The paradigm shift from post disaster response to a proactive risk reduction approach requires meteorological, hydrological and climate services to support science-based risk management decisions, as well as investments in early warning systems (Figure 2).
An increasing number of countries are taking steps at national to local levels to reduce risks associated with natural hazards. Among issues hampering these efforts is a lack of data concerning a country’s past climate to quantify hazard characteristics (e.g., frequency, severity and location) of local climatic extremes in the future.
An essential starting point for reducing risks is a quantitative assessment which combines information about the hazards with exposures and vulnerabilities of the population or assets (e.g., agricultural production, infrastructure and homes, etc). The hazard side of the equation uses historical data and forward looking modelling and forecasting about environmental conditions such as tropical cyclones, rainfall, soil moisture and hill slope stability, mountain weather patterns and river basin hydrology. This must be augmented with socio-economic data that quantifies exposure and vulnerability (for instance casualties, construction damages, crop yield reduction and water shortages). Equipped with the quantitative risk information, countries can develop risk management strategies using early warning systems to reduce casualties; medium and long-term sectoral planning (such as land zoning, infrastructure development, water resource management, agricultural planning) to reduce economic losses and build livelihood resilience, and weather-indexed insurance and risk financing mechanisms to transfer the financial impacts of disasters. This must be underpinned by effective policies, legislation and legal frameworks, and institutional coordination mechanisms as well as information and knowledge sharing, education and training.
Figure 2: Elements of a comprehensive DRR Framework based on the Hyogo Framework for Action 2005-2015
The emergence of climate prediction provides opportunities to increase the lead times of early warnings (Figure 3). For instance, seasonal climate outlooks help governments predict – and manage – excessive or deficient rainfall. Historical data has traditionally been used for analysis of hazards patterns. But this is no longer sufficient, because hazard characteristics are changing as a result of climate change. For instance a 100-year flood or drought may become a 30-year flood or drought or, simply said, more severe events could happen more frequently in the future weather and climate services with forecasts from the next hour to seasonal through to decadal time scales are therefore needed to inform long-term investments and strategic planning, for instance, coastal zone management, development of new building codes and the retrofitting of infrastructure to withstand more frequent and severe hazards.
Figure 3: Seamless hydrometeorological and climate services for various risk management applications
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