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

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.

Sensitivity of Extreme Rainfall to Atmospheric Moisture Content in the Arid/Semiarid Southwestern United States: Implications for Probable Maximum Precipitation Estimates

“…There are a variety of ways to "maximize" a storm in numerical simulations, for instance, maximizing moisture profiles (Chen & Bradley, 2006;Ohara et al, 2017), increasing temperature profiles (Abbs, 1999;Ishida et al, 2016;Rastogi et al, 2017), and manipulating domain boundaries or direction/persistency of critical synoptic flows favorable for convective activities (Ishida et al, 2016; Journal of Geophysical Research: Atmospheres 10.1002/2017JD027850 Ohara et al, 2017). Due to the nonlinear relationships between extreme rainfall and atmospheric moisture content, "tailored" changes in model configurations may not always guarantee the increased rainfall intensity over the regions of interest (see also, e.g., Ohara et al, 2017).…”

Probable Maximum Precipitation in the U.S. Pacific Northwest in a Changing Climate

“…Previous studies have used dynamically downscaled climate model data (Beauchamp et al, ; Rastogi et al, ; Rouhani & Leconte, ; Rousseau et al, ). Compared with these studies, our approach involves as much raw climate model output as possible, and we show that with the advance of computationally efficient techniques (such as statistical downscaling, and HYSPLIT), the raw model output can be quickly converted to ready‐to‐use data for the engineering communities.…”

“…In atmospheric model‐based estimates, PMP is obtained by modifying the initial/boundary conditions of extreme precipitation event simulations, such as increased moisture availability (usually by setting relative humidity RH to 100%), increased air temperature, spatially shifted initial/boundary conditions, or artificially generated convergent wind fields. Most studies focused on the construction of PMP from various atmospheric reanalysis data, although climate model data have also been explored (Beauchamp et al, ; Lee et al, ; Ohara et al, ; Rastogi et al, ; Rouhani & Leconte, ; Rousseau et al, ; Tan, ). These studies suggest that carefully selected climate data, such as the CMIP5 data, may have value for historical PMP estimation.…”

“…Alternatively, regional climate model output can be used for PMP estimation with the advantage of providing more spatially resolved precipitation features. These studies reveal the potential of climate projections to quantify the sensitivity of PMP to climate change (Beauchamp et al, ; Rastogi et al, ; Rousseau et al, ).…”

“…Such inconsistency makes it hard to use the new results to reevaluate the safety of infrastructures. Lastly, most of the modelling studies focused on selected watersheds, making it harder to derive general guidelines for engineering designing across regions (an exception is the study by Rastogi et al (), which focused on building the depth‐area‐duration curves).…”