• Ashley, S. T., and W. S. Ashely, 2008: The storm morphology of deadly flooding events in the United States. Int. J. Climatol., 28, 493503, https://doi.org/10.1002/joc.1554.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ban, N., J. Schmidli, and C. Schar, 2015: Heavy precipitation in a changing climate: Does short term summer precipitation increase faster? Geophys. Res. Lett., 42, 11651172, https://doi.org/10.1002/2014GL062588.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beck, H. E., and et al. , 2019: Daily evaluation of 26 precipitation datasets using Stage-IV gauge radar data for the CONUS. Hydrol. Earth Syst. Sci., 23, 207224, https://doi.org/10.5194/hess-23-207-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berghuijs, W. R., R. A. Woods, C. J. Hutton, and M. Sivapalan, 2016: Dominant flood generating mechanisms across the United States. Geophys. Res. Lett., 43, 43824390, https://doi.org/10.1002/2016GL068070.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J. A., A. Dai, Y. Zhang, and K. L. Rasmussen, 2020: Changes in convective available potential energy and convective inhibition under global warming. J. Climate, 33, 20252050, https://doi.org/10.1175/JCLI-D-19-0461.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dai, A., R. M. Rasmussen, C. Liu, K. Ikeda, and A. F. Prein, 2017: A new mechanism for warm season precipitation response to global warming based on convection-permitting simulations. Climate Dyn., 55, 343368, https://doi.org/10.1007/s00382-017-3787-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, R. S., 2001: Flash flood forecast and detection methods. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 481–525.

    • Crossref
    • Export Citation
  • Demuth, J., M. DeMaria, and J. A. Knaff, 2006: Improvement of advanced microwave sounder unit tropical cyclone intensity and size estimation algorithms. J. Appl. Meteor. Climatol., 45, 15731581, https://doi.org/10.1175/JAM2429.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, H. E. Brooks, and R. A. Maddox, 1996: Flash flood forecasting: An ingredients-based methodology. Wea. Forecasting, 11, 560581, https://doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dougherty, E., and K. L. Rasmussen, 2019: Climatology of flood-producing storms and their associated rainfall characteristics in the United States. Mon. Wea. Rev., 147, 38613877, https://doi.org/10.1175/MWR-D-19-0020.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dougherty, E., and K. L. Rasmussen, 2020: Changes in flash flood–producing storms in the United States. J. Hydrometeor., 21, 22212236, https://doi.org/10.1175/JHM-D-20-0014.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dougherty, E., E. Sherman, and K. L. Rasmussen, 2020: Future changes in the hydrologic cycle associated with flood-producing storms in California. J. Hydrometeor., 21, 26072621, https://doi.org/10.1175/JHM-D-20-0067.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feser, F., B. Rockel, H. von Storch, J. Winterfeldt, and M. Zahn, 2011: Regional climate models add value to global model data: A review and selected examples. Bull. Amer. Meteor. Soc., 92, 11811192, https://doi.org/10.1175/2011BAMS3061.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frans, C., E. Istanbullugolu, V. Mishra, F. Munoz-Arriola, and D. P. Lettenmaier, 2013: Are climatic or land cover changes the dominant cause of runoff trends in the Upper Mississippi River Basin? Geophys. Res. Lett., 40, 11041110, https://doi.org/10.1002/grl.50262.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fritsch, J. M., and R. Carbone, 2004: Improving quantitative precipitation forecasts in the warm season: A USWRP research and development strategy. Bull. Amer. Meteor. Soc., 85, 955966, https://doi.org/10.1175/BAMS-85-7-955.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fritsch, J. M., R. J. Kane, and C. R. Chelius, 1986: The contribution of mesoscale convective weather systems to the warm season precipitation in the United States. J. Climate Appl. Meteor., 25, 13331345, https://doi.org/10.1175/1520-0450(1986)025,1333: TCOMCW.2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grabowski, W. W., and A. F. Prein, 2019: Separating dynamic and thermodynamic impacts of climate change on daytime convective development over land. J. Climate, 32, 52135234, https://doi.org/10.1175/JCLI-D-19-0007.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gutmann, E. D., and et al. , 2018: Changes in hurricanes from a 13-yr convection-permitting pseudo global warming simulation. J. Climate, 31, 36433657, https://doi.org/10.1175/JCLI-D-17-0391.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herman, G. R., and R. S. Schumacher, 2018: Flash flood verification: Pondering precipitation proxies. J. Hydrometeor., 19, 17531776, https://doi.org/10.1175/JHM-D-18-0092.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirabayashi, Y., R. Mahendran, S. Koirala, L. Konoshima, D. Yamazaki, S. Watanabe, H. Kim, and S. Kanae, 2013: Global flood risk under climate change. Nat. Climate Change, 3, 816821, https://doi.org/10.1038/nclimate1911.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoogewind, K. A., M. E. Baldwin, and R. J. Trapp, 2017: The impact of climate change on hazardous convective weather in the United States: Insights from high-resolution dynamical downscaling. J. Climate, 30, 10 08110 100, https://doi.org/10.1175/JCLI-D-16-0885.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., 2004: Mesoscale convective systems. Rev. Geophys., 42, RG4003, https://doi.org/10.1029/2004RG000150.

  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jha, M., Z. Pan, E. S. Takle, and R. Gu, 2004: Impacts of climate change on streamflow in the Upper Mississippi River Basin: A regional climate model perspective. J. Geophys. Res., 109, D09105, https://doi.org/10.1029/2003JD003686.

    • Search Google Scholar
    • Export Citation
  • Keller, M., and et al. , 2018: The sensitivity of Alpine summer convection to surrogate climate change: An intercomparison between convection-parameterizing and convection-resolving models. Atmos. Chem. Phys., 18, 52535264, https://doi.org/10.5194/acp-18-5253-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kendon, E., N. M. Roberts, C. A. Senior, and M. J. Roberts, 2012: Realism of rainfall in a very high-resolution regional climate model. J. Climate, 25, 57915806, https://doi.org/10.1175/JCLI-D-11-00562.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kendon, E., and et al. , 2017: Do convection-permitting regional climate models improve projections of future precipitation change? Bull. Amer. Meteor. Soc., 98, 7983, https://doi.org/10.1175/BAMS-D-15-0004.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., R. A. Houze Jr., and K. L. Rasmussen, 2014: Simulation of a flash flooding storm at the steep edge of the Himalayas. J. Hydrometeor., 15, 212228, https://doi.org/10.1175/JHM-D-12-0155.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kunkel, K. E., D. R. Easterling, D. A. R. Kristovich, B. Gleason, L. Stoecker, and R. Smith, 2012: Meteorological causes of the secular variations in observed extreme precipitation events for the conterminous United States. J. Hydrometeor., 13, 11311141, https://doi.org/10.1175/JHM-D-11-0108.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lackmann, G. M., 2013: The south-central U.S. flood of May 2010: Present and future. J. Climate, 26, 46884709, https://doi.org/10.1175/JCLI-D-12-00392.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, Y., and K. E. Mitchell, 2005: The NCEP Stage II/IV hourly precipitation analyses: Development and applications. 19th Conf. on Hydrology, San Diego, CA, Amer. Meteor. Soc., 1.2, https://ams.confex.com/ams/Annual2005/techprogram/paper_83847.htm.

  • Liu, C., and et al. , 2017: Continental-scale convection-permitting modeling of the current and future climate of North America. Climate Dyn., 49, 7195, https://doi.org/10.1007/s00382-016-3327-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loriaux, J. M., G. Lenderink, and A. P. Siebesma, 2017: Large-scale controls on extreme precipitation. J. Climate, 30, 955968, https://doi.org/10.1175/JCLI-D-16-0381.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, N., G. Y. Niu, Y. Xia, X. Cai, Y. Zhang, Y. Ma, and Y. Fang, 2017: A systematic evaluation of Noah-MP in simulating land-atmosphere energy, water, and carbon exchanges over the continental United States. J. Geophys. Res. Atmos., 122, 12 24512 268, https://doi.org/10.1002/2017JD027597.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maddox, R. A., C. F. Chappell, and L. R. Hoxit, 1979: Synoptic and meso-α scale aspects of flash flood events. Bull. Amer. Meteor. Soc., 60, 115123, https://doi.org/10.1175/1520-0477-60.2.115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahoney, K., D. Swales, M. J. Mueller, M. Alexander, M. Hughes, and K. Malloy, 2018: An examination of inland-penetrating atmospheric river flood event under potential future thermodynamic conditions. J. Climate, 31, 62816297, https://doi.org/10.1175/JCLI-D-18-0118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nelson, B., O. P. Prat, D.-J. Seo, and E. Habib, 2016: Assessment and implications of NCEP Stage IV quantitative precipitation estimates for product intercomparisons. Wea. Forecasting, 31, 371394, https://doi.org/10.1175/WAF-D-14-00112.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nielsen, E. R., and R. S. Schumacher, 2018: Dynamical insights into extreme short-term precipitation associated with supercells and mesovortices. J. Atmos. Sci., 75, 29833009, https://doi.org/10.1175/JAS-D-17-0385.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niu, G. Y., and et al. , 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010JD015139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Gorman, P. A., 2015: Precipitation extremes under climate change. Curr. Climate Change Rep., 1, 4959, https://doi.org/10.1007/s40641-015-0009-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prein, A. F., and et al. , 2015: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Rev. Geophys., 53, 323361, https://doi.org/10.1002/2014RG000475.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prein, A. F., R. M. Rasmussen, K. Ikeda, C. Liu, M. P. Clark, and G. J. Holland, 2017a: The future intensification of hourly precipitation extremes. Nat. Climate Change, 7, 4852, https://doi.org/10.1038/nclimate3168.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prein, A. F., C. Liu, K. Ikeda, R. Bullock, R. M. Rasmussen, G. J. Holland, and M. Clark, 2017b: Simulating North American mesoscale convective systems with a convection-permitting climate model. Climate Dyn., 55, 95110, https://doi.org/10.1007/s00382-017-3993-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prein, A. F., C. Liu, K. Ikeda, S. B. Trier, R. M. Rasmussen, G. J. Holland, and M. P. Clark, 2017c: Increased rainfall volume from future convective storms in the US. Nat. Climate Change, 7, 880884, https://doi.org/10.1038/s41558-017-0007-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasmussen, K. L., A. F. Prein, R. M. Rasmussen, K. Ikeda, and C. Liu, 2017: Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States. Climate Dyn., 55, 383408, https://doi.org/10.1007/S00382-017-4000-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasmussen, R., and et al. , 2011: High-resolution coupled climate runoff simulations of seasonal snowfall over Colorado: A process study of current and warmer climate. J. Climate, 34, 30153048, https://doi.org/10.1175/2010JCLI3985.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasmussen, R., and et al. , 2014: Climate change impacts on the water balance of the Colorado Headwaters: High-resolution regional climate model simulations. J. Hydrometeor., 15, 10911116, https://doi.org/10.1175/JHM-D-13-0118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saharia, M., P. Kirsteetter, H. Vergara, J. J. Gourley, Y. Hong, and M. Giroud, 2017: Mapping flash flood severity in the United States. J. Hydrometeor., 18, 397411, https://doi.org/10.1175/JHM-D-16-0082.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schär, C., C. Frei, D. Luthi, and H. C. Davies, 1996: Surrogate climate-change scenarios for regional climate models. Geophys. Res. Lett., 23, 669672, https://doi.org/10.1029/96GL00265.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schroeder, A. J., J. Basara, J. M. Sheperd, S. Nelson, 2016: Insights into atmospheric contributors to urban flash flooding across the United States using an analysis of rawinsode data and associated calculated parameters. J. Appl. Meteor. Climatol., 55, 313323, https://doi.org/10.1175/JAMC-D-14-0232.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., and R. H. Johnson, 2005: Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Mon. Wea. Rev., 133, 961976, https://doi.org/10.1175/MWR2899.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., and R. H. Johnson, 2006: Characteristics of U.S. extreme rain events during 1999–2003. Wea. Forecasting, 21, 6985, https://doi.org/10.1175/WAF900.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., and R. H. Johnson, 2009: Quasi-stationary, extreme-rain-producing convective systems associated with midlevel cyclonic circulations. Wea. Forecasting, 24, 555574, https://doi.org/10.1175/2008WAF2222173.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., A. J. Clark, M. Xue, and F. Kong, 2013: Factors influencing the development and maintenance of nocturnal heavy-rain-producing convective systems in a storm-scale ensemble. Mon. Wea. Rev., 141, 27782801, https://doi.org/10.1175/MWR-D-12-00239.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shen, S., Y. Mei, and E. M. Anagnostou, 2017: A comprehensive database of flood events in the contiguous United States from 2002 to 2013. Bull. Amer. Meteor. Soc., 98, 14931502, https://doi.org/10.1175/BAMS-D-16-0125.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sukovich, E. M., F. M. Ralph, F. E. Barthold, D. W. Reynolds, and D. R. Novak, 2014: Extreme quantitative precipitation forecast performance at the Weather Prediction Center from 2001 to 2011. Wea. Forecasting, 29, 894911, https://doi.org/10.1175/WAF-D-13-00061.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, G., and T. Eidhammer, 2014: A study of aerosol impacts on clouds and precipitation development in a large winter cyclone. J. Atmos. Sci., 71, 36363658, https://doi.org/10.1175/JAS-D-13-0305.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., K. A. Hoogewind, and S. Lasher-Trapp, 2019: Future changes in hail occurrence in the United States determined through convection-permitting dynamical downscaling. J. Climate, 32, 54935509, https://doi.org/10.1175/JCLI-D-18-0740.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., 1999: Conceptual framework for changes of extremes of the hydrological cycle with climate change. Climatic Change, 42, 327339, https://doi.org/10.1023/A:1005488920935.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 12051218, https://doi.org/10.1175/BAMS-84-9-1205.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van der Wiel, K., S. B. Kapnick, G. A. Vecchi, J. A. Smith, P. C. D. Milly, and L. Jia, 2018: 100-year lower Mississippi floods in a global climate model: Characteristics and future changes. J. Hydrometeor., 19, 15471563, https://doi.org/10.1175/JHM-D-18-0018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Villarini, G., R. Goska, J. A. Smith, and G. A. Vecchi, 2014: North Atlantic tropical cyclones and U.S. flooding. Bull. Amer. Meteor. Soc., 95, 13811388, https://doi.org/10.1175/BAMS-D-13-00060.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, 2004: Image quality assessment: From error visibility to structural similarity. IEEE Trans. Image Process., 13, 600612, https://doi.org/10.1109/TIP.2003.819861.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, J., P. Gentine, S. Zhou, S. C. Sullivan, R. Wang, Y. Zhang, and S. Guo, 2018: Large increase in global storm runoff extremes driven by climate and anthropogenic changes. Nat. Commun., 9, 4389, https://doi.org/10.1038/s41467-018-06765-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 309 309 20
Full Text Views 57 57 9
PDF Downloads 80 80 12

Variations in Flash Flood–Producing Storm Characteristics Associated with Changes in Vertical Velocity in a Future Climate in the Mississippi River Basin

View More View Less
  • 1 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
  • | 2 National Center for Atmospheric Research, Boulder, Colorado
© Get Permissions
Restricted access

Abstract

The Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood–producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood–producing storms in the MRB. Specifically, the variations in flash flood–producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood–producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo–global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood–producing storms in the MRB. While rainfall increases in all flash flood–producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood–producing storms in order to create more resilient communities.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erin Dougherty, doughert@ucar.edu

Abstract

The Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood–producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood–producing storms in the MRB. Specifically, the variations in flash flood–producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood–producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo–global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood–producing storms in the MRB. While rainfall increases in all flash flood–producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood–producing storms in order to create more resilient communities.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erin Dougherty, doughert@ucar.edu
Save