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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Understanding and Constraining the Midlatitude Cloud Optical Depth Feedback in Climate Models (Final Report)

The objectives of this investigation are to provide a deeper understanding of the brightening of middle and high latitude clouds that occurs in many climate models as the climate warms, and to better understand why models give varying estimates of the strength of this negative feedback. The investigation may also provide new information on why models are deficient in their simulation of the present day clouds in these regions. The analysis will reveal which models simulate current clouds most realistically in the regions of interest, and relate this to the strength of the cloud feedbacks in the models. This will improve the uncertainty quantification of climate simulations and will provide theoretical understanding potentially leading to increased reliability of climate change projections. This will enhance the predictive understanding of the Earth system by analyzing the natural and anthropogenic components of global climate change in models. The primary methods involve the study of the clouds in the suite of CMIP5 model climate simulations and comparison of clouds in climate simulations with data from satellite measurement systems, with a particular emphasis on mixed-phase cloud physics, for which ice and water are present simultaneously. State-of-the-art climate model feedback analysis will be combined with new and more comprehensive observations of clouds available from modern measurement systems. Novel use of model simulations in combination with observations enables a deeper understanding of the role of clouds in climate change. Metrics that facilitate model-to-model and model-to-observation comparisons related to mixed-phase cloud physics will be developed and used to highlight challenges and opportunities for improving the state-of-the-science models. This investigation is a collaboration between the University of Washington, where the data work is concentrated and LLNL where the model data and the tools and expertise to do cloud feedback analysis are located. The grant supported the work of 3 different graduate students at different times (McCoy, Wall and Berry) Post-doctoral researcher Blaž Gasparini was also partially supported on this grant and led our collaboration with PNNL scientists. PNNL scientists also collaborated in the work of graduate student Wall (Po-Lun Ma). The main results of our research efforts are reported in 6 papers and 1 book chapter that were supported by this grant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Water and Climate Impacts on ERCOT Long-Term Systems Assessment

Water and climate change pose many potential challenges to the electric power system. Substantial water is withdrawn every day to support thermoelectric power generating unit operations, and changes to water supply have the potential to affect generation dispatch. Climate change can accelerate growing demand for electricity, which can necessitate additional generating capacity, often in locations with limited water supply. Drought conditions also threaten thermoelectric power plant operations due to streamflow and reservoir levels dropping below intake structures, or water temperatures exceeding a power plants' permitted operating conditions. Here we explore how future climate change might influence decisions related to electricity capacity expansion planning in Electric Reliability Council of Texas (ERCOT) using a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on the future water supply for thermoelectric and hydropower generation for four future climate projections. Separately, temperature impacts on electricity load are evaluated for these scenarios. These climate impacts are applied to five alternative electricity futures in an electricity capacity expansion model that projects future generation and transmission capacity additions in ERCOT. Results indicate that climate has a measurable influence on future generation and transmission capacity needs, with temperature-driven increases in peak and average load resulting in 5-15 GW additional generating capacity and up to 1 GW additional transmission capacity. Additional capacity is a diverse mix of PV, natural gas, and wind, depending on the makeup of economic, policy and technology assumptions. Climate impacts increase total system costs 2-5%, while the marginal cost of energy and emissions are not affected substantially by climate change effects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2013

Detection and Attribution of Anthropogenic Climate Change Impacts

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

detection↗
NASA NTRS2015

Ringberg15: Earth's Climate Sensitivities

To assess gaps in understanding of Earth's climate sensitivities a workshop was organised under the auspices of the WCRP (World Climate Research Programme) Grand Science Challenge on Clouds, Circulation and Climate Sensitivity (Ringberg15). The workshop took place in March 2015 and gathered together over thirty experts from around the world for one week. Attendees each gave short presentations and participated in moderated discussions of specific questions related to understanding Earth's climate sensitivities. Most of the time was focused on understanding of the equilibrium climate sensitivity, defined as the equilibrium near-surface warming associated with a doubling of atmospheric carbon dioxide. The workshop produced nine recommendations, many of them focusing on specific research avenues that could be exploited to advance understanding of climate sensitivity. Many of these dealt, in one fashion or another, with the need to more sharply focus research on identifying and testing story lines for a high (larger than 4 degrees Kelvin) or low (less than 2 degrees Kelvin) equilibrium climate sensitivity. Additionally, a subset of model intercomparison projects (CFMIP (Cloud Feedback Model Intercomparison Project), PMIP (Palaeoclimate Modelling Intercomparison Project), PDRMIP (Precipitation Driver and Response Model Intercomparison Project), RFMIP (Radiative Forcing Model Intercomparison Project) and VolMIP (Volcanic Forcings Model Intercomparison Project)) that have been proposed for inclusion within CMIP were identified as being central to resolving important issues raised at the workshop; for this reason modelling groups were strongly encouraged to participate in these projects. Finally the workshop participants encouraged the WCRP to initiate and support an assessment process lead by the Grand Science Challenge on Clouds, Circulation and Climate Sensitivity on the topic of Earth's Climate Sensitivities, culminating in a report that will be published in 2019, forty years after the seminal report by Charney and co-authors.

Sensitivity↗
NASA NTRSDate not supplied

Climate change reshapes the drivers of false spring risk across European trees

Temperate and boreal forests are shaped by late spring freezing events after budburst, which are also known as false springs. Research has generated conflicting results on whether or not these events will change with climate change, potentially because---to date---no study has compared the myriad climatic and geographic factors that contribute to a plant's risk of a false spring. We assessed and compared the strength of the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six temperate, decidious tree species across 11,648 sites in Central Europe and how these predictors shifted with climate change. Across species before recent warming, mean spring temperature and distance from the coast were the strongest predictors, with higher mean spring temperatures associated with decreased risk in false springs (–7.64% per 2°C increase) and sites further from the coast experiencing an increased risk (5.32% per 150km from the coast). Elevation (2.23% per 200m increase in elevation) and NAO index (1.91% per 0.3 increase) also increased false spring risk. With climate change, elevation and distance from coast---i.e., the geographic factors---remain relatively stable, while climatic factors shifted in magnitude for mean spring temperature (down to -2.84% in risk per 2°C), and in direction, with positive NAO phases leading to lower risk (-9.15% per 0.3). The residual effects of climate change---unexplained by the climatic and geographic factors already included in the model---magnified the species-level variation in risk, with risk increasing among early-leafout species (i.e., Aesculus hippocastanum, Alnus glutinosa and Betula pendula) but a decline or no change in risk among late-leafout species (i.e., Fagus sylvatica, Fraxinus excelsior and Quercus robur). Our results show that climate change has reshaped the major drivers of false spring risk and highlight how considering multiple factors can yield a better understanding of the complexities of climate change.

Climate change↗
NASA NTRSDate not supplied

Open Science Approach to Analyze Climate-Crop Relationships in the US Leveraging GES DISC and Galaxy Workflows

Understanding the intricate relationship between climate variability and agricultural production is crucial for ensuring food security. This study investigates the impact of climate parameters, such as temperature, precipitation, and soil moisture, on major US crop yields. Adopting an open science approach, the study analyzes the impact of climate on agricultural production in the United States. The Galaxy workflow engine serves as the primary tool for integrating climate data from the Goddard Earth Sciences Data and Information Services Center (GES DISC), retrieved via the Giovanni system, with yield statistics from the United States Department of Agriculture’s National Agricultural Statistics Service (USDA NASS). Extensions for reading, preprocessing, and analyzing external data have been developed, enabling the creation of workflows within the Galaxy platform. The development of a reproducible workflow allows for the calculation of seasonal climate averages, which are then assessed for their correlation with crop yields. This methodology ensures the replicability of the research, promoting transparency and collaboration in the scientific community. Correlational and regression analyses have been applied to different sub-zones and crops. The findings from this research offer valuable insights into the relationship between climate parameters and crop yields. These insights contribute to a deeper understanding of climate-crop relationships, providing a solid foundation for informed decision-making in the agricultural sector. The high correlation values indicate a significant relationship between climate parameters and crop yields, underscoring the importance of considering climate factors in agricultural planning and policymaking. This research also exemplifies the power of open science in advancing our understanding of complex environmental and agricultural phenomena. By leveraging open data and services, it provides a robust and replicable framework for future studies in this critical field.

Open science↗
DOE OSTI2020

Modeling Streamflow and Sediment Transport Under Current and Future Climates at the West Valley Site - 20231

Performance Assessment models often require inputs representing specific hydrologic processes such as streamflow and sediment flux. This paper details the development of a process-level hydrologic model and its use in a Probabilistic Performance Assessment (PPA) system-level model for the West Valley Site in western New York. For this PPA model, a watershed model was developed using SWAT (Soil and Water Assessment Tool) and used to evaluate water and sediment fluxes in nearby streams draining the Site. A particular challenge of probabilistic modeling over long periods of time is scaling parameters appropriately so that outcomes are not grossly over- or underestimated. This challenge is especially important when the spatial and temporal scales of process and system level models differ. In this instance, the SWAT watershed model and GoldSim PPA model have similar spatial scales of stream reaches and sub-catchments within a single watershed (approximately hundreds to tens of thousands of square meters, but the temporal scales differ considerably. The SWAT model calculates streamflow and sediment transport rates at the daily scale, while the PPA model requires long-term average values that are applied over hundreds to thousands of year-long periods. As such, distributions of daily climatic parameters such as average precipitation rate, temperature, wind speed, and relative humidity were developed to force a transient SWAT model that captures the dynamic behavior of the watershed in response to daily changes in the weather. Output from the model, which includes stream flow (m{sup 3}/y) and sediment transport rate (Mg/y) is then averaged over a 100-year period as an approximation for the long-term average values which can be applied in GoldSim. A single SWAT model was run 5000 times with varying climatic inputs and deterministic soil, land use, and elevation data, and the range of outputs were compiled into a distribution which can be implemented stochastically into the PPA Model. Additionally, this paper includes a high-level discussion of how changes in future climate affect weather input distributions, and a summary of how those changes in weather affect the outcomes from the SWAT model and the inputs into the PPA model. In this analysis, future climate distributions were developed based on climate research documenting the expected changes to precipitation and temperature in western New York. The 5,000 SWAT simulations were then repeated with these future climate distributions, and the resulting output was implemented into the PPA Model as hydrologic conditions under a future climate. In the current version of the PPA Model, hydrologic parameters change linearly from the 'current climate' conditions to the 'future climate' conditions over a period of 100 years, after which they remain constant. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Towards a comprehensive climate impacts assessment of solar geoengineering

Despite a growing literature on the climate response to solar geoengineering—proposals to cool the planet by increasing the planetary albedo—there has been little published on the impacts of solar geoengineering on natural and human systems such as agriculture, health, water resources, and ecosystems. An understanding of the impacts of different scenarios of solar geoengineering deployment will be crucial for informing decisions on whether and how to deploy it. Here we review the current state of knowledge about impacts of a solar-geoengineered climate and identify the major research gaps. We suggest that a thorough assessment of the climate impacts of a range of scenarios of solar geoengineering deployment is needed and can be built upon existing frameworks. However, solar geoengineering poses a novel challenge for climate impacts research as the manner of deployment could be tailored to pursue different objectives making possible a wide range of climate outcomes. We present a number of ideas for approaches to extend the survey of climate impacts beyond standard scenarios of solar geoengineering deployment to address this challenge. Reducing the impacts of climate change is the fundamental motivator for emissions reductions and for considering whether and how to deploy solar geoengineering. This means that the active engagement of the climate impacts research community will be important for improving the overall understanding of the opportunities, challenges, and risks presented by solar geoengineering.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Projecting future climate change impacts on heat-related mortality in large urban areas in China

Highlights: • The study projects future heat-related mortality risk in 51 major cities in China. • The projections are based on high resolution climate and population projections. • Future heat mortality risk is likely to be considerable under all emission scenarios. • Climate mitigation and heat risk management are needed to reduce such risk. Global climate change is anticipated to raise overall temperatures and has the potential to increase future mortality attributable to heat. Urban areas are particularly vulnerable to heat because of high concentrations of susceptible people. As the world's largest developing country, China has experienced noticeable changes in climate, partially evidenced by frequent occurrence of extreme heat in urban areas, which could expose millions of residents to summer heat stress that may result in increased health risk, including mortality. While there is a growing literature on future impacts of extreme temperatures on public health, projecting changes in future health outcomes associated with climate warming remains challenging and underexplored, particularly in developing countries. This is an exploratory study aimed at projecting future heat-related mortality risk in major urban areas in China. We focus on the 51 largest Chinese cities that include about one third of the total population in China, and project the potential changes in heat-related mortality based on 19 different global-scale climate models and three Representative Concentration Pathways (RCPs). City-specific risk estimates for high temperature and all-cause mortality were used to estimate annual heat-related mortality over two future twenty-year time periods. We estimated that for the 20-year period in Mid-21st century (2041–2060) relative to 1970–2000, incidence of excess heat-related mortality in the 51 cities to be approximately 37,800 (95% CI: 31,300–43,500), 31,700 (95% CI: 26,200–36,600) and 25,800 (95% CI: 21,300–29,800) deaths per year under RCP8.5, RCP4.5 and RCP2.6, respectively. Slowing climate change through the most stringent emission control scenario RCP2.6, relative to RCP8.5, was estimated to avoid 12,900 (95% CI: 10,800–14,800) deaths per year in the 51 cities in the 2050s, and 35,100 (95% CI: 29,200–40,100) deaths per year in the 2070s. The highest mortality risk is primarily in cities located in the North, East and Central regions of China. Population adaptation to heat is likely to reduce excess heat mortality, but the extent of adaptation is still unclear. Future heat mortality risk attributable to exposure to elevated warm season temperature is likely to be considerable in China's urban centers, with substantial geographic variations. Climate mitigation and heat risk management are needed to reduce such risk and produce substantial public health benefits.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

climate change↗
DOE OSTI2015

Multicentury changes in ocean and land contributions to the climate-carbon feedback

Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO 2 . Each simulation had a different degree of radiative coupling for CO 2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surface air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO 2 , warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO 2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The water–climate nexus: Intersections across sectors

Water security and climate change are important priorities for communities and regions worldwide. The intersections between water and climate change extend across many environmental and human activities. This Primer is intended as an introduction, grounded in examples, for students and others considering the interactions between climate, water, and society. In this Primer, we summarize key intersections between water and climate across four sectors: environment; drinking water, sanitation, and hygiene; food and agriculture; and energy. We begin with an overview of the fundamental water dynamics within each of these four sectors, and then discuss how climate change is impacting water and society within and across these sectors. Emphasizing the relationships and interconnectedness between water and climate change can encourage systems thinking, which can show how activities in one sector may influence activities or outcomes in other sectors. We argue that to achieve a resilient and sustainable water future under climate change, proposed solutions must consider the water–climate nexus to ensure the interconnected roles of water across sectors are not overlooked. Toward that end, we offer an initial set of guiding questions that can be used to inform the development of more holistic climate solutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Observations of greenhouse gases as climate indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO<:sub>2 GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modelling climate analogue regions for a central European city

In this study, we describe a methodology to derive climate analogue cities for spatially highly resolved future climate scenarios. For the computation, a reduced and in hindsight bias-adjusted EURO-CORDEX EUR-11 dataset is used based on two climate scenarios (RCP4.5 and RCP8.5). A total of 389 European cities are processed by the algorithm, which uses five statistical climate variables (2-m air temperature average and amplitude, precipitation sum and amplitude, correlation between 2-m air temperature average and precipitation sum). Additionally, extreme weather events (hot days, summer days, tropical nights, extreme precipitation events) are calculated for further comparison and validation. Finding an appropriate analogue permits a more accurate derivation and depiction of necessary climate adaptation efforts and therefore assist decision-making in city planning. As an example of our method, we searched for plausible climate twins for the mid-sized city of Aachen (Germany) at the end of the twenty-first century. Our results show that the French city of Dijon is highly likely to become Aachen’s climate twin by the end of the century for RCP4.5. As for the scenario RCP8.5, no clear European analogue city could be determined, indicating that the city might enter a novel climate. The nearest match suggests the cities of Florence and Prato in Tuscany. However, considering climate indices, the encompassing region of the French–Spanish city triangle Bordeaux–Toulouse–Bilbao is a better fit. The developed algorithm can be applied to any of the cities included in the dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

New tree-ring data from Canadian boreal and hemi-boreal forests provide insight for improving the climate sensitivity of terrestrial biosphere models

Understanding boreal/hemi-boreal forest growth sensitivity to seasonal variations in temperature and water availability provides important basis for projecting the potential impacts of climate change on the productivity of these ecosystems. Our best available information currently comes from a limited number of field experiments and terrestrial biosphere model (TBM) simulations of varying predictive accuracy. Here, we assessed the sensitivity of annual boreal/hemi-boreal forest growth in Canada to yearly fluctuations in seasonal climate variables using a large tree-ring dataset and compared this to the climate sensitivity of annual net primary productivity (NPP) estimates obtained from fourteen TBMs. We found that boreal/hemi-boreal forest growth sensitivity to fluctuations in seasonal temperature and precipitation variables changed along a southwestern to northeastern gradient, with growth limited almost entirely by temperature in the northeast and west and by water availability in the southwest. We also found a lag in growth climate sensitivity, with growth largely determined by the climate during the summer prior to ring formation. Analyses of NPP sensitivity to the same climate variables produced a similar southwest to northeast gradient in growth climate sensitivity for NPP estimates from all but three TBMs. However, analyses of growth from tree-ring data and analyses of NPP from TBMs produced contrasting evidence concerning the key climate variables limiting growth. While analyses of NPP primarily indicated a positive relationship between growth and seasonal temperature, tree-ring analyses indicated negative growth relationships to temperature. Also, the positive effect of precipitation on NPP derived from most TBMs was weaker than the positive effect of precipitation on tree-ring based growth: temperature had a more important limiting effect on NPP than tree-ring data indicated. These mismatches regarding the key climate variables limiting growth suggested that characterization of tree growth in TBMs might need revision, particularly regarding the effects of stomatal conductance and carbohydrate reserve dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Uncertainty in Simulating Wheat Yields Under Climate Change

Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments1,2. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change has been increasingly described in the literature3,4 while assessments of the uncertainty in crop responses to climate change are very rare. Systematic and objective comparisons across impact studies is difficult, and thus has not been fully realized5. Here we present the largest coordinated and standardized crop model intercomparison for climate change impacts on wheat production to date. We found that several individual crop models are able to reproduce measured grain yields under current diverse environments, particularly if sufficient details are provided to execute them. However, simulated climate change impacts can vary across models due to differences in model structures and algorithms. The crop-model component of uncertainty in climate change impact assessments was considerably larger than the climate-model component from Global Climate Models (GCMs). Model responses to high temperatures and temperature-by-CO2 interactions are identified as major sources of simulated impact uncertainties. Significant reductions in impact uncertainties through model improvements in these areas and improved quantification of uncertainty through multi-model ensembles are urgently needed for a more reliable translation of climate change scenarios into agricultural impacts in order to develop adaptation strategies and aid policymaking.

Asseng, S.↗
DOE OSTI2022

Social inequalities in climate change-attributed impacts of Hurricane Harvey

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA’s 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Global-scale multidecadal variability missing in state-of-the-art climate models

Reliability of future global warming projections depends on how well climate models reproduce the observed climate change over the twentieth century. In this regard, deviations of the model-simulated climate change from observations, such as a recent “pause” in global warming, have received considerable attention. Such decadal mismatches between model-simulated and observed climate trends are common throughout the twentieth century, and their causes are still poorly understood. Here we show that the discrepancies between the observed and simulated climate variability on decadal and longer timescale have a coherent structure suggestive of a pronounced Global Multidecadal Oscillation. Surface temperature anomalies associated with this variability originate in the North Atlantic and spread out to the Pacific and Southern oceans and Antarctica, with Arctic following suit in about 25–35 years. While climate models exhibit various levels of decadal climate variability and some regional similarities to observations, none of the model simulations considered match the observed signal in terms of its magnitude, spatial patterns and their sequential time development. These results highlight a substantial degree of uncertainty in our interpretation of the observed climate change using current generation of climate models.

54 ENVIRONMENTAL SCIENCES↗