Increased rainfall volume from future convective storms in the US

Mesoscale convective system (MCS)-organized convective storms with a size of ~100 km have increased in frequency and intensity in the USA over the past 35 years1, causing fatalities and economic losses2. However, their poor representation in traditional climate models hampers the understanding of their change in the future3. Here, a North American-scale convection-permitting model which is able to realistically simulate MSCs4 is used to investigate their change by the end-of-century under RCP8.5 (ref. 5). A storm-tracking algorithm6 indicates that intense summertime MCS frequency will more than triple in North America. Furthermore, the combined effect of a 15–40% increase in maximum precipitation rates and a significant spreading of regions impacted by heavy precipitation results in up to 80% increases in the total MCS precipitation volume, focussed in a 40 km radius around the storm centre. These typically neglected increases substantially raise future flood risk. Current investments in long-lived infrastructures, such as flood protection and water management systems, need to take these changes into account to improve climate-adaptation practices.Limitations with climate models have previously prevented accurate diagnosis of future changes in mesoscale convective systems (MCSs). A convection-permitting model now indicates that summer MCSs will triple by 2100 in the United States, with a corresponding increase in rainfall rates and areal extent.

[1]  W. Collins,et al.  Radiative forcing by long‐lived greenhouse gases: Calculations with the AER radiative transfer models , 2008 .

[2]  K. Trenberth,et al.  The changing character of precipitation , 2003 .

[3]  J. Dudhia,et al.  Continental-scale convection-permitting modeling of the current and future climate of North America , 2017, Climate Dynamics.

[4]  B. Brown,et al.  Object-Based Verification of Precipitation Forecasts. Part I: Methodology and Application to Mesoscale Rain Areas , 2006 .

[5]  Kevin W. Manning,et al.  Use of the Parcel Buoyancy Minimum (Bmin) to Diagnose Simulated Thermodynamic Destabilization. Part II: Composite Analysis of Mature MCS Environments , 2014 .

[6]  Martin Scherer,et al.  Robust increases in severe thunderstorm environments in response to greenhouse forcing , 2013, Proceedings of the National Academy of Sciences.

[7]  G. Holland,et al.  Simulating North American mesoscale convective systems with a convection-permitting climate model , 2017, Climate Dynamics.

[8]  Harold E. Brooks,et al.  Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing , 2007, Proceedings of the National Academy of Sciences.

[9]  J. Dudhia,et al.  High resolution coupled climate-runoff simulations of seasonal snowfall over Colorado: A process study of current and warmer climate , 2011 .

[10]  J. Dudhia,et al.  A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes , 2006 .

[11]  H. Fowler,et al.  Future changes to the intensity and frequency of short‐duration extreme rainfall , 2014 .

[12]  B. Brown,et al.  The Method for Object-Based Diagnostic Evaluation (MODE) Applied to Numerical Forecasts from the 2005 NSSL/SPC Spring Program , 2009 .

[13]  Louisa Nance,et al.  Observations of Precipitation Size and Fall Speed Characteristics within Coexisting Rain and Wet Snow , 2006 .

[14]  T. Karl,et al.  Global climate change impacts in the United States. , 2009 .

[15]  R. Leung,et al.  A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges , 2015, Reviews of geophysics.

[16]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements , 2011 .

[17]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[18]  Kevin W. Manning,et al.  Use of the Parcel Buoyancy Minimum (Bmin) to Diagnose Simulated Thermodynamic Destabilization. Part I: Methodology and Case Studies of MCS Initiation Environments , 2014 .

[19]  T. Mote,et al.  Downscaled estimates of late 21st century severe weather from CCSM3 , 2015, Climatic Change.

[20]  Jiwen Fan,et al.  Evaluation of cloud‐resolving and limited area model intercomparison simulations using TWP‐ICE observations: 1. Deep convective updraft properties , 2014 .

[21]  L. Leung,et al.  More frequent intense and long-lived storms dominate the springtime trend in central US rainfall , 2016, Nature Communications.

[22]  J. Fritsch,et al.  The Contribution of Mesoscale Convective Weather Systems to the Warm-Season Precipitation in the United States , 1986 .

[23]  G. Lackmann The South-Central U.S. Flood of May 2010: Present and Future* , 2013 .

[24]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[25]  John D. Tuttle,et al.  Inferences of Predictability Associated with Warm Season Precipitation Episodes , 2001 .

[26]  G. Thompson,et al.  A Study of Aerosol Impacts on Clouds and Precipitation Development in a Large Winter Cyclone , 2014 .

[27]  T. Shepherd Atmospheric circulation as a source of uncertainty in climate change projections , 2014 .

[28]  W. Briggs Statistical Methods in the Atmospheric Sciences , 2007 .

[29]  J. Molinari,et al.  Projected increase in lightning strikes in the United States due to global warming , 2014, Science.

[30]  R. Schumacher,et al.  Near-Surface Thermodynamic Sensitivities in Simulated Extreme-Rain-Producing Mesoscale Convective Systems , 2017 .

[31]  R. Trapp Mesoscale Convective Systems , 2013 .

[32]  G. Holland,et al.  The future intensification of hourly precipitation extremes , 2016 .

[33]  G. Bryan,et al.  Sensitivity of a Simulated Squall Line to Horizontal Resolution and Parameterization of Microphysics , 2012 .

[34]  R. C. Srivastava A model of intense downdrafts driven by the melting and evaporation of precipitation , 1987 .

[35]  H. Morrison,et al.  Effects of Horizontal and Vertical Grid Spacing on Mixing in Simulated Squall Lines and Implications for Convective Strength and Structure , 2015 .

[36]  C. Schär,et al.  Bulk Convergence of Cloud-Resolving Simulations of Moist Convection over Complex Terrain , 2012 .

[37]  E. Fischer,et al.  Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate , 2016, Climate Dynamics.

[38]  William C. Skamarock,et al.  A time-split nonhydrostatic atmospheric model for weather research and forecasting applications , 2008, J. Comput. Phys..

[39]  Ashish Sharma,et al.  Reduced spatial extent of extreme storms at higher temperatures , 2016 .

[40]  Adam J. Clark,et al.  Application of Object-Based Time-Domain Diagnostics for Tracking Precipitation Systems in Convection-Allowing Models , 2014 .

[41]  H. Storch,et al.  A Spectral Nudging Technique for Dynamical Downscaling Purposes , 2000 .

[42]  Yuan Wang,et al.  Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges , 2016 .

[43]  Charles A. Doswell,et al.  Severe Convective Storms , 2001 .

[44]  H. Fowler,et al.  Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change? , 2017 .