Abstract
Mississippi River basin floods impart large socioeconomic impacts over the central United States. Improving flood predictability depends on our understanding of the dynamical controls on Mississippi basin hydroclimate. However, short instrumental records make it difficult to constrain the connections between flooding and climate variability. Here, we use the Paleo Hydrodynamics Data Assimilation product, spanning the Last Millennium, to investigate the impacts of tropical Pacific and North Atlantic sea surface temperature (SST) variability on hydrological extremes across the Mississippi River and its major tributaries. Wet extremes are associated with strong El Niño-like warming over the tropical Pacific, but specific SST patterns matter: dry (wet) conditions occur during Central Pacific (Eastern Pacific) El Niño events. The influence of North Atlantic SSTs is less clear, but cool SSTs contribute to Ohio basin wet extremes. These results are relevant for seasonal-to-interannual flood hazard prediction on the fourth largest river basin in the world.
Original language | American English |
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Article number | e2022GL100715 |
Journal | Geophysical Research Letters |
Volume | 50 |
Issue number | 2 |
DOIs | |
State | Published - 28 Jan 2023 |
Bibliographical note
Funding Information:This work was supported by the National Oceanic and Atmospheric Administration (NOAA Award Number NA18OAR4310427) awarded to S.D., the National Science Foundation (NSF CLD-214778) to S.D. and S.M., and by a graduate fellowship from the Department of Earth, Environmental, and Planetary Sciences at Rice University to X.L. N.S. was supported in part by NSF AGS-1805490 and ISF 2654/20.
Funding Information:
This work was supported by the National Oceanic and Atmospheric Administration (NOAA Award Number NA18OAR4310427) awarded to S.D., the National Science Foundation (NSF CLD‐214778) to S.D. and S.M., and by a graduate fellowship from the Department of Earth, Environmental, and Planetary Sciences at Rice University to X.L. N.S. was supported in part by NSF AGS‐1805490 and ISF 2654/20.
Publisher Copyright:
© 2022. The Authors.