TY - JOUR
T1 - A Geographic Information System (GIS)-based approach to adaptation to regional climate change
T2 - A case study of Okutama-machi, Tokyo, Japan
AU - Bai, Yingjiu
AU - Kaneko, Ikuyo
AU - Kobayashi, Hikaru
AU - Kurihara, Kazuo
AU - Takayabu, Izuru
AU - Sasaki, Hidetaka
AU - Murata, Akihiko
N1 - Funding Information:
As mentioned above, free international daily datasets including data applicable at national levels in digital form have been improved worldwide (Alexander et al. 2006) and these datasets include climate observations and climate models, have worldwide open-access, and are updated by IPCC Data Distribution Centre (http://ww.ipccdata.orgobs/index.html). Also, a number of new results have been published; RCMs can resolve features down to 50 km or less and many regional high-resolution (about 25 km) projections of future climate change have been developed (Hayhoe et al. 2008; Elguindi and Grundstein 2012; Patricola and Cook 2010). The Earth System Grid Federation (ESGF) is a coordinated international collaboration of individuals and institutions that is developing, deploying and maintaining software infrastructure for the management of model output and observational data. Researchers worldwide can now access ESGF data holdings through any of the gateways hosted by ESGF partners, including laboratories in the U.S. funded by the Department of Energy (DOE), the National Science Foundation (NSF), the National Aeronautics and Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA), and at laboratories elsewhere, including the Australian National University (ANU) National Computational Infrastructure (NCI), the British Atmospheric Data Center (BADC), the Max Planck Institute for Meteorology of the German Climate Computing Centre (DKRZ). Users can access all data sets freely using web browsers (ESGF gateways <http://esgf.org/> or ESGF data nodes <http://www-pcmdi.llnl.gov/>).
Funding Information:
In this study, we used a high-quality daily dataset from the JMA Observations (Surface observations http://www.jma.go.jp/jma/en/Activities/observations.html) and projections (5 km resolution) from the NHRCM-5 km following the SRES-A1B scenario developed by the Meteorological Research Institute (MRI), JMA supported by Innovative Program of Climate Change Projection for the 21st Century (KAKUSHIN Program). The NHRCM-5 km is a dynamic downscaling of results from MRI-AGCM3.2S (20 km resolution) under CMIP5 (the MRI-AGCM3.2S output can be downloaded from CMIP5 or the IPCC Data Distribution Centre webpage). Also, we re-produced the GIS statistics conducted stepwise for local governments by the Ministry of International Affairs and Communications, Japan (Statistics Bureau: Database of the national census) using the basic DMT.
PY - 2014/6
Y1 - 2014/6
N2 - Recently, local governments have an increasing need to take extensive and effective local measures to adapt to regional climate change, but have difficulty knowing how and when to adapt to such change. This study aims: 1) to characterize an efficient and cost-effective database management tool (DMT) for developing a Geographic Information System (GIS) based approach to using observed and projected data, for decision-making by non-expert government authorities, and 2) to document how DMT can be used to provide specialized yet understandable climate change information to assist local decision-makers in clarifying regional priorities within a wide array of adaptation options. The DMT combines climate change mapping, statistical GIS, and a vulnerability assessment. Okutama-machi, a 225.63 km2 sparsely populated mountainous region (2012 population 5,856) northwest of Tokyo, Japan, was chosen for this pilot study. In this paper, the most recent regional climate projections (5 km resolution) are transcribed into an understandable form for use by non-expert citizens who use the GIS-based DMT. Results illustrate qualitative agreement in projection of summer daily mean temperatures; the mean temperature increase at Okutama-machi is the greatest of any area in Tokyo. In comparing near future and future conditions, August monthly mean temperature will increase more than 0.7-0.9 °C and 2.8-2.9 °C, and monthly precipitation by 50 % and 25-41 %, respectively. However, the root mean square (RMS) errors and bias of percentage change for monthly precipitation in summertime are 26.8 % and 4.3 %, respectively. These data provide an early warning and have implications for local climate policy response.
AB - Recently, local governments have an increasing need to take extensive and effective local measures to adapt to regional climate change, but have difficulty knowing how and when to adapt to such change. This study aims: 1) to characterize an efficient and cost-effective database management tool (DMT) for developing a Geographic Information System (GIS) based approach to using observed and projected data, for decision-making by non-expert government authorities, and 2) to document how DMT can be used to provide specialized yet understandable climate change information to assist local decision-makers in clarifying regional priorities within a wide array of adaptation options. The DMT combines climate change mapping, statistical GIS, and a vulnerability assessment. Okutama-machi, a 225.63 km2 sparsely populated mountainous region (2012 population 5,856) northwest of Tokyo, Japan, was chosen for this pilot study. In this paper, the most recent regional climate projections (5 km resolution) are transcribed into an understandable form for use by non-expert citizens who use the GIS-based DMT. Results illustrate qualitative agreement in projection of summer daily mean temperatures; the mean temperature increase at Okutama-machi is the greatest of any area in Tokyo. In comparing near future and future conditions, August monthly mean temperature will increase more than 0.7-0.9 °C and 2.8-2.9 °C, and monthly precipitation by 50 % and 25-41 %, respectively. However, the root mean square (RMS) errors and bias of percentage change for monthly precipitation in summertime are 26.8 % and 4.3 %, respectively. These data provide an early warning and have implications for local climate policy response.
KW - Climate change projection
KW - Database management system (DMS)
KW - Geographic information system (GIS)
KW - Local government decision-making
KW - Okutama-machi
KW - Regional climate change
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U2 - 10.1007/s11027-013-9450-6
DO - 10.1007/s11027-013-9450-6
M3 - Article
AN - SCOPUS:84899930190
SN - 1381-2386
VL - 19
SP - 589
EP - 614
JO - Mitigation and Adaptation Strategies for Global Change
JF - Mitigation and Adaptation Strategies for Global Change
IS - 5
ER -
