Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim; Mei, Rui; Kabela, Erik D.; Gangrade, Sudershan; Naz, Bibi S.; Preston, Benjamin L.; Singh, Nagendra; Anantharaj, Valentine G.

doi:10.1002/2016JD026001

Title: Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

Journal Article · Thu Apr 13 00:00:00 EDT 2017 · Journal of Geophysical Research: Atmospheres

DOI:https://doi.org/10.1002/2016JD026001· OSTI ID:1366376

Rastogi, Deeksha ^[1];

^[2];

^[3]; Mei, Rui ^[3]; Kabela, Erik D. ^[4];

^[2];

^[5]; Preston, Benjamin L. ^[6]; Singh, Nagendra ^[7]; Anantharaj, Valentine G. ^[8]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.; Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Nuclear Security and Isotope Technology Division
Forschungszentrum Julich (Germany). Inst. of Bio- and Geosciences, Agrosphere (IBG-3)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division; RAND Corporation, Santa Monica, CA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Sciences and Engineering Division
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences

Abstract Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics‐based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama‐Coosa‐Tallapoosa (ACT) River Basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth‐area‐duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981–2010 baseline values by around 20% in the 2021–2050 near‐future and 44% in the 2071–2100 far‐future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserve more in‐depth examination.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1366376

Alternate ID(s):: OSTI ID: 1402405

Journal Information:: Journal of Geophysical Research: Atmospheres, Vol. 122, Issue 9; ISSN 2169-897X

Publisher:: American Geophysical UnionCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 28 works

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Understanding Convective Extreme Precipitation Scaling Using Observations and an Entraining Plume Model Loriaux, Jessica M.; Lenderink, Geert; De Roode, Stephan R. Journal of the Atmospheric Sciences, Vol. 70, Issue 11 https://doi.org/10.1175/JAS‐D‐12‐0317.1	journal	October 2013
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Physically Based Estimation of Maximum Precipitation over American River Watershed, California Ohara, N.; Kavvas, M. L.; Kure, S. Journal of Hydrologic Engineering, Vol. 16, Issue 4 https://doi.org/10.1061/(ASCE)HE.1943‐5584.0000324	journal	April 2011
A probabilistic approach to the concept of Probable Maximum Precipitation Papalexiou, S. M.; Koutsoyiannis, D. Advances in Geosciences, Vol. 7 https://doi.org/10.5194/adgeo‐7‐51‐2006	journal	January 2006
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Generating surfaces of daily meteorological variables over large regions of complex terrain Thornton, Peter E.; Running, Steven W.; White, Michael A. Journal of Hydrology, Vol. 190, Issue 3-4 https://doi.org/10.1016/S0022‐1694(96)03128‐9	journal	March 1997
Impacts of Postdam Land Use/Land Cover Changes on Modification of Extreme Precipitation in Contrasting Hydroclimate and Terrain Features Woldemichael, Abel T.; Hossain, Faisal; Pielke, Roger Journal of Hydrometeorology, Vol. 15, Issue 2 https://doi.org/10.1175/JHM‐D‐13‐085.1	journal	April 2014
Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies Klein, Iris M.; Rousseau, Alain N.; Frigon, Anne Elsevier https://doi.org/10.5167/uzh-151187	text	January 2016
Development of a methodology to evaluate probable maximum precipitation (PMP) under changing climate conditions: Application to southern Quebec, Canada Rousseau, Alain N.; Klein, Iris M.; Freudiger, Daphné Elsevier https://doi.org/10.5167/uzh-151189	text	January 2014

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