust, water ice, CO(2) surface ice and other atmospheric quantities. Reanalyses are useful for both science and engineering studies, including investigations of transient eddies, the polar vortex, thermal tides and dust storms, and during spacecraft operations. |
format | Online Article Text |
id | pubmed-6919928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69199282019-12-30 The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 Greybush, Steven J. Kalnay, Eugenia Wilson, R. John Hoffman, Ross N. Nehrkorn, Thomas Leidner, Mark Eluszkiewicz, Janusz Gillespie, Hartzel E. Wespetal, Matthew Zhao, Yongjing Hoffman, Matthew Dudas, Patrick McConnochie, Timothy Kleinböhl, Armin Kass, David McCleese, Daniel Miyoshi, Takemasa Geosci Data J Data Papers The Ensemble Mars Atmosphere Reanalysis System (EMARS) dataset version 1.0 contains hourly gridded atmospheric variables for the planet Mars, spanning Mars Year (MY) 24 through 33 (1999 through 2017). A reanalysis represents the best estimate of the state of the atmosphere by combining observations that are sparse in space and time with a dynamical model and weighting them by their uncertainties. EMARS uses the Local Ensemble Transform Kalman Filter (LETKF) for data assimilation with the GFDL/NASA Mars Global Climate Model (MGCM). Observations that are assimilated include the Thermal Emission Spectrometer (TES) and Mars Climate Sounder (MCS) temperature retrievals. The dataset includes gridded fields of temperature, wind, surface pressure, as well as dust, water ice, CO(2) surface ice and other atmospheric quantities. Reanalyses are useful for both science and engineering studies, including investigations of transient eddies, the polar vortex, thermal tides and dust storms, and during spacecraft operations. John Wiley and Sons Inc. 2019-08-23 2019-11 /pmc/articles/PMC6919928/ /pubmed/31894192 http://dx.doi.org/10.1002/gdj3.77 Text en © 2019 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Papers Greybush, Steven J. Kalnay, Eugenia Wilson, R. John Hoffman, Ross N. Nehrkorn, Thomas Leidner, Mark Eluszkiewicz, Janusz Gillespie, Hartzel E. Wespetal, Matthew Zhao, Yongjing Hoffman, Matthew Dudas, Patrick McConnochie, Timothy Kleinböhl, Armin Kass, David McCleese, Daniel Miyoshi, Takemasa The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title | The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title_full | The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title_fullStr | The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title_full_unstemmed | The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title_short | The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0 |
title_sort | ensemble mars atmosphere reanalysis system (emars) version 1.0 |
topic | Data Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919928/ https://www.ncbi.nlm.nih.gov/pubmed/31894192 http://dx.doi.org/10.1002/gdj3.77 |
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