An Evaluation of the Community Land Model (Version 3.5) and Noah Land Surface Models for Temperature and Precipitation Over Nebraska (Central Great Plains): Implications for Agriculture in Simulations of Future Climate Change and Adaptation

  • Jane A. Okalebo
  • Robert J. Oglesby
  • Song Feng
  • Kenneth Hubbard
  • Ayse Kilic
  • Michael Hayes
  • Cynthia Hays
Part of the Climate Change Management book series (CCM)


With increasing evidence of climate change, future decision-making among crop modelers and agronomists will require the inclusion of high-resolution climate predictions from regional climate models as input into agricultural system simulation models to assess the impacts of projected ambient CO2 increases, temperature and general climatic change on crop production. Before they can be implemented in climate adaption studies and decision-support systems, weather variables must be reliable and accurate. This study evaluated weather variables generated from computer simulations using two land surface models, (LSMs) coupled to a regional climate model, namely, Weather Research Forecasting (WRF 3.2). The land surface models tested are the Community Land Surface Model CLM 3.5 and the Noah Land surface model. Ground truth observations from 7 stations in Nebraska from a dry year, a normal year and a wet year (2002, 2005 and 2008 respectively) were used to evaluate the model results. Model results were also compared for their spatial ability to mimic distance-standard error weather variables. Both LSMs performed well in predicting the maximum and minimum temperatures in 2002, 2005 and 2008. Rainfall predictions by both models were not as reliable, based on evaluation for individual stations as well as spatially (state-wide).


Climate change Land surface models Regional climate models 



We would like to acknowledge the use datasets from the High Plains Regional Climate Center weather, NCEP North American Regional Reanalysis datasets and Oregon’s State University’s PRISM dataset. Appreciation is also accorded to all the technical staff and support personnel at NCAR who revise and respond to questions regarding NCL. The authors would also like to thank the anonymous reviewers who critiqued the manuscript to improve it.


  1. Bathke DJ, Oglesby RJ, Rowe CM, Wilhite DA (2014) Understanding and assessing climate change University of Nebraska–Lincoln implications for Nebraska. A synthesis report to support decision making and natural resource management in a changing climate. Available at Accessed 22 Mar 2014
  2. Bonan GB, Levis S, Kergoat L, Oleson KW (2002) Landscapes as patches of plant functional types: an integrating concept for climate and ecosystem models. Glob Biogeochem Cycles 16. doi: 10.1029/2000GB001360
  3. Brown RA, Rosenberg NJ, Hays CJ, Easterling WE, Mearns LO (2000) Potential production and environmental effects of switchgrass and traditional crops under current and greenhouse-altered climate in the central United States: a simulation study. Agric Ecosyst Environ 78:31–47CrossRefGoogle Scholar
  4. Caldwell P (2010) California wintertime precipitation bias in regional and global climate models. J Appl Meteorol Climatol 49(10):2147–2158CrossRefGoogle Scholar
  5. 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
  6. Collins WD, Bitz CM, Blackmon ML, Bonan GB, Bretherton CS, Carton JA, Smith RD (2006) The community climate system model version 3 (CCSM3). J Climate 19(11):2122–2143CrossRefGoogle Scholar
  7. Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33:140–158CrossRefGoogle Scholar
  8. Davis C, Brown B, Bullock R (2006) Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas. Mon Weather Rev 134:1772–1784CrossRefGoogle Scholar
  9. Dickinson RE, Oleson KW, Bonan G, Hoffman F, Thornton P, Vertenstein M, Yang Z-L, Zeng X (2006) The community land model and its climate statistics as a component of the community climate system model. J Climate 19:2302–2324CrossRefGoogle Scholar
  10. Done JM, Leung LR, Davis CA, Kuo B (2005) Simulation of warm season rainfall using WRF regional climate model. In: 6th WRF/15th MM5 users’ workshop, Boulder, CO, USA, June 2005Google Scholar
  11. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46(20):3077–3107CrossRefGoogle Scholar
  12. Duffy PB, Govindasamy B, Taylor K, Wehner M, Lamont A, Thompson S (2003) High resolution simulations of global climate. Part I: Present climate. Clim Dyn 21:371–390CrossRefGoogle Scholar
  13. Easterling WE, Mearns LO, Hays CJ, Marx D (2001) Comparison of agricultural impacts of climate change calculated from high and low resolution climate change scenarios: part II. Accounting for adaptation and CO2 direct effects. Clim Change 51(2):173–197CrossRefGoogle Scholar
  14. Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 108(D22):8851. doi: 10.1029/2002JD003296 CrossRefGoogle Scholar
  15. Evans JP, Oglesby RJ, Lapenta WM (2005) Time series analysis of regional climate model performance. J Geophys Res 110(D4):DO4104. doi: 10.1029/2004JD005406 CrossRefGoogle Scholar
  16. Feng X, Sahoo A, Arsenault K, Houser P, Luo Y, Troy T (2008) The impact of snow model complexity at three CLPX sites. J Hydrometeorol 9:1464–1481CrossRefGoogle Scholar
  17. High Plains Regional Climate Center (HPRCC) (2013) Climate change on the Prairie: a basic guide to climate change in the high plains region—UPDATE. Available at Accessed 16 Jun 2014
  18. Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132(1):103–120CrossRefGoogle Scholar
  19. Hornbeck R, Keskin P (2014) The historically evolving impact of the Ogallala aquifer: agricultural adaptation to groundwater and drought. Am Econ J Appl Econ 6(1):190–219CrossRefGoogle Scholar
  20. Jin J, Miller NL (2010) Improvement of snowpack simulations in a regional climate model. Hydrol Process. doi: 10.1002/hyp.7975 Google Scholar
  21. Jin J, Miller NL, Schlegel N (2010) Sensitivity study of four land surface schemes in the WRF model. Adv MeteorolGoogle Scholar
  22. Kluzek E (2013) CCSM research tools: CLM4.0 user’s guide documentation. Available at Accessed 15 Feb 2014
  23. Ko J, Ahuja LR, Kimball BA, Anapalli S, Ma L, Green TR, Ruane A, Wall GW, Pinter PJ Jr, Bader D (2010) Simulation of free air CO2 enriched wheat growth and interaction with water, nitrogen, and temperature. Agric For Meteorol 150:1331–1346CrossRefGoogle Scholar
  24. Kueppers LM, Snyder MA, Sloan LC, Cayan D, Jin J, Kanamaru H, Kanamitsu M, Miller NL, Tyree M, Du H, Weare B (2008) Seasonal temperature responses to land-use change in the western United States. Global Planet Change 60:250–264CrossRefGoogle Scholar
  25. Mahrt L, Pan H (1984) A two-layer model of soil hydrology. Bound-Lay Meteorol 29(1):1–20CrossRefGoogle Scholar
  26. Mearns LO, Easterling W, Hays C, Marx D (2001) Comparison of agricultural impacts of climate change calculated from high and low resolution climate change scenarios: part I. the uncertainty due to spatial scale. Clim Change 51(2):131–172CrossRefGoogle Scholar
  27. 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 Atmos 102(D14):16663–16682CrossRefGoogle Scholar
  28. Niu X, Easterling W, Hays CJ, Jacobs A, Mearns L (2009) Reliability and input-data induced uncertainty of the EPIC model to estimate climate change on sorghum yields in the U.W. Great Plains. Agric Ecosyst Environ 129(1–3):268–276Google Scholar
  29. Oleson KW, Niu GY, Yang ZL, Lawrence DM, Thornton PE, Lawrence PJ et al (2008) Improvements to the community land model and their impact on the hydrological cycle. J Geophys Res Biogeosci (2005–2012) 113(G1)Google Scholar
  30. Pitman AJ, Henderson-Sellers A, Desborough CE, Yang Z-L, Abramopoulos F, Boone A, Dickinson RE, Gedney N, Koster R, Kowalczyk E, Lettenmaier D, Liang X, Mahfouf J-F, Noilhan J, Polcher J, Qu W, Robock A, Rosenzweig C, Schlosser CA, Shmakin AB, Smith J, Suarez M, Verseghy D, Wetzel P, Wood E, Xue Y (1999) Key results and implications from phase 1(c) of the project for intercomparison of land-surface parameterization schemes. Climate Dynam 15:673–684CrossRefGoogle Scholar
  31. 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 Technical note NCAR/TN-475 + STR, June 2008Google Scholar
  32. Slater AG, Bohn TJ, McCreight JL, Serreze MC, Lettenmaier DP (2007) A multimodel simulation of pan-Arctic hydrology. J Geophys Res 112:G04S45. doi: 10.1029/2006JG000303 CrossRefGoogle Scholar
  33. Stöckli R, Lawrence DM, Niu G-Y, Oleson KW, Thornton PE, Yang Z-L, Bonan GB, Denning AS, Running SW (2008) Use of FLUXNET in the community land model development. J Geophys Res 113:G01025. doi: 10.1029/2007JG000562 Google Scholar
  34. Wei J, Dirmeyer PA, Guo Z, Zhang L, Misra V (2009) How much do different land models matter for climate simulation? Part 1: climatology and variability. J Climate 23:3120–3134CrossRefGoogle Scholar
  35. Wilhite DA (2014) Understanding and assessing climate change: implications for Nebraska. Heurmann Lecture. September 25, 3:30 p.m. Available at Accessed 22 Mar 2015

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jane A. Okalebo
    • 1
  • Robert J. Oglesby
    • 2
    • 3
  • Song Feng
    • 4
  • Kenneth Hubbard
    • 2
  • Ayse Kilic
    • 2
  • Michael Hayes
    • 2
  • Cynthia Hays
    • 2
  1. 1.School of Natural ResourcesUniversity of Nebraska-LincolnLincolnUSA
  2. 2.School of Natural ResourcesUniversity of Nebraska-LincolnLincolnUSA
  3. 3.Earth and Atmospheric SciencesUniversity of Nebraska-LincolnLincolnUSA
  4. 4.Department of GeosciencesUniversity of ArkansasFayettevilleUSA

Personalised recommendations