Objective estimate of future climate analogues projected by an ensemble AGCM experiment under the SRES A1B scenario
- 1k Downloads
Climate analogues (CAs), regions whose present climates are similar to the future climate of a target place, are identified to assess the effects of climate change towards the end of the 21st century. The location of CAs and their present climates yield information that may be used to mitigate the harmful impacts of climate change. Present (1979–2003) and future (2075–2099) climates are projected in an ensemble experiment using the atmospheric general circulation model of the Meteorological Research Institute in Japan. The ensemble members consist of combinations of four distributions of sea surface temperature, three convection schemes, and two initial conditions. The emission scenario for greenhouse gases is A1B of the Special Report on Emissions Scenarios. A new method to identify the location of CAs is introduced, in which the uncertainty in the climate projection is taken into account. CAs for all land regions of the world are presented and those of four capital cities are analyzed in detail. The CAs are generally distributed equator-ward from the target places, consistent with the global warming. It is also found that ensemble experiments that encompass the uncertainty of climate projections can yield robust results for the CA and lead to reliable assessments of climate change.
KeywordsFuture Climate Root Mean Square Difference Similarity Score Ensemble Member Convection Scheme
We are thankful to Drs Mizuta and Yoshida of the Meteorological Research Institute for providing the results of the AGCMs analyzed in this paper. This research is supported by the SOUSEI program of MEXT, Japan.
- Endo H, Kitoh A, Ose T, Mizuta R, Kusunoki S (2012) Future changes and uncertainties in Asian precipitation simulated by multiphysics and multi–sea surface temperature ensemble experiments with high-resolution meteorological research institute atmospheric general circulation models (MRI-AGCMs). J Geophys Res Atmos (1984–2012) 117(D16)Google Scholar
- Kain JS, Fritsch JM (1993) Convective parameterization for mesoscale models: the Kain-Fritsch scheme. In: Emanuel KA, Raymond DJ (eds) The representation of cumulus convection in numerical models, Meteorol Monogr, vol 24, no 46. American Meteorological Society, Boston, pp 165– 170Google Scholar
- Nakaegawa T, Kitoh A, Hosaka M (2013) Discharge of major global rivers in the late 21st century climate projected with the high horizontal resolution MRI-AGCMs. Hydrol Process 27(23):3301– 3318Google Scholar
- Nakicenovic N, Alcamo J, Davis G, Vries Bd, Fenhann JV, Gaffin S, Gregory K, Grübler A, Jung TY, Kram T et al (2000) Special report on emissions scenarios: special report of working group iii of the intergovernmental panel on climate changeGoogle Scholar
- Ramírez-Villegas J, Lau C, Kohler A, Jarvis A, Arnell N, Osborne T, Hooker J (2011) Climate analogues: finding tomorrow’s agriculture todayGoogle Scholar
- Randall D, Pan D (1993) Implementation of the Arakawa-Schubert cumulus parameterization with a prognostic closure. In: Emanuel KA, Raymond DJ (eds) The representation of cumulus convection in numerical models, Meteor Monogr, vol 24, no 46. American Meteorological Society, Boston , pp 137–144Google Scholar
- Rayner N, Parker DE, Horton E, Folland C, Alexander L, Rowell D, Kent E, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos (1984–2012) 108(D14)Google Scholar
- Veloz SD, Williams JW, Blois JL, He F, Otto-Bliesner B, Liu Z (2012) No-analog climates and shifting realized niches during the late quaternary: implications for 21st-century predictions by species distribution models. Glob Chang Biol 18(5):1698–1713Google Scholar
- Wilby R, Charles S, Zorita E, Timbal B, Whetton P, Mearns L (2004) Guidelines for use of climate scenarios developed from statistical downscaling methodsGoogle Scholar
- Yukimoto S, Yoshimura H, Hosaka M, Sakami T, Tsujino H, Hirabara M, Tanaka TY, Deushi M, Obata A, Nakano H, Adachi Y, Shindo E, Yabu S, Ose T, Kitoh A (2011) Meteorological research institute earth system model version 1 (MRI-ESM1): model descriptionGoogle Scholar