TY - JOUR
T1 - The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0
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
N1 - Funding Information:
Funding information This article was funded by grants from NASA MDAP NNX007AM97G, NNX11AL25G, NNX14AM13G and 80NSSC17K0690. We thank Luca Montabone, Thomas Navarro, Todd Mooring, Mike Smith, Jeff Barnes, Michael Battalio, anonymous reviewers and others for valuable discussions on this work. The development of EMARS made use of computational resources at the University of Maryland and the Pennsylvania State University, including the Institute for CyberScience Advanced CyberInfrastructure (ICS-ACI). The support of the NASA Mars Data Analysis Program (MDAP) and PATM is acknowledged, including Grants NNX007AM97G, NNX11AL25G, NNX14AM13G and 80NSSC17K0690. Work at the Jet Propulsion Laboratory, California Institute of Technology, is performed under contract with the National Aeronautics and Space Administration.
Publisher Copyright:
© 2019 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.
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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U2 - 10.1002/gdj3.77
DO - 10.1002/gdj3.77
M3 - Article
C2 - 31894192
AN - SCOPUS:85070988256
SN - 2049-6060
VL - 6
SP - 137
EP - 150
JO - Geoscience Data Journal
JF - Geoscience Data Journal
IS - 2
ER -