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LA_06: Assessment of Impacts and Adaptation Measures for the Water Resources Sector due to Extreme Events under Climate Change Conditions in Central America Countries: Guatemala, Belize, Honduras, Nicaragua, El Salvador, Costa Rica and Panama. Sectors: Water resources and interacting sectors (Agriculture, tourism, disaster management) PI: Dr. Walter Fernández, UCR. Projects in Meso-America: LA__29: Integrated Assessment of Social Vulnerability and Adaptation to Climate Variability and Change Among Farmers in Mexico and Argentina Countries: 2, Mexico and Argentina, also includes Colombia, Brazil and Chile. Sectors: Agriculture and Water PI: Dr. Carlos Gay, UNAM. SIS_06. The Threat of Dengue Fever – Assessment of Impacts and Adaptation to Climate Change in Human Health in the Caribbean. Countries: Jamaica, Barbados, Trinidad and Tobago and St. Kitts. Sectors: Climate-Health and disease. PI: Drs. A. A. Chen, UWI and S. C. Rawlins, CAREC.

LA_06: Assessment of Impacts and Adaptation Measures for the Water Resources Sector due to Extreme Events under Climate Change Conditions in Central America

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 LA_06: Assessment of Impacts and Adaptation Measures for the Water Resources Sector due to Extreme Events under Climate Change Conditions in Central America Countries: Guatemala, Belize, Honduras, Nicaragua, El Salvador, Costa Rica and Panama. Sectors: Water resources and interacting sectors (Agriculture, tourism, disaster management)PI: Dr. Walter Fernández, UCR.

Projects in Meso-America:

LA__29: Integrated Assessment of Social Vulnerability and Adaptation to Climate Variability and Change Among Farmers in Mexico and ArgentinaCountries: 2, Mexico and Argentina, also includes Colombia, Brazil and Chile. Sectors: Agriculture and WaterPI: Dr. Carlos Gay, UNAM.

SIS_06. The Threat of Dengue Fever – Assessment of Impacts and Adaptation to Climate Change in Human Health in the Caribbean. Countries: Jamaica, Barbados, Trinidad and Tobago and St. Kitts. Sectors: Climate-Health and disease.PI: Drs. A. A. Chen, UWI and S. C. Rawlins, CAREC.

LA06:

Hypothetical “Amoeba” Diagram of Community Adaptive Capacity

100 75 50 25

0

Optimum

Income Agricultural Diversity

Yield Variability

Physical Resource Index

Market Involvement

Hazard frequency

Production Costs

Accessibility of Services

Community 1

Community 2

LA29 Methodology for V&A:

SIS06, Methodology SIS06, Methodology include:include:

Retrospective study Retrospective study (interdisciplinary)(interdisciplinary)

Statistical downscalingStatistical downscaling Pilot ProjectPilot Project SRES emission scenariosSRES emission scenarios

The linkage between climate and non-climate scenarios will be achieved by

Interdisciplinary teams work.Interdisciplinary teams work.

Future Global and Regional Future Global and Regional Scenarios (Tools like MAGICC & Scenarios (Tools like MAGICC & SCENGEN, PRECIS ?,…).SCENGEN, PRECIS ?,…).

Climate Information used by the Climate Information used by the three projects includesthree projects includes

1.1.              Historical climatic data. Historical climatic data. – a.a.              Local/regional data. Public domain databases. Local/regional data. Public domain databases.

National Meteorological Services & Local stationsNational Meteorological Services & Local stations– b.b.       R       Re-analyses (e-analyses (NCEP)NCEP)

  2.2. Aerological DataBases: CARDS, Aerological DataBases: CARDS, PACS-SONETPACS-SONET

3. 3. GCM outputsGCM outputs..

Variables required for I, A & V Variables required for I, A & V

assessment:assessment:

Temperature (Max., Min., Mean)Temperature (Max., Min., Mean) PrecipitationPrecipitation Solar RadiationSolar Radiation WindsWinds RunoffRunoff Also, some non-climate variables: power Also, some non-climate variables: power

generation, yields, population growth, generation, yields, population growth, GDP, etc.GDP, etc.

Some Critical Uncertainties in the Some Critical Uncertainties in the

projects are:projects are:

Spatial downscaling of climate and Spatial downscaling of climate and socio-economic scenarios. socio-economic scenarios.

Behaviour of Extreme Events in Behaviour of Extreme Events in climate change scenarios: trends, climate change scenarios: trends, frequency, intensity. frequency, intensity.

Baseline.Baseline.

Spatial and Temporal scales include:Spatial and Temporal scales include:

Spatial scale: Spatial scale: – Local / Regional. Local / Regional. – Global. For climate change scenarios and Global. For climate change scenarios and

downscaling techniquesdownscaling techniques   Temporal: daily, monthly, seasonal, Temporal: daily, monthly, seasonal,

annual, decadal.annual, decadal. Baseline:Baseline: 1961-1990 or at least 30 years 1961-1990 or at least 30 years

of data of the variables described.of data of the variables described.

Other projects in the region:Other projects in the region: ““Development of a regional climate model system for Development of a regional climate model system for

Central America”.Central America”. Supported by NOAA-OGP. Supported by NOAA-OGP. PI. Dr. Jorge PI. Dr. Jorge A. Amador, CIGEFI-UCR, Costa Rica.A. Amador, CIGEFI-UCR, Costa Rica.

““Climate variability and its impacts on the Mexican, Climate variability and its impacts on the Mexican, Central American and Caribbean region”.Central American and Caribbean region”. Supported by Supported by IAI as a CRN. PI. Dr. Victor Magaña, UNAM, México.IAI as a CRN. PI. Dr. Victor Magaña, UNAM, México.

““When Oceans conspire: Examining the effect of When Oceans conspire: Examining the effect of concurrent SST anomalies in the Tropical Atlantic and concurrent SST anomalies in the Tropical Atlantic and Pacific on Caribbean Rainfall”.Pacific on Caribbean Rainfall”. Supported by IAI as a Supported by IAI as a PESCA project. PIs. Drs. Michael Taylor and Anthony Chen, PESCA project. PIs. Drs. Michael Taylor and Anthony Chen, UWI, Jamaica. UWI, Jamaica.

““Multi-objective study of climate variability for mitigation Multi-objective study of climate variability for mitigation in the trade convergence climate complex”.in the trade convergence climate complex”. Supported by Supported by IAI as a CRN. PI. M.Sc. Pilar Cornejo, ESPOL, Ecuador.IAI as a CRN. PI. M.Sc. Pilar Cornejo, ESPOL, Ecuador.