Earth Systems

Challenges in simulating economic effects of climate change on global agricultural markets

Summary: Previous studies on the impacts of climate change on agriculture have the following shortcomings: a) most focus only on a few major crops (maize, wheat, rice or soybeans); b) site-level and global gridded crop models (GGCMs) provide very different impacts of climate effects on crops; c) effects of climate change on livestock are well documented, but rarely quantified; d) there are several elements, causal relations and feedbacks among biophysical, environmental and socioeconomic aspects usually not taken into account in these studies. The goal of this paper is to investigate at the global level how alternative assumptions about these four aspects may affect agricultural markets, food supply, consumer well-being and environmental metrics.

To that end, this study simulates changes in crop yield and livestock productivity in a large-scale socio-economic model of the global economy with detailed representation of the agriculture sector, the MIT EPPA-Agriculture model. The economic model considers many complex socio-economic relationships and feedbacks, such as changes in management and land-use allocation, shifts in demand for food as prices and incomes change, and changing patterns of global trade. The climate shocks considered were median agricultural productivity changes taken from several site-level crop models revised by IPPC and several GGCMs.

The researchers find global welfare impacts several times larger when climate impacts all crops and all livestock. At the regional level, food budget impacts are 10% to 25% in many developing countries, which may challenge food security. Most of the results are due to the role of land area expansion as a major source of adaptation. Climate impacts from site-level crop models revised by the IPCC generate most challenging socio-economic outcomes, while median climate impacts from GGCMs on yield were positive for major crops. However, due to the wide range of impacts from these two types of models, caution is warranted in comparing those median effects.

The study’s conclusions indicate 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-level models are needed to understand their major differences and implications for agricultural systems and food markets.

Predictability of U.S. regional extreme precipitation occurrence based on large-scale meteorological patterns (LSMPs)

Abstract: In this study, we use our analogue method and Convolutional Neural Networks (CNNs) to assess the potential predictability of extreme precipitation occurrence based on Large-Scale Meteorological Patterns (LSMPs) for the winter (DJF) of Pacific Coast California (PCCA) and the summer (JJA) of Midwestern United States (MWST). We evaluate the LSMPs constructed with a large set of variables at multiple atmospheric levels and quantify the prediction skill with a variety of complementary performance measures.

Our results suggest that LSMPs provide useful predictability of extreme precipitation occurrence at a daily scale and its interannual variability over both regions. The 14-year (2006-2019) independent forecast shows Gilbert Skill Scores (GSS) in PCCA range from 0.06 to 0.32 across 24 CNN schemes and from 0.16 to 0.26 across 4 analogue schemes, in contrast to those from 0.1 to 0.24 and from 0.1 to 0.14 in MWST.

Overall, CNN seems more powerful in extracting the relevant features associated with extreme precipitation from the LSMPs than the analogue method, with several single-variate CNN schemes achieving more skillful prediction than the best multi-variate analogue scheme in PCCA and more than half of CNN schemes in MWST. Nevertheless, both methods highlight that Integrated Vapor Transport (IVT, or its zonal and meridional components) enables higher prediction skill than other atmospheric variables over both regions. Warm-season extreme precipitation in MWST presents a forecast challenge with overall lower prediction skill than in PCCA, attributed to the weak synoptic-scale forcing in summer.

Lessons from a pandemic for systems-oriented sustainability research

Abstract: This review examines recent work on the environmental impacts of COVID-19 from the perspective of systems-oriented sustainability research, focusing on three areas in which environmental change occurs in an integrated system together with people and technologies: air quality and human health, climate change, and production and consumption. It summarizes relevant methods and approaches, and identifies criteria for evaluating whether sustainability-relevant research captures important components and dynamics and can lead to broader insights about sustainability. The review then assesses whether and how COVID-19 focused environmental research in the three areas (1) examines components of an integrated system; (2) accounts for interactions including complex, adaptive dynamics; and (3) is oriented to informing actions towards advancing sustainability.

A key finding is that efforts to analyze the environmental impacts of COVID-19 to date have not comprehensively accounted for complex, coupled interactions, especially those involving societal factors, potentially leading to erroneous conclusions about changes and their implications, and hampering the ability of such research to provide broader insights across sustainability-relevant domains. A lack of a systems perspective in COVID-19 focused work is also illustrative of a broader challenge in environmental research, which often neglects societal feedbacks.

The review concludes by suggesting practical steps through which researchers can better incorporate systems perspectives in research on sustainability-relevant systems, including using frameworks to identify important components and interactions, developing new approaches that connect analytical frameworks to models and methods, and advancing theory and methodology within the field of sustainability science.

Mitigation of CO2 emissions from international shipping through national allocation

Abstract: Neither international treaties nor domestic policies control carbon dioxide (CO2) emissions from international shipping. To enhance mitigation, a new multilateral mechanism could allocate these emissions to national carbon budgets, where different options could be used based on the location of industry actors and ships.

We analyze five allocation options, showing that a clear majority of CO2 emissions would be distributed to ten countries under each option; however, the top ten countries vary across allocation options and the amount of CO2 emissions allotted to individual countries could increase their carbon budgets thousand-fold or more.

We further examine how the different objectives, principles for decision-making, and geographical coverage of the United Nations Framework Convention on Climate Change (UNFCCC) and the International Maritime Organization influence the design and implementation of an allocation mechanism under each of these two bodies. We find that the allocation mechanism that best meets criteria related to effectiveness and equity would be one in which emissions are assigned to countries of ship owners, and which operates under the UNFCCC.

Toward resilient energy infrastructure: Understanding the effects of changes in the climate mean and extreme events in the Northeastern United States

Abstract: Infrastructure systems are vulnerable to weather risks. With climate change, extreme events are expected to increase.To evaluate these changes in the Northeastern United States, state-of-the-art high-resolution, convection-permitting regional climate modeling simulations are carried out to downscale projections of the Community Earth System Model (CESM) to 3 km horizontal resolution under a high impact emissions scenario for a near future time period (2025-2041). Changes in mean climate and extreme events are assessed relative to the present-day climate (2006-2020) for three key weather elements affecting electricity grid infrastructure and operations: temperatures, wind speeds and ice accumulation on infrastructure surfaces. An assessment of exceedance threshold calculations based on the safety thresholds set by National Electric Safety Code (NESC) and International Organization for Standardization (ISO) is also provided.

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