ELPIS-JP: A dataset of local-scale daily climate change scenarios for Japan

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Volumn 370, Issue 1962, 2012, Pages 1121-1139

  Iizumi, Toshichika ^a   Semenov, Mikhail A ^b   Nishimori, Motoki ^a   Ishigooka, Yasushi ^a   Kuwagata, Tsuneo ^a  

^a NATIONAL INSTITUTE FOR AGRO ENVIRONMENTAL SCIENCES   (Japan)

^b ROTHAMSTED RESEARCH   (United Kingdom)

Author keywords

Climate change; ELPIS JP; Impact assessment; Japan; LARS WG; Stochastic weather generator

Indexed keywords

CLIMATE MODELS; RATING; STATISTICAL TESTS; STOCHASTIC SYSTEMS; SUN;

ELPIS-JP; IMPACT ASSESSMENT; JAPAN; LARS-WG; STOCHASTIC WEATHER GENERATOR;

CLIMATE CHANGE;

ARTICLE; CLIMATE CHANGE; FACTUAL DATABASE; JAPAN;

CLIMATE CHANGE; DATABASES, FACTUAL; JAPAN;

EID: 84857295061     PISSN: 1364503X     EISSN: None     Source Type: Journal    
DOI: 10.1098/rsta.2011.0305     Document Type: Article

References (69)

1. Mizuta, R. et al. 2006 20-km-mesh global climate simulations using JMA-GSM model: mean climate states. J. Meteorol. Soc. Jpn 84, 165-185. (doi:10.2151/jmsj.84.165) (Pubitemid 43676123)
2. Murphy, J. M. et al. 2009 UK climate projections science report: climate change projections. Exeter, UK: Met Office Hadley Centre.
3. Semenov, M. A., Donatelli, M., Stratonovitch, P., Chatzidaki, E. & Baruth, B. 2010 ELPIS: adataset of local-scale daily climate scenarios for Europe. Clim. Res. 44, 3-15. (doi:10.3354/cr00 865)
4. Castro, C. L., Pielke, R. A. & Leoncini, G. 2005 Dynamical downscaling: assessment of value retained and added using the regional atmospheric modeling system (RAMS). J. Geophys. Res. 110, D05108. (doi:10.1029/2004JD004721) (Pubitemid 40815053)
5. Baigorria, G. A., Jones, J. W., Shin, D.-W., Mishra, A. & O'Brien, J. J. 2007 Assessing uncertainties in crop model simulations using daily bias-corrected regional circulation model outputs. Clim. Res. 34, 211-222. (doi:10.3354/cr00703) (Pubitemid 351736067)
6. Iizumi, T., Nishimori, M. & Yokozawa, M. 2010 Diagnostics of climate model biases in summer temperature and warm season insolation for the simulation of regional paddy rice yield in Japan. J. Appl. Meteorol. Climatol. 49, 574-591. (doi:10.1175/2009JAMC2225.1)
7. Semenov, M. A. & Barrow, E. M. 1997 Use of a stochastic weather generator in the development of climate change scenarios. Clim. Change 35, 397-414. (doi:10.1023/A:1005342632279) (Pubitemid 27191191)
8. Barrow, E. M. & Semenov, M. A. 1995 Climate change scenarios with high spatial and temporal resolution for agricultural applications. Forestry 68, 349-360. (doi:10.1093/forestry/68.4.349) (Pubitemid 26443410)
9. Qian, B., Hayhoe, H. & Gameda, S. 2005 Evaluation of the stochastic weather generators LARSWG and AAFC-WG for climate change impact studies. Clim. Res. 29, 3-21. (doi:10.3354/cr02 9003) (Pubitemid 41110407)
10. Semenov, M. A. 2007 Development of high resolution UKCIP02-based climate change scenarios in the UK. Agric. For. Meteorol. 144, 127-138. (doi:10.1016/j.agrformet.2007.02.003) (Pubitemid 46527963)
11. Cowden, J. R., Watkins Jr, D. W. & Mihelcic, J. R. 2008 Stochastic rainfall modeling in West Africa: parsimonious approaches for domestic rainwater harvesting assessment. J. Hydrol. 361, 64-77. (doi:10.1016/j.jhydrol.2008.07. 025)
12. Qian, B., Gameda, S. & Hayhoe, H. 2008 Performance of stochastic weather generators LARSWG and AAFC-WG for reproducing daily extremes of diverse Canadian climates. Clim. Res. 37, 17-33. (doi:10.3354/cr00755)
13. Allen, D. M., Cannon, A. J., Toews, M. W. & Scibek, J. 2010 Variability in simulated recharge using different GCMs. Water Resour. Res. 46, W00F03. (doi:10.1029/2009WR008932)
14. 2 and climate change in an unfertilized grass-clover sward. Clim. Res. 41, 221-232. (doi:10.3354/cr00847)
15. Luo, Q., Bellotti, W., Hayman, P., Williams, M. & Devoil, P. 2010 Effects of changes in climatic variability on agricultural production. Clim. Res. 42, 111-117. (doi:10.3354/cr00868)
16. Rahman, M., Bolisetti, T. & Balachandar, R. 2010 Effect of climate change on low-flow conditions in the Ruscom River watershed, Ontario. Trans ASABE 53, 1521-1532.
17. Utset, A. & Del Rio, B. 2011 Reliability of current Spanish irrigation designs in a changed climate: a case study. J. Agric. Sci. 149, 171-183. (doi:10.1017/S0021859610001073)
18. Bae, D. H., Jung, I. W. & Chang, H. 2008 Potential changes in Korean water resources estimated by high-resolution climate simulation. Clim. Res. 35, 213-226. (doi:10.3354/cr00704) (Pubitemid 351721162)
19. Abdulharis, A., Khan, M. A., Vandana, C., Sandeep, B. & Arvind, P. 2010 Evaluation of LARS-WG for generating long term data for assessment of climate change impact in Bihar. J. Agrometeorol. 12, 198-201.
20. 2 concentration. J. Agric. Meteorol. 59, 117-130. (doi:10.2480/agrmet.59.117)
21. Okada, M., Iizumi, T., Nishimori, M. & Yokozawa, M. 2009 Mesh climate change data of Japan ver. 2 for climate change impact assessments under IPCC SRES A1B and A2. J. Agric. Meteorol. 65, 97-109. (doi:10.2480/agrmet.65.1.4)
22. Iizumi, T., Nishimori, M., Ishigooka, Y. & Yokozawa, M. 2010 Introduction to climate change scenario derived by statistical downscaling. J. Agric. Meteorol. 66, 131-143. [In Japanese.] (doi:10.2480/agrmet.66.2.5)
23. Iizumi, T., Nishimori, M., Dairaku, K., Adachi, S. A. & Yokozawa, M. 2011 Evaluation and intercomparison of downscaled daily precipitation indices over Japan in present-day climate: strengths and weaknesses of dynamical and bias correction-type statistical downscaling methods. J. Geophys. Res. 116, D01111. (doi: 10.1029/2010JD014513)
24. Nishimori, M. & Kitoh, A. 2006 Estimation of future regional-scale heavy rainfall change over Japan and East Asia under the global climate change by using the statistical downscaling method. In Proc. Int. Symp. Disaster Management, Kochi, Japan, 10-12 March 2006.
25. Nakicenovic, N. & Swart, R. (eds) 2000 Special report on emissions scenarios: a special report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.
26. Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J. & Taylor, K. E. 2007 The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull. Am. Meteorol. Soc. 88, 1383-1394. (doi:10.1175/BAMS-88-9-1383) (Pubitemid 47616759)
27. Ishizaki, N. et al. In press. Inter-comparison of the skill in the Japan region of five RCMs nested in JRA-25. J. Meteorol. Soc. Jpn.
28. Arritt, R. W. & Rummukainen, M. 2011 Challenges in regional-scale climate modeling. Bull. Am. Meteorol. Soc. 92, 365-368. (doi:10.1175/ 2010BAMS2971.1)
29. Kuwagata, T., Yoshimoto, M., Ishigooka, Y. & Hasegawa, T. 2008 Model-coupled agrometeorological database for estimating the effects of global warming and climate variability on rice production. In NIAES Annual Report 2008 (ed. Y. Sato). Tsukuba, Japan: National Institute for Agro-Environmental Sciences. See http://www.niaes.affrc.go.jp/ann ual/r2008/index.html.
30. Kuwagata, T., Yoshimoto, M., Ishigooka, Y., Hasegawa, T. & Nishimori, M. 2009 Model coupled agro-meteorological database (MeteoCrop DB) for estimating the effect of global warming and climate variability on rice production. J. Agric. Sci. 64, 325-329. [In Japanese.]
31. Kuwagata, T., Yoshimoto, M., Ishigooka, Y., Hasegawa, T., Nishimori, M. & Masaki, Y. 2010 Model coupled crop-meteorological database (MeteoCrop DB)for estimating the effect of global warming and climate change on rice. Bull JAALD 158, 23-26. [In Japanese.]
32. Ångström, A. 1924 Solar and terrestrial radiation. Q. J. R. Meteorol. Soc. 50, 121-125. (doi:10.1002/qj.49705021008)
33. Prescott, J. A. 1940 Evaporation from water surface in relation to solar radiation. Trans. R. Soc. Aust. 64, 114-125.
34. Kondo, J., Nakamura, T. & Yamazaki, T. 1991 Estimation of the solar and downward atmospheric radiation. Tenki 38, 41-48. [In Japanese.]
35. Mitchell, T. D. & Jones, P. D. 2005 An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol. 25, 693-712. (doi:10.1002/joc.1181) (Pubitemid 40815726)
36. Déqué, M., Dreveton, C., Braun, A. & Cariolle, D. 1994 The ARPEGE/IFS atmosphere model: a contribution to the French community climate modeling. Clim. Dyn. 10, 249-266. (doi:10.1007/s003820050047)
37. Flato, G. M., Boer, G. J., Lee, W. G., McFarlane, N. A., Ramsden, D., Reader, M. C. &Weaver, A. J. 2000 The Canadian centre for climate modeling and analysis global coupled model and its climate. Clim. Dyn. 16, 451-467. (doi:10.1007/s003820050339) (Pubitemid 30454354)
38. Wang, B., Wan, H., Ji, Z., Zhang, X., Yu, R., Yu, Y. & Liu, H. 2004 Design of a new dynamical core for global atmospheric models based on some efficient numerical ethods. Sci. China Ser. A 47, 4-21. (doi:10.1360/04za0001)
39. Russell, G. L., Miller, J. R. & Rind, D. 1995 A coupled atmosphere ocean model for transient climate change studies. Atmos. Ocean 33, 683-730. (doi:10.1080/07055900.1995.9649550) (Pubitemid 126071228)
40. Galin, V. Y., Volodin, E. M. & Smyshliaev, S. P. 2003 Atmospheric general circulation model of INM RAS with ozone dynamics. Russ. Meteorol. Hydrol. 5, 13-22.
41. Hourdin, F. et al. 2006 The LMDZ4 general circulation model: climate performance and sensitivity to parameterized physics with emphasis on tropical convection. Clim. Dyn. 27, 787-813. (doi:10.1007/s00382-006-0158-0) (Pubitemid 44550673)
42. K-1 Model Developers. 2004 K-1 coupled GCM (MIROC) description. In K-1 technical report no. 1 (eds H. Hasumi & S. Emori). Tokyo, Japan: Centre for Climate System Research, University of Tokyo.
43. Yukimoto, S. & Noda, A. 2002 Improvements of the Meteorological Research Institute global ocean-atmosphere coupled GCM (MRI-CGCM2) and its climate sensitivity. CGCR Supercomputer Activity Report, no. 10. Tsukuba, Japan: National Institute for Environmental Studies.
44. Saito, K. et al. 2006 The operational JMA nonhydrostatic mesoscale model. Mon. Weather Rev. 134, 1266-1298. (doi:10.1175/MWR3120.1)
45. Ishizaki, N. & Takayabu, I. 2009 On the warming events over Toyama plain by using NHRCM. SOLA 5, 129-132. (doi:10.2151/sola.2009-033)
46. Pielke, R. A. et al. 1992 A comprehensive meteorological modeling system-RAMS. Meteorol. Atmos. Phys. 49, 69-91. (doi:10.1007/BF01025401)
47. Dairaku, K., Emori, S. & Higashi, H. 2008 Potential changes in extreme events under global climate change. J. Disaster Res. 3, 39-50.
48. Dairaku, K., Emori, S. & Nozawa, T. 2008 Impacts of global warming on hydrological cycles in the Asian monsoon region. Adv. Atmos. Sci. 25, 960-973. (doi:10.1007/s00376-008-0960-1)
49. Dairaku, K., Iizuka, S., Sasaki, W., Beltran, A. & Pielke, R. A. 2008 Assessment of dynamical downscaling in Japan using an atmosphere-biosphere- river coupling regional climate model. In Proc. Eos Trans AGU Fall Meet. Suppl., San Francisco, CA, 13-17 December 2008.
50. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W. & Powers, J. G. 2008 A description of the advanced research WRF version 3. Technical note no. 475. Boulder, CO: National Centre for Atmospheric Research.
51. Semenov, M. A. & Stratonovitch, P. 2010 Use of multi-model ensembles from global climate models for impact assessments of climate change. Clim. Res. 41, 1-14. (doi:10.3354/cr00836)
52. Racsko, P., Szeidl, L. & Semenov, M. A. 1991 A serial approach to local stochastic weather models. Ecol. Model. 57, 27-41. (doi:10.1016/0304- 3800(91)90053-4)
53. Semenov, M. A., Brooks, R. J., Barrow, E. M. & Richardson, C. W. 1998 Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Clim. Res. 10, 95-107. (doi:10.3354/cr010095) (Pubitemid 29126268)
54. Qian, B., Gameda, S., Hayhoe, H., De Jong, R. & Bootsma, A. 2004 Comparison of LARS-WG and AAFC-WG stochastic weather generators for diverse Canadian climates. Clim. Res. 26, 175-191. (doi:10.3354/cr026175) (Pubitemid 39130975)
55. Semenov, M. A. 2008 Simulation of weather extreme events by stochastic weather generator. Clim. Res. 35, 203-212. (doi:10.3354/cr00731) (Pubitemid 351721161)
56. Priestley, C. H. B. & Taylor, R. J. 1972 On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Weather Rev. 100, 81-82. (doi:10.1175/1520-0493(1972)100 <0081:OTAOSH>2.3.CO;2)
57. Suleiman, A. A. & Hoogenboom, G. 2007 Comparison of Priestley-Taylor and FAO-56 Penman- Monteith for daily reference evapotranspiration estimation in Georgia. J. Irrigat. Drain Eng. 133, 175-182. (doi:10.1061/(ASCE)0733- 9437(2007)133:2(175)) (Pubitemid 46454839)
58. Yoshimoto, M., Oue, H., Takahashi, H. & Kobayashi, K. 2005 The effects of FACE (Free-Air CO2 Enrichment) on temperatures and transpiration of rice panicles at flowering stage. J. Agric. Meteorol. 60, 597-600.
59. Sharpley, A. N. & Williams, J. R. 1990 EPIC-Erosion/productivity impact calculator. I. Model Documentation. Technical bulletin no. 1768. Washington, DC: U.S. Department of Agriculture.
60. Donatelli, M., Bellocchi, G., Habyarimana, E., Confalonieri, R. & Micale, F. 2009 An extensible model library for generating wind speed data. Comput. Electron Agr. 69, 165-170. (doi:10.1016/j.compag.2009.07.022)
61. Press, W. H., Teukolsky, S. A., Vetterling, W. T. & Flannery, B. P. 1992 Numerical recipes in FORTRAN 77: the art of scientific computing, 2nd edn. New York, NY: Cambridge University Press.
62. Semenov, M. A. & Barrow, E. M. 2002 LARS-WG: a stochastic weather generator for use in climate impact studies, version 3, user manual. Harpenden, UK: Rothamsted Research. See http://www.rothamsted.bbsrc.ac.uk/mas-models/ download/ LARS-WG-Manual.pdf.
63. Mochizuki, T. et al. 2010 Pacific decadal oscillation hindcasts relevant to near-term climate prediction. Proc. Natl Acad. Sci. USA 107, 1833-1837. (doi:10.1073/pnas.0906531107)
64. IPCC 2010 Meeting report of the Intergovernmental Panel on Climate Change Expert Meeting on Assessing and Combining Multi Model Climate Projections (eds T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor & P. M. Midgley), p. 117. IPCC Working Group I Technical Support Unit. Bern, Switzerland: University of Bern.
65. Kamiguchi, K., Arakawa, O., Kitoh, A., Yatagai, A., Hamada, A. & Yasutomi, N. 2010 Development of APHRO JP, the first Japanese high-resolution daily precipitation product for more than 100 years. Hydrol. Res. Lett. 4, 60-64. (doi:10.3178/hrl.4.60)
66. Seino, H. 1993 An estimation of distribution of meteorological elements using GIS and AMeDAS data. J. Agric. Meteorol. 48, 379-383. [In Japanese.] (doi:10.2480/agrmet.48.379)
67. Kitamura, O. 1990 A study for the production and application of the mesh climatic data file. J. Geogr. 99, 56-63. [In Japanese.]
68. Wilks, D. S. 2008 High-resolution spatial interpolation of weather generator parameters using local weighted regressions. Agric. For. Meteorol. 148, 111-120. (doi:10.1016/j.agrformet.2007.09.005) (Pubitemid 350297481)
69. Wilks, D. S. 2009 A gridded multisite weather generator and synchronization to observed weather data. Water Resour. Res. 45, W10419. (doi:10.1029/2009WR007902)