Gourevitch, J. D. et al. Unpriced climate risk and the potential consequences of overvaluation in US housing markets. Nat. Clim. Chang. 13, 250–257 (2023).
KTOO Climate change exacerbates deadly floods worldwide. https://www.ktoo.org/2023/09/15/climate-change-exacerbates-deadly-floodsworldwide/#:~:text=Catastrophic%20floods%20in%20eastern%20Libya,heavy%20rain%20was%20to%20blame (2023)
François, B., Schlef, K. E., Wi, S. & Brown, C. M. Design considerations for riverine floods in a changing climate—A review. J. Hydrol. https://doi.org/10.1016/j.jhydrol.2019.04.068 (2019).
Katz, R. W., Parlange, M. B. & Naveau, P. Statistics of extremes in hydrology. Adv. Water Resour. 25, 1287–1304 (2002).
Salas, J. D. & Obeysekera, J. Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J. Hydrol. Eng. 19, 554–568 (2014).
Serinaldi, F. & Kilsby, C. G. Stationarity is undead: Uncertainty dominates the distribution of extremes. Adv. Water Resour. 77, 17–36 (2015).
USGS. Guidelines for Determining Flood Flow Frequency Bulletin 17C. (2019).
Natural Environment Research Council (NERC). Flood Studies Report Vol. 1 (Natural Environment Research Council, 1975).
Kundzewicz, Z. W. et al. Differences in flood hazard projections in Europe–their causes and consequences for decision making. Hydrol. Sci. J. 62, 1–14 (2017).
Woetzel, J., Pinner, D. & Samandari, H. Climate risk and response: Physical hazards and socioeconomic impacts. (2020).
Nieto, M. J. Banks, climate risk and financial stability. J. Financ. Regul. Compliance https://doi.org/10.1108/JFRC-03-2018-0043 (2019).
Gambhir, A. et al. Near-term transition and longer-term physical climate risks of greenhouse gas emissions pathways. Nat. Climate Change 12(1), 88–96 (2022).
van Benthem, A. A., Crooks, E., Giglio, S., Schwob, E. & Stroebel, J. The effect of climate risks on the interactions between financial markets and energy companies. Nat. Energy 7, 690–697 (2022).
Global Center on Adaptation. (2023). Summary: Global Center on Adaptation for COP28. https://unfccc.int/sites/default/files/resource/Summary_GCA_COP28.pdf
Feist, M. & Geden, O. No title. Climate negotiations in times of multiple crises: Credibility and trust in international climate politics after COP 27 (2023).
Jain, S. & Lall, U. Floods in a changing climate: Does the past represent the future?. Water Resour. Res. 37, 3193–3205 (2001).
Berz, G. Flood disasters: lessons from the past—worries for the future. In Proceedings of the Institution of Civil Engineers-Water and Maritime Engineering Ser. 142, (Thomas Telford Ltd, 2000).
Cheng, L. & AghaKouchak, A. Nonstationary precipitation intensity-duration-frequency curves for infrastructure design in a changing climate. Sci. Rep. 4, 78–93 (2014).
Konapala, G., Mishra, A. K., Wada, Y. & Mann, M. E. Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nat. Commun. 11, 3044 (2020).
Skliris, N., Zika, J. D., Nurser, G., Josey, S. A. & Marsh, R. Global water cycle amplifying at less than the Clausius–Clapeyron rate. Sci. Rep. 6, 38752 (2016).
Lenderink, G., Barbero, R., Loriaux, J. M. & Fowler, H. J. Super-Clausius–Clapeyron scaling of extreme hourly convective precipitation and its relation to large-scale atmospheric conditions. J. Clim. 30, 6037–6052 (2017).
Coelho, G. D. A. et al. Potential Impacts of future extreme precipitation changes on flood engineering design across the contiguous United States. Water Resour. Res. 58, e2021WR031432 (2022).
Sohoulande Djebou, D. C. & Singh, V. P. Impact of climate change on precipitation patterns: A comparative approach. Int. J. Climatol. 36, 3588–3606 (2016).
Tabari, H. Extreme value analysis dilemma for climate change impact assessment on global flood and extreme precipitation. J Hydrol 593, 125932 (2021).
Fowler, H. J. et al. Anthropogenic intensification of short-duration rainfall extremes. Nat. Rev. Earth Environ. 2, 107–122 (2021).
Chang, H. & Bonnette, M. R. Climate change and water-related ecosystem services: Impacts of drought in California. USA 2, e01254 (2016).
Littell, J. S. Drought and fire in the western USA: Is climate attribution enough?. Curr. Clim. Change Rep. 4, 396–406 (2018).
Tabari, H. Climate change impact on flood and extreme precipitation increases with water availability. Sci. Rep. 10, 1–10 (2020).
John, A., Douville, H., Ribes, A. & Yiou, P. Quantifying CMIP6 model uncertainties in extreme precipitation projections. Weather Clim Extrem. 36, 100435 (2022).
Watson, A. J. Certainty and uncertainty in climate change predictions: What use are climate models?. Environ. Resour. Econ. 39, 37–44 (2008).
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).
Dai, A. Precipitation characteristics in eighteen coupled climate models. J. Clim. 19, 4605–4630 (2006).
Rahat, S. H. et al. Characterizing hydrologic vulnerability under nonstationary climate and antecedent conditions using a process-informed stochastic weather generator. J. Water Resour. Plann. Manage. 148, 04022028 (2022).
Steinschneider, S., Ray, P., Rahat, S. H. & Kucharski, J. A weather-regime based stochastic weather generator for climate vulnerability assessments of water systems in the Western United States. Water Resour. Res. https://doi.org/10.1029/2018WR024446 (2019).
Miura, Y. et al. A methodological framework for determining an optimal coastal protection strategy against storm surges and sea level rise. Nat. Hazards 107, 1821–1843 (2021).
Abatzoglou, J. T. Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol. 33, 121–131 (2013).
Fiedler, T. et al. Business risk and the emergence of climate analytics. Nat. Clim. Change 11, 87–94 (2021).
Weinhofer, G. & Busch, T. Corporate strategies for managing climate risks. Bus. Strategy Environ. 22, 121–144 (2013).
Pendergrass, A. G. & Hartmann, D. L. Changes in the distribution of rain frequency and intensity in response to global warming. J. Clim. 27, 8372–8383 (2014).
Tippett, M. K., Sobel, A. H. & Camargo, S. J. Association of US tornado occurrence with monthly environmental parameters. Geophys. Res. Lett. https://doi.org/10.1029/2011GL050368 (2012).
Brauer, N. S., Basara, J. B., Homeyer, C. R., McFarquhar, G. M. & Kirstetter, P. E. Quantifying precipitation efficiency and drivers of excessive precipitation in post-landfall Hurricane Harvey. J. Hydrometeorol. 21, 433–452 (2020).
Chang, H. I. et al. Enhancing extreme precipitation predictions with dynamical downscaling: A convection-permitting modeling study in Texas and Oklahoma. J. Geophys. Res. Atmos. 129(8), e2023038765 (2024).
Huang, H., Patricola, C. M., Winter, J. M., Osterberg, E. C. & Mankin, J. S. Rise in Northeast US extreme precipitation caused by Atlantic variability and climate change. J. Geophys. Res. Atmos. 33, 100351 (2021).
Jong, B., Delworth, T. L., Cooke, W. F., Tseng, K. & Murakami, H. Increases in extreme precipitation over the Northeast United States using high-resolution climate model simulations. npj Clim. Atmos. Sci. 6, 18 (2023).
Brooks, H. E., Carbin, G. W. & Marsh, P. T. Increased variability of tornado occurrence in the United States. Science 346, 349–352 (2014).
Galway, J. G. Relationship between precipitation and tornado activity. Water Resour. Res. 15, 961–964 (1979).
Tippett, M. K., Sobel, A. H. & Camargo, S. J. Association of US tornado occurrence with monthly environmental parameters. Geophys. Res. Lett. https://doi.org/10.1029/2011GL050368 (2012).
Wang, S. et al. A Comparison between the kuroshio extension and pineapple express atmospheric rivers affecting the West Coast of North America. J. Clim. 35, 3905–3925 (2022).
Liu, Z., Herman, J. D., Huang, G., Kadir, T. & Dahlke, H. E. Identifying climate change impacts on surface water supply in the southern Central Valley. California. Sci. Total Environ. 759, 143429 (2021).
Hawkins, E. & Sutton, R. The potential to narrow uncertainty in projections of regional precipitation change. Clim. Dyn. 37, 407–418 (2011).
Ford, T. W., Chen, L. & Schoof, J. T. Variability and transitions in precipitation extremes in the Midwest United States. J. Hydrometeorol. 22, 533–545 (2021).
Hoell, A., Ford, T. W., Woloszyn, M., Otkin, J. A. & Eischeid, J. Characteristics and predictability of Midwestern United States drought. J. Hydrometeorol. 22, 3087–3105 (2021).
U.S. Census Bureau (2021) 2020 Census Demographic Data Map Viewer. https://www.census.gov/library/visualizations/2021/geo/demographicmapviewer.html
Wuebbles, D. et al. Climate science special report: Fourth national climate assessment (NCA4), vol. I (2017)
ArcGIS Online. (n.d.). Community Development Block Grant Grantee Areas. HUD. Accessed 14 August 2023; https://hudgis-hud.opendata.arcgis.com/datasets/HUD::community-development-block-grant-grantee-areas/about
McDermott, T. K. Global exposure to flood risk and poverty. Nat. Commun. 13, 3529 (2022).
Shively, D. Flood risk management in the USA: Implications of National Flood Insurance Program changes for social justice. Reg. Environ. Change 17, 1663–1672 (2017).
Svoboda, M., Hayes, M. & Wood, D. Standardized precipitation index: user guide. (2012).
Mitra, S. & Srivastava, P. Spatiotemporal variability of meteorological droughts in southeastern USA. Nat. Hazards 86, 1007–1038 (2017).
Swain, S. & Hayhoe, K. CMIP5 projected changes in spring and summer drought and wet conditions over North America. Clim. Dyn. 44, 2737–2750 (2015).
Huang, X. & Swain, D. L. Climate change is increasing the risk of a California megaflood. Sci. Adv. 8(31), eabq0995 (2022).
Lark, T. J., Schelly, I. H. & Gibbs, H. K. Accuracy, bias, and improvements in mapping crops and cropland across the United States using the USDA Cropland Data Layer. Remote Sens. 13(5), 968 (2021).
Rising, J. & Devineni, N. Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5. Nat. Commun. 11(1), 4991 (2020).
Tamaddun, K. A., Kalra, A., Bernardez, M. & Ahmad, S. Effects of ENSO on temperature, precipitation, and potential evapotranspiration of North India’s monsoon: An analysis of trend and entropy. Water 11(2), 189 (2019).
World Meteorological Organization. Copernicus confirms July 2023 was hottest month ever recorded. https://public.wmo.int/en/media/press-release/world-meteorological-organization-declares-onset-of-el-ni%C3%B1o-conditions (2023)
National Weather Service. El Niño is likely to continue into the spring 2023. National Weather Service News Releases. Accessed from 26 July 2023; https://www.weather.gov/news/230706-ElNino (2023)
Carlowicz, M. & Schollaert Uz, S. El Niño: pacific wind and current changes bring warm, wild weather. 14 (2017).
Wengel, C. et al. Future high-resolution El Niño/Southern Oscillation dynamics. Nat. Clima. Change 11, 758–765 (2021).
United Nations. Hottest July ever signals ‘era of global boiling has arrived’ says UN chief. United Nations News. https://news.un.org/en/story/2022/08/1123812 (2022).
Tabari, H. Climate change impact on flood and extreme precipitation increases with water availability. Sci. Rep. 10, 13768 (2020).
Dai, A. Drought under global warming: A review. Wiley Interdiscip. Rev. Clim. Change 2, 45–65 (2011).
Mirzabaev, A. et al. Climate change and food systems. In Science and Innovations for Food Systems Transformation (eds von Braun, J. et al.) 511 (Springer, 2023).
Konapala, G. & Mishra, A. Quantifying climate and catchment control on hydrological drought in the continental United States. Water Resour. Res. 56, e2018WR024620 (2020).
Robertson, A. W., Kushnir, Y., Lall, U. & Nakamura, J. Weather and Climatic Drivers of Extreme Flooding Events Over the Midwest of the United States 113–124 (Wiley, 2015).
Breinl, K. et al. Can weather generation capture precipitation patterns across different climates, spatial scales and under data scarcity?. Sci. Rep. 7, 5449 (2017).
Clarke, B., Otto, F., Stuart-Smith, R. & Harrington, L. Extreme weather impacts of climate change: an attribution perspective. Environ. Res. Clim. 1, 012001 (2022).
Neelin, J. D. et al. Precipitation extremes and water vapor: Relationships in current climate and implications for climate change. Curr. Clim. Change Rep. 8, 17–33 (2022).
Emori, S. & Brown, S. J. Dynamic and thermodynamic changes in mean and extreme precipitation under changed climate. Geophys. Res. Lett. https://doi.org/10.1029/2005GL023272 (2005).
Van Montfort, M. & Witter, J. V. The generalized Pareto distribution applied to rainfall depths. Hydrol. Sci. J. 31, 151–162 (1986).
Blankenau, P. A., Kilic, A. & Allen, R. An evaluation of gridded weather data sets for the purpose of estimating reference evapotranspiration in the United States. Agric. Water Manage. 242, 106376 (2020).
NOAA National Centers for Environmental Information. NOAA Optimum Interpolation Sea Surface Temperature (OISST) High-Resolution Dataset, Version 2. Accessed 14 August 2023; https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html