scholarly journals Hands-on Tutorial on a Modeling Framework for Projections of Climate Change Impacts on Health

Epidemiology ◽  
2019 ◽  
Vol 30 (3) ◽  
pp. 321-329 ◽  
Author(s):  
Ana M. Vicedo-Cabrera ◽  
Francesco Sera ◽  
Antonio Gasparrini
2012 ◽  
Vol 9 (11) ◽  
pp. 13037-13081 ◽  
Author(s):  
E. Sproles ◽  
A. Nolin ◽  
K. Rittger ◽  
T. Painter

Abstract. Globally maritime snow comprises 10% of seasonal snow and is considered highly sensitive to changes in temperature. This study investigates the effect of climate change on maritime mountain snowpack in the McKenzie River Basin (MRB) in the Cascades Mountains of Oregon, USA. Melt water from the MRB's snowpack provides critical water supply for agriculture, ecosystems, and municipalities throughout the region especially in summer when water demand is high. Because maritime snow commonly falls at temperatures close to 0 °C, accumulation of snow versus rainfall is highly sensitive to temperature increases. Analyses of current climate and projected climate change impacts show rising temperatures in the region. To better understand the sensitivity of snow accumulation to increased temperatures, we modeled the spatial distribution of snow water equivalent (SWE) in the MRB for the period of 1989–2009 with the SnowModel spatially distributed model. Simulations were evaluated using point-based measurements of SWE, precipitation, and temperature that showed Nash-Sutcliffe Efficiency coefficients of 0.83, 0.97, and 0.80, respectively. Spatial accuracy was shown to be 82% using snow cover extent from the Landsat Thematic Mapper. The validated model was used to evaluate the sensitivity of snowpack to projected temperature increases and variability in precipitation, and how changes were expressed in the spatial and temporal distribution of SWE. Results show that a 2 °C increase in temperature would shift peak snowpack 12 days earlier and decrease basin-wide volumetric snow water storage by 56%. Snowpack between the elevations of 1000 and 1800 m is the most sensitive to increases in temperature. Upper elevations were also affected, but to a lesser degree. Temperature increases are the primary driver of diminished snowpack accumulation, however variability in precipitation produce discernible changes in the timing and volumetric storage of snowpack. This regional scale study serves as a case study, providing a modeling framework to better understand the impacts of climate change in similar maritime regions of the world.


2020 ◽  
Author(s):  
Aksara Putthividhya ◽  
Wimolpat Bumbudsanpharoke Khamkanya ◽  
Somkiat Prajamwong

<p>Recent research has demonstrated the multidimensional and multi-sectoral impacts of climate change, evidencing the need to develop national and sub-national integrated tools and policies for the analysis of impacts and adaptation, especially central to local policy recommendation and implementation. This framework combines an area-based economic optimization model with the hydrological model WEAP, and represents the socio-economic, agronomic, and hydrologic systems in a spatially explicit manner covering dimensions and scales relevant to downscaled climate change impacts.  Simulated scenarios are setup to incorporate climate scenario, prior-historic dependence to adaptation conformity, and two policy-based adaptation scenarios. Preliminary results indicate that climate change may impact severely in rain-fed agricultural area and also to irrigation systems reducing water availability and security and crop yields, and increasing in more efficient irrigation water allocation.  The adaptation strategies analysis based on socio-economic, agronomic, and hydrologic dimensions capitalizes the key role of Thailand supply- and demand-side management policy in facilitating adaptation. The under developing framework is currently anticipated to be a useful tool for supporting water resources and climate change policy making.  It can contribute to improve understanding on potential impacts of climate change, multi-sectoral linkages, multi-scale vulnerability, and adaptation programs.   </p>


2019 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)

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