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At least 379 records · Page 21

The impact of agricultural trade approaches on global economic modeling

Future socioeconomic and climate scenarios have been explored using integrated assessment models (IAMs) to understand interactions between human development and global environmental change in the long run. However, differences in trade modeling approaches are an important source of uncertainty in the assessments, particularly for regional projections. Here, we explore the critical role of trade modeling in assessing the potential future of global agroeconomics and terrestrial carbon emissions with a well-established IAM, the Global Change Assessment Model (GCAM). We update the crop trade modeling framework in GCAM from a Heckscher-Ohlin-Vanek (HOV) structure with integrated world markets (IWM) to a newly developed logit-based Armington approach with segmented regional markets (SRM). The updates make it possible to study the sensitivity of model projections of future agroeconomics and terrestrial carbon emissions to assumptions of the state and magnitude of global market integration. Our results demonstrate that assuming full global market integration, represented by homogeneous product modeling, neglecting economic geography, and excluding margins and tariffs, could lead to lower cropland use (i.e., by 115 million hectares globally) and terrestrial carbon fluxes (i.e., by 25%) by the end of the century. However, the results are highly heterogeneous across regions with more pronounced regional trade responses driven by global market integration. Our study highlights the critical role of trade modeling around product differentiation, economic geography, and regional trade parameterization in global economic or integrated assessment modeling. The results also imply that further reconciliations in trade model approaches could improve the convergence of regional results among models in model intercomparison studies.

54 ENVIRONMENTAL SCIENCES↗

The Hunga Volcanic Eruption Atmospheric Impacts Report

On 15 January 2022 a highly explosive eruption of the Hunga volcano occurred in the Kingdom of Tonga in the South Pacific Ocean (175°24’ W, 20°33’ S). The Volcanic Explosivity Index (VEI) 6 eruption originated from a shallow submarine vent, making it distinct from large subaerial eruptions of recent decades (e.g., 1982 El Chichón, 1991 Mt. Pinatubo). In particular, seawater enhanced explosivity and dampened sulfur dioxide (SO 2 ) emissions. The eruption was the culmination of ~1 month of precursory activity; however, the timing and size of the eruption were unexpected, partly due to the challenges of monitoring submarine volcanoes. The stratospheric hydration caused by the eruption was unprecedented in magnitude, altitude, and duration in the satellite record. This Executive Summary reflects the current assessment of the Hunga eruption and its impact on the climate system. We report key observations of the eruption and its aftermath, as well as simulations of its impact by global chemistry-climate models. The Hunga eruption had an unprecedented impact on the stratosphere and mesosphere due to the plume height and large water content, which increased the global stratospheric water vapour burden by 10%. Most of this water has remained in the atmosphere into 2025. However, Hunga’s net impact on surface climate was small compared to that of earlier large-magnitude volcanic eruptions, due to limited sulfate aerosol loading in the stratosphere and the high altitude of the water vapour injection.

58 GEOSCIENCES↗

A global ensemble of ocean wave climate projections from CMIP5-driven models

This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (H S ), mean wave period (T m ), and mean wave direction (θ m ) computed over time-slices 1979–2004 and 2081–2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.

Science & Technology - Other Topics↗

Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions

As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.

Environmental sciences↗

Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations

Abstract Accurate simulations of high‐latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO 2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Many such models represent high‐latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine Arctic‐specific PFTs. The newly developed PFTs include: (1) nonvascular mosses and lichens, (2) deciduous and evergreen shrubs of various height classes, including an alder PFT, (3) graminoids, and (4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario and constant PFT fractional areas showed alder‐dominated plant communities gaining more biomass and lichen‐dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗

High-performance computing leadership to enable advances in artificial intelligence and a thriving compute ecosystem

The past three decades have witnessed the widespread adoption of high-performance computing (HPC) as an essential tool in the advancement of science. From accelerating critical research in the wake of a global pandemic to climate modelling and national security, HPC has become integral to the most cutting-edge scientific research around the world and across application domains. The global competition to debut the next fastest supercomputer keeps pushing the field forward. Meanwhile, increasing capabilities are bringing hallmarks of science fiction, such as artificial intelligence (AI), into daily life. However, the tremendous power of new computing systems comes with an increased concern about equitable access to these resources and their impact on supporting a thriving workforce.

Tourassi, Georgia↗

The Critical Role Of Conversion Cost And Comparative Advantage In Modeling Agricultural Land Use Change

The difference in land use modeling approaches is an important uncertain factor in evaluating future climate scenarios in global economic models. We compare five widely used land use modeling approaches: constrained optimization, constant elasticity of transformation (CET), the additive form of constant elasticity of transformation (ACET), logit, and Ricardian. We demonstrate that the approaches differ not only by the extent of parameter uses but also by the definition of conversion cost and the consideration of comparative advantage implied by land heterogeneity. We develop a generalized hybrid approach that incorporates ACET/logit and Ricardian to account for both conversion cost and comparative advantage. We use this hybrid approach to estimate future climate impacts on agriculture. We find a welfare loss of about 0.38–0.46% of the global GDP. We demonstrate that ignoring land heterogeneity or land conversion costs underestimates climate impacts on agricultural production and welfare.

54 ENVIRONMENTAL SCIENCES↗

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Jagermeyr, Jonas↗

Comparing different generations of idealized solar geoengineering simulations in the Geoengineering Model Intercomparison Project (GeoMIP)

Abstract. Solar geoengineering has been receiving increased attention in recent years as a potential temporary solution to offset global warming. One method of approximating global-scale solar geoengineering in climate models is via solar reduction experiments. Two generations of models in the Geoengineering Model Intercomparison Project (GeoMIP) have now simulated offsetting a quadrupling of the CO2 concentration with solar reduction. This simulation is idealized and designed to elicit large responses in the models. Here, we show that energetics, temperature, and hydrological cycle changes in this experiment are statistically indistinguishable between the two ensembles. Of the variables analyzed here, the only major differences involve highly parameterized and uncertain processes, such as cloud forcing or terrestrial net primary productivity. We conclude that despite numerous structural differences and uncertainties in models over the past two generations of models, including an increase in climate sensitivity in the latest generation of models, the models are consistent in their aggregate climate response to global solar dimming.

54 ENVIRONMENTAL SCIENCES↗

TRACER-VOC: Speciated Volatile Organic Compounds at the Tracking Aerosol Convection Interactions Experiment Field Campaign Report

Formation of secondary organic aerosol (SOA) is responsible for the growth of particles into cloud condensation nuclei (CCN)-relevant sizes and accounts for a substantial fraction of aerosol mass in the troposphere. Despite its wide abundance and importance, capturing SOA in regional and climate models is still challenging due to complex chemical transformations involved in production of SOA. Oxidation products of biogenic hydrocarbons, such as isoprene, monoterpenes, and sesquiterpenes account for the largest fraction of SOA mass over the continents. As such, biogenic SOA is an important source of continental CCN, and has been recently shown to nucleate ice in the deposition mode. To better account for the processes involved in SOA formation in global and regional climate models, we need better measurements of sources and transformations of volatile organic compounds (VOCs), the precursors to SOA formation in the atmosphere. Understanding aerosol-deep convection interactions is an important science driver of the Tracking Aerosol Convection Interactions Experiment (TRACER), requiring a characterization of the critical controls on aerosol properties and processes, and how those properties and processes vary spatially and temporally in the Houston area. In that environment, the atmospheric photo-oxidative chemistry that drives the evolution and transformation of aerosol properties and processes is strongly impacted by the emission of VOCs, which have both anthropogenic (e.g., industrial, urban, transportation, biomass burning) and biogenic (e.g., marine) sources in the region. Understanding (and disentangling) the complex role of VOCs in such a heterogenous region requires high-time-resolution, speciated VOC measurements that are spatially resolved. To meet these measurement requirements, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s time-of-flight proton transfer reaction-mass spectrometer (ToF-PTR-MS) was deployed during the TRACER intensive operational period (IOP) from June to September, 2022 at the ancillary site (ANC), which was sited to provide a characterization of the rural atmospheric environment in contrast to the main site.

54 ENVIRONMENTAL SCIENCES↗

The influence of recent and future climate change on spring Arctic cyclones

In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.

54 ENVIRONMENTAL SCIENCES↗

Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models

Diurnal precipitation is a fundamental mode of variability that climate models have difficulty in accurately simulating. Here, in this work, the diurnal cycle of precipitation (DCP) in participating climate models from the Global Energy and Water Exchanges' DCP project is evaluated over the tropics and central United States. Common model biases such as excessive precipitation over the tropics, too frequent light-to-moderate rain, and the failure to capture propagating convection in the central United States still exist. Over the central United States, the issues of too weak rainfall intensity in climate runs is well improved in their hindcast runs with initial conditions from numerical weather prediction analyses. But the improvement is minimal over the central Amazon. Incorporating the role of the large-scale environment in convective triggering processes helps resolve the phase-locking issue in many models where precipitation often incorrectly peaks near noon due to maximum insolation over land. Allowing air parcels to be lifted above the boundary layer improves the simulation of nocturnal precipitation which is often associated with the propagation of mesoscale systems. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall; however, it also weakens the diurnal variability. Simply increasing model resolution (with cumulus parameterizations still used) cannot fully resolve the biases of low-resolution climate models in DCP. The hierarchy modeling framework from this study is useful for identifying the missing physics in models and testing new development of model convective processes over different convective regimes.

58 GEOSCIENCES↗

Simulating Pyrocumulonimbus Clouds Using a Multiscale Wildfire Simulation Framework

Pyrocumulonimbus (pyroCb) clouds, driven by extreme fires under favorable meteorological conditions, can inject smoke into the stratosphere at magnitudes comparable to those of moderate volcanic eruptions, potentially altering the global radiative balance and atmospheric composition. However, simulating pyroCb is particularly challenging in Earth system models. Using the Energy Exascale Earth System Model (E3SM), we developed a novel global multiscale framework to model pyroCb events in California, which includes a high‐resolution fire radiative power time series, a one‐dimensional plume‐rise parameterization, a fire‐induced vertical water vapor transport scheme, and a surface wildfire sensible heat flux representation. Our simulation successfully reproduces many pyroCb features, including cloud height, spatiotemporal evolution, and convective intensity in comparison with satellite and ground‐based observations. Sensitivity experiments show that realistic pyroCb simulation depends on vertical water vapor transport. These advances provide a basis for future exploration of pyroCb impacts at regional and global scales within climate models.

E3SM↗

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)—key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO 2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

58 GEOSCIENCES↗

Characterizing the impact of water uptake on light absorption by aerosol particles

Absorbing aerosols (AA) have an important impact on the global radiation budget. The composition and properties of AA can vary substantially throughout the atmosphere, depending on the particle source and the influence of chemical aging. Uncertainties associated with the radiative effects of AA remain substantial. A key contributor to this uncertainty is understanding the extent to which water uptake alters absorption by AA particles and how this depends on particle composition. We have used new and existing experimental tools to systematically characterize the relationship(s) between AA chemical and physical characteristics, relative humidity, and mixing of AA with other aerosol components through a combination of laboratory and field measurements. We have developed fundamental understanding through laboratory experiments that will enable interpretation of field observations at DOE ARM sites and facilitate process-based improvements in the simulation of absorption by carbonaceous aerosols in climate models. In the laboratory experiments we have considered a variety of different AA types, including fullerene soot (a surrogate for refractory black carbon, or BC) and nigrosine (a surrogate for partially soluble brown carbon, or BrC). By examining a range of AA types we will develop insight into how the chemical and physical properties of AA particles (e.g. whether they are refractory or soluble) impact the influence of water uptake on absorption. These AA particles will also be mixed—both internally and externally—with compounds having a wide range of hygroscopic properties to establish how the impact of water uptake on absorption will vary with photochemical processing. These laboratory observations have been compared with commonly used theoretical models, enabling development of empirical models that will facilitate improved representation of absorption by AA particles in regional and global climate models. Overall, our study has contributed to the mission of the Atmospheric System Research program by quantifying how interactions between aerosols and radiation depend on relative humidity. Through this, our work will improve understanding and model representation of aerosol processes as they affect the Earth’s radiation budget.

54 ENVIRONMENTAL SCIENCES↗

Rapid increase in tropospheric ozone over Southeast Asia attributed to changes in precursor emission source regions and sectors

Observations indicate that tropospheric ozone (O 3 ) concentrations over Southeast Asia have been increasing rapidly since the 1990s. Here, we quantify source contributions from geographical regions and emission sectors of the two distinct types of O 3 precursors, i.e., nitrogen oxides (NO x ) and volatile organic compounds (VOCs), to the increase in tropospheric O 3 in Southeast Asia during 1990–2019 using an O 3 source tagging technique implemented in a global chemistry-climate model. In this work, the results show that although local anthropogenic emission of NO x in Southeast Asia only contributes 18% of the annual averaged near-surface O 3 concentration, the increase in local NO x emission dominates the increasing trend of O 3 concentration in Southeast Asia, accounting for 107% of the regional averaged trend of 1.07 ppb decade -1 . Increases in NO x emissions from East Asia and South Asia explain 29% of the increasing trend, but 9% is offset by the emission reduction in North America. Ground transportation is responsible for 79% of the rapid O 3 increase, followed by 39% contribution from international shipping. Because an increase in anthropogenic NO x emissions enhances the O 3 production efficiency by VOCs, the increase in near-surface O 3 concentrations in Southeast Asia is thereby largely contributed by methane and biogenic VOCs.

54 ENVIRONMENTAL SCIENCES↗

Global Simulations Suggest Biomass Burning Aerosol Emissions From Grassland Fires Could Be Important Ice Nucleating Particles

Ice nucleating particles (INP) capable of nucleating ice crystals via immersion freezing at temperatures above approximately −35°C may strongly influence cloud glaciation, with implications for global precipitation and climate feedback. In addition to mineral dust, soil dust, and marine organics, laboratory and field measurements suggest biomass burning aerosols (BBA) can act as immersion-mode INP between around −30°C and −15°C. However, the contribution of BBA to the global INP budget remains poorly understood due to poor knowledge of which fuels yield INPs, uncertainties in global coverage of those fuels, and unknown size distributions of the INPs in the BBA. Nonetheless, with some understanding of these uncertainties from sensitivity studies, the relative importance of ice nucleation activity of BBA compared to other INP sources can be quantified. In this work, we investigate the potential global importance of BBA as INP using a global aerosol-climate model, specifically the UK Met Office Unified Model (UM). We evaluate the model using field campaign data sets. We examine potential uncertainties in fuel types and particle sizes on BBA-based INP concentrations. Averaged over June–September between 15°S and 50°S, BBA is a more important INP than dust and marine INP about 30% of the time at altitudes with temperatures between −30°C and −20°C. Our simulations therefore suggest BBA INPs may be at least as important as mineral dust and marine INP over the atmospheric regions and seasons where grassland fires are frequent.

Gohil, Kanishk [Carnegie Mellon University, Pittsb↗

Linking large-scale circulation patterns to low-cloud properties

Abstract. The North Pacific High (NPH) is a fundamental meteorological feature present during the boreal warm season. Marine boundary layer (MBL) clouds, which are persistent in this oceanic region, are influenced directly by the NPH. In this study, we combine 11 years of reanalysis and an unsupervised machine learning technique to examine the gamut of 850 hPa synoptic-scale circulation patterns. This approach reveals two distinguishable regimes – a dominant NPH setup and a land-falling cyclone – and in between a spectrum of large-scale patterns. We then use satellite retrievals to elucidate for the first time the explicit dependence of MBL cloud properties (namely cloud droplet number concentration, liquid water path, and shortwave cloud radiative effect – CRESW) on 850 hPa circulation patterns over the northeast Pacific Ocean. We find that CRESW spans from −146.8 to −115.5 W m−2, indicating that the range of observed MBL cloud properties must be accounted for in global and regional climate models. Our results demonstrate the value of combining reanalysis and satellite retrievals to help clarify the relationship between synoptic-scale dynamics and cloud physics.

54 ENVIRONMENTAL SCIENCES↗