Description: During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this paper, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Description: Systemic threats to food-energy-environment-water systems require national policy responses. Yet complete control of these complex systems is impossible and attempts to mitigate systemic risks can generate unexpected feedback effects. Perverse outcomes from national policy can emerge from the diverse responses of decision-makers across different levels and scales of resource governance. Participatory risk assessment processes can help planners to understand sub-national dynamics and ensure that policies do not undermine the resilience of social-ecological systems and infrastructure networks. Researchers can play an important role in participatory processes as both technical specialists and brokers of stakeholder knowledge on the feedbacks generated by systemic risks and policy decisions. Here, we evaluate the use of causal modeling and participatory risk assessment to develop national policy on systemic water risks. We present an application of the Risks and Options Assessment for Decision-Making (ROAD) process to a district of Vietnam where national agricultural water reforms are being piloted. The methods and results of this project provide general insights about how to support resilient decision-making, including the transfer of knowledge across administrative levels, identification of feedback effects, and the effective implementation of risk assessment processes.

Description: Risk-based water resources management is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost-benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk-based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, whilst robustness is interpreted in the decision-theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade-off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London’s water supply system using state of the art regional climate simulations to inform the estimation of risk and robustness.

Description: Particulate matter with the diameter smaller than 2.5 micrometers (PM2.5) poses health threats to human population. Regardless of efforts to regulate the pollution sources, it is unclear how climate change caused by greenhouse gases (GHGs) would affect PM2.5 levels. Using century-long ensemble simulations with Community Earth System Model 1 (CESM1), we show that, if the anthropogenic emissions would remain at the level in the year 2005, the global surface concentration and atmospheric column burden of sulfate, black carbon, and primary organic carbon would still increase by 5-10% at the end of 21st century (2090-2100) due to global warming alone. The decrease in the wet removal flux of PM2.5, despite an increase in global precipitation, is the primary cause of the increase in the PM2.5 column burden. Regionally over North America and East Asia, a shift of future precipitation toward more frequent heavy events contributes to weakened wet removal fluxes. Our results suggest climate change impact needs to be accounted for to define the future emission standards necessary to meet air quality standard.

Description: The impacts of land use have been shown to have considerable influence on regional climate. With the recent international commitment to limit global warming to well below 2°C, emission reductions need to be ambitious and could involve major land-use change (LUC). Land-based mitigation efforts to curb emissions growth include increasing terrestrial carbon sequestration through reforestation, or the adoption of bioenergy crops. These activities influence local climate through biogeophysical feedbacks however it is uncertain how important they are for a 1.5 degree climate target. This was the motivation for HAPPI-Land: the Half a degree Additional warming, Prognosis and Projected Impacts – Land use scenario experiment. Using four Earth System Models we present the first multi-model results from HAPPI-Land and demonstrate the critical role of land use for understanding characteristics of regional climate extremes in low-emission scenarios. In particular, our results show that changes in temperature extremes due to LUC are comparable in magnitude to changes arising from half a degree of global warming. We also demonstrate that LUC contributes to more than 20% of the change in temperature extremes for large land areas concentrated over the Northern Hemisphere. However, we also identify sources of uncertainty that influence the multi-model consensus of our results including how LUC is implemented and the corresponding biogeophysical feedbacks that perturb climate. Therefore our results highlight the urgent need to resolve the challenges in implementing LUC across models to quantify the impacts and consider how LUC contributes to regional changes in extremes associated with sustainable development pathways.

Description: In light of the Paris Agreement, it is essential to identify regional impacts of half a degree additional global warming to inform climate adaptation and mitigation strategies. We investigate the effects of 1.5 ° C and 2.0 ° C global warming above pre-industrial conditions, relative to present day (2006–2015), over the Asian-Australian monsoon region (AAMR) using five models from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. There is considerable inter-model variability in projected changes to mean climate and extreme events in 2.0 ° C and 1.5 ° C scenarios. There is high confidence in projected increases to mean and extreme surface temperatures over AAMR, as well as more-frequent persistent daily temperature extremes over East Asia, Australia and northern India with an additional 0.5 ° C warming, which are likely to occur. Mean and extreme monsoon precipitation amplify over AAMR, except over Australia at 1.5 ° C where there is uncertainty in the sign of the change. Persistent daily extreme precipitation events are likely to become more frequent over parts of East Asia and India with an additional 0.5 ° C warming. There is lower confidence in projections of precipitation change than in projections of surface temperature change. These results highlight the benefits of limiting the global-mean temperature change to 1.5 ° C above pre-industrial, as the severity of the above effects increases with an extra 0.5 ° C warming.

Description: The most common approaches to detection and attribution of extreme weather events using FAR or RR (Fraction of Attributable Risk or Risk Ratio) answer a particular form of research question, namely, “What is the probability of a certain class of weather events, given global climate change, relative to a world without?” In a set of recent papers, Kevin Trenberth et al. (2015) and Theodore Shepherd (2016) have argued that this is not always the best tool for analyzing causes, or for communicating with the public about climate events and extremes. Instead, they promote the idea of a “storyline” approach, which ask complementary questions, such as “How much did climate change affect the severity of a given storm?” From the vantage of history and philosophy of science, a proposal to introduce a new approach or to answer different research questions—especially those of public interest—does not appear particularly controversial. However, the proposal proved highly controversial, with the majority of detection and attribution scientists reacting in a very negative and even personal manner. Some suggested the proposed alternatives amount to a weakening of standards, or an abandonment of scientific method. Here, we address the question: Why is this such a controversial proposition? We argue that there is no “right” or “wrong” approach to D&A in any absolute sense, but rather that in different contexts society may have a greater or lesser concern with errors of a particular type. How we view the relative risk of over-estimation vs. under-estimation of harm is context-dependent. [250]

Description: Even if global warming is kept below +2°C, European agriculture will be significantly impacted. Soil degradation may amplify these impacts substantially and thus hamper crop production further. We quantify biophysical consequences and bracket uncertainty of +2°C warming on calories supply from ten major crops and vulnerability to soil degradation in Europe using crop modelling. The Environmental Policy Integrated Climate (EPIC) model together with regional climate projections from the European branch of the Coordinated Regional Downscaling Experiment (EURO-CORDEX) were used for this purpose. A robustly positive calorie yield change was estimated for the EU Member States except for some regions in Southern and South-Eastern Europe. The mean impacts range from +30 Gcal ha –1 in the north, through +25 and +20 Gcal ha –1 in Western and Eastern Europe, respectively, to +10 Gcal ha –1 in the south if soil degradation and heat impacts are not accounted for. Elevated CO 2 and increased temperature are the dominant drivers of the simulated yield changes in high-input agricultural systems. The growth stimulus due to elevated CO 2 may offset potentially negative yield impacts of temperature increase by +2°C in most of Europe. Soil degradation causes a calorie vulnerability ranging from 0 to 80 Gcal ha –1 due to insufficient compensation for nutrient depletion and this might undermine climate benefits in many regions, if not prevented by adaptation measures, especially in Eastern and North-Eastern Europe. Uncertainties due to future potentials for crop intensification are about two to fifty times higher than climate change impacts.

Description: Worldwide, humans are facing high risks from natural hazards, especially in coastal regions with high population densities. Rising sea levels due to global warming are making coastal communities’ infrastructure vulnerable to natural disasters. The present study aims to provide a coupling approach of vulnerability and resilience through restoration and conservation of lost or degraded coastal natural habitats to reclamation under different climate change scenarios. The Integrated Valuation of Ecosystems and Tradeoffs (InVEST) model is used to assess the current and future vulnerability of coastal communities. The model employed is based on seven different bio-geophysical variables to calculate a Natural Hazard Index (NHI) and to highlight the criticality of the restoration of natural habitats. The results show that roughly 25 percent of the coastline and more than 5 million residents are in highly vulnerable coastal areas in China, and these numbers are expected to double by 2100. Our study suggests that restoration and conservation in recently reclaimed areas have the potential to reduce this vulnerability by 45 percent. Hence, natural habitats have proved to be a great defense against coastal hazards and should be prioritized in coastal planning and development. The findings confirm that natural habitats are critical for coastal resilience and can act as a recovery force of coastal functionality loss. Therefore, we recommend that the Chinese government prioritize restoration where possible and conservation of the remaining habitats for the sake of coastal resilience to prevent natural hazards from escalating into disasters.