The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0

Steven J. Greybush; Eugenia Kalnay; R. John Wilson; Ross N. Hoffman; Thomas Nehrkorn; Mark Leidner; Janusz Eluszkiewicz; Hartzel E. Gillespie; Matthew Wespetal; Yongjing Zhao; Matthew Hoffman; Patrick Dudas; Timothy McConnochie; Armin Kleinböhl; David Kass; Daniel McCleese; Takemasa Miyoshi

doi:10.1002/gdj3.77

The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0

Steven J. Greybush, Eugenia Kalnay, R. John Wilson, Ross N. Hoffman, Thomas Nehrkorn, Mark Leidner, Janusz Eluszkiewicz, Hartzel E. Gillespie, Matthew Wespetal, Yongjing Zhao, Matthew Hoffman, Patrick Dudas, Timothy McConnochie, Armin Kleinböhl, David Kass, Daniel McCleese, Takemasa Miyoshi

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33 Scopus citations

Abstract

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, CO₂ 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.

Original language	English (US)
Pages (from-to)	137-150
Number of pages	14
Journal	Geoscience Data Journal
Volume	6
Issue number	2
DOIs	https://doi.org/10.1002/gdj3.77
State	Published - Nov 1 2019

All Science Journal Classification (ASJC) codes

General Earth and Planetary Sciences

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10.1002/gdj3.77

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Greybush, S. J., Kalnay, E., Wilson, R. J., Hoffman, R. N., Nehrkorn, T., Leidner, M., Eluszkiewicz, J., Gillespie, H. E., Wespetal, M., Zhao, Y., Hoffman, M., Dudas, P., McConnochie, T., Kleinböhl, A., Kass, D., McCleese, D., & Miyoshi, T. (2019). The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0. Geoscience Data Journal, 6(2), 137-150. https://doi.org/10.1002/gdj3.77

@article{802fefead098455fbd73bcf09ca35318,

title = "The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0",

abstract = "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, CO2 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.",

author = "Greybush, {Steven J.} and Eugenia Kalnay and Wilson, {R. John} and Hoffman, {Ross N.} and Thomas Nehrkorn and Mark Leidner and Janusz Eluszkiewicz and Gillespie, {Hartzel E.} and Matthew Wespetal and Yongjing Zhao and Matthew Hoffman and Patrick Dudas and Timothy McConnochie and Armin Kleinb{\"o}hl and David Kass and Daniel McCleese and Takemasa Miyoshi",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.",

year = "2019",

month = nov,

day = "1",

doi = "10.1002/gdj3.77",

language = "English (US)",

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pages = "137--150",

journal = "Geoscience Data Journal",

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Greybush, SJ, Kalnay, E, Wilson, RJ, Hoffman, RN, Nehrkorn, T, Leidner, M, Eluszkiewicz, J, Gillespie, HE, Wespetal, M, Zhao, Y, Hoffman, M, Dudas, P, McConnochie, T, Kleinböhl, A, Kass, D, McCleese, D & Miyoshi, T 2019, 'The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0', Geoscience Data Journal, vol. 6, no. 2, pp. 137-150. https://doi.org/10.1002/gdj3.77

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AU - Greybush, Steven J.

AU - Kalnay, Eugenia

AU - Wilson, R. John

AU - Hoffman, Ross N.

AU - Nehrkorn, Thomas

AU - Leidner, Mark

AU - Eluszkiewicz, Janusz

AU - Gillespie, Hartzel E.

AU - Wespetal, Matthew

AU - Zhao, Yongjing

AU - Hoffman, Matthew

AU - Dudas, Patrick

AU - McConnochie, Timothy

AU - Kleinböhl, Armin

AU - Kass, David

AU - McCleese, Daniel

AU - Miyoshi, Takemasa

PY - 2019/11/1

Y1 - 2019/11/1

N2 - 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, CO2 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.

AB - 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, CO2 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.

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The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0

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