Atmospheric River Reconnaissance 2021: A Review
dc.contributor.author | Cobb, Alison | |
dc.contributor.author | Ralph, F. Martin | |
dc.contributor.author | Tallapragada, Vijay | |
dc.contributor.author | Wilson, Anna M. | |
dc.contributor.author | Murphy, Michael | |
dc.contributor.author | et al | |
dc.date.accessioned | 2024-04-10T16:43:30Z | |
dc.date.available | 2024-04-10T16:43:30Z | |
dc.date.issued | 2022-06-01 | |
dc.description | Authors: Alison Cobb, F. Martin Ralph, Vijay Tallapragada, Anna M. Wilson, Christopher A. Davis, Luca Delle Monache, James D. Doyle, Florian Pappenberger, Carolyn A. Reynolds, Aneesh Subramanian, Peter G. Black, Forest Cannon, Chris Castellano, Jason M. Cordeira, Jennifer S. Haase, Chad Hecht, Brian Kawzenuk, David A. Lavers, Michael Murphy , Jack Parrish, Ryan Rickert, Jonathan J. Rutz, Ryan Torn, Xingren Wu, and Minghua Zheng | |
dc.description.abstract | Atmospheric River Reconnaissance (AR Recon) is a targeted campaign that complements other sources of observational data, forming part of a diverse observing system. AR Recon 2021 operated for ten weeks from January 13 to March 22, with 29.5 Intensive Observation Periods (IOPs), 45 flights and 1142 successful dropsondes deployed in the northeast Pacific. With the availability of two WC-130J aircraft operated by the 53rd Weather Reconnaissance Squadron (53 WRS), Air Force Reserve Command (AFRC) and one National Oceanic and Atmospheric Administration (NOAA) Aircraft Operations Center (AOC) G-IVSP aircraft, six sequences were accomplished, in which the same synoptic system was sampled over several days. The principal aim was to gather observations to improve forecasts of landfalling atmospheric rivers on the U.S. West Coast. Sampling of other meteorological phenomena forecast to have downstream impacts over the U.S. was also considered. Alongside forecast improvement, observations were also gathered to address important scientific research questions, as part of a Research and Operations Partnership. Targeted dropsonde observations were focused on essential atmospheric structures, primarily atmospheric rivers. Adjoint and ensemble sensitivities, mainly focusing on predictions of U.S. West Coast precipitation, provided complementary information on locations where additional observations may help to reduce the forecast uncertainty. Additionally, Airborne Radio Occultation (ARO) and tail radar were active during some flights, 30 drifting buoys were distributed, and 111 radiosondes were launched from four locations in California. Dropsonde, radiosonde and buoy data were available for assimilation in real-time into operational forecast models. Future work is planned to examine the impact of AR Recon 2021 data on model forecasts. | |
dc.description.sponsorship | AR Recon 2021 involved many scientists, engineers, air crews, project managers, program managers, and others. These include individuals from NOAA, NASA, the 53rd Weather Reconnaissance Squadron (53 WRS), Air Force Reserve Command (AFRC), and elsewhere. Without their efforts, these data would not be available for this study. We also acknowledge Bing Cao, Bruce Ingleby, Luca Centurioni, Allison Michaelis, Adam Sisco for their contributions to AR Recon 2021. Heini Wernli, Maxi Boettcher, and Hanin Binder of ETH Zürich are acknowledged for providing forecasts of warm conveyor belt (WCB) activity. The authors are grateful to the two anonymous reviewers whose comments helped to clarify and improve the paper. This research was supported by the California Department of Water Resources AR research program (Award 4600013361) and the U.S. Army Corps of Engineers Engineer Research and Development Center (Awards 609 W912HZ-15-2-0019 and W912HZ-19-2-0023). ARO observations were supported by NSF GRANT AGS-1642650 and AGS-1454125, and NASA GRANT NNX15AU19G. CAR and JDD were supported by the supported by the Chief of Naval Research through the NRL Base Program, PE 0601153N (NRL 6.1 Atmospheric Rivers Project), and used computational resources provided by the Navy DoD Supercomputing Resource Center. | |
dc.description.uri | https://journals.ametsoc.org/view/journals/wefo/aop/WAF-D-21-0164.1/WAF-D-21-0164.1.xml?tab_body=pdf | |
dc.format.extent | 52 pages | |
dc.genre | journal articles | |
dc.identifier | doi:10.13016/m2rygy-g6lh | |
dc.identifier.citation | Cobb, Alison, F. Martin Ralph, Vijay Tallapragada, Anna M. Wilson, Christopher A. Davis, Luca Delle Monache, James D. Doyle, et al. “Atmospheric River Reconnaissance 2021: A Review.” Weather and Forecasting 1, no. aop (June 1, 2022). https://doi.org/10.1175/WAF-D-21-0164.1. | |
dc.identifier.uri | https://doi.org/10.1175/WAF-D-21-0164.1 | |
dc.identifier.uri | http://hdl.handle.net/11603/32968 | |
dc.language.iso | en_US | |
dc.publisher | AMS | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC GESTAR II Collection | |
dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | |
dc.rights | Public Domain | en |
dc.rights.uri | https://creativecommons.org/publicdomain/mark/1.0/ | |
dc.title | Atmospheric River Reconnaissance 2021: A Review | |
dc.type | Text | |
dcterms.creator | https://orcid.org/0000-0003-3309-1597 |