Projected changes in rare extreme precipitation design values in the United States due to global warming

Abstract

There is high confidence that extreme precipitation will increase in most areas if the globe continues to warm. In the US, NOAA Atlas 14 (NA14) is the most authoritative source for heavy rainfall frequency values used in infrastructure planning and design. However, NA14 assumes a stationary climate and uses only historical observations to estimate values. Thus, use of such values for design may lead to underperformance of long-lived infrastructure, thereby placing people and property at increased risk from flooding. Analyses of global climate model (GCM) simulations suggest that projected extreme precipitation changes will be positive nearly everywhere in the US and will be larger for shorter durations, lower annual exceedance probabilities (AEPs), and higher emissions. Herein, we provide adjustment factors that can be applied to observations-based precipitation frequency values to estimate potential future changes under selected global warming levels. These are derived from two statistically downscaled daily precipitation datasets (STAR and LOCA2) developed using modern methods that focus in part on modeling the high tail of the precipitation distribution with a high degree of fidelity. These datasets, each consisting of 16 ensemble members downscaled from a common set of 16 CMIP6 GCMs, provide estimates for durations of daily and longer. The set of adjustment factors are extended using seven models from the NA-CORDEX suite of dynamically downscaled simulations by analyzing the change in adjustment factors from daily to hourly durations. There is an average increase in the adjustment factors of about 1.3. This factor is applied to the daily adjustment factors from STAR and LOCA2 to produce estimates for the hourly duration.

Graphical abstract

Keywords

precipitation / extremes / climate / projections

References

[1] Basile S, Crimmins A R, Avery C W, Hamlington B D, Kunkel K E (2023). Appendix 3. Scenarios and datasets. In: Fifth National Climate Assessment. Crimmins A R, Avery C W, Easterling D R, Kunkel K E, Stewart B C, and Maycock T K, Eds. U. S. Global Change Research Program, Washington, DC, USA

[2] BonninG M, MartinD, LinB, Parzybok T, YektaM, RileyD (2006a). NOAA Atlas 14 Precipitation-Frequency Atlas of the United States Volume 1 Version 4.0: Semiarid Southwest (Arizona, Southeast California, Nevada, New Mexico, Utah). Technical Report, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Maryland: Silver Spring

[3] BonninG M, MartinD, LinB, Parzybok T, YektaM, RileyD (2006b). NOAA Atlas 14 Precipitation-Frequency Atlas of the United States Volume 2 Version 3.0: Delaware, District of Columbia, Illinois, Indiana, Kentucky, Maryland, New Jersey, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Virginia, West Virginia. Technical Report, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Maryland: Silver Spring

[4] BonninG M, MartinD, LinB, Parzybok T, YektaM, RileyD (2006c). NOAA Atlas 14 Precipitation-Frequency Atlas of the United States Volume 3 Version 3.0: Puerto Rico and the U.S. Virgin Islands. Technical Report, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Maryland: Silver Spring

[5] DeGaetano A T, Castellano C M (2017). Future projections of extreme precipitation intensity-duration- frequency curves for climate adaptation planning in New York State.Clim Serv, 5: 23–35

[6] DouvilleH, Raghavan K, RenwickJ, AllanR P, AriasP A, BarlowM, Cerezo-Mota R, CherchiA, GanT Y, GergisJ, JiangD, Khan A, MbaW P, RosenfeldD, Tierney J, ZolinaO (2021). Water Cycle Changes. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte V, Zhai P, Pirani A, Connors S L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis M I, Huang M, Leitzell K, Lonnoy E, Matthews J B R, Maycock T K, Waterfield T, Yelekçi O, Yu R, and Zhou B (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1055–1210.

[7] Eyring V, Bony S, Meehl G A, Senior C A, Stevens B, Stouffer R J, Taylor K E (2016). Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization.Geosci Model Dev, 9(5): 1937–1958

[8] Förster K, Thiele L B (2020). Variations in sub-daily precipitation at centennial scale.NPJ Climate and Atmospheric Science, 3: 13

[9] Hayhoe K, Scott-Fleming I Stoner A, Wuebbles D (2024). STAR-ESDM: a generalizable approach to generating high-resolution climate projections through signal decomposition.Earth's Future, 12: e2023EF004107

[10] HoltonJ R (1992). An Introduction to Dynamic Meteorology, 3rd Ed. New York: Academic Press

[11] IPCC (1995). Climate Change 1995: A Report of the Intergovernmental Panel on Climate Change (Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press)

[12] IPCC (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press

[13] Kunkel K E, Easterling D R, Kristovich D A R, Gleason B, Stoecker L, Smith R (2012). Meteorological causes of the secular variations in observed extreme precipitation events for the conterminous United States.J Hydrometeorol, 13(3): 1131–1141

[14] Kunkel K E, Karl T R, Squires M F, Yin X, Stegall S T, Easterling D R (2020a). Precipitation extremes: trends and relationships with average precipitation and precipitable water in the contiguous united states.J Appl Meteorol Climatol, 59(1): 125–142

[15] Kunkel K E, Stevens S E, Stevens L E, Karl T R (2020b). Observed climatological relationships of extreme daily precipitation events with precipitable water and vertical velocity in the Contiguous United States.Geophys Res Lett, 47(12): e2019GL086721

[16] Li C, Zwiers F, Zhang X, Chen G, Lu J, Li G, Norris J, Tan Y, Sun Y, Liu M (2019). Larger increases in more extreme local precipitation events as climate warms.Geophys Res Lett, 46(12): 6885–6891

[17] Marvel K, Su W, Delgado R, Aarons S, Chatterjee A, Garcia M E, Hausfather Z, Hayhoe K, Hence D A, Jewett E B, Robel A, Singh D, Tripati A, Vose R S (2023). Ch. 2. Climate trends. In: Crimmins A R, Avery C W, Easterling D R, Kunkel K E, Stewart B C, and Maycock T K, eds. Fifth National Climate Assessment U. S. Global Change Research Program, Washington, DC, USA

[18] NASEM (National Academies of Sciences, Engineering, Medicine) (2024). Modernizing Probable Maximum Precipitation Estimation. Washington, DC: The National Academies Press

[19] NAST (2000). Climate Change Impacts on the United States: The Potential Consequences of Climate Variability and Change. In: Report for the US Global Change Research Program, Cambridge: Cambridge University Press

[20] Nazarian R H, Vizzard J V, Agostino C P, Lutsko N J (2022). Projected changes in future extreme precipitation over the Northeast United States in the NA-CORDEX ensembles.J Appl Meteorol Climatol, 61(11): 1649–1668

[21] Neelin J D, Martinez-Villalobos C, Stechmann S N, Ahmed F, Chen G, Norris J M, Kuo Y H, Lenderink G (2022). Precipitation extremes and water vapor: relationships in current climate and implications for climate change.Curr Clim Change Rep, 8(1): 17–33

[22] O’Gorman P A (2015). Precipitation extremes under climate change.Curr Clim Change Rep, 1(2): 49–59

[23] O’Gorman P A, Schneider T (2009). The physical basis for increases in precipitation extremes in simulations of 21st-century climate change.Proc Natl Acad Sci USA, 106(35): 14773–14777

[24] O’Neill B C, Tebaldi C, van Vuuren D P, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J F, Lowe J, Meehl G A, Moss R, Riahi K, Sanderson B M (2016). The scenario model intercomparison project (ScenarioMIP) for CMIP6.Geosci Model Dev, 9(9): 3461–3482

[25] OWP (2022). Analysis of Impact of Nonstationary Climate on NOAA Atlas 14 Estimates. Technical Report, National Weather Service, Office of Water Prediction

[26] Pierce D W, Cayan D R, Feldman D R, Risser M D (2023). Future increases in North American extreme precipitation in CMIP6 downscaled with LOCA.J Hydrometeorol, 24(5): 951–975

[27] Prein A, Rasmussen R, Ikeda K, Liu C, Clark M P, Holland G J (2017). The future intensification of hourly precipitation extremes.Nat Clim Chang, 7(1): 48–52

[28] Rasmussen R M, Chen F, Liu C, Ikeda K, Prein A, Kim J, Schneider T, Dai A, Gochis D, Dugger A, Zhang Y, Jaye A, Dudhia J, He C, Harrold M, Xue L, Chen S, Newman A, Dougherty E, Abolafia-Rosenzweig R, Lybarger N D, Viger R, Lesmes D, Skalak K, Brakebill J, Cline D, Dunne K, Rasmussen K, Miguez-Macho G (2023). CONUS404: The NCAR–USGS 4-km long-term regional hydroclimate reanalysis over the CONUS.Bull Am Meteorol Soc, 104(8): E1382–E1408

[29] Schlef K E, Kunkel K E, Brown C, Demissie Y, Lettenmaier D P, Wagner A, Wigmosta M S, Karl T R, Easterling D R, Wang K J, Francois B, Yan E (2023). Incorporating non-stationarity from climate change into rainfall frequency and intensity-duration-frequency (IDF) curves.J Hydrol (Amst), 616: 128757

[30] SeneviratneS I, ZhangX, AdnanM, Badi W, DereczynskiC, Di LucaA, GhoshS, IskanderI, Kossin J, LewisS, OttoF, PintoI, SatohM, Vicente-Serrano S M, WehnerM, ZhouB (2021). Weather and Climate Extreme Events in a Changing Climate (Chapter 11). In: IPCC 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. [Masson-Delmotte V, Zhai P, Pirani A, Connors S L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis M I, Huang M, Leitzell K, Lonnoy E, Matthews J B R, Maycock T K, Waterfield T, Yelekçi O, Yu R, and Zhou B (eds.). Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press, 1513–1766

[31] USGCRP (2023). Fifth National Climate Assessment. In: U.S. Global Change Research Program. Washington, DC, USA

[32] Wilks D S (2016). “The stippling shows statistically significant grid points”: How research results are routinely overstated and overinterpreted, and what to do about it.Bull Am Meteorol Soc, 97(12): 2263–2273

[33] Wright D B, Bosma C D, Lopez-Cantu T (2019). U. S. hydrologic design standards insufficient due to large increases in frequency of rainfall extremes.Geophys Res Lett, 46(14): 8144–8153

[34] Wright D B, Samaras C, Lopez-Cantu T (2021). Resilience to extreme rainfall starts with science.Bull Am Meteorol Soc, 102(4): E808–E813

RIGHTS & PERMISSIONS

The Author(s). This article is published with open access at link.springer.com and journal.hep.com.cn