Nikolay Khabarov

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

Significance Agriculture is arguably the sector most affected by climate change, but assessments differ and are thus difficult to compare. We provide a globally consistent, protocol-based, multimodel climate change assessment for major crops with explicit characterization of uncertainty. Results with multimodel agreement indicate strong negative effects from climate change, especially at higher levels of warming and at low latitudes where developing countries are concentrated. Simulations that consider explicit nitrogen stress result in much more severe impacts from climate change, with implications for adaptation planning. Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Constraints and potentials of future irrigation water availability on agricultural production under climate change

Significance Freshwater availability is relevant to almost all socioeconomic and environmental impacts of climate and demographic change and their implications for sustainability. We compare ensembles of water supply and demand projections driven by ensemble output from five global climate models. Our results suggest reasons for concern. Direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–2,600 Pcal (8–43% of present-day total). Freshwater limitations in some heavily irrigated regions could necessitate reversion of 20–60 Mha of cropland from irrigated to rainfed management, and a further loss of 600–2,900 Pcal. Freshwater abundance in other regions could help ameliorate these losses, but substantial investment in infrastructure would be required. We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

Multisectoral climate impact hotspots in a warming world

The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980–2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

Consistent negative response of US crops to high temperatures in observations and crop models

High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 °C. Elevated CO2 can only weakly reduce these yield losses, in contrast to irrigation.

Climate change induced transformations of agricultural systems: insights from a global model

Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemispheres temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis.

An integrated CVaR and real options approach to investments in the energy sector

The objective of this paper is to combine a real options framework with portfolio optimization techniques and to apply this new framework to investments in the electricity sector. In particular, a real options model is used to assess the adoption decision of particular technologies under uncertainty. These technologies are coal-fired power plants, biomassfired power plants and onshore wind mills, and they are representative of technologies based on fossil fuels, biomass and renewables, respectively. The return distributions resulting from this analysis are then used as an input to a portfolio optimization, where the measure of risk is the Conditional Value-at-Risk (CVaR).

Affordable nutrient solutions for improved food security as evidenced by crop trials.

The continuing depletion of nutrients from agricultural soils in Sub-Saharan African is accompanied by a lack of substantial progress in crop yield improvement. In this paper we investigate yield gaps for corn under two scenarios: a micro-dosing scenario with marginal increases in nitrogen (N) and phosphorus (P) of 10 kg ha−1 and a larger yet still conservative scenario with proposed N and P applications of 80 and 20 kg ha−1 respectively. The yield gaps are calculated from a database of historical FAO crop fertilizer trials at 1358 locations for Sub-Saharan Africa and South America. Our approach allows connecting experimental field scale data with continental policy recommendations. Two critical findings emerged from the analysis. The first is the degree to which P limits increases in corn yields. For example, under a micro-dosing scenario, in Africa, the addition of small amounts of N alone resulted in mean yield increases of 8% while the addition of only P increased mean yields by 26%, with implications for designing better balanced fertilizer distribution schemes. The second finding was the relatively large amount of yield increase possible for a small, yet affordable amount of fertilizer application. Using African and South American fertilizer prices we show that the level of investment needed to achieve these results is considerably less than 1% of Agricultural GDP for both a micro-dosing scenario and for the scenario involving higher yet still conservative fertilizer application rates. In the latter scenario realistic mean yield increases ranged between 28 to 85% in South America and 71 to 190% in Africa (mean plus one standard deviation). External investment in this low technology solution has the potential to kick start development and could complement other interventions such as better crop varieties and improved economic instruments to support farmers.

Modeling biomass burning and related carbon emissions during the 21st century in Europe

In this study we present an assessment of the impact of future climate change on total fire probability, burned area, and carbon (C) emissions from fires in Europe. The analysis was performed with the Community Land Model (CLM) extended with a prognostic treatment of fires that was specifically refined and optimized for application over Europe. Simulations over the 21st century are forced by five different high-resolution Regional Climate Models under the Special Report on Emissions Scenarios A1B. Both original and bias-corrected meteorological forcings is used. Results show that the simulated C emissions over the present period are improved by using bias corrected meteorological forcing, with a reduction of the intermodel variability. In the course of the 21st century, burned area and C emissions from fires are shown to increase in Europe, in particular in the Mediterranean basins, in the Balkan regions and in Eastern Europe. However, the projected increase is lower than in other studies that did not fully account for the effect of climate on ecosystem functioning. We demonstrate that the lower sensitivity of burned area and C emissions to climate change is related to the predicted reduction of the net primary productivity, which is identified as the most important determinant of fire activity in the Mediterranean region after anthropogenic interaction. This behavior, consistent with the intermediate fire-productivity hypothesis, limits the sensitivity of future burned area and C emissions from fires on climate change, providing more conservative estimates of future fire patterns, and demonstrates the importance of coupling fire simulation with a climate driven ecosystem productivity model.

Global food markets, trade and the cost of climate change adaptation

Achieving food security in the face of climate change is a major challenge for humanity in the 21st century but comprehensive analyses of climate change impacts, including global market feedbacks are still lacking. In the context of uneven impacts of climate change across regions interconnected through trade, climate change impact and adaptation policies in one region need to be assessed in a global framework. Focusing on four Eastern Asian countries and using a global integrated modeling framework we show that i) once imports are considered, the overall climate change impact on the amount of food available could be of opposite sign to the direct domestic impacts and ii) production and trade adjustments following price signals could reduce the spread of climate change impacts on food availability. We then investigated how pressure on the food system in Eastern Asia could be mitigated by a consumer support policy. We found that the costs of adaptation policies to 2050 varied greatly across climate projections. The costs of consumer support policies would also be lower if only implemented in one region but market price leakage could exacerbate pressure on food systems in other regions. We conclude that climate adaptation should no longer be viewed only as a geographically isolated local problem.

Valuing Weather Observation Systems For Forest Fire Management

Weather information is an integral part of modern fire management systems. In this paper, we investigate, by means of simulation studies, how improvements in the weather observation systems help to reduce burned area by targeting and monitoring places ripe fires are likely to occur. In our model, the air patrolling schedule is determined by the Nesterov index, which is calculated from observed weather data. We use two weather data sets based on ldquoroughrdquo and ldquofinerdquo grids. The reduction of the total burned area, associated with an air patrolling schedule based on the ldquofinerdquo grid, indicates the benefits of using better weather observations. We, also, consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. Finally, we investigate the system of systems effect. We find the largest marginal improvement from the rough grid results when we increase the quality of observations in most critical areas.