HR: 1340h
AN: GC43A-0936 [Abstracts]
TI: Utilizing the Koeppen climate classification to assess the future climate change
AU: * Hori, M E
EM: mhori@hyarc.nagoya-u.ac.jp
AF: Graduate School of Environmental Studies, Nagoya University, Room 515, Institute for
Advanced Research Hall, Nagoya University Furo-cho, Chikusa-ku, Nagoya city, Aichi prefecture, Nagoya, 464-
8601, Japan
AU: Yasunari, T
EM: yasunari@hyarc.nagoya-u.ac.jp
AF: HyArc, Nagoya University, HyArc, Nagoya University Furo-cho, Chikusa-ku, Nagoya city,
Aichi prefecture, Nagoya, 464-8601, Japan
AB:
It is suggested that global warming due to anthropogenic greenhouse gasses will cause a large change in the
mean temperature and precipitation patterns of the future. One way to quantify the impact of this change is to use
the climate classification method. Classifying the climate into regions with distinct properties instead of using
only physical properties such as temperature and precipitation helps to give an objective view of how climate
change affects the environment such as the land-surface types and vegetation. TheKoeppen climate
classification has a long history of application and modification and is known to give a robust classification of the
mean climate that closely follows the distribution of vegetation types. In this study, we apply theKoeppen climate
classification on the result of 19 Atmosphere-Ocean GCM results provided by the PCMDI for the upcoming IPCC -
AR4. By applying this method to the long-term future projection of climate models, instability of a particular climate
region and its expected change in the longer timescales are quantified. The classification is performed on the
20th century simulation (20C3M) and the SRES-A1B / A2 scenario based on the long-term monthly climatology.
The overall changes in classifications as well as inter-model distribution is calculated for all each model and the
skill weighted ensemble mean. Results show that due to warmer climate and increase in moisture, large area of
western Russian region and north America experience a shift from aDf (snow / fully moist) climate to Cf (Warm
temperate / fully moist) classification which is in good agreement with the stronger NAO/AO phase in the north
Atlantic. On the other hand, coastal Greenland region changes from a Ef (Polar frost) classification to Ef (Polar
tundra) classification, which is in good agreement with the SST and sea-ice distribution. In contrast, northern
China undergoes a change from Cf classification to Cw (Warm temperate / winter dry) classification which marks
a drying of this region. Weakening of the Aleutian low and a strongerENSO signal among models may have
contributed to this result. In the presentation, major changed in classification and its physical background is
highlighted.
DE: 1622 Earth system modeling (1225)
DE: 1630 Impacts of global change (1225)
DE: 1632 Land cover change
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting