Abstract
Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.
| Original language | English |
|---|---|
| Article number | e2021JD036155 |
| Number of pages | 20 |
| Journal | Journal of Geophysical Research: Atmospheres |
| Volume | 127 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 27 Apr 2022 |
| Externally published | Yes |
Keywords
- atmospheric river
- ERA5
- JRA-55
- MERRA-2
- reanalysis intercomparison
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}
In: Journal of Geophysical Research: Atmospheres, Vol. 127, No. 8, e2021JD036155, 27.04.2022.
Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - An Overview of ARTMIP's Tier 2 Reanalysis Intercomparison
T2 - Uncertainty in the Detection of Atmospheric Rivers and Their Associated Precipitation
AU - Collow, A. B.Marquardt
AU - Shields, C. A.
AU - Guan, B.
AU - Kim, S.
AU - Lora, J. M.
AU - McClenny, E. E.
AU - Nardi, K.
AU - Payne, A.
AU - Reid, K.
AU - Shearer, E. J.
AU - Tomé, R.
AU - Wille, J. D.
AU - Ramos, A. M.
AU - Gorodetskaya, I. V.
AU - Leung, L. R.
AU - O’Brien, T. A.
AU - Ralph, F. M.
AU - Rutz, J.
AU - Ullrich, P. A.
AU - Wehner, M.
N1 - Funding Information: ARTMIP is a grassroots community effort and includes a collection of international researchers from universities, laboratories, and agencies. Cochairs and committee members include Jonathan Rutz, Christine Shields, L. Ruby Leung, F. Martin Ralph, Michael Wehner, Ashley Payne, and Travis O'Brien, and Allison Collow. Details on catalogue developers can be found on the ARTMIP website, https://www.cgd.ucar.edu/projects/artmip/ . ARTMIP has received support from the U.S. Department of Energy Office of Science Biological and Environmental Research (BER) as part of the Regional and Global Model Analysis program area, and the Center for Western Weather and Water Extremes (CW3E) at Scripps Institute for Oceanography at the University of California, San Diego. Allison Collow was supported by NASA's Earth Science Research Program and would like to thank Mike Bosilovich for his support and guidance through this endeavor. B.G. was supported by NASA (grants 80NSSC20K1344 and 80NSSC21K1007) and the California Department of Water Resources. A.M.R. was supported by the Scientific Employment Stimulus 2017 (CEECIND/00027/2017), and also by the project “HOLMODRIVE—North Atlantic Atmospheric Patterns Influence on Western Iberia Climate: From the Late Glacial to the Present (PTDC/CTA‐GEO/29029/2017), both funded by Fundação para a Ciência e a Tecnologia(FCT), Portugal. J.D.W was supported by the Agence Nationale de la Recherche projects ANR‐20‐CE01‐0013 (ARCA), ANR‐14‐CE01‐0001 (ASUMA), and ANR‐16‐CE01‐0011 (EAIIST). T.A.O was supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, Regional & Global Model Analysis Program, under Award Number DE‐AC02‐05CH11231; and in part by the Environmental Resilience Institute, funded by Indiana University's Prepared for Environmental Change Grand Challenge initiative. E.J.S. was supported by the Ridge to Reef Graduate Training Program funded by NSF‐NRT award DGE‐1735040. K.J.R was supported by the Australian Government Research Training Program Scholarship, Australian Research Council (DE180100638) and the National Computational Infrastructure Australia. C. A. Shields was supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program under Award Number DE‐SC0022070 and National Science Foundation (NSF) IA 1947282. As well as the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under Cooperative Agreement No. 1852977. Funding Information: ARTMIP is a grassroots community effort and includes a collection of international researchers from universities, laboratories, and agencies. Cochairs and committee members include Jonathan Rutz, Christine Shields, L. Ruby Leung, F. Martin Ralph, Michael Wehner, Ashley Payne, and Travis O'Brien, and Allison Collow. Details on catalogue developers can be found on the ARTMIP website, https://www.cgd.ucar.edu/projects/artmip/. ARTMIP has received support from the U.S. Department of Energy Office of Science Biological and Environmental Research (BER) as part of the Regional and Global Model Analysis program area, and the Center for Western Weather and Water Extremes (CW3E) at Scripps Institute for Oceanography at the University of California, San Diego. Allison Collow was supported by NASA's Earth Science Research Program and would like to thank Mike Bosilovich for his support and guidance through this endeavor. B.G. was supported by NASA (grants 80NSSC20K1344 and 80NSSC21K1007) and the California Department of Water Resources. A.M.R. was supported by the Scientific Employment Stimulus 2017 (CEECIND/00027/2017), and also by the project ?HOLMODRIVE?North Atlantic Atmospheric Patterns Influence on Western Iberia Climate: From the Late Glacial to the Present (PTDC/CTA-GEO/29029/2017), both funded by Funda??o para a Ci?ncia e a Tecnologia(FCT), Portugal. J.D.W was supported by the Agence Nationale de la Recherche projects ANR-20-CE01-0013 (ARCA), ANR-14-CE01-0001 (ASUMA), and ANR-16-CE01-0011 (EAIIST). T.A.O was supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, Regional & Global Model Analysis Program, under Award Number DE-AC02-05CH11231; and in part by the Environmental Resilience Institute, funded by Indiana University's Prepared for Environmental Change Grand Challenge initiative. E.J.S. was supported by the Ridge to Reef Graduate Training Program funded by NSF-NRT award DGE-1735040. K.J.R was supported by the Australian Government Research Training Program Scholarship, Australian Research Council (DE180100638) and the National Computational Infrastructure Australia. C. A. Shields was supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program under Award Number DE-SC0022070 and National Science Foundation (NSF) IA 1947282. As well as the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under Cooperative Agreement No. 1852977. Publisher Copyright: © 2022. American Geophysical Union. All Rights Reserved.
PY - 2022/4/27
Y1 - 2022/4/27
N2 - Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.
AB - Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.
KW - atmospheric river
KW - ERA5
KW - JRA-55
KW - MERRA-2
KW - reanalysis intercomparison
UR - https://www.scopus.com/pages/publications/85129249127
U2 - 10.1029/2021JD036155
DO - 10.1029/2021JD036155
M3 - Article
AN - SCOPUS:85129249127
SN - 2169-897X
VL - 127
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
IS - 8
M1 - e2021JD036155
ER -