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Advancing representations of equity and justice in climate mitigation futures

THIS PAPER WAS PRIMARILY COMPLETED PRIOR TO THE AUTHOR JOINING PNNL AND NO DOE FUNDING WAS USED FOR THIS PAPER. In this work, we review how equity and justice issues in global climate mitigation scenarios are addressed within Integrated Assessment Models (IAMs) and propose a new research agenda to strengthen their integration in model development and application. We begin by examining prominent concerns at the science-policy interface. We introduce a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological biases that shape what integrated assessment models can reveal at policy-relevant scales. Reflecting on these concerns, we propose a research agenda that describes new avenues of work and draws together distinct emerging initiatives. This agenda is based on the feasibility and depth of required interventions, from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, it addresses the operational challenges of translating justice concepts into metrics, including risks of reductionism, tokenism, and narrow definitions. Underlying this research agenda is a recognition that modeling communities must engage more critically with implicit assumptions in model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development goals, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, they can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal.

Pachauri, Shonali↗

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗

Climatic effects of atmospheric aerosols

It is shown quantitatively how radiative climatic forcing by aerosols depends on the physical properties of the aerosols. The special case of atmospheric aerosols produced by volcanic explosions is considered, and evidence is presented which indicates that even the simple climate models available today may be able to capture some of the basic effects of aerosols on global climate. Possible effects of anthropogenic aerosols are briefly examined. It is noted that additional evidence for the significant influence of aerosols on climate may be found in data obtained from recent spacecraft missions to Venus and Mars.

Hansen, J. E.↗

Short-term climatic fluctuations forced by thermal anomalies

A two level, global, spectral model using pressure as a vertical coordinate was developed. The system of equations describing the model is nonlinear and quasi-geostrophic (linear balance). Static stability is variable in the model. A moisture budget is calculated in the lower layer only. Convective adjustment is used to avoid supercritical temperature lapse rates. The mechanical forcing of topography is introduced as a vertical velocity at the lower boundary. Solar forcing is specified assuming a daily mean zenith angle. The differential diabatic heating between land and sea is paramterized. On land and sea ice surfaces, a steady state thermal energy equation is solved to calculate the surface temperature. On the oceans, the sea surface temperature is specified as the climatological average for January. The model is used to simulate the January, February and March circulations.

Hanna, A. F.↗

Short-term climatic fluctuations forced by thermal anomalies

A two level, global, spectral model using pressure as a vertical coordinate was developed. The system of equations describing the model is nonlinear and quasi-geostrophic (linear balance). Static stability is variable in the model. A moisture budget is calculated in the lower layer only. Convective adjustment is used to avoid supercritical temperature lapse rates. The mechanical forcing of topography is introduced as a vertical velocity at the lower boundary. Solar forcing is specified assuming a daily mean zenith angle. The differential diabatic heating between land and sea is parameterized. On land and sea ice surfaces, a steady state thermal energy equation is solved to calculate the surface temperature. On the oceans, the sea surface temperature is specified as the climatological average for January. The model is used to simulate the January, February and March circulations. Previously announced in STAR as N83-14822

Hanna, A. F.↗

Short-term climatic fluctuations forced by thermal anomalies

A two level, global, spectral model using pressure as a vertical coordinate was developed. The system of equations describing the model is nonlinear and quasi-geostrophic (linear balance). Static stability is variable in the model. A moisture budget is calculated in the lower layer only. Convective adjustment is used to avoid supercritical temperature lapse rates. The mechanical forcing of topography is introduced as a vertical velocity at the lower boundary. Solar forcing is specified assuming a daily mean zenith angle. The differential diabatic heating between land and sea is parameterized. On land and sea ice surfaces, a steady state thermal energy equation is solved to calculate the surface temperature. On the oceans, the sea surface temperature is specified as the climatological average for January. The model is used to simulate the January, February and March circulations. Previously announced in STAR as N83-14822

Hanna, A. F.↗

Basic Mechanisms of Solar Variability

In order to simulate the behavior of a changing Sun in a realistic way, researchers have used a perturbation analysis (the results are summarized in Endal et al. 1985). In this approach, they use a standard solar model and then vary several of the model parameters to mimic the sudden or gradual change of some physical property within the Sun. The evolution following the perturbation is followed in a physically self-consistent way, that is, hydrostatic and thermal processes occur in their normal timescales. This treatment has allowed us to determine the sensitivity of the various global parameters to physical processes affecting the solar interior, and it has guided us in defining the least complex global solar model which can address the question of climatically significant variability. Not surprisingly, magnetic fields play the crucial role. The current status of the model, what researchers have already learned from it, and the future prospects are discussed.

Sofia, Sabatino↗

Assimilating GCOM-W AMSR2 Radiance Data in Future GEOS Reanalysis

Surface and atmospheric radiation are being measured by space-borne conical scanning microwave radiometers with high accuracy and spatial resolution since 1980s'. These radiometers include Special Sensor Microwave Imager (SSM/I) onboard various NOAA's polar-orbiting satellites, Special Sensor Microwave Imager Sounder (SSMIS) onboard Defense Meteorological Satellite Program (DMSP) satellites, and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), and Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard NASA and JAXA's satellites. Atmospheric temperature, humidity, clouds, and precipitation are retrieved using brightness temperature data at frequencies between 22 GHz – 183 GHz. Some of the brightness temperature and retrieved rain rate data made by these imagers are assimilated in NASA Global Modelling and Assimilation Office (GMAO)'s weather and climate data sets including the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets. However, those radiance data are assimilated with the Goddard Earth Observing System model, version 5 (GEOS-5) only in clear-sky conditions. Recently, we started assimilate GPM/GMI radiance data with GEOS-5's atmospheric data assimilation system GSI under all-sky conditions in order to have better constraints in analyzed hydrological properties. GMAO plans to assimilate more microwave radiometers' brightness temperature data in its analyses. In this talk, we will discuss TMI and AMSR2 data's impact in temperature, humidity, clouds and precipitation under all-sky conditions in future GEOS reanalysis.

Jin, Jianjun↗

Dynamical Sensitivity in Response to a Wide Range of Abrupt CO 2 Forcings

An improved understanding of dynamical variability is important for projecting future changes in extratropical weather and the interaction between the extratropical troposphere and the tropics, stratosphere, cryosphere and ocean. Despite their simplicity, the abrupt 2x- and 4xCO 2 forcing simulations from the Coupled Model Intercomparison Project (CMIP) Phase 6 DECK experiments enable a mechanistic look into the forcing and feedback response characteristics of models that can be unambiguously attributed to an increase in carbon dioxide concentrations. Thus, while typically used to evaluate the climate sensitivity in models, with a primary focus on global surface temperature change, here we focus on several measures of extratropical variability, including projected changes in the storm tracks and in stratospheric polar vortex variability. Results are primarily based on simulations produced using low- and high-top versions of the NASA Goddard Institute for Space Studies Model (ModelE) but results are also presented from the larger CMIP6 multi-model ensemble. In addition to the 2x- and 4xCO 2 simulations, we also explore the linearity of the response of extratropical dynamical variability in ModelE to varying levels of CO 2 spanning the range 1/8-8xCO 2 . In particular, we show that the expansion of the jet streams varies nonlinearly with increasing CO 2 , especially in the Northern Hemisphere, and that this can be interpreted in terms of variations in ocean heat transport. The impact of composition feedbacks on changes in variability is also discussed.

dynamical variability↗

DAVINCI: Venus Atmospheric Model Comparisons

The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging(DAVINCI) mission aims to answer long-standing questions regarding Venus’ origin using Zephyr, an atmospheric descent probe. Zephyr will be the first probe to take high-resolution aerial photographs of a mountainous tesserae surface as it descends over the Alpha Regio highlands region, which has the oldest surfaces of Venus. The Zephyr’s descent trajectory that determines the touchdown in the Alpha Regio, which is crucial for the DAVINCI mission, depends on Venus’ atmospheric properties and winds. Unfortunately, the atmospheric data for Venus from previous missions is sparse. Therefore, it is essential to consider various atmospheric models and scenarios from past flight data to predict Zephyr’s flight performance, specifically landing ellipse. To this end, this work compares three atmospheric models: the Venus Global Reference Atmospheric Model (Venus-GRAM), the Venus Climate Database(VCD), and an empirical wind model developed by Ralph Lorenz for the DAVINCI trajectory simulation and modeling. This paper compares the mean and variations of different atmospheric properties and winds from these atmospheric models. In addition, this work combines the atmospheric properties and the wind variability from the Venus-GRAM with the winds from the Lorenz-based model to have more stressing Venus wind dispersions that allow for more conservative trajectory analysis. Furthermore, this work relies on the DAVINCI landing ellipse size as a metric to measure how robust the trajectory analysis will be to the change in the atmospheric properties and winds of the Venus atmosphere.

Pardha Sai Chadalavada↗

The Transition of Satellite Observations Assimilated in GEOS to JEDI

The Goddard Earth Observing System (GEOS) is used by NASA’s Global Modeling and Assimilation Office (GMAO) to produce weather, climate, and air quality forecasts and reanalysis datasets. In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) system into GEOS it is necessary to provide a validated set of input observations in JEDI. The GMAO, in collaboration with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) in JEDI and adding all the necessary features to replicate the existing capability of the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures to assimilate the vast array of satellite and conventional observations assimilated in GEOS, including the GEOS all-sky microwave radiance assimilation framework to assimilate those observations in the UFO. Robust tests have been conducted to ensure correct configurations of observational data bias correction, quality control, and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations will be reported in this presentation.

Jianjun Jin↗

Exploring Western North Pacific Tropical Cyclone Activity in the High‐Resolution Community Atmosphere Model

Abstract High‐resolution climate models (∼28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present‐day (1980–2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under‐represent the basin's dominant share in observations. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid‐level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large‐scale environment on TC development by nudging WNP temperature field toward reanalysis at various strengths. Temperature nudging elicits a significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large‐scale environment can lead to improvements in simulated TCs, suggesting future model developments in relation to model physics. In this way, the potential improvements in model fidelity will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.

58 GEOSCIENCES↗

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R(exp 2) = 0.75) and gross primary productivity (R(exp 2) = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Ecosystem model↗

Plant Physiology Increases the Magnitude and Spread of the Transient Climate Response to CO 2 in CMIP6 Earth System Models

Increasing concentrations of CO 2 in the atmosphere influence climate both through CO 2 ’s role as a greenhouse gas and through its impact on plants. Plants respond to atmospheric CO 2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded in most Earth system models, and a robust literature demonstrates that they can affect global-scale temperature. However, the physiological contribution to transient warming has yet to be assessed systematically in Earth system models. Here this gap is addressed using carbon cycle simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-yr window centered on the time of CO 2 doubling relative to preindustrial CO 2 concentrations. In CMIP6 models, the physiological effect contributes 0.12°C ( σ : 0.09°C; range: 0.02°–0.29°C) of warming to the TCR, corresponding to 6.1% of the full TCR ( σ : 3.8%; range: 1.4%–13.9%). Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the intermodel spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO 2 -forced warming—and the intermodel spread in warming—occurs over land, especially in forested regions.

54 ENVIRONMENTAL SCIENCES↗

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

Abstract A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO 2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

54 ENVIRONMENTAL SCIENCES↗

Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

sea level↗

The Description and Validation of a Computationally-Efficient CH4-CO-OH (ECCOHv1.01) Chemistry Module for 3D Model Applications

We present the Efficient CH4-CO-OH (ECCOH) chemistry module that allows for the simulation of the methane, carbon monoxide, and hydroxyl radical (CH4-CO- OH) system, within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH4-CO-OH system, which primarily determines the global atmospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to methane, CO, and OH, and the concomitant impacts on climate. We implemented the ECCOH chemistry module in the NASA GEOS-5 atmospheric global circulation model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over 2 decades, and evaluated the model output with surface and satellite data sets of methane and CO. The favorable comparison of output from the ECCOH chemistry module (as configured in the GEOS- 5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.

carbon cycle model↗

Impact of Growth Phase, Pigment Adaptation, and Climate Change Conditions on the Cellular Pigment and Carbon Content of Fifty‐One Phytoplankton Isolates

Owing to their importance in aquatic ecosystems, the demand for models that estimate phytoplankton biomass and community composition in the global ocean has increased over the last decade. Moreover, the impacts of climate change, including elevated carbon dioxide (CO2), increased stratification, and warmer sea surface temperatures, will likely shape phytoplankton community composition in the global ocean. Chemotaxonomic methods are useful for modeling phytoplankton community composition from marker pigments normalized to chlorophyll a (Chl a). However, photosynthetic pigments, particularly Chl a, are sensitive to nutrient and light conditions. Cellular carbon is less sensitive, so using carbon biomass instead may provide an alternative approach. To this end, cellular pigment and carbon concentrations were measured in 51 strains of globally relevant, cultured phytoplankton. Pigment-to-Chl a and pigment-to-carbon ratios were computed for each strain. For 25 strains, measurements were taken during two growth phases. While some differences between growth phases were observed, they did not exceed within class differences. Multiple strains of Amphidinium carterae, Ditylum brightwellii and Heterosigma akashiwo were measured to determine whether time in culture influenced pigment and carbon composition. No appreciable trends in cellular pigment or carbon content were observed. Lastly, the potential impact of climate change conditions on the pigment ratios was assessed using a multistressor experiment that included increased mean light, temperature, and elevated pCO2 on three species: Thalassiosira oceanica, Ostreococcus lucimarinus, and Synechococcus. The largest differences were observed in the pigment-to-carbon ratios, while the marker pigments largely covaried with Chl a. The implications of these observations to chemotaxonomic applications are discussed.

Pigments↗