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Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier2 High-Resolution Global Warming Experiment

Authors :
Christine A. Shields
Ashley E. Payne
Eric J. Shearer
Michael F. Wehne
Travis A. O' Brien
Jonathan J. Rutz
L. Ruby Leung
F. Martin Ralph
Allison B. Marquardt Collow
Paul A. Ullrich
Qizhen Dong
Alexander Gershunov
Helen Griffith
Bin Guan
Juan M. Lora
Mengqian Lu
Elizabeth McClenny
Kyle M. Nardi
Mengxin Pan
Yun Qian
Alexandre M. Ramos
Tamara Shulgina
Maximiliano VialeI
Chandan Sarangi
Ricardo Tomé
Colin Zarzycki
Source :
Geophysical Research Letters. 50(6)
Publication Year :
2023
Publisher :
United States: NASA Center for Aerospace Information (CASI), 2023.

Abstract

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common dataset consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Subjects

Subjects :
Meteorology and Climatology

Details

Language :
English
ISSN :
19448007 and 00948276
Volume :
50
Issue :
6
Database :
NASA Technical Reports
Journal :
Geophysical Research Letters
Notes :
80NSSC22M0001, , SPEC5732, , J-090014, , DE-SC0022070, , AC02-05CH11231, , DE-AC05-76RL01830, , DE-SC0016605, , NSF IA 1947282, , 1852977, , 1010971, , 1016611, , AGS-1916689, , NA19OAR4310363, , 16200920, , CE/20-21/065/NFIG/008961, , 80NSSC20K1344, , 80NSSC21K1007, , UIDB/50019/2020, , FONCYT PICT-2020-11722, , NE/P010040/1
Publication Type :
Report
Accession number :
edsnas.20230002321
Document Type :
Report
Full Text :
https://doi.org/10.1029/2022GL102091