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IntroductionThe scarcity of resources have affected food production, which has challenged the ability of Iran to provide adequate food for the population. Iterative and mounting sanctions on Iran by the international community have seriously eroded Iran's access to agricultural technology and resources to support a growing population. Limited moisture availability also affects Iran's agricultural production. The aim of this study was to analyze the influence of inflation, international sanctions, weather disturbances, and domestic crop production on the price of rice, wheat and lentils from 2010 to 2021 in Iran.MethodData were obtained from the statistical yearbooks of the Ministry of Agriculture in Iran, Statistical Center of Iran, and the Central Bank of Iran. We analyzed econometric measures of food prices, including CPI, food inflation, subsidy reform plan and sanctions to estimate economic relationships. After deflating the food prices through CPI and detrending the time series to resolve the non-linear issue, we used monthly Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation data to analyze the influence of weather disturbances on food prices.Results and discussionThe price of goods not only provides an important indicator of the balance between agricultural production and market demand, but also has strong impacts on food affordability and food security. This novel study used a combination of economic and climate factors to analyze the food prices in Iran. Our statistical modeling framework found that the monthly precipitation on domestic food prices, and ultimately food access, in the country is much less important than the international sanctions, lowering Iran's productive capability and negatively impacting its food security.

Agricultural scientists are pursuing sustainable intensification strategies to increase global food availability, but integration from research to impact at the local-level requires knowledge of demographic and human-environment to enhance the adaptive capacity of farmers cultivating via nutrition-sensitive agricultural investments.

Virtually all climate monitoring and forecasting efforts concentrate on hazards rather than on impacts, while the latter are a priority for planning emergency activities and for the evaluation of mitigation strategies. Effective disaster risk management strategies need to consider the prevailing "human terrain" to predict who is at risk and how communities will be affected. There has been little effort to align the spatiotemporal granularity of socioeconomic assessments with the granularity of weather or climate monitoring. The lack of a high-resolution socioeconomic baseline leaves methodical approaches like machine learning virtually untapped for pattern recognition of extreme climate impacts on livelihood conditions. While the request for "better" socioeconomic data is not new, we highlight the need to collect and analyze environmental and socioeconomic data together and discuss novel strategies for coordinated data collection via mobile technologies from a drought risk management perspective. A better temporal, spatial, and contextual understanding of socioeconomic impacts of extreme climate conditions will help to establish complex causal pathways and quantitative proof about climate-attributable livelihood impacts. Such considerations are particularly important in the context of the latest big data-driven initiatives, such as the World Bank's Famine Action Mechanism (FAM).

Changing precipitation patterns caused by climate change are expected to have major impacts on food security and nutrition in agrarian areas in developing countries. However, the linkages between the duration and severity of precipitation shocks and their effects on child nutrition and household food security metrics remain underexplored. In this study, we used Feed the Future datasets from Ghana and Bangladesh to examine the impact of precipitation extremes on nutrition, measured by children’s height-for-age and weight-for-height Z-scores, and food security, measured by the Household Hunger Scale. We used a spatial error regression to control for the effects of spatial autocorrelation, and we found an association between precipitation shocks and household hunger in both Ghana and Bangladesh, as well as an association between higher rainfall and worse child nutrition in Ghana.

Early warnings of the risks of pest and disease outbreaks are becoming more urgent, with substantial increases in threats to agriculture from invasive pests. With geospatial data improvements in quality and timeliness, models and analytical systems can be used to estimate potential areas at high risk of yield impacts. The development of decision support systems requires an understanding of what information is needed, when it is needed, and at what resolution and accuracy. Here, we report on a professional review conducted with 53 professional agronomists, retailers, distributors, and growers in East Africa working with the Syngenta Foundation for Sustainable Agriculture. The results showed that respondents reported fall armyworm, stemborers and aphids as being among the most common pests, and that crop diversification was a key strategy to reduce their impact. Chemical and cultural controls were the most common strategies for fall armyworm (FAW) control, and biological control was the least known and least used method. Of the cultural control methods, monitoring and scouting, early planting, and crop rotation with non-host crops were most used. Although pests reduced production, only 55% of respondents were familiar with early warning tools, showing the need for predictive systems that can improve farmer response.

Despite early warning signs about threats to food security, humanitarian interventions often lag behind these warning signs. Climate and conflict conditions are among the most important factors preceding food system failures and malnutrition crises around the world. Research shows how conflict and climate conditions can upend functional food and economic systems, but this research does not address the severe health impacts of these conditions on infants and young children. Translating quantitative research findings into humanitarian interventions requires geographical detail, resulting in location-specific alerts of risks of food insecurity. We describe how the use of readily available, spatially referenced quantitative data can support targeted interventions for nutrition resiliency. Effective humanitarian programmes for targeted nutrition interventions require real-time datasets on food security drivers and models that can provide actionable guidance to mitigate negative impacts of conflict and climate conditions on the people most susceptible to food insecurity. Although treatment of acute malnutrition is important, treating existing malnutrition is not enough. Instead, action to prevent acute malnutrition should be taken to minimise suffering and to maximise wellbeing, particularly in contexts prone to worsening climate and conflict conditions.

Food systems are at the center of a brewing storm consisting of a rapidly changing climate, rising hunger and malnutrition, and significant social inequities. At the same time, there are vast opportunities to ensure that food systems produce healthy and safe food in equitable ways that promote environmental sustainability, especially if the world can come together at the UN Food Systems Summit in late 2021 and make strong and binding commitments toward food system transformation. The NIH-funded Nutrition Obesity Research Center at Harvard and the Harvard Medical School Division of Nutrition held their 22nd annual Harvard Nutrition Obesity Symposium entitled “Global Food Systems and Sustainable Nutrition in the 21st Century” in June 2021. This article presents a synthesis of this symposium and highlights the importance of food systems to addressing the burden of malnutrition and noncommunicable diseases, climate change, and the related economic and social inequities. Transformation of food systems is possible, and the nutrition and health communities have a significant role to play in this transformative process.

Substantial investment from both the private and public sectors will be needed to achieve the ambitious Sustainable Development Goal 2 (SDG2), which focuses on ending poverty and achieving zero hunger. To harness the private sector, high quality, transparent metrics are needed to ensure that every dollar spent reaches the most marginalized segments of a community while still helping institutions achieve their goals. Satellite-derived Earth observations will be instrumental in accelerating these investments and targeting them to the regions with the greatest need. This article proposes two quantitative metrics that could be used to evaluate the impact of private sector activities on SDG2: measuring increases in yield over baseline and ensuring input availability and affordability in all markets.

As climate change continues, it is expected to have increasingly adverse impacts on child nutrition outcomes, and these impacts will be moderated by a variety of governmental, economic, infrastructural, and environmental factors. To date, attempts to map the vulnerability of food systems to climate change and drought have focused on mapping these factors but have not incorporated observations of historic climate shocks and nutrition outcomes. We significantly improve on these approaches by using over 580,000 observations of children from 53 countries to examine how precipitation extremes since 1990 have affected nutrition outcomes. We show that precipitation extremes and drought in particular are associated with worse child nutrition. We further show that the effects of drought on child undernutrition are mitigated or amplified by a variety of factors that affect both the adaptive capacity and sensitivity of local food systems with respect to shocks. Finally, we estimate a model drawing on historical observations of drought, geographic conditions, and nutrition outcomes to make a global map of where child stunting would be expected to increase under drought based on current conditions. As climate change makes drought more commonplace and more severe, these results will aid policy-makers by highlighting which areas are most vulnerable as well as which factors contribute the most to creating resilient food systems.

The goal of drought-related weather index insurance (WII) is to protect smallholder farmers against the risk of weather shocks and to increase their agricultural productivity. Estimates of precipitation and vegetation greenness are the two dominant satellite datasets. However, ignoring additional moisture- and energy-related processes that influence the response of vegetation to rainfall leads to an incomplete representation of the hydrologic cycle. This study evaluates the added value of considering multiple independent satellite-based variables to design, calibrate, and validate weather insurance indices on the African continent. The satellite data include two rainfall datasets, soil moisture, the evaporative stress index (ESI), and vegetation greenness. We limit artificial advantages by resampling all datasets to the same spatial (0.25°) and temporal (monthly) resolution, although datasets with a higher spatial resolution might have an added value, if considered as the single source of information for localized applications. A higher correlation coefficient between the moisture-focused variables and the normalized difference vegetation index (NDVI), an indicator for vegetation vigor, provides evidence for the datasets’ capability to capture agricultural drought conditions on the ground. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset, soil moisture, and ESI show higher correlations with the (lagged) NDVI in large parts of Africa, for different land covers and various climate zones, than the African Rainfall Climatology, version 2 (ARC2), rainfall dataset, which is often used in WII. A comparison to drought years as reported by farmers in Ethiopia, Senegal, and Zambia indicates a high “hit rate” of all satellite-derived anomalies regarding the detection of severe droughts but limitations regarding moderate drought events.

Aquaculture has the potential to sustainably meet the growing demand for animal protein. The availability of water is essential for aquaculture development, but there is no knowledge about the potential inland water resources of the Rwenzori region of Uganda. Though remote sensing is popularly utilized during studies involving various aspects of surface water, it has never been employed in mapping inland water bodies of Uganda. In this study, we assessed the efficiency of seven remote-sensing derived water index methods to map the available surface water resources in the Rwenzori region using moderate resolution Sentinel 2A/B imagery. From the four targeted sites, the Automated Water Extraction Index for urban areas (AWEInsh) and shadow removal (AWEIsh) were the best at identifying inland water bodies in the region. Both AWEIsh and AWEInsh consistently had the highest overall accuracy (OA) and kappa (OA &gt, 90%, kappa &gt, 0.8 in sites 1 and 2, OA &gt, 84.9%, kappa &gt, 0.61 in sites 3 and 4), as well as the lowest omission errors in all sites. AWEI was able to suppress classification noise from shadows and other non-water dark surfaces. However, none of the seven water indices used during this study was able to efficiently extract narrow water bodies such as streams. This was due to a combination of factors like the presence of terrain shadows, a dense vegetation cover, and the image resolution. Nonetheless, AWEI can efficiently identify other surface water resources such as crater lakes and rivers/streams that are potentially suitable for aquaculture from moderate resolution Sentinel 2A/B imagery.

Migration has long been used as a strategy for livelihood diversification in rural, subsistence communities. Yet in order for migration to effectively serve as a livelihood diversification strategy, it should meet certain conditions: migration should ease financial burdens, should confer access to economically valuable resources and information, and should broaden social networks. Using qualitative data gathered in 25 interviews with rural migrants to Ouagadougou, Burkina Faso, we examine how mobile phone technology has impacted migration as a livelihood diversification strategy. Our results show that while mobile phones facilitate migration, the advantages conferred may benefit migrants at the expense of the home communities. Mobile phones alleviate financial constraints, enable access to broader networks, and facilitate informational and resource support among migrants. Our results show limited evidence of migrants using mobile phone technology to provide resources or information to the home community. Our results highlight the need to reconsider the ways in which migration can be used as a livelihood diversification strategy in light of changing communication technologies to promote the economic success of both migrants and their home communities.

Rapidly expanding global trade in the past three decades has lifted millions out of people out of poverty. Trade has also reduced manufacturing wages in high income countries and made entire industries uncompetitive in some communities, giving rise to nationalist politics that seek to stop or reverse further trade expansion in the United States and Europe. Given complex and uncertain political support for trade, how might changes in trade policy affect the global food system’s ability to adapt to climate change? Here we argue that we can best understand food security in a changing climate as a double exposure: the exposure of people and processes to both economic and climate-related shocks and stressors. Trade can help us adapt to climate change, or not. If trade restrictions proliferate, double exposure to both a rapidly changing climate and volatile markets will likely jeopardize the food security of millions. A changing climate will present both opportunities and challenges for the global food system, and adapting to its many impacts will affect food availability, food access, food utilization and food security stability for the poorest people across the world. Global trade can continue to play a central role in assuring that global food system adapts to a changing climate. This potential will only be realized, however, if trade is managed in ways that maximize the benefits of broadened access to new markets while minimizing the risks of increased exposure to international competition and market volatility. For regions like Africa, for example, enhanced transportation networks combined with greater national reserves of cash and enhanced social safety nets could reduce the impact of ‘double exposure’ on food security.

Failures in either water systems or food systems, or a combination of system failures, could provide the underlying explanation for continued high levels of malnutrition in many regions. We focus on child health and offer the first spatially explicit analysis of the interaction between water source and food insecurity on children’s health in Burkina Faso, an African nation that continues to struggle with poor children’s health. We combine data from the 2010 Demographic and Health Survey, a small USAID water quality survey collected from community wells, and remotely sensed imagery. Results suggest that, in a few cases, reliable and clean water sources are positively correlated to children’s linear growth and weight gain, although in many regions, the interaction with community-level food production is critical to understanding health outcomes. The results also suggest that maternal health and nutrition during pregnancy and breastfeeding are foundational to the healthy development of young children. In all, the findings provide evidence of the importance of multi-sectoral interventions targeted at improving children’s health.

Ethiopia experiences significant climate-induced drought and stress on crop and livestock productivity, contributing to widespread food insecurity. Here, we present subseasonal crop water stress analyses that indicate degrading, growing conditions along Ethiopia’s eastern highlands, including productive and populated highland regions. These seasonally shifting areas of increasing water stress stretch from the north to south across eastern Ethiopia, intersecting regions of acute food insecurity and/or high population. Crop model simulations indicate that between 1982 and 2014, parts of eastern Amhara and eastern Oromia experienced increasing water deficits during the critical sowing, flowering, and ripening periods of crop growth. These trends occurred while population in these regions increased by 143% between 2000 and 2015. These areas of enhanced crop water stress in south-central Ethiopia coincide with regions of high population growth and ongoing crop extensification. Conversely, large regions of relatively unpopulated western Ethiopia are becoming wetter. These areas may therefore be good targets for agricultural development.

North Africa, the world's largest dust source, is non-uniform, consisting of a permanently arid region (Sahara), a semi-arid region (Sahel), and a relatively moist vegetated region (Savanna), each with very different rainfall patterns and surface conditions. This study aims to better understand the controlling factors that determine the variation of dust emission in North Africa over a 27-year period from 1982 to 2008, using observational data and model simulations. The results show that the model-derived Saharan dust emission is only correlated with the 10-m winds (W10m) obtained from reanalysis data, but the model-derived Sahel dust emission is correlated with both W10m and the Normalized Difference Vegetation Index (NDVI) that is obtained from satellite. While the Saharan dust accounts for 82% of the continental North Africa dust emission (1340–1570 Tg year−1) in the 27-year average, the Sahel accounts for 17% with a larger seasonal and inter-annual variation (230–380 Tg year−1), contributing about a quarter of the transatlantic dust transported to the northern part of South America. The decreasing dust emission trend over the 27-year period is highly correlated with W10m over the Sahara (R = 0.92). Over the Sahel, the dust emission is correlated with W10m (R = 0.69) but is also anti-correlated with the trend of NDVI (R = -0.65). W10m is decreasing over both the Sahara and the Sahel between 1982 and 2008, and the trends are correlated (R = 0.53), suggesting that Saharan/Sahelian surface winds are a coupled system, driving the inter-annual variation of dust emission.

NASA's Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, scheduled to launch no later than April 2018 (and currently slated for October 2017), is being developed to continue the multiyear observations of the earth's surface elevation, ice, and clouds started by ICESat. To increase the use of the satellite data after launch, the ICESat-2 mission invested in an applications program aimed at innovatively applying the data in a variety of fields. The program provides a framework for building a broad and well-defined user community during the prelaunch period to maximize the use of data products after launch and to provide early insight into the range of potential uses of the mission data. Ideas and research on how altimetry data will be used for decision making arise from the end users; therefore, the ICESat-2 mission is extending itself through its applications program.

A challenge in addressing climate risk in developing countries is that many regions have extremely limited formal data sets, so for these regions, people must rely on technologies like remote sensing for solutions. However, this means the necessary formal weather data to design and validate remote sensing solutions do not exist. Therefore, many projects use farmers’ reported perceptions and recollections of climate risk events, such as drought. However, if these are used to design risk management interventions such as insurance, there may be biases and limitations which could potentially lead to a problematic product. To better understand the value and validity of farmer perceptions, this paper explores two related questions: (1) Is there evidence that farmers reporting data have any information about actual drought events, and (2) is there evidence that it is valuable to address recollection and perception issues when using farmer-reported data? We investigated these questions by analyzing index insurance, in which remote sensing products trigger payments to farmers during loss years. Our case study is perhaps the largest participatory farmer remote sensing insurance project in Ethiopia. We tested the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as droughts by independent satellite data sources. We found evidence that farmer-reported events are independently reflected in multiple remote sensing datasets, suggesting that there is legitimate information in farmer reporting. Repeated community-based meetings over time and aggregating independent village reports over space lead to improved predictions, suggesting that it may be important to utilize methods to address potential biases.

It is widely anticipated that climate change will negatively affect both food security and diet diversity. Diet diversity is especially critical for children as it correlates with macro and micronutrient intake important for child development. Despite these anticipated links, little empirical evidence has demonstrated a relationship between diet diversity and climate change, especially across large datasets spanning multiple global regions and with more recent climate data. Here we use survey data from 19 countries and more than 107 000 children, coupled with 30 years of precipitation and temperature data, to explore the relationship of climate to child diet diversity while controlling for other agroecological, geographic, and socioeconomic factors. We find that higher long-term temperatures are associated with decreases in overall child diet diversity, while higher rainfall in the previous year, compared to the long-term average rainfall, is associated with greater diet diversity. Examining six regions (Asia, Central America, North Africa, South America, Southeast Africa, and West Africa) individually, we find that five have significant reductions in diet diversity associated with higher temperatures while three have significant increases in diet diversity associated with higher precipitation. In West Africa, increasing rainfall appears to counterbalance the effect of rising temperature impacts on diet diversity. In some regions, the statistical effect of climate on diet diversity is comparable to, or greater than, other common development efforts including those focused on education, improved water and toilets, and poverty reduction. These results suggest that warming temperatures and increasing rainfall variability could have profound short- and long-term impacts on child diet diversity, potentially undermining widespread development interventions aimed at improving food security.

The NASA Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) have been planned and funded by the NASA Earth Science Division. Both programs have a focus on engaging stakeholders and developing science useful for decision making. The resulting programs have funded significant scientific output and advancements in understanding how satellite remote sensing observations can be used to not just study how the Earth is changing, but also create data products that are of high utility to stakeholders and decisions makers. In this paper we focus on documenting thematic diversity of research themes and methods used, and how the CMS and ABoVE themes are related. We do this through developing a Correlated Topic Model on the 521 papers produced by the two programs and plotting the results in a network diagram. Through analysis of the themes in these papers, we document the relationships between researchers and institutions participating in CMS and ABoVE programs and the benefits from sustained engagement with stakeholders due to recurring funding. We note an absence of policy engagement in the papers and conclude that funded researchers need to be more ambitious and explicit in drawing the connection between their research and carbon policy implications in order to meet the stated goals of the CMS and ABoVE programs.

As our climate changes through time there is an ever-increasing need to quantify how and where it is changing so that mitigation strategies can be implemented. Urban areas have a disproportionate amount of warming due, in part, to the conductive properties of concrete and asphalt surfaces, surface albedo, heat capacity, lack of water, etc. that make up an urban environment. The NASA Climate Adaptation Science Investigation working group at Goddard Space Flight Center in Greenbelt, MD, conducted a study to collect temperature and humidity data at 15 min intervals from 12 sites at the center. These sites represent the major surface types at the center: asphalt, building roof, grass field, forest, and rain garden. The data show a strong distinction in the thermal properties of these surfaces at the center and the difference between the average values for the center compared to a local meteorological station. The data have been submitted to Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) for archival in comma separated value (csv) file format (Carroll et al., 2016) and can be found by following this link: http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1319.

Climate change and a rapidly growing human population have put ever greater strains on the global food system. Although the number of food insecure people in the world has reached a record low, changing land use and climate variability will threaten our ability to maintain this progress. Profound changes in the structure of economies around the world have affected agricultural production and how food is delivered to the consumer. This paper explores connections between land use, environmental change and food availability, access, and utilization. Each of these elements of food security has vulnerabilities to changing environmental conditions and land use that can be explored using satellite remote sensing observations. Technology is a key way environmental changes can be quantified and used in food security assessment.

The Coordination Group for Meteorological Satellites (CGMS) provides an international forum for the exchange of technical information on geostationary and polar-orbiting meteorological satellite systems. In 2013, the CMGS established the Socioeconomic Benefits Tiger Team (SETT) to develop a credible methodology and common terminology for articulating the socioeconomic benefits of satellite observing systems, and to explore the most effective ways to communicate the benefits to decision makers and stakeholders. As part of its first years’ activities, the SETT gathered examples of socioeconomic studies across all member organizations. This article describes key elements of these studies, and identified eight key themes that are presented. We welcome additional collaborations to identify opportunities to incorporate socioeconomic best practices, integrate these into additional or subsequent phases of work on new instruments and satellites, and develop recommendations for the way forward for the broader meteorological community.

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

In the context of a changing climate, there is an urgent need to better understand the impact that weather disturbances have on food affordability in the developing world. While the influence of international markets on local food markets has received considerable attention, in contrast, the potential influence of weather disturbances on local food markets has received much less attention. In fact, local weather disturbances may have an adverse impact on the poorest households in developing countries. Here we quantify the short-run impact of both weather disturbances as well as international price changes on monthly food prices across 554 local commodity markets in 51 countries during the period between 2008 and 2012. We find that almost 20% of local market prices were affected by domestic weather disturbances in the short run, 9% by international price changes and 4% by both domestic weather disturbances and international price changes during the period. An improved understanding of the magnitude and relative importance of weather disturbances and international price changes on rural economies will inform public policies that are designed to mitigate the impact of adverse weather disturbances.

The world has experienced rapid urbanization over the past five decades, with resulting substantial changes to the food system. Strong urbanization is associated with economic growth, which allows for investment in substantial increases in energy, water, and land used in intensive agriculture required to support urban populations. Given the cost of moving goods from distant regions, there has been a growth of small-scale agriculture within urban areas to meet the needs of its population. In this paper, we will describe satellite remote sensing data and methods that can identify urban and peri-urban farms and gardens in the United States and in developing countries, starting with global approaches and then providing case studies that explore different techniques. An examination of the increasing importance of local food to urban populations, and the role remote sensing can play in identifying where urban farming is occurring and its change through time will conclude the article.