Toward a Climate OSSE Framework for Satellite Mission Design

Bulletin of the American Meteorological Society, vol. 107, pp. E431–E445

Abstract

Abstract The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations. Significance Statement When planning a new satellite mission, it is important to first make sure that the new measurements will meet the science and end user goals of the broader community. While there are now well-established ways to quantify observation benefits for weather prediction, there is no such similar established framework for determining satellite measurement benefits for climate prediction. This article describes a new way to determine in advance whether new observations can reduce uncertainty in climate model projections.

Authors 26

1. Ann M. Fridlind

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, New York;

   NASA Goddard Institute for Space Studies, New York, NY

2. Gregory S. Elsaesser

   Goddard Institute for Space Studies · Columbia University

   Affiliation as printed

   Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York;

   NASA Goddard Institute for Space Studies, New York, New York;

   Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY

   NASA Goddard Institute for Space Studies, New York, NY

3. Marcus van Lier‐Walqui

   Goddard Institute for Space Studies · Columbia University

   Affiliation as printed

   Center for Climate Systems Research, Columbia University, New York, New York;

   NASA Goddard Institute for Space Studies, New York, New York;

   Center for Climate Systems Research, Columbia University, New York, NY

   NASA Goddard Institute for Space Studies, New York, NY

4. G Cesana

   Goddard Institute for Space Studies · Columbia University

   Affiliation as printed

   Center for Climate Systems Research, Columbia University, New York, New York;

   NASA Goddard Institute for Space Studies, New York, New York;

   Center for Climate Systems Research, Columbia University, New York, NY

   NASA Goddard Institute for Space Studies, New York, NY

5. Elizabeth C. Weatherhead

   University of Colorado Boulder

   Affiliation as printed

   University of Colorado Boulder, Boulder, Colorado;

   University of Colorado, Boulder, CO

6. George Tselioudis

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, New York;

   NASA Goddard Institute for Space Studies, New York, NY

7. Gavin A. Schmidt

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, New York;

   NASA Goddard Institute for Space Studies, New York, NY

8. Donifan O. Barahona

   Goddard Space Flight Center

   Affiliation as printed

   NASA Goddard Space Flight Center, Greenbelt, Maryland;

   NASA Goddard Space Flight Center, Greenbelt, MD

9. William D. Collins

   Lawrence Berkeley National Laboratory

   Affiliation as printed

   Lawrence Berkeley National Laboratory, Berkeley, California;

   Lawrence Berkeley National Laboratory, Berkeley, CA

10. David B. Considine

    National Aeronautics and Space Administration

    Affiliation as printed

    NASA Headquarters, Washington, D.C.;

    NASA Headquarters, Washington, DC

11. Lídia Cucurull

    National Oceanic and Atmospheric Administration · NOAA Environmental Modeling Center · NOAA Office of Modeling and Development

    Affiliation as printed

    NOAA/Environmental Modeling Center, College Park, Maryland;

    NOAA Environmental Modeling Center, College Park, MD

12. Larry DiGirolamo

    University of Illinois Urbana-Champaign

    Affiliation as printed

    University of Illinois Urbana–Champaign, Urbana, Illinois;

    University of Illinois at Urbana-Champaign, Urbana, IL

13. Amber E. Emory

    National Aeronautics and Space Administration

    Affiliation as printed

    NASA Headquarters, Washington, D.C.;

    NASA Headquarters, Washington, DC

14. Otto Hasekamp Aachen Netherlands Institute for Space Research

    Space Research Organisation Netherlands

    Affiliation as printed

    Netherlands Institute for Space Research, Leiden, Netherlands;

    Netherlands Institute for Space Research, Leiden, Netherlands

15. Shan He

    Stony Brook University

    Affiliation as printed

    Stony Brook University, State University of New York, Stony Brook, New York;

    Stony Brook University, Stony Brook, NY

16. Ryan J. Kramer

    NOAA Geophysical Fluid Dynamics Laboratory

    Affiliation as printed

    Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey;

    Geophysical Fluid Dynamics Laboratory, Princeton, NJ

17. Matthew Lebsock

    California Institute of Technology · Jet Propulsion Laboratory

    Affiliation as printed

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California;

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA

18. Tsengdar J. Lee

    National Aeronautics and Space Administration

    Affiliation as printed

    NASA Headquarters, Washington, D.C.;

    NASA Headquarters, Washington, DC

19. S. S. Leroy

    Atmospheric and Environmental Research

    Affiliation as printed

    Atmospheric and Environmental Research, Lexington, Massachusetts;

    Atmospheric and Environmental Research, Lexington, MA

20. Wuyin Lin

    Brookhaven National Laboratory

    Affiliation as printed

    Brookhaven National Laboratory, Brookhaven, New York;

    Brookhaven National Laboratory, Brookhaven, NY

21. Steven Lugauer

    University of Kentucky

    Affiliation as printed

    University of Kentucky, Lexington, Kentucky;

    University of Kentucky, Lexington, KY

22. Daniel J. Miller

    Goddard Space Flight Center · University of Maryland, Baltimore County

    Affiliation as printed

    NASA Goddard Space Flight Center, Greenbelt, Maryland;

    University of Maryland, Baltimore County, Baltimore, Maryland;

    NASA Goddard Space Flight Center, Greenbelt, MD

    University of Maryland, Baltimore County, MD

23. Johannes Mülmenstädt

    Pacific Northwest National Laboratory

    Affiliation as printed

    Pacific Northwest National Laboratory, Richland, Washington;

    Pacific Northwest National Laboratory, Richland, WA

24. Lazaros Oreopoulos

    Goddard Space Flight Center

    Affiliation as printed

    NASA Goddard Space Flight Center, Greenbelt, Maryland;

    NASA Goddard Space Flight Center, Greenbelt, MD

25. Derek J. Posselt

    California Institute of Technology · Jet Propulsion Laboratory

    Affiliation as printed

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California;

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA

26. Mark D. Zelinka

    Lawrence Livermore National Laboratory

    Affiliation as printed

    Lawrence Livermore National Laboratory, Livermore, California

    Lawrence Livermore National Laboratory, Livermore, CA