An appraisal of downscaling methods used in climate change research

Wiley Interdisciplinary Reviews: Climate Change

Volumn 6, Issue 3, 2015, Pages 301-319

  Ekström, Marie ^a   Grose, Michael R ^a   Whetton, Penny H ^a  

^a CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE MODELS; RISK ASSESSMENT; TRANSLATION (LANGUAGES);

DOWNSCALING METHODS; GLOBAL CLIMATE MODEL; GLOBAL CLIMATE MODEL SIMULATIONS; REGIONAL CLIMATE; REGIONAL CLIMATE CHANGES; REGIONAL RISK ASSESSMENT; SCALE PROPERTIES; SPATIAL RESOLUTION;

CLIMATE CHANGE;

CLIMATE CHANGE; CLIMATE MODELING; COMPUTER SIMULATION; DOWNSCALING; GLOBAL CLIMATE; SPATIAL RESOLUTION; VULNERABILITY;

EID: 84926507520     PISSN: 17577780     EISSN: 17577799     Source Type: Journal    
DOI: 10.1002/wcc.339     Document Type: Review

References (126)

1. Barsugli JJ, Guentchev G, Horton RM, Wood A, Mearns LO, Liang X-Z, Winkler JA, Dixon K, Hayhoe K, Rood RB, et al. The practitioner's dilemma: how to assess the credibility of downscaled climate projections. Eos Trans Amer Geophys Union 2013, 94:424-425.
2. Wilby R, Troni J, Biot Y, Tedd L, Hewitson B, Smith D, Sutton R. A review of climate risk information for adaptation and development planning. Int J Climatol 2009, 29:1193-1215.
3. Ekström M, Kuruppu N, Wilby RL, Fowler HJ, Chiew FHS, Dessai S, Young WJ. Examination of climate risk using a modified uncertainty matrix framework-applications in the water sector. Glob Environ Chang 2013, 23:115-129.
4. Giorgi F. Uncertainties in climate change projections, from the global to the regional scale. EPJ Web of conferences 2010, 9:115-129. doi:http://dx.doi.org/10.1051/epjconf/201009009.
5. Whetton P, Hennessy K, Clarke J, McInnes K, Kent D. Use of representative climate futures in impact and adaptation assessment. Clim Change 2012, 115:433-442.
6. Hulme M, Dessai S, Lorenzoni I, Nelson DR. Unstable climates: exploring the statistical and social constructions of 'normal' climate. Geoforum 2009, 40:197-206.
7. IPCC-TGICA. General guidelines on the use of scenario data for climate impact and adaptation assessment. Prepared by T.R. Carter on behalf of the Intergovernmental Panel on Climate Change, Task Group on Data and Scenario Support for Impact and Climate Assessment. 2007, Vol. 2. Available at: http://www.ipcc-data.org/guidelines/TGICA_guidance:sdciaa_v2_final.pdf. (Accessed April 13, 2011).
8. Harris RMB, Grose MR, Lee G, Bindoff NL, Porfirio LL, Fox-Hughes P. Climate projections for ecologists. WIREs Clim Change 2014, 5:621-637.
9. Knutti R, Allen MR, Friedlingstein P, Gregory JM, Hegerl GC, Meehl GA, Meinshausen M, Murphy JM, Plattner GK, Raper SCB, et al. A review of uncertainties in global temperature projections over the twenty-first century. J Clim 2008, 21:2651-2663.
10. IPCC. Appendix 1: emissions scenarios from the response strategies working group of the Intergovernmental Panel on Climate Change. In: Houghton JT, Jenkins GJ, Ephraums JJ, eds. Climate Change: The IPCC Scientific Assessment (1990) Report prepared for Intergovernmental Panel on Climate Change by Working Group I. Cambridge, UK: Cambridge University Press; 1990, 1.
11. IPCC. Climate change: the IPCC Scientific Assessment (1990). In: Report Prepared for Intergovernmental Panel on Climate Change by Working Group I. Cambridge, UK: Cambridge University Press; 1990.
12. Leggett J, Pepper WJ, Swart RJ. Section A3: emissions scenarios for the IPCC: an update. In: Houghton JT, Callander BA, Varney SK, eds. Climate Change 1992: The Supplementary Report to The Intergovernmental Panel on Climate Change Scientific Assessment. Cambridge, UK: Cambridge University Press; 1992, 68-95.
13. IPCC. Climate Change 1995: The Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 1996.
14. IPCC. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 2001.
15. Nakićenović N, Alcamo J, Davis G, de Vries HJM, Fenhann J, Gaffin S, Gregory K, Grubler A, Jung TY, Kram T, et al. Special Report on Emissions Scenarios. A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 2000.
16. IPCC. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 2007.
17. Moss R, Edmonds J, Hibbard K, Manning M, Rose S, van Vuuren D, Carter T, Emori S, Kainuma M, Kram T, et al. The next generation of scenarios for climate change research and assessment. Nature 2010, 463:747-756.
18. IPCC. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York: Cambridge University Press; 2013.
19. van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque JF, et al. The representative concentration pathways: an overview. Clim Change 2011, 109:5-31.
20. Collins M, Allen MR. Assessing the relative roles of initial and boundary conditions in interannual to decadal climate predictability. J Clim 2002, 15:3104-3109.
21. Sanderson BM, Knutti R, Aina T, Christensen C, Faull N, Frame DJ, Ingram WJ, Piani C, Stainforth DA, Stone DA, et al. Constraints on model response to greenhouse gas forcing and the role of subgrid-scale processes. J Clim 2008, 21:2384-2400.
22. Webb MJ, Lambert FH, Gregory JM. Origins of differences in climate sensitivity, forcing and feedback in climate models. Clim Dyn 2012, 40:677-707.
23. Hawkins E, Sutton R. The potential to narrow uncertainty in projections of regional precipitation change. Clim Dyn 2011, 37:407-418.
24. Rowell DP. Sources of uncertainty in future changes in local precipitation. Clim Dyn 2012, 39:1929-1950.
25. Jenkins G, Lowe J. Handling uncertainties in the UKCIP02 scenarios of climate change. Hadley Centre Technical Note 2003, 15. Available at: http://www.metoffice.gov.uk/media/pdf/r/a/HCTN_44.pdf. (Accessed April 8, 2013).
26. Deser C, Knutti R, Solomon S, Phillips AS. Communication of the role of natural variability in future North American climate. Nat Clim Change 2012, 2:775-779.
27. Tebaldi C, Sanso B. Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach. J R Stat Soc Ser A Stat Soc 2009, 172:83-106.
28. Wigley TML, Raper SCB. Interpretation of high projections for global-mean warming. Science 2001, 293:451-454.
29. Tebaldi C, Knutti R. The use of the multi-model ensemble in probabilistic climate projections. Philos Trans R Soc A Math Phys Eng Sci 2007, 365:2053-2075.
30. Murphy J, Sexton D, Barnett D, Jones G, Webb M, Stainforth D. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 2004, 430:768-772.
31. Stainforth DA, Aina T, Christensen C, Collins M, Faull N, Frame DJ, Kettleborough JA, Knight S, Martin A, Murphy JM, et al. Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 2005, 433:403-406.
32. Meehl GA, Covey C, McAvaney B, Latif M, Stouffer RJ. Overview of the Coupled Model Intercomparison Project. Bull Am Meteorol Soc 2005, 86:89-93.
33. Taylor KE, Stouffer RJ, Meehl GA. An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 2012, 93:485-498.
34. Grose M, Moise AF, Timbal B, Katzfey JJ, Ekström M, Whetton PH. Climate projections for southern Australian cool-season rainfall: insights from a downscaling comparison. Clim Res 2015, 62:251-265.
35. Evans J, Ekström M, Ji F. Evaluating the performance of a WRF physics ensemble over South-East Australia. Clim Dyn 2012, 39:1241-1258.
36. Kay AL, Jones DA. Transient changes in flood frequency and timing in Britain under potential projections of climate change. Int J Climatol 2012, 32:489-502.
37. Schmidli J, Goodess CM, Frei C, Haylock MR, Hundecha Y, Ribalaygua J, Schmith T. Statistical and dynamical downscaling of precipitation: an evaluation and comparison of scenarios for the European Alps. J Geophys Res 2007, 112:D04105. doi:10.1029/2005JD007026.
38. Gutmann ED, Rasmussen RM, Liu C, Ikeda K, Gochis DJ, Clark MP, Dudhia J, Thompson G. A comparison of statistical and dynamical downscaling of winter precipitation over complex terrain. J Clim 2012, 25:262-281.
39. Fowler H, Blenkinsop S, Tebaldi C. Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 2007, 27:1547-1578.
40. Mearns LO, Giorgi F, Whetton P, Pabon D, Hulme M, Lal M. Guidelines for use of climate scenarios developed from regional climate model experiments. 2003, 38. Available at: http://www.ipcc-data.org/guidelines/dgm_no1_v1_10-2003.pdf. (Accessed April 13, 2011).
41. Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO. Guidelines for use of climate scenarios developed from statistical downscaling methods. 2004, 27. Available at: http://www.ipcc-data.org/guidelines/dgm_no2_v1_09_2004.pdf. (Accessed April 13, 2011).
42. Maraun D, Wetterhall F, Ireson A, Chandler R, Kendon E, Widmann M, Brienen S, Rust H, Sauter T, Themessl M, et al. Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 2010, 48:RG3003. doi:10.1029/2009RG000314.
43. Laprise R. Regional climate modelling. J Comput Phys 2008, 227:3641-3666.
44. Rummukainen M. State-of-the-art with regional climate models. WIREs Clim Change 2010, 1:82-96.
45. Laprise R, de Elia R, Caya D, Biner S, Lucas-Picher P, Diaconescu E, Leduc M, Alexandru A, Separovic L. Canadian Network Regional C. Challenging some tenets of Regional Climate Modelling. Meteorog Atmos Phys 2008, 100:3-22.
46. Feser F, Rockel B, von Storch H, Winterfeldt J, Zahn M. Regional climate models add value to global model data: a review and selected examples. Bull Am Meteorol Soc 2011, 92:1181-1192.
47. New M, Lopez A, Dessai S, Wilby R. Challenges in using probabilistic climate change information for impact assessments: an example from the water sector. Philos Trans R Soc A Math Phys Eng Sci 2007, 365:2117-2131.
48. Mitchell T. Pattern scaling: an examination of the accuracy of the technique for describing future climates. Clim Change 2003, 60:217-242.
49. Tebaldi C, Arblaster JM. Pattern scaling: its strengths and limitations, and an update on the latest model simulations. Clim Change 2014, 122:459-471.
50. Vidal J, Wade S. A framework for developing high-resolution multi-model climate projections: 21st century scenarios for the UK. Int J Climatol 2008, 28:843-858.
51. Cannon AJ. Negative ridge regression parameters for improving the covariance structure of multivariate linear downscaling models. Int J Climatol 2009, 29:761-769.
52. Charles SP, Bates BC, Smith IN, Hughes JP. Statistical downscaling of daily precipitation from observed and modelled atmospheric fields. Hydrol Process 2004, 18:1373-1394.
53. Mehrotra R, Sharma A. A multisite stochastic downscaling model of daily rainfall occurrences with long term persistence. In: MODSIM 2007: International Congress on Modelling and Simulation: Land, Water and Environmental Management: Integrated Systems for Sustainability, Christchurch, New Zealand, 2007, 1485-1491.
54. Hellstrom C, Chen DL. Statistical downscaling based on dynamically downscaled predictors: application to monthly precipitation in Sweden. Adv Atmos Sci 2003, 20:951-958.
55. Kidson JW, Thompson CS. A comparison of statistical and model-based downscaling techniques for estimating local climate variations. J Clim 1998, 11:735-753.
56. Busuioc A, Chen DL, Hellstrom C. Performance of statistical downscaling models in GCM validation and regional climate change estimates: application for Swedish precipitation. Int J Climatol 2001, 21:557-578.
57. Zorita E, von Storch H. The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 1999, 12:2474-2489.
58. Huth R. Statistical downscaling in central Europe: evaluation of methods and potential predictors. Clim Res 1999, 13:91-101.
59. Timbal B, McAvaney BJ. An analogue-based method to downscale surface air temperature: application for Australia. Clim Dyn 2001, 17:947-963.
60. Wilks D, Wilby R. The weather generation game: a review of stochastic weather models. Prog Phys Geogr 1999, 23:329-357.
61. Chun KP, Wheater HS, Onof C. Comparison of drought projections using two UK weather generators. Hydrolog Sci J 2013, 58:295-309.
62. Wilks DS. Stochastic weather generators for climate-change downscaling, part II: multivariable and spatially coherent multisite downscaling. WIREs Clim Change 2012, 3:267-278.
63. Wilks DS. Use of stochastic weather generators for precipitation downscaling. WIREs Clim Change 2010, 1:898-907.
64. Deque M, Jones RG, Wild M, Giorgi F, Christensen JH, Hassell DC, Vidale PL, Rockel B, Jacob D, Kjellstrom E, et al. Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results. Clim Dyn 2005, 25:653-670.
65. Colette A, Vautard R, Vrac M. Regional climate downscaling with prior statistical correction of the global climate forcing. Geophys Res Lett 2012, 39:L13707. doi:10.1029/2012GL052258.
66. Giorgi F. Regionalization of climate change information for impact assessment and adaptation. WMO Bull 2008, 57:86-92.
67. Cubasch U, Waszkewitz J, Hegerl G, Perlwitz J. Regional climate changes as simulated in time-slice experiments. Clim Change 1995, 31:273-304.
68. McGregor JL, Dix MR. An updated description of the Conformal-Cubic atmospheric model. In: High Resolution Numerical Modelling of the Atmosphere and Ocean. New York: Springer; 2008, 51-75.
69. Kokic P, Jin H, Crimp S. Improved point scale climate projections using a block bootstrap simulation and quantile matching method. Clim Dyn 2013, 41:853-866.
70. Williamson G, Prior L, Grose M, Harris R, Bowman D. Predicting canopy cover change in Tasmanian eucalypt forests using dynamically downscaled regional climate projections. Reg Environ Chang 2014, 14:1373-1386.
71. Chiew FHS, Teng J, Vaze J, Post DA, Perraud JM, Kirono DGC, Viney NR. Estimating climate change impact on runoff across southeast Australia: method, results, and implications of the modeling method. Water Resour Res 2009, 45:W10414. doi:10.1029/2008WR007338.
72. Burt TP, Howden NJK. North Atlantic Oscillation amplifies orographic precipitation and river flow in upland Britain. Water Resour Res 2013, 49:3504-3515.
73. Mehrotra R, Sharma A. Evaluating spatio-temporal representations in daily rainfall sequences from three stochastic multi-site weather generation approaches. Adv Water Resour 2009, 32:948-962.
74. Wilby R, Tomlinson O, Dawson C. Multi-site simulation of precipitation by conditional resampling. Clim Res 2003, 23:183-194.
75. Charles SP, Bates BC, Whetton PH, Hughes JP. Validation of downscaling models for changed climate conditions: case study of southwestern Australia. Clim Res 1999, 12:1-14.
76. Wilby RL, Wigley TML. Downscaling general circulation model output: a review of methods and limitations. Prog Phys Geogr 1997, 21:530-548.
77. Burger G, Murdock TQ, Werner AT, Sobie SR, Cannon AJ. Downscaling extremes: an intercomparison of multiple statistical methods for present climate. J Clim 2012, 25:4366-4388.
78. Leung LR, Kuo Y-H, Tribbia J. Research needs and directions of regional climate modeling using WRF and CCSM. Bull Am Meteorol Soc 2006, 87:1747-1751.
79. Grose M, Corney S, Katzfey J, Bennett J, Holz G, White C, Bindoff N. A regional response in mean westerly circulation and rainfall to projected climate warming over Tasmania, Australia. Clim Dyn 2013, 40:2035-2048.
80. Xu Z, Yang Z-L. An Improved dynamical downscaling method with GCM bias corrections and its validation with 30 years of climate simulations. J Clim 2012, 25:6271-6286.
81. White RH, Toumi R. The limitations of bias correcting regional climate model inputs. Geophys Res Lett 2013, 40:2907-2912.
82. Fowler HJ, Kilsby CG. Using regional climate model data to simulate historical and future river flows in northwest England. Clim Change 2007, 80:337-367.
83. Hay L, Wilby R, Leavesley G. A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. J Am Water Resour Assoc 2000, 36:387-397.
84. Leander R, Buishand TA. Resampling of regional climate model output for the simulation of extreme river flows. J Hydrol 2007, 332:487-496.
85. Leander R, Buishand TA, van den Hurk BJJM, de Wit MJM. Estimated changes in flood quantiles of the river Meuse from resampling of regional climate model output. J Hydrol 2008, 351:331-343.
86. Bennett JC, Grose MR, Corney SP, White CJ, Holz GK, Katzfey JJ, Post DA, Bindoff NL. Performance of an empirical bias-correction of a high-resolution climate dataset. Int J Climatol 2013, 34:2189-2204.
87. Bennett JC, Ling FLN, Post DA, Grose MR, Corney SP, Graham B, Holz GK, Katzfey JJ, Bindoff NL. High-resolution projections of surface water availability for Tasmania, Australia. Hydrol Earth Syst Sci 2012, 16:1287-1303.
88. Berg P, Feldmann H, Panitz HJ. Bias correction of high resolution regional climate model data. J Hydrol 2012, 448:80-92.
89. Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J. HESS opinions: "should we apply bias correction to global and regional climate model data?" Hydrol Earth Syst Sci 2012, 16:3391-3404.
90. Maraun D. Bias correction, quantile mapping, and downscaling: revisiting the inflation issue. J Clim 2013, 26:2137-2143.
91. Lafon T, Dadson S, Buys G, Prudhomme C. Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods. Int J Climatol 2013, 33:1367-1381.
92. Teutschbein C, Seibert J. Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods. J Hydrol 2012, 456:12-29.
93. Kilsby CG, Jones PD, Burton A, Ford AC, Fowler HJ, Harpham C, James P, Smith A, Wilby RL. A daily weather generator for use in climate change studies. Environ Model Softw 2007, 22:1705-1719.
94. Foley AM. Uncertainty in regional climate modelling: a review. Prog Phys Geogr 2010, 34:647-670.
95. Pielke RA Sr, Wilby RL. Regional climate downscaling: what's the point? Eos Trans Amer Geophys Union 2012, 93:52-53.
96. Argüeso D, Evans J, Fita L, Bormann K. Temperature response to future urbanization and climate change. Clim Dyn 2014, 42:2183-2199.
97. Giorgi F, Jones C, Asrar GR. Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 2009, 58:175-183.
98. Rasmussen DJ, Holloway T, Nemet GF. Opportunities and challenges in assessing climate change impacts on wind energy-a critical comparison of wind speed projections in California. Environ Res Lett 2011, 6:9.
99. Kendon E, Jones R, Kjellstrom E, Murphy J. Using and designing GCM-RCM ensemble regional climate projections. J Clim 2010, 23:6485-6503.
100. Kjellstrom E, Boberg F, Castro M, Christensen J, Nikulin G, Sanchez E. Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. Clim Res 2010, 44:135-150.
101. Kjellstrom E, Giorgi F. Regional climate model evaluation and weighting Introduction. Clim Res 2010, 44:117-119.
102. Goodess CM, Anagnostopoulou C, Bárdossy A, Frei C, Harpham C, Haylock MR, Hundecha Y, Maheras P, Ribalaygua J, Schmidli J, et al. An intercomparison of statistical downscaling methods for Europe and European regions - assessing their performance with respect to extreme temperature and precipitation events. CRU Research Publications series 2012, CRU_RP11. Available at: http://www.cru.uea.ac.uk/documents/421974/1301877/CRU_RP11.pdf/b01b7b53-55cf-4dad-8d94-185c1f436cb9. (Accessed March 6, 2015).
103. Maraun D, Widmann M, Gutiérrez JM, Kotlarski S, Chandler RE, Hertig E, Wibig J, Huth R, Wilcke RAI. VALUE: a framework to validate downscaling approaches for climate change studies. Earth's Future 2015, 3:1-14.
104. Haylock M, Cawley G, Harpham C, Wilby R, Goodess C. Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios. Int J Climatol 2006, 26:1397-1415.
105. Lempert R, Kalra N. Managing climate risks in developing countries with robust decision making. World Resources Report Uncertainty Series, 2011, 9. Available at: http://www.wri.org/sites/default/files/uploads/wrr_lempert_and_kalra_uncertainty_.pdf. (Accessed November 19, 2014).
106. Salathe EP, Mote PW, Wiley MW. Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States pacific northwest. Int J Climatol 2007, 27:1611-1621.
107. Semenov MA. Simulation of extreme weather events by a stochastic weather generator. Clim Res 2008, 35:203-212.
108. Sherwood SC, Roca R, Weckwerth TM, Andronova NG. Tropospheric water vapor, convection, and climate. Rev Geophys 2010, 48:RG2001. doi:10.1029/2009RG000301.
109. Kendon EJ, Roberts NM, Fowler HJ, Roberts MJ, Chan SC, Senior CA. Heavier summer downpours with climate change revealed by weather forecast resolution model. Nat Clim Change 2014, 4:570-576.
110. Tryhorn L, DeGaetano A. A comparison of techniques for downscaling extreme precipitation over the Northeastern United States. Int J Climatol 2011, 31:1975-1989.
111. Fowler HJ, Ekstroem M. Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes. Int J Climatol 2009, 29:385-416.
112. Kendon EJ, Roberts NM, Senior CA, Roberts MJ. Realism of rainfall in a very high-resolution regional climate model. J Clim 2012, 25:5791-5806.
113. Jones PG, Thornton PK. Generating downscaled weather data from a suite of climate models for agricultural modelling applications. Agric Syst 2013, 114:1-5.
114. McKenney DW, Pedlar JH, Lawrence K, Campbell K, Hutchinson MF. Potential impacts of climate change on the distribution of North American trees. Bioscience 2007, 57:939-948.
115. Frost AJ, Charles SP, Timbal B, Chiew FHS, Mehrotra R, Nguyen KC, Chandler RE, McGregor JL, Fu G, Kirono DGC, et al. A comparison of multi-site daily rainfall downscaling techniques under Australian conditions. J Hydrol 2011, 408:1-18.
116. Mehrotra R, Sharma A, Cordery I. Comparison of two approaches for downscaling synoptic atmospheric patterns to multisite precipitation occurrence. J Geophys Res 2004, 109:D14107. doi:10.1029/2004JD004823.
117. Franklin J, Davis FW, Ikegami M, Syphard AD, Flint LE, Flint AL, Hannah L. Modeling plant species distributions under future climates: how fine scale do climate projections need to be? Glob Chang Biol 2013, 19:473-483.
118. Tabor K, Williams J. Globally downscaled climate projections for assessing the conservation impacts of climate change. Ecol Appl 2010, 20:554-565.
119. Mokany K, Harwood TD, Williams KJ, Ferrier S. Dynamic macroecology and the future for biodiversity. Glob Chang Biol 2012, 18:3149-3159.
120. Xu T, Hutchinson MF. New developments in the ANUCLIM bioclimatic modelling package. In: International Congress on Environmental Modelling and Software: Managing Resources of a Limited Planet. International Environmental Modelling and Software Society: Leipzig, Germany; 2012.
121. Knutti R, Furrer R, Tebaldi C, Cermak J, Meehl G. Challenges in combining projections from multiple climate models. J Clim 2010, 23:2739-2758.
122. UNFCCC. Compendium on methods and tools to evaluate impacts of, and vulnerability and adaptation to, climate change. 2008. Available at: http://unfccc.int/files/adaptation/nairobi_workprogramme/compendium_on_methods_tools/application/pdf/20080307_compendium_m_t_complete.pdf.
123. Denis B, Laprise R, Caya D, Cote J. Downscaling ability of one-way nested regional climate models: the Big-Brother experiment. Clim Dyn 2002, 18:627-646.
124. Hattermann FF, Weiland M, Huang SC, Krysanova V, Kundzewicz ZW. Model-supported impact assessment for the water sector in central Germany under climate change: a case study. Water Resour Manag 2011, 25:3113-3134.
125. Fung F, Watts G, Lopez A, Orr HG, New M, Extence C. Using large climate ensembles to plan for the hydrological impact of climate change in the freshwater environment. Water Resour Manag 2013, 27:1063-1084.
126. Kuruppu N, Liverman D. Mental preparation for climate adaptation: the role of cognition and culture in enhancing adaptive capacity of water management in Kiribati. Global Environ Change 2011, 21:657-669.