Adaptation Baselines Through V&A Assessments Prof. Helmy Eid Climate Change Experts (SWERI) ARC Egypt Material for : Montreal Workshop 2001.

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Presentation transcript:

Adaptation Baselines Through V&A Assessments Prof. Helmy Eid Climate Change Experts (SWERI) ARC Egypt Material for : Montreal Workshop 2001

ADAPTATION BASELINES General Recommendations on Adaptation Baselines ■ - Baseline (reference). The baseline is any datum against which change is measured. It might be a “current baseline,” in which case it represents observable, present-day conditions. - It also might be a “future baseline,” which is a projected future set of conditions, excluding the driving factor of interest. - Alternative interpretations of reference conditions can give rise to multiple baselines. ■ Adaptation baseline of policies and measures could be defined as the set of policies and measures already taken by various concerned authorities, and NGOs within the frame of the precautionary principle, to help agriculture, water resources and demand, human health and coastal zones as well as minimize adverse impacts of warming and sea level rise.

■ It is recommended that the V&A assessments need to develop dataset and baseline, and this could be done by identifying data needs and availability and establishing dataset and baselines as follows: ■ Identify climatological and sea-level rise that are relevant to studied method(s). ■ Identify non-climatic data required for method development, calibration and testing (e.g. river flow data, maps of crop distribution), for methods application (e.g. soil data, beach profile data, country GDP), and any additional data (e.g. population density statistics). ■ Assess availability of data; sources, forms, problems of obtaining data (cost, accessibility, status of data, documentation, compatibility and uncertainty) ■ Evaluate available data to establish their stability for selected methods by determining; time resolution, completeness of records, quality, sites number and their spatial distribution (for spatial interpolations).

■ Develop the baseline climate dataset: ■ Identify stations with a good length of record (ideally 30 years), check data for errors, missing data, clean data, availability at appropriate time resolution, spatial or temporal interpolation. - Daily data can be derived from monthly values by simple interpolation or using a weather generators. - Spatial datasets can be developed by tools available (GIS, and UNUSPLIN). ■Additional non-climatic data may be required for method development (calibration and application, specific data relating to sector and exposure unit will be required (observed crop phenology and yield, soil data, river discharge, health statistics, historical changes in relative sea- level.

■Interpret results and Synthesis: A range of climatic and non-climatic data may be required; geographical, technological, managerial, legislative, economic, social and political. ■ Interpret data to describe baselines: Having developed a good quality datasets to complete the assessment, it is necessary to interpret data for describing climatic and non-climatic baselines, which - Need to meet the specific requirements of sector and exposure unit. - Need to full the requirements of the entire assessment including cross-sectoral dependencies. ■ In any adaptation plan, a survey of adaptation baseline policies, measures, environmental conditions, available technical tools and past experience is necessary to ensure suitability of the adaptation measure to be taken. ■ It could be recommended that a strategic environmental impact assessment must be carried out for any policy of adaptation and an environmental impact assessment of any measure.

■ The use of linked model approach uses GCM results and results from simple climate models to obtain regional projections of climate change. (SCENGEN, CLIMPACTS VANDACLIM) are suitable for a multiple sectors impact assessment and allow the user to explore a wide range of uncertainty and introduce a time dimension. ■ It is recommended to assess availability of input data for an RCM to improve climate change scenarios. ■ The use of the process-based models (Simulation models (e.g. DSSAT, COTTAM, SORKAM, and CROPSYST) is more efficient in the V&A assessments especially in the agricultural sector. ■ It could be recommended that the use of the cost-benefit models and the General equilibrium models (Basic Linked System; BLS) as socioeconomic models is more efficient in the V&A assessments especially in the agricultural sector. Recardian (Cross sectional) Model could be used also. ■ Adaptation baselines could be established in the agriculture, water resources, coastal zones and human health sectors through the experiences detected from the general current presentation on V&A methodologies.

■ ■ Improving Assessments of Impacts, Vulnerability and Adaptation The following are only three from high priorities for narrowing gaps between current knowledge and policymaking needs: (The IPCC WG II report). - Quantitative assessment of the sensitivity adaptive capacity and vulnerability of natural and human systems to climate change. - Assessment of opportunities to include scientific information on impacts, vulnerability, and adaptation in decision-making processes. - Improvement of systems and methods for long term monitoring and understanding. Can you add more to the list? ■ The Egyptian V&A assessment study on the agricultural sector can be followed in the near countries with similar conditions (an outline for the case study is available in the current presentation) Do you want to see?

Steps of Vulnerability and Adaptation Assessment SCENGEN Monthly Climatic Data CLIMATE DATA GENERATOR Daily Climatic Data DSSAT Other Simulation models developed in Crystal Ball Impact Assessment MAGICC Climatic Data in DSSATS Model Format Experiments/ Technology options Adaptation Options Experiments/ Technology options Develop scenarios Select GCM Socio-economic scenario