| World Climate Applications and Services Programme (WCASP) |
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Programmes > WCP > WCASP / CLIPS >
The World Climate Applications and Services Programme (WCASP) fosters the effective application of climate knowledge and information for the benefit of society and the provision of climate services, including the prediction of significant climate variations both natural and as a result of human activity. The Climate Information and Prediction Services (CLIPS) project is an implementation arm of WCASP around the globe. It strives to take advantage of current data bases, increasing climate knowledge and improving prediction capabilities to limit the negative impacts of climate variability and to enhance planning activities based on the developing capacity of climate science.
CLIMATE APPLICATIONS
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CLIPS Project
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Climate and Health
Floods, storms and heat directly affect health. Climate indirectly affects health through its influence on air pollution, on the ecosystems that provide food and water and on vectors and pathogens that cause infectious diseases.
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Background
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Climate and Energy
Climate information supports optimal development and use of renewable energy resources such as hydropower and wind, solar, biological and geothermal energies.
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Capacity Building
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Climate and Tourism
The tourism industry, particularly in coastal zones and mountain areas, is highly vulnerable to climate hazards, and to sea level rise and changing snow and glacier conditions due to climate change. Climate information helps reduce risks and plan effectively.
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CLIPS Focal Points
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Urban and Building Climatology
Climate information on energy balance, heat or cool islands, winds and air quality as well as storms, floods and droughts is vital to urban design and management.
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Regional Climate Outlook Forums (RCOFs)
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Climate and Water
Effective integration of climate and hydrological information in decision making in water resource management reduces risk to climate variability and change.
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Seasonal-Interannual Predictions
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Climate and Agriculture
The use of seasonal prediction and climate change scenarios are important in agricultural production and food security systems.
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El Niño/La Niña
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