Climate Dynamics

, Volume 37, Issue 3–4, pp 677–688 | Cite as

Regional climate of hazardous convective weather through high-resolution dynamical downscaling

  • Robert J. TrappEmail author
  • Eric D. Robinson
  • Michael E. Baldwin
  • Noah S. Diffenbaugh
  • Benjamin R. J. Schwedler


We explore the use of high-resolution dynamical downscaling as a means to simulate the regional climatology and variability of hazardous convective-scale weather. Our basic approach differs from a traditional regional climate model application in that it involves a sequence of daily integrations. We use the weather research and forecasting (WRF) model, with global reanalysis data as initial and boundary conditions. Horizontal grid lengths of 4.25 km allow for explicit representation of deep convective storms and hence a compilation of their occurrence statistics over a large portion of the conterminous United States. The resultant 10-year sequence of WRF model integrations yields precipitation that, despite its positive bias, has a diurnal cycle consistent with observations, and otherwise has a realistic geographical distribution. Similarly, the occurrence frequency of short-duration, potentially flooding rainfall compares well to analyses of hourly rain gauge data. Finally, the climatological distribution of hazardous-thunderstorm occurrence is shown to be represented with some degree of skill through a model proxy that relates rotating convective updraft cores to the presence of hail, damaging surface winds, and tornadoes. The results suggest that the proxy occurrences, when coupled with information on the larger-scale atmosphere, could provide guidance on the reliability of trends in the observed occurrences.


Severe thunderstorm Heavy rainfall Dynamical downscaling Reanalysis Weather research and forecasting model 



This research was supported in part by NSF ATM-0756624 (RT, MB, ND, and ER), DOE DE-FG02-08ER64649 (ND), and benefitted from computing resources provided through the NCAR Accelerated Scientific Discovery program and by the Purdue University Rosen Center for Advanced Computing. Dr. David Ahijevych at NCAR provided helpful information regarding the Hovmöller diagrams. Comments made by the two anonymous reviewers helped us clarify and improve our discussion. This is PCCRC Paper #0920.


  1. Ahijevych DA, Carbone RE, Tuttle JD, Trier SB (2005) Radar data and climatological statistics associated with warm season precipitation episodes over the continental U.S. NCAR Tech. Note TN-448+STR, 24 ppGoogle Scholar
  2. Bell GD, Halpert MS, Ropelewski CF, Kousky VE, Douglas AV, Schnell RC, Gelman ME (1999) Climate assessment for 1998. BAMS 80:S1–S48CrossRefGoogle Scholar
  3. Brooks HE, Stensrud DS (2000) Climatology of heavy rain events in the United States from hourly precipitation observations. Mon Weather Rev 128:1194–1201CrossRefGoogle Scholar
  4. Brooks HE, Doswell CA III, Kay MP (2003a) Climatological estimates of local daily tornado probability for the United States. Weather Forecast 18:626–640CrossRefGoogle Scholar
  5. Brooks HE, Lee JW, Craven JP (2003b) The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data. Atmos Res 67:73–94CrossRefGoogle Scholar
  6. Bunkers MJ, Hjelmfelt MR, Smith PL (2006) An observational examination of long-lived supercells. Part I: characteristics, evolution, and demise. Weather Forecast 21:673–688CrossRefGoogle Scholar
  7. Carbone RE, Tuttle JD, Ahijevych DA, Trier SB (2002) Inferences of predictability associated with warm season precipitation episodes. J Atmos Sci 59:2033–2056CrossRefGoogle Scholar
  8. Chen F, Dudhia J (2001) Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: model description and implementation. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  9. Del Genio AD, Yao M-S, Jonas J (2007) Will moist convection be stronger in a warmer climate? Geophys Res Lett 34:L16703. doi: 10.1029/2007GL030525 CrossRefGoogle Scholar
  10. Diffenbaugh NS, Trapp RJ, Brooks HE (2008) Challenges in identifying influences of global warming on tornado activity. Eos Trans 89(53):553–554CrossRefGoogle Scholar
  11. Doswell CA III, Bosart LF (2001) Extratropical synoptic-scale processes and severe convection. In: Doswell CA III (ed) Severe convective storms. American Meteorological Society, Boston, pp 27–69Google Scholar
  12. Doswell CA III, Brooks HE, Maddox RA (1996) Flash flood forecasting: an ingredients-based methodology. Weather Forecast 11:560–581CrossRefGoogle Scholar
  13. Doswell CA III, Brooks HE, Kay MP (2005) Climatological estimates of daily nontornadic severe thunderstorm probability for the United States. Weather Forecast 20:577–595CrossRefGoogle Scholar
  14. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107CrossRefGoogle Scholar
  15. Duffy PB, Govindasamy B (2003) High resolution simulations of global climate. Part 1: simulations of the present climate. Clim Dyn 21:371–390CrossRefGoogle Scholar
  16. Ebert E (2008) Fuzzy verification of high-resolution gridded forecasts: a review and proposed framework. Meteorol Appl 15:51–64. doi: 10.1002/met.25 CrossRefGoogle Scholar
  17. Gallus WA, Snook NA, Johnson EV (2008) Spring and summer severe weather reports over the Midwest as a function of convective mode: a preliminary study. Weather Forecast 23:101–113CrossRefGoogle Scholar
  18. Giorgi F, Mearns LO (1999) Introduction to special section: regional climate modeling revisited. J Geophys Res 104(D6):6335–6352CrossRefGoogle Scholar
  19. Hitchens N, Trapp RJ, Baldwin ME, Gluhovsky A (2010) Characterizing sub-diurnal extreme precipitation in the Midwestern United States. J Hydrometeorol. doi: 10.1175/2009JHM1129.1
  20. Hong SY, Kalnay E (2002) The 1998 Oklahoma-Texas drought: mechanistic experiments with NCEP global and regional models. J Clim 15:945–963CrossRefGoogle Scholar
  21. Hong SY, Lim JOJ (2006) The WRF single-moment 6-class microphysics scheme (WSM6). J Korean Meteor Soc 42:129–151Google Scholar
  22. Iacono MJ, Mlawer EJ, Clough SA, Morcrette JJ (2000) Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR Community Climate Model, CCM3. J Geophys Res 105:14873–14890CrossRefGoogle Scholar
  23. Intergovernmental Panel on Climate Change (2007) Climate change 2007: the physical science basis. Cambridge University Press, CambridgeGoogle Scholar
  24. Kain JS, Weiss SJ, Levit JJ, Baldwin ME, Bright DR (2006) Examination of convection-allowing configurations of the WRF model for the prediction of severe convective weather: the SPC/NSSL spring program 2004. Weather Forecast 21:167–181CrossRefGoogle Scholar
  25. Kain JS et al (2008) Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Weather Forecast 23:931–952Google Scholar
  26. Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. BAMS 77:437–471CrossRefGoogle Scholar
  27. Kelly DL, Schaefer JT, McNulty RP, Doswell CA III, Abbey RF Jr (1978) An augmented tornado climatology. Mon Weather Rev 106:1172–1183CrossRefGoogle Scholar
  28. Kelly DL, Schaefer JT, Doswell CA III (1985) Climatology of nontornadic severe thunderstorm events in the United States. Mon Weather Rev 113:1997–2014CrossRefGoogle Scholar
  29. Lorenz EN (1969) The predictability of a flow which possesses many scales of motion. Tellus 3:289–307CrossRefGoogle Scholar
  30. Mellor GL, Yamada T (1982) Development of a turbulence closure model for geophysical fluid problems. Rev Geophys Space Phys 20:851–875CrossRefGoogle Scholar
  31. Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16663–16682CrossRefGoogle Scholar
  32. NCDC (2009) NCDC storm event database.
  33. Pielke RA, Dalu G, Snook JS, Lee TJ, Kittel TGF (1991) Nonlinear influence of mesoscale land use on weather and climate. J Clim 4:1053–1069CrossRefGoogle Scholar
  34. Roberts NM, Lean HW (2008) Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon Weather Rev 136:78–97CrossRefGoogle Scholar
  35. Skamarock WC (2004) Evaluating mesoscale NWP models using kinetic energy spectra. Mon Weather Rev 132:3019–3032CrossRefGoogle Scholar
  36. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang X-Y, Wang W, Powers JG (2008) A description of the advanced research WRF version 3. NCAR Tech. Note TN-475+STR, 113 ppGoogle Scholar
  37. Trapp RJ, Tessendorf SA, Savageau EG, Brooks HE (2005) Tornadoes in squall lines and bow echoes. Part I: climatological distribution. Weather Forecast 40:23–34CrossRefGoogle Scholar
  38. Trapp RJ, Diffenbaugh NS, Brooks HE, Baldwin ME, Robinson ED, Pal JS (2007a) Changes in severe thunderstorm frequency during the 21st century due to anthropogenically enhanced global radiative forcing. Proc Natl Acad Sci 104:19719–19723. doi: 10.1073/pnas.0705494104 CrossRefGoogle Scholar
  39. Trapp RJ, Halvorson B, Diffenbaugh NS (2007b) Telescoping, multi-model approaches to evaluate extreme convective weather under future climates. J Geophys Res 112:D20109. doi: 10.1029/2006JD008345 CrossRefGoogle Scholar
  40. Trapp RJ, Diffenbaugh NS, Gluhovsky A (2009) Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations. Geophys Res Lett 36:L01703. doi: 10.1029/2008GL036203 CrossRefGoogle Scholar
  41. US Global Change Research Program (2009) Global climate change impacts in the United States. Cambridge University PressGoogle Scholar
  42. Van Klooster SL, Roebber PJ (2009) Surface-based convective potential in the contiguous United States in a business-as-usual future climate. J Clim 22:3317–3330CrossRefGoogle Scholar
  43. Walker MD, Diffenbaugh NS (2009) Evaluation of high-resolution simulations of daily-scale temperature and precipitation over the United States. Clim Dyn. doi: 10.1007/s00382-009-0603-y
  44. Weaver CP, Avissar R (2001) Atmospheric disturbances caused by human modification of the landscape. BAMS 82:269–281CrossRefGoogle Scholar
  45. Weisman ML, Klemp JB (1982) The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon Weather Rev 110:504–520CrossRefGoogle Scholar
  46. Weisman ML, Trapp RJ (2003) Low-level mesovortices within squall lines and bow echoes. Part I: overview and dependence on environmental shear. Mon Weather Rev 131:2779–2803CrossRefGoogle Scholar
  47. Weisman ML, Skamarock WC, Klemp JB (1997) The resolution dependence of explicitly modeled convective systems. Mon Weather Rev 125:527–548CrossRefGoogle Scholar
  48. Weisman ML, Davis C, Wang W, Manning KW, Klemp JB (2008) Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Weather Forecast 23:407–437CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Robert J. Trapp
    • 1
    Email author
  • Eric D. Robinson
    • 1
  • Michael E. Baldwin
    • 1
  • Noah S. Diffenbaugh
    • 2
  • Benjamin R. J. Schwedler
    • 1
  1. 1.Department of Earth and Atmospheric Sciences, Purdue Climate Change Research CenterPurdue UniversityWest LafayetteUSA
  2. 2.Department of Environmental Earth System ScienceWoods Institute for the Environment Stanford UniversityStanfordUSA

Personalised recommendations