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Ground-based disaster damage assessments typically take the form of a team of experts being sent to the affected areas to conduct a survey. This approach is time-consuming, difficult, and costly. An alternative to this is an assessment based on satellite data, which can provide faster, cheaper, and possibly accurate insights into disaster’s specific impacts. An even timelier option of disaster ‘nowcasting’ is supposed to inform on impacts during or very shortly after the event. Typically, this has been done using risk models, but these usually do not account for compounding and cascading effects. We propose a novel nowcasting approach for tropical cyclones employing pre-existing socio-economic and demographic data and calibrated with satellite data. The method could be used to assess cyclone impacts based only on its known trajectory, and even before post-event satellite imagery is available. We investigate the feasibility of this approach focusing on Fiji and its agricultural sector. We link remote sensing data with available household surveys and the agricultural census data to identify potential correlates of vegetation damage from cyclones. If robust enough, these correlates could later be used for nowcasting cyclone impacts. We show that remote sensing data, when combined with pre-event socio-economic and demographic data, can be used for both nowcasting and post-disaster damage assessments.

Many approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets., United States. Department of Energy. Office of Science (DE-FG02-94ER61937), Brazil. National Council for Scientific and Technological Development (Processes 312975/2017-1 and 449951/2014-6), Integrated Global Systems Model (IGSM), Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change

This study quantifies the impact of typhoons on rice production in the Philippines. To this end, satellite-derived reflectance data are used to detect the location of rice fields at 500-m resolution. Utilizing typhoon-track data within a wind field model and satellite-derived precipitation measures, fragility curves are then employed to proxy the damage of storms on rice production within each rice field. The results from a panel spatial regression model show that typhoons substantially reduced local provincial production in the quarter of the strike, having caused losses of up to 12.5 million tons since 2001. Using extreme value theory to predict future losses, the results suggest that a typhoon like the recent Haiyan, which is estimated to have caused losses of around 260 000 tons, has a return period of 13 years. This methodology can provide a relatively timely tool for rice damage assessments after tropical cyclones in the region., United States. Dept. of Energy. Office of Science (Grant DE-FG02-94ER61937), United States. Environmental Protection Agency (Grant XA-83600001-1), Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change

We investigate the effect of climate change on crop productivity in Africa using satellite derived data on land use and net primary productivity (NPP) at a small river basin scale, distinguishing between the impact of local and upper-catchment weather. Regression results show that both of these are determining factors of local cropland productivity. These estimates are then combined with climate change predictions obtained from two general circulation models (GCMs) under two greenhouse gas emissions (GHG) assumptions to evaluate the impact of climate change by 2100. For some scenarios significant decreases are predicted over the northern and southern parts of Africa.

PR, IFPRI4; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

We assess the ability of global water systems, resolved at 282 large river basins or Assessment Sub Regions (ASRs), to the meet water requirements over the coming decades under integrated projections of socioeconomic growth and climate change. We employ a Water Resource System (WRS) component embedded within the MIT Integrated Global System Model (IGSM) framework in a suite of simulations that consider a range of climate policies and regional hydroclimatic changes through the middle of this century. We find that for many developing nations water-demand increases due to population growth and economic activity have a much stronger effect on water stress than climate change. By 2050, economic growth and population change alone can lead to an additional 1.8 billion people living in regions with at least moderate water stress. Of this additional 1.8 billion people, 80% are found in developing countries. Uncertain regional climate change can play a secondary role to either exacerbate or dampen the increase in water stress due to socioeconomic growth. The strongest climate impacts on relative changes in water stress are seen over many areas in Africa, but strong impacts also occur over Europe, Southeast Asia and North America. The combined effects of socioeconomic growth and uncertain climate change lead to a 1.0 to 1.3 billion increase of the world's 2050 projected population living in regions with overly exploited water conditions— where total potential water requirements will consistently exceed surface-water supply. Under the context of the WRS model framework, this would imply that adaptive measures would be taken to meet these surface-water shortfalls and would include: water-use efficiency, reduced and/or redirected consumption, recurrent periods of water emergencies or curtailments, groundwater depletion, additional inter-basin transfers, and overdraw from flow intended to maintain environmental requirements.

PR, IFPRI3; ISI; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

PR, IFPRI3; ISI; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

PR, IFPRI3; ISI; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

PR, IFPRI3; ISI; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)