Climate Dynamics

, Volume 40, Issue 3–4, pp 805–821 | Cite as

Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation

Article

Abstract

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.

Keywords

Downscaling Regional climate model Ensemble Stochastic weather generator Watershed 

Supplementary material

382_2012_1490_MOESM1_ESM.doc (1.1 mb)
Supplementary material 1 (DOC 1,096 kb)

References

  1. Abler D, Shortle J, Carmichael J, Horan R (2002) Climate change, agriculture, and water quality in the Chesapeake Bay Region. Clim Change 55:339–359CrossRefGoogle Scholar
  2. Borah DK, Bera M (2004) Watershed-scale hydrologic and nonpoint-source pollution models: review of applications. Trans ASAE 47:789–803Google Scholar
  3. Chen B, Jing L, Zhang BY, Liu S (2011a) Wetland monitoring, characterization and modelling under changing climate in the Canadian subarctic. J Environ Inform 18:55–64CrossRefGoogle Scholar
  4. Chen J, Brissette FP, Poulin A, Leconte R (2011b) Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed. Water Resour Res 47, W12509. doi:10.1029/2011WR010602
  5. Christensen JH, Raisanen J, Iversen T, Bjorge D, Christensen OB, Rummukainen M (2001) A synthesis of regional climate change simulations—a Scandinavian perspective. Geophys Res Lett 28:1003–1006CrossRefGoogle Scholar
  6. Christensen JH, Kjellstrom E, Giorgi F, Lenderink G, Rummukainen M (2010) Weight assignment in regional climate models. Clim Res 44:179–194CrossRefGoogle Scholar
  7. Coppola E, Giorgi F, Rauscher SA, Piani C (2010) Model weighting based on mesoscale structures in precipitation and temperature in an ensemble of regional climate models. Clim Res 44:121–134CrossRefGoogle Scholar
  8. Deque M, Somot S (2010) Weighted frequency distributions express modelling uncertainties in the ENSEMBLES regional climate experiments. Clim Res 44:195–209CrossRefGoogle Scholar
  9. Deque M, Rowell DP, Luthi D, Giorgi F, Christensen JH, Rockel B, Jacob D, Kjellstrom E, de Castro M, van den Hurk B (2007) An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Clim Change 81:53–70CrossRefGoogle Scholar
  10. Diez E, Primo C, Garcia-Moya JA, Gutierrez JM, Orfila B (2005) Statistical and dynamical downscaling of precipitation over Spain from DEMETER seasonal forecasts. Tellus Ser A Dyn Meteorol Oceanogr 57:409–423CrossRefGoogle Scholar
  11. Feng JM, Lee DK, Fu CB, Tang JP, Sato Y, Kato H, McGregor JL, Mabuchi K (2011) Comparison of four ensemble methods combining regional climate simulations over Asia. Meteorol Atmos Phys 111:41–53CrossRefGoogle Scholar
  12. Foley AM (2010) Uncertainty in regional climate modelling: a review. Prog Phys Geogr 34:647–670CrossRefGoogle Scholar
  13. Fowler HJ, Ekstrom M (2009) Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes. Int J Climatol 29:385–416CrossRefGoogle Scholar
  14. Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578CrossRefGoogle Scholar
  15. Giorgi F, Mearns LO (2002) Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J Clim 15:1141–1158CrossRefGoogle Scholar
  16. Gleckler PJ, Taylor KE, Doutriaux C (2008) Performance metrics for climate models. J Geophys Res Atmos 113. D06104. doi:10.1029/2007JD008972
  17. Gutowski WJ Jr, Arritt RW, Kawazoe S, Flory DM, Takle ES, Biner S, Caya D, Jones RG, Laprise R, Leung LR, Mearns LO, Moufouma-Okia W, Nunes AMB, Qian Y, Roads JO, Sloan LC, Snyder MA (2010) Regional extreme monthly precipitation simulated by NARCCAP RCMs. J Hydrometeorol 11:1373–1379CrossRefGoogle Scholar
  18. Hellstrom C, Chen DL (2003) Statistical downscaling based on dynamically downscaled predictors: application to monthly precipitation in Sweden. Adv Atmos Sci 20:951–958CrossRefGoogle Scholar
  19. Huang YT, Liu L (2008) A hybrid perturbation and morris approach for identifying sensitive parameters in surface water quality models. J Environ Inform 12:150–159CrossRefGoogle Scholar
  20. Huang GH, Cohen SJ, Yin YY, Bass B (1996) Incorporation of inexact dynamic optimization with fuzzy relation analysis for integrated climate change impact study. J Environ Manage 48:45–68CrossRefGoogle Scholar
  21. Huang GH, Cohen SJ, Yin YY, Bass B (1998) Land resources adaptation planning under changing climate—a study for the Mackenzie Basin. Resour Conserv Recycl 24:95–119CrossRefGoogle Scholar
  22. Hutchinson MF, McKenney DW, Lawrence K, Pedlar JH, Hopkinson RF, Milewska E, Papadopol P (2009) Development and testing of Canada-wide interpolated spatial models of daily minimum-maximum temperature and precipitation for 1961–2003. J Appl Meteorol Climatol 48:725–741CrossRefGoogle Scholar
  23. IPCC (2007) Climate change 2007—synthesis report. In: Intergovernmental panel on climate change, Cambridge, UKGoogle Scholar
  24. Jing L, Chen B (2011) Field investigation and hydrological modelling of a subarctic wetland—the deer river watershed. J Environ Inform 17:36–45CrossRefGoogle Scholar
  25. Kim YO, Lee JK (2010) Addressing heterogeneities in climate change studies for water resources in Korea. Curr Sci 98(8):1077–1083Google Scholar
  26. Kite G (2001) Modelling the Mekong: hydrological simulation for environmental impact studies. J Hydrol 253(1–4):1–13Google Scholar
  27. Lambert SJ, Boer GJ (2001) CMIP1 evaluation and intercomparison of coupled climate models. Clim Dyn 17:83–106CrossRefGoogle Scholar
  28. Lehner B, Doll P, Alcamo J, Henrichs T, Kaspar F (2006) Estimating the impact of global change on flood and drought risks in Europe: a continental, integrated analysis. Clim Change 75:273–299CrossRefGoogle Scholar
  29. Lorenz P, Jacob D (2010) Validation of temperature trends in the ENSEMBLES regional climate model runs driven by ERA40. Clim Res 44:167–177CrossRefGoogle Scholar
  30. Mao XF, Yang ZF, Chen B (2011) Network analysis and comparative studies on baiyangdian and okefenokee wetland systems in China and US. J Environ Inform 18:46–54CrossRefGoogle Scholar
  31. Maurer EP (2007) Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California, under two emissions scenarios. Clim Change 82:309–325CrossRefGoogle Scholar
  32. McGinn SM (2010) Weather and climate patterns in Canada’s prairie grasslands. In: Shorthouse JD, Floate KD (eds) Arthropods of Canadian grasslands (vol 1): ecology and interactions in grassland habitats. Biological Survey of CanadaGoogle Scholar
  33. McKenney DW, Hutchinson MF, Papadopol P, Lawrence K, Pedlar J, Campbell K, Milewska E, Hopkinson RF, Price D, Owen T (2011) Customized spatial climate models for North America. Bull Am Meteorol Soc 92:1611–1622CrossRefGoogle Scholar
  34. Mearns L, Gutowski W, Jones R, Leung R, McGinnis S, Nunes A, Qian Y (2009) A regional climate change assessment program for North America. Eos Trans AGU 90(36):311. doi:10.1029/2009EO360002 Google Scholar
  35. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset—a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394CrossRefGoogle Scholar
  36. Nakicenovic N, Swart R (2000) Special report on emissions scenarios: a special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, p 612Google Scholar
  37. Nasiri F, Huang G (2008) A fuzzy decision aid model for environmental performance assessment in waste recycling. Environ Model Softw 23:677–689CrossRefGoogle Scholar
  38. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and water assessment tool: theoretical documentation (version 2005). In: Agricultural Research Service, Temple, TexasGoogle Scholar
  39. Palmer MA, Liermann CAR, Nilsson C, Florke M, Alcamo J, Lake PS, Bond N (2008) Climate change and the world’s river basins: anticipating management options. Front Ecol Environ 6:81–89CrossRefGoogle Scholar
  40. 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 20:4356–4376CrossRefGoogle Scholar
  41. Pham SV, Leavitt PR, McGowan S, Peres-Neto P (2008) Spatial variability of climate and land-use effects on lakes of the northern Great Plains. Limnol Oceanogr 53:728–742CrossRefGoogle Scholar
  42. Pitman AJ, Perkins SE (2008) Regional projections of future seasonal and annual changes in rainfall and temperature over Australia based on skill-selected AR(4) models. Earth Interact 12:1–51CrossRefGoogle Scholar
  43. Raisanen J, Ruokolainen L, Ylhaisi J (2010) Weighting of model results for improving best estimates of climate change. Clim Dyn 35:407–422CrossRefGoogle Scholar
  44. Sanchez E, Gallardo C, Gaertner MA, Arribas A, Castro M (2004) Future climate extreme events in the mediterranean simulated by a regional climate model: a first approach. Glob Planet Change 44:163–180CrossRefGoogle Scholar
  45. Sanchez E, Romera R, Gaertner MA, Gallardo C, Castro M (2009) A weighting proposal for an ensemble of regional climate models over Europe driven by 1961–2000 ERA40 based on monthly precipitation probability density functions. Atmos Sci Lett 10:241–248Google Scholar
  46. Semenov MA, Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Clim Change 35:397–414CrossRefGoogle Scholar
  47. Semenov MA, Brooks RJ, Barrow EM, Richardson CW (1998) Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Clim Res 10(2):95–107CrossRefGoogle Scholar
  48. Shrestha RR, Dibike YB, Prowse TD (2012) Modeling climate change impacts on hydrology and nutrient loading in the upper Assiniboine catchment. J Am Water Resour Assoc 48:74–89CrossRefGoogle Scholar
  49. Sobolowski S, Pavelsky T (2012) Evaluation of present and future North American Regional Climate Change Assessment Program (NARCCAP) regional climate simulations over the southeast United States. J Geophys Res Atmos 117:D01101CrossRefGoogle Scholar
  50. Toews MW, Allen DM (2009) Evaluating different GCMs for predicting spatial recharge in an irrigated arid region. J Hydrol 374:265–281CrossRefGoogle Scholar
  51. Tebaldi C, Smith, RL, Nychka D, Mearns LO (2005) Quantifying uncertainty in projections of regional climate change: a Bayesian approach to the analysis of multimodel ensembles. J Clim 18(10):1524–1540Google Scholar
  52. Vidal JP, Wade SD (2008) Multimodel projections of catchment-scale precipitation regime. Journal of Hydrol 353(1-2):143–158Google Scholar
  53. Wang S-Y, Gillies RR, Takle ES, Gutowski WJ Jr (2009) Evaluation of precipitation in the intermountain region as simulated by the NARCCAP regional climate models. Geophys Res Lett 36, L11704. doi:10.1029/2009GL037930
  54. Weigel AP, Knutti R, Liniger MA, Appenzeller C (2010) Risks of model weighting in multimodel climate projections. J Clim 23:4175–4191CrossRefGoogle Scholar
  55. Wilby RL, Hay LE, Gutowski WJ, Arritt RW, Takle ES, Pan ZT, Leavesley GH, Clark MP (2000) Hydrological responses to dynamically and statistically downscaled climate model output. Geophys Res Lett 27:1199–1202CrossRefGoogle Scholar
  56. Williams, JR (1995) The EPIC model. In: Singh VP (ed), Computer models of watershed hydrology. Water Resources Publications, p 1130Google Scholar
  57. Wood AW, Leung LR, Sridhar V, Lettenmaier DP (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62:189–216CrossRefGoogle Scholar
  58. Xu Y, Gao XJ, Giorgi F (2010) Upgrades to the reliability ensemble averaging method for producing probabilistic climate-change projections. Clim Res 41:61–81CrossRefGoogle Scholar
  59. Zhang H, Huang GH, Wang D, Zhang X (2011a) Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering. Adv Water Resour 34:1292–1303CrossRefGoogle Scholar
  60. Zhang H, Huang GH, Wang D, Zhang X (2011b) Uncertainty assessment of climate change impacts on the hydrology of small prairie wetlands. J Hydrol 396:94–103CrossRefGoogle Scholar
  61. Zhang H, Huang GH, Wang D, Zhang X, Li G, An C, Cui Z, Liao R, Nie X (2012) An integrated multi-level watershed-reservoir modeling system for examining hydrological and biogeochemical processes in small prairie watersheds. Water Res 46:1207–1224CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Institute for Energy, Environment and Sustainable CommunitiesUniversity of ReginaReginaCanada

Personalised recommendations