Simulating precipitation and temperature in the Lake Champlain basin using a regional climate model: limitations and uncertainties

  • Huanping HuangEmail author
  • Jonathan M. Winter
  • Erich C. Osterberg
  • Janel Hanrahan
  • Cindy L. Bruyère
  • Patrick Clemins
  • Brian Beckage


The Lake Champlain Basin has socioeconomic and ecological significance for the Northeastern United States and Quebec, Canada. Temperatures and extreme precipitation events have been increasing across this region over the past three decades. Accurate, high-resolution climate simulations are critical to assessing potential climate change risk in the Lake Champlain Basin. We evaluate the performance of a regional climate model, the Weather Research and Forecasting (WRF) model, to downscale ERA-Interim reanalysis data to 4 km for the Lake Champlain Basin. Specifically, we compare an ensemble of five WRF experiments with different physics configurations using a one-way, triple-nested domain (36, 12, and 4 km) over three 5-year periods (1980–1984, 1995–1999, and 2010–2014) to Daymet, a gridded observational dataset. We find that WRF simulations of the Lake Champlain Basin generally reproduce the observed temperature and precipitation seasonal cycles, but have cold and wet biases. The simulation of mean temperature by WRF is most sensitive to the choice of radiation scheme, while the simulation of mean precipitation is most sensitive to the choice of radiation, cumulus, and microphysics scheme. We find that turning the cumulus scheme on improves the simulation of the precipitation seasonal cycle at a 4 km resolution, but also substantially enhances the wet bias. Using a coarser resolution (36 km) produces smaller regionally averaged precipitation biases, but not improved correlations between simulated and observed monthly precipitation. Both spatial resolution and turning the cumulus scheme off have minor effects on simulated temperature.


Regional climate modeling WRF Model evaluation Extreme events Lake Champlain Basin Physics parameterization 



This work is funded by the Vermont Established Program for Stimulating Competitive Research (NSF Award OIA 1556770). We thank the WRF Help team and Dartmouth Research Computing for their support configuring and running the WRF simulations. Finally, we appreciate the thoughtful feedback of our editor and reviewers.

Supplementary material

382_2019_4987_MOESM1_ESM.docx (1.9 mb)
Supplementary material 1 (DOCX 1911 kb)


  1. Annor T, Lamptey B, Wagner S et al (2018) High-resolution long-term WRF climate simulations over Volta Basin. Part 1: validation analysis for temperature and precipitation. Theor Appl Climatol 133:829–849. CrossRefGoogle Scholar
  2. Beranger B, Duong T, Perkins-Kirkpatrick SE, Sisson SA (2016) Exploratory data analysis for moderate extreme values using non-parametric kernel methodsGoogle Scholar
  3. Bowman A, Azzalini A (1997) Applied smoothing techniques for data analysis. Oxford University Press, New YorkGoogle Scholar
  4. Bruyère CL, Rasmussen R, Gutmann E, et al (2017) Impact of climate change on Gulf of Mexico hurricanes. NCAR Technical Note NCAR/TN‐535 + STR.
  5. Bukovsky MS, Karoly DJ, Bukovsky MS, Karoly DJ (2011) A regional modeling study of climate change impacts on warm-season precipitation in the Central United States. J Clim 24:1985–2002. CrossRefGoogle Scholar
  6. Castle SS, Howe EA, Bird EL, Howland WG (2013) Flood resilience in the Lake Champlain basin and Upper Richelieu river. Lake Champlain Basin Program. Accessed 4 Oct 2018
  7. de Elía R, Caya D, Côté H et al (2008) Evaluation of uncertainties in the CRCM-simulated North American climate. Clim Dyn 30:113–132. CrossRefGoogle Scholar
  8. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. CrossRefGoogle Scholar
  9. Deng A, Stauffer DR, Deng A, Stauffer DR (2006) On improving 4-km mesoscale model simulations. J Appl Meteorol Climatol 45:361–381. CrossRefGoogle Scholar
  10. Easterling DR, Kunkel KE, Arnold JR, et al (2017) Chapter 7: precipitation change in the United States. In: Wuebbles DJ, Fahey DW, Hibbard KA, Dokken DJ, Stewart BC, Maycock TK (eds) Climate science special report: fourth national climate assessment, Volume 1. US Global Change Research Program, Washington, DC, pp 207–230.
  11. European Centre for Medium-Range Weather Forecasts (2009) ERA-Interim Project. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Accessed 27 June 2017
  12. Fan F, Bradley RS, Rawlins MA (2014) Climate change in the northeastern US: regional climate model validation and climate change projections. Clim Dyn 43:145–161. CrossRefGoogle Scholar
  13. Fischer EM, Beyerle U, Knutti R (2013) Robust spatially aggregated projections of climate extremes. Nat Clim Chang 3:1033–1038. CrossRefGoogle Scholar
  14. Frei A, Kunkel KE, Matonse A (2015) The seasonal nature of extreme hydrological events in the northeastern United States. J Hydrometeorol 16:2065–2085. CrossRefGoogle Scholar
  15. Frich P, Alexander L, Della-Marta P et al (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19:193–212. CrossRefGoogle Scholar
  16. Gao Y, Leung LR, Zhao C, Hagos S (2017) Sensitivity of US summer precipitation to model resolution and convective parameterizations across gray zone resolutions. J Geophys Res Atmos 122:2714–2733. CrossRefGoogle Scholar
  17. Giorgi F, Bi X (2000) A study of internal variability of a regional climate model. J Geophys Res Atmos 105:29503–29521. CrossRefGoogle Scholar
  18. Giorgi F, Gutowski WJ (2015) Regional dynamical downscaling and the CORDEX initiative. Annu Rev Environ Resour 40:467–490. CrossRefGoogle Scholar
  19. Giorgi F, Mearns LO (1999) Introduction to special section: regional climate modeling revisited. J Geophys Res Atmos 104:6335–6352. CrossRefGoogle Scholar
  20. Guilbert J, Beckage B, Winter JM et al (2014) Impacts of projected climate change over the Lake Champlain basin in Vermont. J Appl Meteorol Climatol 53:1861–1875. CrossRefGoogle Scholar
  21. Han J-Y, Hong S-Y (2018) Precipitation forecast experiments using the weather research and forecasting (WRF) model at gray-zone resolutions. Weather Forecast 33:1605–1616. CrossRefGoogle Scholar
  22. Hong S-Y, Dudhia J, Hong S-Y, Dudhia J (2012) Next-generation numerical weather prediction: bridging parameterization, explicit clouds, and large eddies. Bull Am Meteorol Soc 93:ES6–ES9. Scholar
  23. Horton R, Yohe G, Easterling W, et al (2014). Chapter 16: Northeast. In: Melillo JM, Richmond TC, Yohe GW (eds.) Climate change impacts in the united states: the third national climate assessment. US Global Change Research Program, Washington, DC, pp 371–395.
  24. Huang H, Winter JM, Osterberg EC et al (2017) Total and extreme precipitation changes over the Northeastern United States. J Hydrometeorol. CrossRefGoogle Scholar
  25. Huang H, Winter JM, Osterberg EC (2018) Mechanisms of abrupt extreme precipitation change over the Northeastern United States. J Geophys Res Atmos. CrossRefGoogle Scholar
  26. Ji L, Senay GB, Verdin JP et al (2015) Evaluation of the global land data assimilation system (GLDAS) air temperature data products. J Hydrometeorol 16:2463–2480. CrossRefGoogle Scholar
  27. Karki R, ul Hasson S, Gerlitz L et al (2017) Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas. Earth Syst Dyn 8:507–528. CrossRefGoogle Scholar
  28. Katragkou E, García-Díez M, Vautard R et al (2015) Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble. Geosci Model Dev 8:603–618. CrossRefGoogle Scholar
  29. Kim T-W, Valdés JB, Yoo C (2003) Nonparametric approach for estimating return periods of droughts in arid regions. J Hydrol Eng 8:237–246. CrossRefGoogle Scholar
  30. Kim J, Guan B, Waliser DE et al (2018) Winter precipitation characteristics in western US related to atmospheric river landfalls: observations and model evaluations. Clim Dyn 50:231–248. CrossRefGoogle Scholar
  31. Lake Champlain Basin Program (2018) Lake and basin facts. Lake Champlain Basin Program. Accessed 4 Oct 2018
  32. Li R, Jin J, Wang S-Y, Gillies RR (2015) Significant impacts of radiation physics in the weather research and forecasting model on the precipitation and dynamics of the West African Monsoon. Clim Dyn 44:1583–1594. CrossRefGoogle Scholar
  33. Liu C, Ikeda K, Rasmussen R et al (2017) Continental-scale convection-permitting modeling of the current and future climate of North America. Clim Dyn 49:71–95. CrossRefGoogle Scholar
  34. Livneh B, Bohn TJ, Pierce DW et al (2015) A spatially comprehensive, hydrometeorological data set for Mexico, the US, and Southern Canada 1950–2013. Sci Data 2:150042. CrossRefGoogle Scholar
  35. Loikith PC, Waliser DE, Kim J, Ferraro R (2018) Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts. Clim Dyn 50:3711–3727. CrossRefGoogle Scholar
  36. Lucas-Picher P, Caya D, de Elía R, Laprise R (2008) Investigation of regional climate models’ internal variability with a ten-member ensemble of 10-year simulations over a large domain. Clim Dyn 31:927–940. CrossRefGoogle Scholar
  37. Mearns LO, Gutowski W, Jones R et al (2009) A regional climate change assessment program for North America. EOS Trans Am Geophys Union 90:311. CrossRefGoogle Scholar
  38. Mearns LO, Sain S, Leung LR et al (2013) Climate change projections of the North American regional climate change assessment program (NARCCAP). Clim Change 120:965–975. CrossRefGoogle Scholar
  39. Medalie L, Olson SA (2013) High-water marks from flooding in Lake Champlain from April through June 2011 and Tropical Storm Irene in August 2011 in Vermont. U.S. Geological Survey. Accessed 4 Oct 2018
  40. Newman AJ, Clark MP, Craig J et al (2015) Gridded Ensemble Precipitation and Temperature Estimates for the Contiguous United States. J Hydrometeorol 16:2481–2500. CrossRefGoogle Scholar
  41. O’Brien TA, Sloan LC, Snyder MA (2011) Can ensembles of regional climate model simulations improve results from sensitivity studies? Clim Dyn 37:1111–1118. CrossRefGoogle Scholar
  42. Perkins SE, Pitman AJ, Holbrook NJ, McAneney J (2007) Evaluation of the AR4 climate Models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J Clim 20:4356–4376. CrossRefGoogle Scholar
  43. Peterson TC, Heim RR, Hirsch R et al (2013) Monitoring and understanding changes in heat waves, cold waves, floods, and droughts in the united states: state of knowledge. Bull Am Meteorol Soc 94:821–834. CrossRefGoogle Scholar
  44. Prein AF, Holland GJ, Rasmussen RM et al (2016) Running dry: the U.S. Southwest’s drift into a drier climate state. Geophys Res Lett 43:1272–1279. CrossRefGoogle Scholar
  45. Rawlins MA, Bradley RS, Diaz HF (2012) Assessment of regional climate model simulation estimates over the northeast United States. J Geophys Res Atmos. CrossRefGoogle Scholar
  46. Skamarock WC, Klemp JB, Dudhia J, et al (2008) A description of the advanced research WRF version 3. NCAR Technical Note NCAR/TN-475 + STR.
  47. Solman SA, Pessacg NL (2012) Evaluating uncertainties in regional climate simulations over South America at the seasonal scale. Clim Dyn 39:59–76. CrossRefGoogle Scholar
  48. Suro TP, Roland MA, Kiah RG (2015) Flooding in the Northeastern United States, 2011. U.S. Geological Survey Professional Paper 1821.
  49. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106:7183–7192. CrossRefGoogle Scholar
  50. Thornton PE, Running SW, White MA (1997) Generating surfaces of daily meteorological variables over large regions of complex terrain. J Hydrol 190:214–251. CrossRefGoogle Scholar
  51. Thornton PE, Thornton MM, Mayer BW, et al (2016) Daymet: daily surface weather data on a 1-km grid for North America, version 3. ORNL DAAC, Oak Ridge. Accessed 20 October 2017
  52. Walsh J, Wuebbles D, Hayhoe K et al (2014). Chapter 2: Our Changing Climate. In Melillo JM, Richmond TC, Yohe GW (eds.) Climate change impacts in the United States: The Third national climate assessment. U.S. Global Change Research Program, Washington, DC, pp 19–67.
  53. Wang W, Bruyère C, Duda M et al (2016) WRF ARW-version 3 modelling system user’s guide. National Center for Atmospheric Research, BoulderGoogle Scholar
  54. Wootten A, Bowden JH, Boyles R et al (2016) The sensitivity of WRF downscaled precipitation in puerto rico to cumulus parameterization and interior grid nudging. J Appl Meteorol Climatol 55:2263–2281. CrossRefGoogle Scholar
  55. Zittis G, Bruggeman A, Camera C et al (2017) The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean. Atmos Res 191:20–33. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Earth SciencesDartmouth CollegeHanoverUSA
  2. 2.Department of GeographyDartmouth CollegeHanoverUSA
  3. 3.Department of Atmospheric SciencesNorthern Vermont University–LyndonLyndonvilleUSA
  4. 4.National Center for Atmospheric ResearchBoulderUSA
  5. 5.Environmental Sciences and ManagementNorth-West UniversityPotchefstroomSouth Africa
  6. 6.Department of Plant BiologyUniversity of VermontBurlingtonUSA
  7. 7.Department of Computer ScienceUniversity of VermontBurlingtonUSA

Personalised recommendations