Geoscientific Model Development (Jun 2018)
Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design
- C. A. Shields,
- J. J. Rutz,
- L.-Y. Leung,
- F. M. Ralph,
- M. Wehner,
- B. Kawzenuk,
- J. M. Lora,
- E. McClenny,
- T. Osborne,
- A. E. Payne,
- P. Ullrich,
- A. Gershunov,
- N. Goldenson,
- B. Guan,
- Y. Qian,
- A. M. Ramos,
- C. Sarangi,
- S. Sellars,
- I. Gorodetskaya,
- K. Kashinath,
- V. Kurlin,
- K. Mahoney,
- G. Muszynski,
- G. Muszynski,
- R. Pierce,
- A. C. Subramanian,
- R. Tome,
- D. Waliser,
- D. Walton,
- G. Wick,
- A. Wilson,
- D. Lavers,
- Prabhat,
- A. Collow,
- H. Krishnan,
- G. Magnusdottir,
- P. Nguyen
Affiliations
- C. A. Shields
- Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80302, USA
- J. J. Rutz
- Science and Technology Infusion Division, National Weather Service Western Region Headquarters, National Oceanic and Atmospheric Administration, Salt Lake City, UT 84138, USA
- L.-Y. Leung
- Earth Systems Analysis and Modeling, Pacific Northwest National Laboratory, Richland, WA 99354, USA
- F. M. Ralph
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- M. Wehner
- Computational Chemistry, Materials, and Climate Group, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- B. Kawzenuk
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- J. M. Lora
- Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, CA 90095, USA
- E. McClenny
- Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
- T. Osborne
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- A. E. Payne
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- P. Ullrich
- Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
- A. Gershunov
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- N. Goldenson
- Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
- B. Guan
- Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, USA
- Y. Qian
- Earth Systems Analysis and Modeling, Pacific Northwest National Laboratory, Richland, WA 99354, USA
- A. M. Ramos
- Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
- C. Sarangi
- Earth Systems Analysis and Modeling, Pacific Northwest National Laboratory, Richland, WA 99354, USA
- S. Sellars
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- I. Gorodetskaya
- Centre for Environmental and Marine Studies, University of Aveiro, 3810-193 Aveiro, Portugal
- K. Kashinath
- Data & Analytics Services, National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- V. Kurlin
- Department Computer Science Liverpool, Liverpool, L69 3BX, UK
- K. Mahoney
- Physical Sciences Division, Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305, USA
- G. Muszynski
- Data & Analytics Services, National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- G. Muszynski
- Department Computer Science Liverpool, Liverpool, L69 3BX, UK
- R. Pierce
- National Weather Service Forecast Office, National Oceanic and Atmospheric Administration, San Diego, CA 92127, USA
- A. C. Subramanian
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- R. Tome
- Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
- D. Waliser
- Earth Science and Technology Directorate, Jet Propulsion Laboratory, Pasadena, CA 91109, USA
- D. Walton
- Institute of the Environment and Sustainability, University of California, Los Angeles, CA 90095, USA
- G. Wick
- Physical Sciences Division, Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305, USA
- A. Wilson
- Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, La Jolla, CA 92037, USA
- D. Lavers
- European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
- Prabhat
- Computational Chemistry, Materials, and Climate Group, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- A. Collow
- Universities Space Research Association, Columbia, MD 21046, USA
- H. Krishnan
- Computational Chemistry, Materials, and Climate Group, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- G. Magnusdottir
- Department of Earth System Science, University of California Irvine, Irvine, CA 92697, USA
- P. Nguyen
- Department of Civil & Environmental Engineering, University of California Irvine, Irvine, CA 92697, USA
- DOI
- https://doi.org/10.5194/gmd-11-2455-2018
- Journal volume & issue
-
Vol. 11
pp. 2455 – 2474
Abstract
The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month proof-of-concept trial run designed to illustrate the utility and feasibility of the ARTMIP project.
