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| Titel |
Mapping Heat-related Risks for Community-based Adaptation Planning under Uncertainty |
| VerfasserIn |
Yingjiu Bai, Ikuyo Kaneko, Hikaru Kobayashi, Kazuo Kurihara, Hidetaka Sasaki, Akihiko Murata, Izuru Takayabu |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250136344
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| Publikation (Nr.) |
 EGU/EGU2016-17364.pdf |
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| Zusammenfassung |
| Climate change is leading to more frequent and intense heat waves. Recently, epidemiologic
findings on heat-related health impacts have reinforced our understanding of the mortality
impacts of extreme heat. This research has several aims: 1) to promote climate prediction
services with spatial and temporal information on heat-related risks, using GIS (Geographical
Information System), and digital mapping techniques; 2) to propose a visualization approach
to articulating the evolution of local heat-health responses over time and the evaluation of
new interventions for the implementation of valid community-based adaptation strategies and
reliable actionable planning; and 3) to provide an appropriate and simple method of adjusting
bias and quantifying the uncertainty in future outcomes, so that regional climate
projections may be transcribed into useful forms for a wide variety of different
users.
Following the 2003 European heat wave, climatologists, medical specialists, and social
scientists expedited efforts to revise and integrate risk governance frameworks for
communities to take appropriate and effective actions themselves. Recently, the Coupled
Model Intercomparison Project (CMIP) methodology has made projections possible for
anyone wanting to openly access state-of-the-art climate model outputs and climate
data to provide the backbone for decisions. Furthermore, the latest high-solution
regional climate model (RCM) has been a huge increase in the volumes of data
available.
In this study, we used high-quality hourly projections (5-km resolution) from the
Non-Hydrostatic Regional Climate Model (NHRCM-5km), following the SRES-A1B
scenario developed by the Meteorological Research Institute (MRI) and observational data
from the Automated Meteorological Data Acquisition System, Japan Meteorological Agency
(JMA). The NHRCM-5km is a dynamic downscaling of results from the MRI-AGCM3.2S
(20-km resolution), an atmospheric general circulation model (AGCM) driven by the
ensemble of mean sea surface temperatures derived from the CMIP3 coupled GCMs. This
contribution demonstrates how composite heat-related risk maps with a visualization of
combined predicted population and the 5-km resolution climate projections, can be used in
community-based adaptation planning in Japan. To test this approach, Tokyo (area 2190.9
km2; population 13.50 million as of 1 December 2015), a Japanese megacity, was chosen for
a pilot study. Our challenges will be facilitated by the formation of research partnerships
involving epidemiologists, climate scientists, and local stakeholders. Hopefully, the
methodology could be transferred to developing countries to aid in planning heat adaptation. |
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