May 25, 2024
A warming-induced reduction in snow fraction amplifies rainfall extremes – Nature

A warming-induced reduction in snow fraction amplifies rainfall extremes – Nature

  • Kharin, V. V., Zwiers, F. W., Zhang, X. & Hegerl, G. C. Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. J. Clim. 20, 1419–1444 (2007).

    Article 
    ADS 

    Google Scholar
     

  • Sun, Y., Solomon, S., Dai, A. & Portmann, R. W. How often will it rain? J. Clim. 20, 4801–4818 (2007).

    Article 
    ADS 

    Google Scholar
     

  • Pall, P., Allen, M. R. & Stone, D. A. Testing the Clausius–Clapeyron constraint on changes in extreme precipitation under CO2 warming. Clim. Dyn. 28, 351–363 (2006).

    Article 

    Google Scholar
     

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

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Donat, M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. & Maher, N. More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Change 6, 508–513 (2016).

    Article 
    ADS 

    Google Scholar
     

  • Davenport, F. V., Herrera-Estrada, J. E., Burke, M. & Diffenbaugh, N. S. Flood size increases nonlinearly across the western United States in response to lower snow–precipitation ratios. Water Resour. Res. 56, e2019WR025571 (2020).

  • Handwerger, A. L. et al. Widespread initiation, reactivation, and acceleration of landslides in the Northern California coast ranges due to extreme rainfall. J. Geophys. Res. Earth Surf. 124, 1782–1797 (2019).

    Article 
    ADS 

    Google Scholar
     

  • Haque, U. et al. The human cost of global warming: deadly landslides and their triggers (1995–2014). Sci. Total Environ. 682, 673–684 (2019).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Martha, T. R. et al. Landslides triggered by the June 2013 extreme rainfall event in parts of Uttarakhand State, India. Landslides 12, 135–146 (2014).

    Article 

    Google Scholar
     

  • Morán-Ordóñez, A. et al. Future impact of climate extremes in the mediterranean: soil erosion projections when fire and extreme rainfall meet. Land Degrad. Dev. 31, 3040–3054 (2020).

    Article 

    Google Scholar
     

  • Nearing, M., Pruski, F. & O’neal, M. Expected climate change impacts on soil erosion rates: a review. J. Soil Water Conserv. 59, 43–50 (2004).


    Google Scholar
     

  • Allen, M. R. & Ingram, W. J. Constraints on future changes in climate and the hydrologic cycle. Nature 419, 228–232 (2002).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Trenberth, K. E. in Weather and Climate Extremes (eds Karl, T. R. et al.) 327–339 (Springer, 1999); https://doi.org/10.1007/978-94-015-9265-9_18.

  • Trenberth, K. E., Dai, A., Rasmussen, R. M. & Parsons, D. B. The changing character of precipitation. Bull. Am. Meteorol. Soc. 84, 1205–1218 (2003).

    Article 
    ADS 

    Google Scholar
     

  • Shi, X. & Durran, D. R. Estimating the response of extreme precipitation over midlatitude mountains to global warming. J. Clim. 28, 4246–4262 (2015).

    Article 
    ADS 

    Google Scholar
     

  • Diffenbaugh, N. S., Pal, J. S., Trapp, R. J. & Giorgi, F. Fine-scale processes regulate the response of extreme events to global climate change. Proc. Natl Acad. Sci. USA 102, 15774–15778 (2005).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Räisänen, J. Warmer climate: less or more snow? Clim. Dyn. 30, 307–319 (2007).

    Article 

    Google Scholar
     

  • Krasting, J. P., Broccoli, A. J., Dixon, K. W. & Lanzante, J. R. Future changes in Northern Hemisphere snowfall. J. Clim. 26, 7813–7828 (2013).

    Article 
    ADS 

    Google Scholar
     

  • O’Gorman, P. A. Contrasting responses of mean and extreme snowfall to climate change. Nature 512, 416–418 (2014).

    Article 
    ADS 
    PubMed 

    Google Scholar
     

  • Rhoades, A. M. et al. Asymmetric emergence of low-to-no snow in the midlatitudes of the American Cordillera. Nat. Clim. Change 12, 1151–1159 (2022).

    Article 
    ADS 

    Google Scholar
     

  • Siirila-Woodburn, E. et al. Evidence of a low-to-no snow future and its impacts on water resources in the western United States. Nat. Revi. Earth Environ. 2, 800–819 (2021).

    Article 
    ADS 

    Google Scholar
     

  • Kirschbaum, D. B., Stanley, T. & Simmons, J. A dynamic landslide hazard assessment system for Central America and Hispaniola. Nat. Hazards Earth Syst. Sci. 15, 2257–2272 (2015).

    Article 
    ADS 

    Google Scholar
     

  • Krøgli, I. K. et al. The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides. Nat. Hazards Earth Syst. Sci. 18, 1427–1450 (2018).

    Article 
    ADS 

    Google Scholar
     

  • Oakley, N. S. A warming climate adds complexity to post-fire hydrologic hazard planning. Earths Future 9, e2021EF002149 (2021).

    Article 
    ADS 

    Google Scholar
     

  • Ombadi, M., Nguyen, P., Sorooshian, S. & Hsu, K.-l Developing intensity–duration–frequency (IDF) curves from satellite-based precipitation: methodology and evaluation. Water Resour. Res. 54, 7752–7766 (2018).

    Article 
    ADS 

    Google Scholar
     

  • Bonnin, G. et al. 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 (NOAA, 2006); https://www.weather.gov/owp/hdsc_currentpf.

  • Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article 
    ADS 

    Google Scholar
     

  • Pepin, N. C. et al. Climate changes and their elevational patterns in the mountains of the world. Rev. Geophys. 60, e2020RG000730 (2022).

    Article 
    ADS 

    Google Scholar
     

  • Hausfather, Z., Marvel, K., Schmidt, G. A., Nielsen-Gammon, J. W. & Zelinka, M. Climate simulations: recognize the ‘hot model’ problem. Nature 605, 26–29 (2022).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Sun, Q., Zhang, X., Zwiers, F., Westra, S. & Alexander, L. V. A global, continental, and regional analysis of changes in extreme precipitation. J. Clim. 34, 243–258 (2021).

    Article 
    ADS 

    Google Scholar
     

  • Pfahl, S., O’Gorman, P. A. & Fischer, E. M. Understanding the regional pattern of projected future changes in extreme precipitation. Nat. Clim. Change 7, 423–427 (2017).

    Article 
    ADS 

    Google Scholar
     

  • Marelle, L., Myhre, G., Hodnebrog, Ø., Sillmann, J. & Samset, B. H. The changing seasonality of extreme daily precipitation. Geophys. Res. Lett. 45, 11–352 (2018).

    Article 

    Google Scholar
     

  • Jennings, K. S., Winchell, T. S., Livneh, B. & Molotch, N. P. Spatial variation of the rain–snow temperature threshold across the Northern Hemisphere. Nat. Commun. 9, 1148 (2018).

  • Risser, M. D. & Wehner, M. F. Attributable human-induced changes in the likelihood and magnitude of the observed extreme precipitation during hurricane Harvey. Geophys. Res. Lett. 44, 12–457 (2017).

    Article 

    Google Scholar
     

  • Paciorek, C. J., Stone, D. A. & Wehner, M. F. Quantifying statistical uncertainty in the attribution of human influence on severe weather. Weather Clim Extrem. 20, 69–80 (2018).

    Article 

    Google Scholar
     

  • Payne, A. E. et al. Responses and impacts of atmospheric rivers to climate change. Nat. Rev. Earth Environ. 1, 143–157 (2020).

    Article 
    ADS 

    Google Scholar
     

  • Immerzeel, W. W. et al. Importance and vulnerability of the world’s water towers. Nature 577, 364–369 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Milly, P. C. D. et al. Stationarity is dead: whither water management? Science 319, 573–574 (2008).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Cheng, L. & AghaKouchak, A. Nonstationary precipitation intensity–duration–frequency curves for infrastructure design in a changing climate. Sci. Rep. 4, 7093 (2014).

  • Ragno, E. et al. Quantifying changes in future intensity–duration–frequency curves using multimodel ensemble simulations. Water Resour. Res. 54, 1751–1764 (2018).

    Article 
    ADS 

    Google Scholar
     

  • Fowler, H. J. et al. Anthropogenic intensification of short-duration rainfall extremes. Nat. Rev. Earth Environ. 2, 107–122 (2021).

    Article 
    ADS 

    Google Scholar
     

  • Delaney, C. J. et al. Forecast informed reservoir operations using ensemble streamflow predictions for a multipurpose reservoir in Northern California. Water Resour. Res. 56, 2019–026604 (2020).

    Article 
    ADS 

    Google Scholar
     

  • O’Gorman, P. A. Precipitation extremes under climate change. Curr. Clim. Change Rep. 1, 49–59 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Condom, T. et al. Climatological and hydrological observations for the South American Andes: in situ stations, satellite, and reanalysis data sets. Front. Earth Sci. 8, 92 (2020).

  • Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E. & Houston, T. G. An overview of the Global Historical Climatology Network-daily database. J. Atmos. Ocean. Technol. 29, 897–910 (2012).

    Article 
    ADS 

    Google Scholar
     

  • Xiong, W., Tang, G., Wang, T., Ma, Z. & Wan, W. Evaluation of IMERG and ERA5 precipitation-phase partitioning on the global scale. Water 14, 1122 (2022).

    Article 

    Google Scholar
     

  • Cartopy: A Cartographic Python Library with a Matplotlib Interface (Met Office, 2010–2015); https://scitools.org.uk/cartopy.

  • Mahto, S. S. & Mishra, V. Does ERA-5 outperform other reanalysis products for hydrologic applications in India? J. Geophys. Res. Atmos. 124, 9423–9441 (2019).

    Article 
    ADS 

    Google Scholar
     

  • Haarsma, R. J. et al. High resolution model intercomparison project (HighResMIP v1.0) for CMIP6. Geosci. Model Dev. 9, 4185–4208 (2016).

    Article 
    ADS 

    Google Scholar
     

  • Sippel, S. et al. Quantifying changes in climate variability and extremes: pitfalls and their overcoming. Geophys. Res. Lett. 42, 9990–9998 (2015).

    Article 
    ADS 

    Google Scholar
     

  • Donat, M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. & Maher, N. Addendum: More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Change 7, 154–158 (2017).

    Article 
    ADS 

    Google Scholar
     

  • Rand’s Global Elevation and Depth Data. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder CO (RAND Corporation, 1980); https://doi.org/10.5065/HKKR-P122.

  • Barbero, R. et al. A synthesis of hourly and daily precipitation extremes in different climatic regions. Weather Clim. Extrem. 26, 100219 (2019).

    Article 
    ADS 

    Google Scholar
     

  • Fowler, H. J. & Kilsby, C. G. Implications of changes in seasonal and annual extreme rainfall. Geophys. Res. Lett. 30, 1720 (2003).

  • Coles, S. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001); https://doi.org/10.1007/978-1-4471-3675-0.

  • Welch, B. L. The generalization of “Student’s” problem when several different population variances are involved. Biometrika 34, 28–35 (1947).

    MathSciNet 
    CAS 
    PubMed 
    MATH 

    Google Scholar
     

  • Feiccabrino, J., Gustafsson, D. & Lundberg, A. Surface-based precipitation phase determination methods in hydrological models. Hydrol. Res. 44, 44–57 (2012).

    Article 

    Google Scholar
     

  • Yang, D. et al. Wind-induced precipitation undercatch of the Hellmann gauges. Hydrol. Res. 30, 57–80 (1999).

    Article 

    Google Scholar
     

  • Wolff, M. A. et al. Derivation of a new continuous adjustment function for correcting wind-induced loss of solid precipitation: results of a Norwegian field study. Hydrol. Earth Syst. Sci. 19, 951–967 (2015).

    Article 
    ADS 

    Google Scholar
     

  • Kochendorfer, J. et al. Undercatch adjustments for tipping-bucket gauge measurements of solid precipitation. J. Hydrometeorol. 21, 1193–1205 (2020).

    Article 
    ADS 

    Google Scholar
     

  • Kelso, N. V. & Patterson, T. World Land-Based Polygon Features, 1:10 Million (North American Cartographic Information Society, 2012); http://www.naturalearthdata.com.

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