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Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural disasters. Agriculture GDP is a critical indicator for measurement of the primary sector, on which 60 percent of the world's population depends for their livelihoods. Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 × 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper examines the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP, where nearly 1.2 billion people live. The findings show an estimated US$432 billion of agricultural GDP circa 2010.

Agricultural productivity.

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This paper describes an approach to forecasting future climate at the local level using historical weather station and satellite data and future projections of climate data from global climate models (GCMs) that is easily understandable by policymakers and planners. It describes an approach to synthesize the myriad climate projections, often with conflicting messages, into an easily-interpreted set of graphical displays that summarizes the basic implications of the ensemble of available climate models. The method described in the paper can be applied to publicly-available data for any country and for any number of climate models. It does not depend on geographic scale and can be applied at the subnational, national, or regional level. The paper illustrates the results for future climate for Ethiopia using future climate scenarios projects by 8 global climate models. The graphical displays of nine possible future climate regimes (average temperature, precipitation and their seasonal distribution) for each grid-cell about 50km X 50 km). It also provides the probability associated with each of the nine-climate regimes.

Climate --- Climate Change --- Climate change --- Climate forecasts --- Climate models --- Climate system --- Climate variation --- Climatic research unit --- Cru --- Emissions --- Environment --- GCM --- Global Environment --- Global scale --- Global warming --- Intergovernmental panel on climate change --- IPCC --- Precipitation --- Rainfall --- Satellites --- Temperature --- Weather --- Weather stations

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Scientific evidence indicates that global warming could well lead to a sea-level rise of 1 meter or more in the 21st century. This paper seeks to quantify how a 1-meter sea-level rise that would affect coastal wetlands in 76 developing countries and territories, taking into account how much of wetlands would be submerged and how likely the wetlands would move inland as the coastline recedes. It is estimated that approximately 64 percent of the freshwater marsh, 66 percent of Global Lakes and Wetlands Database coastal wetlands, and 61 percent of brackish/saline wetlands are at risk. A large percentage of this loss would be shouldered by two regions: East Asia and the Pacific, and the Middle East and North Africa. At the country level, the results are extremely skewed with a small number of countries being severely affected. In East Asia, China and Vietnam would bear the brunt of these losses. In the Middle East and North Africa, Libya and Egypt would see the most losses. A rough estimate of the economic value of the goods and services produced by wetlands at risk is approximately USD 630 million per year in 2000 U.S. dollars.

Biodiversity --- Climate change --- Climate Change and Environment --- Common Property Resource Development --- Energy --- Environment --- Environmental Economics & Policies --- GIS --- Sea level rise --- Valuation --- Wetlands

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Greenhouse gas emissions are largely determined by how energy is created and used, and policies designed to encourage mitigation efforts reflect this reality. However, an unintended consequence of an energy-focused strategy is that the set of policy instruments needed to tap mitigation opportunities in agriculture is incomplete. In particular, market-linked incentives to achieve mitigation targets are disconnected from efforts to better manage carbon sequestered in agricultural land. This is especially important for many countries in Eastern Europe and Central Asia where once-productive land has been degraded through poor agricultural practices. Often good agricultural policies and prudent natural resource management can compensate for missing links to mitigation incentives, but only partially. At the same time, two international project-based programs, Joint Implementation and the Clean Development Mechanism, have been used to finance other types of agricultural mitigation efforts worldwide. Even so, a review of projects suggests that few countries in Eastern Europe and Central Asia take full advantage of these financing paths. This paper discusses mitigation opportunities in the region, the reach of current mitigation incentives, and missed mitigation opportunities in agriculture. The paper concludes with a discussion of alternative policies designed to jointly promote mitigation and co-benefits for agriculture and the environment.

Agriculture --- Climate change --- Climate Change Economics --- Climate Change Mitigation and Green House Gases --- Degraded land --- Energy and Environment --- Environmental Economics & Policies --- Greenhouse gases --- Mitigation --- Rural Development --- Soil carbon sequestration --- Wetlands

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This paper describes an approach to forecasting future climate at the local level using historical weather station and satellite data and future projections of climate data from global climate models (GCMs) that is easily understandable by policymakers and planners. It describes an approach to synthesize the myriad climate projections, often with conflicting messages, into an easily-interpreted set of graphical displays that summarizes the basic implications of the ensemble of available climate models. The method described in the paper can be applied to publicly-available data for any country and for any number of climate models. It does not depend on geographic scale and can be applied at the subnational, national, or regional level. The paper illustrates the results for future climate for Ethiopia using future climate scenarios projects by 8 global climate models. The graphical displays of nine possible future climate regimes (average temperature, precipitation and their seasonal distribution) for each grid-cell about 50km X 50 km). It also provides the probability associated with each of the nine-climate regimes.

Climate --- Climate Change --- Climate change --- Climate forecasts --- Climate models --- Climate system --- Climate variation --- Climatic research unit --- Cru --- Emissions --- Environment --- GCM --- Global Environment --- Global scale --- Global warming --- Intergovernmental panel on climate change --- IPCC --- Precipitation --- Rainfall --- Satellites --- Temperature --- Weather --- Weather stations