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At least 253 records · Page 14

Explicit Consideration of Plant Xylem Hydraulic Transport Improves the Simulation of Crop Response to Atmospheric Dryness in the U.S. Corn Belt

Abstract Atmospheric dryness (i.e., high vapor pressure deficit, VPD), together with soil moisture stress, limits plant photosynthesis and threatens ecosystem functioning. Regions where rainfall and soil moisture are relatively sufficient, such as the rainfed part of the U.S. Corn Belt, are especially prone to high VPD stress. With globally projected rising VPD under climate change, it is crucial to understand, simulate, and manage its negative impacts on agricultural ecosystems. However, most existing models simulating crop response to VPD are highly empirical and insufficient in capturing plant response to high VPD, and improved modeling approaches are urgently required. In this study, by leveraging recent advances in plant hydraulic theory, we demonstrate that the VPD constraints in the widely used coupled photosynthesis‐stomatal conductance models alone are inadequate to fully capture VPD stress effects. Incorporating plant xylem hydraulic transport significantly improves the simulation of transpiration under high VPD, even when soil moisture is sufficient. Our results indicate that the limited water transport capability from the plant root to the leaf stoma could be a major mechanism of plant response to high VPD stress. We then introduce a Demand‐side Hydraulic Limitation Factor (DHLF) that simplifies the xylem and the leaf segments of the plant hydraulic model to only one parameter yet captures the effect of plant hydraulic transport on transpiration response to high VPD with similar accuracy. We expect the improved understanding and modeling of crop response to high VPD to help contribute to better management and adaptation of agricultural systems in a changing climate.

Environmental Sciences & Ecology↗

Unalakleet Climate: Analyzing Permafrost Degradation and Drainage Networks in Unalakleet, Alaska

The coastal community of Unalakleet is currently the 8th most at-risk community in Alaska due to the adverse effects of climate change that include permafrost degradation, severe coastal erosion, and sea-level rise-induced flood inundation caused by increasingly frequent storm surges. In response, the community has started a managed relocation with support from the Native Village of Unalakleet (NVU) and the National Renewable Energy Lab (NREL)’s Alaska campus in Fairbanks. The Unalakleet Climate NASA DEVELOP team partnered with NREL to provide remote sensing support and analysis for resilience planning in Unalakleet, supporting their ongoing relocation efforts and guiding future expansion. The team utilized Sentinel-1 C-Synthetic Aperture Radar (SAR), WorldView-2, and WorldView-3 datasets from 2017 – 2023 to analyze seasonal summer subsidence and utilized a 2014 Ancillary USGS 5 m Alaska DEM to conduct drainage network analyses that included watershed delineation and Height Above Nearest Drainage (HAND) analysis. The team also used high-resolution WorldView images to locate stable reference points that served as quality control for the team’s analyses. The team’s end products included maps containing subsidence and drainage zones information at and surrounding the relocation site. The team’s products provide NREL with valuable data that enables them to better assist Unalakleet’s managed relocation and assists Unalakleet with adapting to the catastrophic effects of climate change and build resilience in a community on the front lines of climate change.

Ian Lee↗

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗

Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

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.

agriculture↗

Climate impacts associated with reduced diet diversity in children across nineteen countries

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.

54 ENVIRONMENTAL SCIENCES↗

Identification of Flights for Cost-Efficient Climate Impact Reduction

The aircraft-induced climate impact has drawn attention in recent years. Aviation operations affect the environment mainly through the release of carbon-dioxide, nitrogen-oxides, and by the formation of contrails. Recent research has shown that altering trajectories can reduce aviation environmental cost by reducing Absolute Global Temperature Change Potential, a climate assessment metric that adapts a linear system for modeling the global temperature response to aviation emissions and contrails. However, these methods will increase fuel consumption that leads to higher fuel costs imposed on airlines. The goal of this work is to identify ights for which the environmental cost of climate impact reduction outweighs the increase in operational cost on an individual aircraft basis. Environmental cost is quanti ed using the monetary social cost of carbon. The increase in operational cost is considering cost of additional fuel usage only. For this paper, an algorithm has been developed that modi es the trajectories of ights to evaluate the e ect of environ- mental cost and operational cost of ights in the United States National Airspace System. The algorithm identi es ights for which the environmental cost of climate impact can be reduced and modi es their trajectories to achieve maximum environmental net bene t, which is the di erence between reduction in environmental cost and additional operational cost. The result shows on a selected day, 16% of the ights among eight major airlines, or 2,043 ights, can achieve environmental net bene t using weather forecast data, resulting in net bene t of around $500,000. The result also suggests that the long-haul ights would be better candidates for cost-ecient climate impact reduction than the short haul ights. The algorithm will help to identify the characteristics of ights that are capable of applying cost-ecient climate impact reduction strategy.

climate impact reduction↗

California’s 2023 snow deluge: Contextualizing an extreme snow year against future climate change

The increasing prevalence of low snow conditions in a warming climate has attracted substantial attention in recent years, but a focus exclusively on low snow leaves high snow years relatively underexplored. However, these large snow years are hydrologically and economically important in regions where snow is critical for water resources. Here, we introduce the term “snow deluge” and use anomalously high snowpack in California’s Sierra Nevada during the 2023 water year as a case study. Snow monitoring sites across the state had a median 41 y return interval for April 1 snow water equivalent (SWE). Similarly, a process-based snow model showed a 54 y return interval for statewide April 1 SWE (90% CI: 38 to 109 y). While snow droughts can result from either warm or dry conditions, snow deluges require both cool and wet conditions. Relative to the last century, cool-season temperature and precipitation during California’s 2023 snow deluge were both moderately anomalous, while temperature was highly anomalous relative to recent climatology. Downscaled climate models in the Shared Socioeconomic Pathway-370 scenario indicate that California snow deluges—which we define as the 20 y April 1 SWE event—are projected to decline with climate change (58% decline by late century), although less so than median snow years (73% decline by late century). This pattern occurs across the western United States. Changes to snow deluge, and discrepancies between snow deluge and median snow year changes, could impact water resources and ecosystems. Understanding these changes is therefore critical to appropriate climate adaptation.

Marshall, Adrienne M.↗

The Use of Correlated k-Distributions to Account for the Radiative Effect of Molecular Absorption Upon Satellite Measured Radiances

Establishing the radiative effect of molecular absorption (emission) in the atmosphere is critical to the proper interpretation of satellite retrieved radiances. Without an accurate accounting for molecular absorption, the assignment of radiative transfer processes to observed radiative effects could be fraught errors. Moreover, since the spectral characteristics of molecular absorption can change quickly with wavenumber, the adaptation of climate model parameterizations has the potential to lead to dubious results unless the chosen spectral range corresponds closely to the response function of the satellite instrument. Thus, an initiative has been undertaken to construct parameterizations that will account for the molecular absorption found in the spectral ranges of several satellite radiometers. Because of its efficiency and accuracy in calculating the molecular absorption for nonhomogeneous paths, the correlated k-distribution procedure has proven to be the most effective parameterization (Fu and Liou, 1992, and Kratz, 1995). A further advantage of the correlated k- distribution procedure is its ability to be incorporated directly into multiple scattering routines that consider scattering, as well as absorption, by clouds and aerosol particles.

Kratz, David P.↗

Evaluating Tradeoffs Between Environmental Impact and Operational Costs for Enroute Air Traffic

The rapid growth of air traffic has drawn attention to aircraft-induced environmental impact. Aviation operations affect the environment mainly through the release of emissions and by the formation of contrails. Recent research has shown that altering aircraft cruise altitudes can reduce aviation environmental impact by reducing Absolute Global Temperature Change Potential, a climate assessment metric that adapts a linear system for modeling the global temperature response to aviation emissions and contrails. However, these methods will increase fuel consumption that leads to higher operational costs imposed on airlines resulting in reluctance to adopt a new routing strategy. This paper evaluates the tradeoff between environmental impact reduction and the corresponding added operational costs for enroute air traffic. The concept of social cost of carbon and the carbon auction price from California's recent cap-and-trade system were used to provide estimates and a methodology to evaluate environmental costs for carbon dioxide emissions and contrail formations. Depending on the specific environmental policy, the strategy is considered favorable when the reduction in environmental costs exceeds the increase in operational costs. The results show how the net environmental bene t varies with different decision-making time horizons, different carbon and fuel costs, and different days. The study provides guidance towards the development of the environmental reduction strategies.

environmental impact↗

Migration Theory in Climate Mobility Research

The purpose of this article is to explore how migration theory is invoked in empirical studies of climate-related migration, and to provide suggestions for engagement with theory in the emerging field of climate mobility. Theory is critical for understanding processes we observe in social-ecological systems because it points to a specific locus of attention for research, shapes research questions, guides quantitative model development, influences what researchers find, and ultimately informs policies and programs. Research into climate mobility has grown out of early studies on environmental migration, and has often developed in isolation from broader theoretical developments in the migration research community. As such, there is a risk that the work may be inadequately informed by the rich corpus of theory that has contributed to our understanding of who migrates; why they migrate; the types of mobility they employ; what sustains migration streams; and why they choose certain destinations over others. On the other hand, there are ways in which climate and broader environment migration research is enriching the conceptual frameworks being employed to understand migration, particularly forced migration. This paper draws on a review of 75 empirical studies and modeling efforts conducted by researchers from a diversity of disciplines, covering various regions, and using a variety of data sources and methods to assess how they used theory in their research. The goal is to suggest ways forward for engagement with migration theory in this large and growing research domain.

migration theory↗

Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

security↗

NASA Earth Observations Informing Energy Management Decision Making

The Energy Sector is experiencing increasing impacts from severe weather and shifting climatic trends, as well as facing a changing political climate, adding uncertainty for stakeholders as they make short- and long-term planning investments. Climate changes such as prolonged extreme heat and drought (leading to wildfire spread, for example), sea level rise, and extreme storms are changing the ways that utilities operate. Energy infrastructure located in coastal or flood-prone areas faces inundation risks, such as damage to energy facilities. The use of renewable energy resources is increasing, requiring more information about their intermittency and spatial patterns. In light of these challenges, public and private stakeholders have collaborated to identify potential data sources, tools, and programmatic ideas. For example, utilities across the country are using cutting-edge technology and data to plan for and adapt to these changes. In the Federal Government, NASA has invested in preliminary work to identify needs and opportunities for satellite data in energy sector application, and the Department of Energy has similarly brought together stakeholders to understand the landscape of climate vulnerability and resilience for utilities and others. However, have these efforts improved community-scale resilience and adaptation efforts? Further, some communities are more vulnerable to climate change and infrastructure impacts than others. This session has two goals. First, panelists seek to share existing and ongoing efforts related to energy management. Second, the session seeks to engage with attendees via group knowledge exchange to connect national energy management efforts to local practice for increased community resilience.

Eckman, Richard↗

The hazard components of representative key risks. The physical climate perspective

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II in order to categorize, assess and communicate a wide range of regional and sectoral key risks, expected to become severe as a consequence of the potentially detrimental convergence of changing climate conditions, exposure and vulnerability of human and natural systems, and responses through (mal)adaptation measures. Other papers in this special issue treat each of eight RKRs by holistically assessing their current status and future evolution as a result of this convergence. However, their treatment cannot always organize such assessment according to a systematic gradation of climatic changes, often times having to extrapolate the big-picture evolution of risk from either qualitative effects of “low” medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C). In this study we offer as systematic a representation as possible – given current literature and assessments – of the future evolution of the hazard components of RKRs. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group 1 (WGI) supplemented when needed by more recent literature. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels to the extent possible. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with global average temperature change has been assessed. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - the link to increasing global temperatures can only be described qualitatively. For some processes - like the behavior of ice-sheets, or changes in circulation dynamics - large uncertainties about the effects of different levels of warming remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems when these changes happen in conjunction with these systems’ conditions of exposure and vulnerability, and in lack of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in an often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future possible evolution which represents an important component – if never the only one – of the potential future evolution of risk severity.

54 ENVIRONMENTAL SCIENCES↗

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 degC 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 degC. 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.

policies↗

Uncertainty in Simulating Wheat Yields Under Climate Change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

exhaust gases↗

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗

Indicators and Monitoring Systems for Urban Climate Resiliency

Cities in the USA and around the world have begun to take an active role in responding to climate change. A central requirement for effective urban climate strategies is the capacity to understand and measure how the climate is changing, the physical, environmental, and social impacts of the changes, and whether adaptation and resiliency policies and programs put in place in response are working. The objective of this paper is to review and assess how urban climate change and resiliency efforts can be measured and to define what might serve as meaningful indicator and monitoring protocols. The New York City Panel on Climate Change (NPCC) is used as a case study along with a reviews of the emerging literature of urban climate change indicators to analyze the requirements and processes needed for a successful urban climate resiliency indicator and monitoring (I and M) system. In the paper, the basic requirements of a proposed Urban Climate Resilience Indicators and Monitoring System are presented. A specific illustration of an I and M system for tracking the urban heat island highlights challenges as well as potential solutions embedded within such systems. Discussions how these protocols can be translated to other locales and settings, as well as the relationship to the US National Climate Assessment indicator process, are presented.

New York City Panel on Climate Change↗