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Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

Aim: Marine biodiversity faces unprecedented threats from anthropogenic climate change. Ecosystem responses to climate change have exhibited substantial variability in the direction and magnitude of redistribution, posing challenges for developing effective climate-adaptive marine management strategies. Location: The California Current Ecosystem (CCE), USA. Methods: We project suitable habitat for 10 highly migratory species in the California Current System using an ensemble of three high-resolution (~10 km) downscaled ocean projections under the Representative Concentration Pathway 8.5 (RCP8.5). Spanning the period from 1980 to 2100, our analysis focuses on assessing the direction and distance of distributional shifts, as well as changes in core habitat area for each species. Results: Our findings reveal a divergent response among species to climate impacts. Specifically, four species were projected to undergo significant poleward shifts exceeding 100 km, and gain habitat (~7%–60%) in response to climate change. Conversely, six species were projected to shift towards the coast, resulting in a loss of habitat ranging from 10% to 66% by the end of the century. These divergent responses could typically be characterized by the mode of thermoregulation (i.e. ectotherm vs. endotherm) and species' affiliations with cool and productive upwelled waters that are characteristic of the region. Furthermore, our study highlights an increase in niche overlap between protected species and those targeted by fisheries, which may lead to increased human interaction events under climate change. Main Conclusions: By providing valuable species distribution projections, our research contributes to the understanding of climate change effects on marine biodiversity and offers critical insight and support for developing climate-ready management of protected and fished species.

The increasing concentration of atmospheric CO2 since the Industrial Revolution has affected surface air temperature. However, the impact of the spatial distribution of atmospheric CO2 concentration on surface air temperature biases remains highly unclear. By incorporating the spatial distribution of satellite-derived atmospheric CO2 concentration in the Beijing Normal University Earth System Model, this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere (NH) under historical conditions from 1976–2005. In comparison with the increase in surface temperature simulated using a uniform distribution of CO2, simulation with a nonuniform distribution of CO2 produced better agreement with the Climatic Research Unit (CRU) data in the NH under the historical condition relative to the baseline over the period 1901–30. Hemispheric June–July–August (JJA) surface air temperature increased by 1.28°C ± 0.29°C in simulations with a uniform distribution of CO2, by 1.00°C ± 0.24°C in simulations with a non-uniform distribution of CO2, and by 0.24°C in the CRU data. The decrease in downward shortwave radiation in the non-uniform CO2 simulation was primarily attributable to reduced warming in Eurasia, combined with feedbacks resulting from increased leaf area index (LAI) and latent heat fluxes. These effects were more pronounced in the non-uniform CO2 simulation compared to the uniform CO2 simulation. Results indicate that consideration of the spatial distribution of CO2 concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models. [ABSTRACT FROM AUTHOR]

Terrestrial, aquatic, and marine ecosystems regulate climate at local to global scales through exchanges of energy and matter with the atmosphere and assist with climate change mitigation through nature‐based climate solutions. Climate science is no longer a study of the physics of the atmosphere and oceans, but also the ecology of the biosphere. This is the promise of Earth system science: to transcend academic disciplines to enable study of the interacting physics, chemistry, and biology of the planet. However, long‐standing tension in protecting, restoring, and managing forest ecosystems to purposely improve climate evidences the difficulties of interdisciplinary science. For four centuries, forest management for climate betterment was argued, legislated, and ultimately dismissed, when nineteenth century atmospheric scientists narrowly defined climate science to the exclusion of ecology. Today's Earth system science, with its roots in global models of climate, unfolds in similar ways to the past. With Earth system models, geoscientists are again defining the ecology of the Earth system. Here we reframe Earth system science so that the biosphere and its ecology are equally integrated with the fluid Earth to enable Earth system prediction for planetary stewardship. Central to this is the need to overcome an intellectual heritage to the models that elevates geoscience and marginalizes ecology and local land knowledge. The call for kilometer‐scale atmospheric and ocean models, without concomitant scientific and computational investment in the land and biosphere, perpetuates the geophysical view of Earth and will not fully provide the comprehensive actionable information needed for a changing climate. Plain Language Summary: Terrestrial ecosystems provide a natural solution to planetary warming by storing carbon, dissipating surface heating through evapotranspiration, and other processes. That forests, in particular, influence climate is a centuries‐old premise, but its potential for planetary stewardship has not been realized. In an acrimonious controversy spanning several centuries, managing forests to purposely change climate was advocated, legislated, and resoundingly dismissed as unscientific. Similar intellectual bias is evident in today's Earth system science and the associated Earth system models, which are the state‐of‐the‐art models used to inform climate policy. The popular characterization of Earth system science lauds its interdisciplinary melding of physics, chemistry, and biology, but the models emphasize the physics and fluid dynamics of the atmosphere and oceans and present a limited perspective of terrestrial ecosystems in the Earth system. Ecologists studying the living world increasingly have a voice in Earth system science as we move beyond the physical basis for climate change to Earth system prediction for planetary stewardship. As we once again look to forests to solve a climate problem, we must surmount the disciplinary narrowness that failed to answer the forest‐climate question in the past and that continues to limit the interdisciplinary potential of Earth system science. Key Points: Nature‐based climate solutions have been advocated for centuries, but have been distorted by academic bias and colonialist prejudiceEarth system science, while recognizing the climate services of the biosphere, has a geophysical bias in interdisciplinary collaborationTo realize the potential for planetary stewardship, Earth system models must embrace the living world equally with the fluid world [ABSTRACT FROM AUTHOR]

Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m−2, while the ZM_plus increases it by 0.27 W m−2, resulting from excessive direct (0.31 W m−2) and indirect forcing (−1.79 W m−2). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m−2) and indirect aerosol forcing (−1.52 W m−2). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m−2 and −1.31 W m−2, respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth. Plain Language Summary: The Energy Exascale Earth System Model (E3SM) exhibits strong direct and indirect aerosol forcings, after advanced stratiform and convective cloud treatments are implemented. This study identifies the primary cause of these excessive aerosol forcings as the significant overestimation of anthropogenic aerosols due to insufficient removal of aerosols by precipitation. To address this issue, we made aerosol wet removal representation more physical, which effectively reduced the overestimation of aerosols, bringing both direct and indirect forcings to the expected ranges. Furthermore, cloud and aerosol climatology are notably improved as the result of these developments in cloud and aerosol treatments. Key Points: The new cloud microphysics scheme P3 improves simulations of cloud properties in the NH and aerosol forcingInsufficient wet removal leads to an overly strong aerosol forcing after incorporating the enhanced deep convection parameterization suiteThe aerosol wet removal improvements lead to more reasonable aerosol forcing and improved aerosol climatology in Energy Exascale Earth System Model [ABSTRACT FROM AUTHOR]

To bridge the knowledge gap between (a) our (instantaneous‐to‐seasonal‐scale) process understanding of plants and water and (b) our projections of long‐term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models—two‐dimensional linear models—and observation‐based data from satellites, eddy covariance towers, weather stations, and machine‐learning‐derived products to determine the dominant sub‐annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal‐scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics—positively sloped tangent lines to a convex long‐term mean‐state curve—is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean‐state pattern, and hypothesize that this may be due to lack of water‐carbon feedbacks at daily scales. [ABSTRACT FROM AUTHOR]

Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well‐resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation‐based assessments of the fraction of days experiencing surface T‐pH and T‐Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases. Plain Language Summary: Ocean ecosystems are under stress from changing temperature and acidity due to the human‐driven increase in global atmospheric carbon dioxide. Global Earth system models (ESMs) are used to study the effects of climate variability and change on marine ecosystems. However, computing power and storage constraints limit the level of detail represented by these simulations. Some short timescale variability present in the real world is missing from ESM output. Despite this inconsistency, we show that at an array of sites where daily observation data from ocean moorings is available, models accurately capture observed spatial patterns in estimates of the amount of time the locations experience combined temperature and acidification stress. We also demonstrate circumstances in which some model errors can be reduced through bias correction. Key Points: Physical and biogeochemical variability from moorings and GFDL ESM4.1 output is most consistent on seasonal and longer time scalesMore high frequency (daily to monthly) variability is present in observations than in ESM outputDespite missing high frequency variability, ESM output can be applied to accurately quantify multiple stressor events [ABSTRACT FROM AUTHOR]

We used the Meteorological Research Institute Earth System Model to investigate land precipitation and net primary production (NPP, proxy for agricultural production here) in terms of food and water security. In the preindustrial state, the largest decrease in Southeast Asian precipitation (> 20%) occurs along with the largest El Niño and positive phase of the Atlantic multidecadal oscillation, consistent with the 1876-78 Great Drought, leading to the largest decrease in NPP (~ 20%); >2 standard deviations, extreme dryness and crop failure. In relatively arid regions (e.g., India and northeastern Brazil), the largest decreases in precipitation and NPP reach ≥ 50%, particularly 80 ~ 90% in Deccan, India. In the 21st century warming projection (Shared Socioeconomic Pathways 5-8.5, the largest CO2 emission scenario), the interannual variability of precipitation and NPP in Monsoon Asia increase under the influence of enhanced El Niño-Southern Oscillation. Although the increased precipitation variability indicates more frequent severer droughts than in the preindustrial state, this severity does not influence NPP so much: the increased NPP variability is negligible compared to the significant increase in normal NPP by CO2 fertilization effect, which indicates usually rich harvests. Compared to a recent severe crop failure (− 25% in Japan in 1993), the simulated preindustrial drought-induced NPP decreases of ≥ 50% in parts of low latitudes are extraordinarily large enough to correspond to devastating crop failures. The model indicates that great famines before the 20th century were natural in origin, and that manmade factors, such as harsh taxes and hoarding and export of grain, made the famines more devastating. [ABSTRACT FROM AUTHOR]

Vertical migrants are a diverse group of organisms, which includes crustaceans, cephalopods and mesopelagic fishes. They play an active role in the biogeochemical cycles but are in general not included in numerical models. In this study we introduce a fully coupled Earth system model that represents vertical migration and with this resolves the key components of the mesopelagic ecosystem, namely migrating zooplankton and mesopelagic fish, including their feedbacks on biogeochemical cycles. The redistribution of nutrients in the water column by vertical migration results in a reduction of the net primary production of 14%–21%, as well as in an asymmetric response in the low oxygenated waters in the tropical Pacific (an increase in the northern and a decrease in the southern oxygen minimum zone). On a global scale, we find the active transport of carbon out of the surface layer to be equivalent to ∼25% of the total export (∼30% relative to passive sinking). In the low latitudes, migration results regionally in a reduction of the shallow export by 2%–10% and an increase of the deep carbon export by 6%–15%. In our simulations, mesopelagic fish, with a biomass of 3–3.4 Gt wet weight, have a slightly larger impact on active carbon flux than migrating zooplankton. Key Points: We present a global model that represents the impact of mesopelagic fish and vertically migrating organisms on the biogeochemical cyclesThe simulated redistribution of nutrients by vertical migration results in a reduction of the global net primary production by 14%–21% compared to the simulation without vertical migrationThe active carbon export out of the surface layers by vertical migration amounts to ∼25% of the total transport (∼30% of the passive sinking) [ABSTRACT FROM AUTHOR]

The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California-focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time-series and causal analysis frameworks are used to examine runoff sensitivities state-wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time-series shape, than forecast lead time, 2-to-4 days prior to the 1997 flood onset.

Simulating the warmth and equability of past hothouse climates has been a challenge since the inception of paleoclimate modeling. The newest generation of Earth system models (ESMs) has shown substantial improvements in the ability to simulate the early Eocene global mean surface temperature (GMST) and equator-to-pole gradient. Results using the Community Earth System Model suggest that parameterizations of atmospheric radiation, convection, and clouds largely determine the Eocene GMST and are responsible for improvements in the new ESMs, but they have less direct influence on the equator-to-pole temperature gradient. ESMs still have difficulty simulating some regional and seasonal temperatures, although improved data reconstructions of chronology, spatial coverage, and seasonal resolution are needed for more robust model assessment. Looking forward, key processes including radiation and clouds need to be benchmarked and improved using more accurate models of limited domain/physics. Earth system processes need to be better explored, leveraging the increasing ESM resolution and complexity. Earth system models (ESMs) are now able to simulate the large-scale features of the early Eocene. Remaining model-data discrepancies exist at regional and seasonal scales and require improvements in both proxy data and ESMs. A hierarchical modeling approach is needed to ensure relevant physical processes are parameterized reasonably well in ESMs. Future work is needed to leverage the continuously increasing resolution and complexity of ESMs. [ABSTRACT FROM AUTHOR]

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations. Plain Language Summary: The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new Land Model (LM4.1) as part of its 4th generation coupled model development. This model includes advances from the previous generation and introduces a new vegetation demography model, multi‐layer canopy, plant hydraulics, fire, and land use representation as well as dynamic atmospheric dust coupling. Coupled within an Earth System Model (ESM4.1), LM4.1 features an improved representation of many ecological processes from the previous generation of GFDL ESMs. Key Points: A new land model LM4.1 is developed at the Geophysical Fluid Dynamics Laboratory (GFDL) for the next‐generation Earth System Model (ESM) ESM4.1LM4.1 integrates age‐height structured vegetation dynamics, multi‐layer canopy‐soil‐snow energy exchanges, and prognostic fires and mineral dustESM4.1/LM4.1 improves patterns of land surface climate and carbon cycle compared to the previous generation GFDL model ESM2G/LM3.0 [ABSTRACT FROM AUTHOR]

Many countries around the world are rapidly advancing sustainable development (SD) through the exploitation of clean energy sources such as solar and wind energy, which are becoming the core of the sustainable energy transition. In recent years, the continuous advancement of Earth system models (ESMs) has facilitated numerous studies utilizing them to predict long-term and large-scale meteorological elements, consequently enabling forecasts of wind and solar energy. These forecasts provide critical guidance for formulating national renewable energy policies. Nevertheless, the current literature on ESMs predicting wind and solar energy lacks sufficient integration. Hence, to comprehend the focal points and future research prospects, we conducted this systematic review, employing four academic search tools to comprehensively analyze the relevant literature from the past five years. We summarized the general analytical process and compared the content and conclusions of the literature. The study reveals that future photovoltaic (PV) potential for electricity generation may increase in certain regions but decrease in others, while the global potential for concentrated solar power (CSP) may diminish, influenced by diverse factors and displaying significant regional disparities. In addition, wind resource trends vary in different regions, and forecasts exhibit considerable uncertainty. Therefore, many studies have corrected wind speeds prior to predicting wind energy. Subsequent research endeavors should concentrate on optimizing ESMs, investigating the impacts of technological innovation, and enhancing the prediction and analysis of extreme weather events. [ABSTRACT FROM AUTHOR]

The physiological tolerances of marine species toward ambient temperature and oxygen can jointly be evaluated in a single metric: the metabolic index. Changes therein characterize a changing aerobic habitat tailored to species‐specific thermal and hypoxia sensitivity traits. If the geographical limits of marine species as indicated by critical thresholds of the metabolic index shift abruptly in response to ocean warming and deoxygenation, aerobic habitat could potentially be lost abruptly. Here, we assess the spatio‐temporal detectability of abrupt shifts in potential habitats for selected marine species within the Shared Socioeconomic Pathway 5–8.5 (SSP5‐8.5) scenario run with the fully coupled Norwegian Earth System Model version 2 (NorESM2‐LM). We use an environmental time series changepoint detection routine and analyze the number and timing of these abrupt changes over the past, present and future. We construct nine ecophysiotypes with low, medium, and high resting vulnerability to hypoxia and sensitivity of hypoxia vulnerability to temperature, respectively, with six different thresholds for minimal oxygen demand. For all ecophysiotypes with positive temperature sensitivity to hypoxia, the volume of non‐viable habitat in the upper ocean expands between 1850 and 2100. Changepoints in the metabolic index are detected in 49.0 ± 9.2% of the volume that eventually becomes non‐viable for all ecophysiotypes over the course of the 21st century. More than 75% of these abrupt shifts occur in response to warming close to the surface, while at depth, the abrupt shifts driven by changes in oxygen partial pressure become more important, with potentially severe consequences for marine species, populations, and ecosystems. Plain Language Summary: Future ocean warming and the accompanying deoxygenation will change the extent of habitats of all marine species. If the rate of future warming and deoxygenation is slow enough, marine species could adapt to the lower oxygen availability or migrate away to places that match their metabolic habitat requirements. However, if these rates are fast, and potentially exacerbated by abrupt shifts, the consequences for the future distribution of marine species will be profound. Here, we analyze abrupt shifts, or changepoints, in the metabolic index as a measure of metabolic habitat requirements for different marine species. Using projections of an Earth system model, we find that approximately half of the eventually lost habitat between 1850 and 2100 experiences abrupt shifts, and most of them occur between 1950 and 2040, mainly driven by the projected warming. Key Points: Marine habitats described by the metabolic index are lost for a range of marine species in a strong emission scenarioAbrupt changes in the metabolic index are detected in all ocean basins over a wide range of depth levelsTemperature changes drive abrupt metabolic index changes close to the surface, while changes in oxygen become important at depth [ABSTRACT FROM AUTHOR]

Two coupled climate models that participated in the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0), and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3) were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air–ice heat flux, radiation penetration and absorption, melt ponds, and ice–ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis products from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of the Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes in spatial patterns of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have the potential for broad application in climate models for simulation and future climate scenario projection, especially for those with underestimated SIT. [ABSTRACT FROM AUTHOR]

Understanding the impacts of drought on plant photosynthetic phenology and physiology is essential for accurately predicting annual gross primary productivity (GPP) and global carbon cycles. While droughts in different seasons can have different effects on plant growth and photosynthesis, a comprehensive understanding of how plant photosynthetic phenology and physiology respond to different seasons’ droughts and their temporal changes is lacking. Here, we comprehensively evaluated the drought sensitivities of plant photosynthetic phenology and physiology and their temporal trends in the past two decades, using the start/end of the photosynthetic seasons (SOS/EOS) and peak GPP (GPPmax) derived from FLUXNET ground observations since the 1990s and remote-sensing data (2001–2020) over the globe. Our results show that spring droughts leads to delayed SOS in arid ecosystems and advanced SOS in humid ecosystems. In contrast, droughts in summer and autumn generally advance EOS. In addition, spring droughts decrease GPPmax in arid regions but increase it in humid regions, whereas summer droughts lead to significant GPPmax reductions. More importantly, we observed significant increases in the drought sensitivity of SOS, EOS, and GPPmax over the last two decades, which is driven by long-term decreases in background soil moisture and increases in atmospheric water deficit under climate change. Furthermore, these increasing trends were projected to persist in the 21st century under Shared Socioeconomic Pathways 8.5 and 4.0. Overall, our findings underscore the critical role of drought timing in shaping ecosystem responses and highlight the growing vulnerability of ecosystem phenology and physiology to drought, which may restrict the increases in terrestrial carbon uptake under warming.

Abstract Terrestrial, aquatic, and marine ecosystems regulate climate at local to global scales through exchanges of energy and matter with the atmosphere and assist with climate change mitigation through nature‐based climate solutions. Climate science is no longer a study of the physics of the atmosphere and oceans, but also the ecology of the biosphere. This is the promise of Earth system science: to transcend academic disciplines to enable study of the interacting physics, chemistry, and biology of the planet. However, long‐standing tension in protecting, restoring, and managing forest ecosystems to purposely improve climate evidences the difficulties of interdisciplinary science. For four centuries, forest management for climate betterment was argued, legislated, and ultimately dismissed, when nineteenth century atmospheric scientists narrowly defined climate science to the exclusion of ecology. Today's Earth system science, with its roots in global models of climate, unfolds in similar ways to the past. With Earth system models, geoscientists are again defining the ecology of the Earth system. Here we reframe Earth system science so that the biosphere and its ecology are equally integrated with the fluid Earth to enable Earth system prediction for planetary stewardship. Central to this is the need to overcome an intellectual heritage to the models that elevates geoscience and marginalizes ecology and local land knowledge. The call for kilometer‐scale atmospheric and ocean models, without concomitant scientific and computational investment in the land and biosphere, perpetuates the geophysical view of Earth and will not fully provide the comprehensive actionable information needed for a changing climate.

Abstract Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m−2, while the ZM_plus increases it by 0.27 W m−2, resulting from excessive direct (0.31 W m−2) and indirect forcing (−1.79 W m−2). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m−2) and indirect aerosol forcing (−1.52 W m−2). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m−2 and −1.31 W m−2, respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

Abstract Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well‐resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation‐based assessments of the fraction of days experiencing surface T‐pH and T‐Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.

Most ecosystems have resistance to soil moisture (SM) deficit, which is termed drought resistance. Drought resistance can be invalid and global terrestrial carbon uptake losses can be aggravated when SM deficit exceeds a critical threshold. However, soil moisture thresholds (SMTs) that detrimentally impact global terrestrial carbon uptake are still unclear. We performed numerical simulations using the Community Earth System Model, and estimated the SMTs by the back propagation neural network method for the years 2004–2014. The SMTs represent the inflection point for vegetation changes from high to low drought resistance phase, and terrestrial carbon uptake losses from low to high rate. Soil moisture‐limited ecoregions have higher SMTs than energy‐limited ecoregions, indicating the increased vulnerability and sensitivity of SM‐limited ecoregions to SM deficit and more easily aggravated terrestrial carbon uptake losses during drought. SMTs varied in different vegetation types and broadleaf deciduous trees displayed the highest SMTs and C3 arctic grasses have lowest thresholds. Humid and high vegetation coverage rate regions have lower thresholds. The SMTs increase with the increase of clay content and the decrease of sand content. In addition, land‐atmosphere feedback caused by SM deficit has a large impact on terrestrial carbon uptake and may be one of the main reasons for the aggravation of vegetation carbon uptake losses. Our results provide a unique perspective for investigating the impact of drought on vegetation. Plain Language Summary: With global warming, severe soil moisture (SM) deficit will become more intense, frequent, and will last longer in many regions. Global terrestrial carbon uptake losses can be aggravated when SM deficit exceeds a critical threshold. However, soil moisture thresholds (SMTs) that detrimentally impact global terrestrial carbon uptake are still unclear. The present study fills this gap. SMTs that aggravate global terrestrial carbon uptake losses are estimated. The SMTs for different climate zones and vegetation types are determined. Estimating SMTs is essential for predicting soil drought risk and preparing for future climate change. Key Points: Simulations conducted by an earth system model estimated the soil moisture thresholds (SMTs) that aggravate global terrestrial carbon uptake lossesSM‐limited ecoregions have higher SMTs than energy‐limited ecoregionsLand‐atmosphere feedback caused by SM deficit is one of the reasons for aggravation of terrestrial carbon uptake losses [ABSTRACT FROM AUTHOR]

The Paris Agreement plans for "net‐zero" carbon dioxide (CO2) emissions during the second half of the 21st century. However, reducing emissions from some sectors is challenging, and "net‐zero" permits carbon dioxide removal (CDR) activities. One CDR scheme is ocean alkalinity enhancement (OAE), which proposes dissolving basic minerals into seawater to increase its buffering capacity for CO2. While modeling studies have often investigated OAE at basin or global scale, some proposals focus on readily accessible coastal shelves, with TA added through the dissolution of seafloor olivine sands. Critically, by settling and dissolving sands on shallow seafloors, this retains the added TA in near‐surface waters in direct contact with atmospheric CO2. To investigate this, we add dissolved TA at a rate of ∼29 Teq y−1 to the global shelves (<100m) of an Earth system model (UKESM1) running a high emissions scenario. As UKESM1 is fully coupled, wider effects of OAE‐mediated increase in ocean CO2 uptake –e.g. atmospheric xCO2, air temperature and marine pH– are fully quantified. Applying OAE from 2020 to 2100 decreases atmospheric xCO2 ∼10 ppm, and increases air‐to‐sea CO2 uptake ∼8%. In‐line with other studies, CO2 uptake per unit of TA added occurs at a rate of ∼0.8 mol C (mol TA)−1. Significantly for monitoring, advection of added TA results in ∼50% of CO2 uptake occurring remotely from OAE operations, and the model also exhibits noticeable land carbon reservoir changes. While practical uncertainties and model representation caveats remain, this analysis estimates the effectiveness of this specific OAE scheme to assist with net‐zero planning. Plain Language Summary: The Paris Agreement aims to limit climate warming below 2.0°C by achieving net‐zero carbon dioxide (CO2) emissions during the 21st century. As they are difficult to abate for some sectors of activity, carbon dioxide removal schemes will be needed to offset residual emissions. One scheme, ocean alkalinity enhancement (OAE), proposes elevating the ocean's storage capacity for CO2 by increasing its alkalinity by adding basic minerals as solutions or particulates. The latter require time to dissolve but risk sinking away from the ocean's surface where they absorb CO2. Coastal OAE proposes adding particulate minerals on the shallow continental shelves, where dissolution products will remain within the upper water column. Here we investigate coastal OAE by adding alkalinity to the ocean of a state‐of‐the‐art Earth system model to quantify enhanced CO2 uptake, where this occurs, its efficiency, and its impacts on atmospheric CO2 concentration and climate. Overall, coastal OAE increased CO2 uptake, and did so with an efficiency of almost 0.8 mol carbon per equivalent alkalinity. Significantly, almost 50% of the additional CO2 uptake took place away from OAE operations, while a noticeable fraction of ocean uptake was balanced by land losses, both factors indicating challenges for monitoring the effectiveness of real‐world deployment. Key Points: Coastal ocean alkalinity enhancement investigated using state‐of‐the‐art Earth system model under high emissions scenarioAlkalinity addition of ∼29 Teq y−1 during 2020–2100 increases ocean CO2 uptake 8% and decreases atmospheric CO2 by 10 ppmAlmost 50% of extra CO2 uptake is remote from ocean alkalinity enhancement operations with implications for measurement, reporting and verification [ABSTRACT FROM AUTHOR]

Advanced numerical climate models are known to exhibit biases in simulating some features of El Niño–Southern Oscillation (ENSO), which is a key mode of interannual climate variability. In this study we analyze how two fundamental features of observed ENSO – asymmetry between hot and cold states and phase-locking to the annual cycle – are reflected in two different versions of the INMCM Earth system model (state-of-the-art Earth system model participating in the Coupled Model Intercomparison Project). We identify the above ENSO features using the conventional empirical orthogonal functions (EOF) analysis, which is applied to both observed and simulated upper ocean heat content (OHC) data in the tropical Pacific. We obtain that the observed tropical Pacific OHC variability is described well by two leading EOF-modes, which roughly reflect the fundamental recharge-discharge mechanism of ENSO. These modes exhibit strong seasonal cycles associated with ENSO phase locking while the revealed nonlinear dependencies between amplitudes of these cycles reflect ENSO asymmetry.We also assess and compare the predictability of observed and simulated ENSO based on linear inverse modelling. We find that the improved INMCM6 model has significant benefits in simulating described features of observed ENSO as compared with the previous INMCM5 model. The improvements of the INMCM6 model providing such benefits are discussed. We argue that proper cloud parameterization scheme is crucial for accurate simulation of ENSO dynamics with numerical climate models. [ABSTRACT FROM AUTHOR]

The frequency, intensity, and duration of extreme droughts, with devastating impacts on tree growth and survival, have increased with climate change over the past decades. Assessing growth resistance and resilience to drought is a crucial prerequisite for understanding the responses of forest functioning to drought events. However, the responses of growth resistance and resilience to extreme droughts with different durations across different climatic zones remain unclear. Here, we investigated the spatiotemporal patterns in growth resistance and resilience in response to extreme droughts with different durations during 1901–2015, relying on tree‐ring chronologies from 2389 forest stands over the mid‐ and high‐latitudinal Northern Hemisphere, species‐specific plant functional traits, and diverse climatic factors. The findings revealed that growth resistance and resilience under 1‐year droughts were higher in humid regions than in arid regions. Significant higher growth resistance was observed under 2‐year droughts than under 1‐year droughts in both arid and humid regions, while growth resilience did not show a significant difference. Temporally, tree growth became less resistant and resilient to 1‐year droughts in 1980–2015 than in 1901–1979 in both arid and humid regions. As drought duration lengthened, the predominant impacts of climatic factors on growth resistance and resilience weakened and instead foliar economic traits, plant hydraulic traits, and soil properties became much more important in both climatic regions; in addition, such trends were also observed temporally. Finally, we found that most of the Earth system models (ESMs) used in this study overestimated growth resistance and underestimated growth resilience under both 1‐year and 2‐year droughts. A comprehensive ecophysiological understanding of tree growth responses to longer and intensified drought events is urgently needed, and a specific emphasis should be placed on improving the performance of ESMs. [ABSTRACT FROM AUTHOR]

Abstract We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations.

Abstract Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

Abstract The physiological tolerances of marine species toward ambient temperature and oxygen can jointly be evaluated in a single metric: the metabolic index. Changes therein characterize a changing aerobic habitat tailored to species‐specific thermal and hypoxia sensitivity traits. If the geographical limits of marine species as indicated by critical thresholds of the metabolic index shift abruptly in response to ocean warming and deoxygenation, aerobic habitat could potentially be lost abruptly. Here, we assess the spatio‐temporal detectability of abrupt shifts in potential habitats for selected marine species within the Shared Socioeconomic Pathway 5–8.5 (SSP5‐8.5) scenario run with the fully coupled Norwegian Earth System Model version 2 (NorESM2‐LM). We use an environmental time series changepoint detection routine and analyze the number and timing of these abrupt changes over the past, present and future. We construct nine ecophysiotypes with low, medium, and high resting vulnerability to hypoxia and sensitivity of hypoxia vulnerability to temperature, respectively, with six different thresholds for minimal oxygen demand. For all ecophysiotypes with positive temperature sensitivity to hypoxia, the volume of non‐viable habitat in the upper ocean expands between 1850 and 2100. Changepoints in the metabolic index are detected in 49.0 ± 9.2% of the volume that eventually becomes non‐viable for all ecophysiotypes over the course of the 21st century. More than 75% of these abrupt shifts occur in response to warming close to the surface, while at depth, the abrupt shifts driven by changes in oxygen partial pressure become more important, with potentially severe consequences for marine species, populations, and ecosystems.

Sea level rise (SLR) due to surface melt and to dynamic losses from the ice sheets—that is via accelerated flow of glaciers into the sea—is something that may be potentially mitigated by cooling the ice sheet and oceans via solar geoengineering. We use two ice dynamic models driven by changes in surface mass balance (SMB) from four climate models to estimate the SLR contribution from the Greenland ice sheet under the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) 4.5, and 8.5, and Geoengineering Model Intercomparison Project G4 scenarios. The G4 scenario adds 5 Tg/yr sulfate aerosols to the equatorial lower stratosphere (equivalent of 1/4 the 1991 Mt Pinatubo SO2 eruption) to the IPCC RCP4.5 scenario, which itself approximates the greenhouse gas emission commitments agreed in Paris in 2015. Over the 2020–2090 period, mass loss under G4 is about 31%–38% that under RCP4.5, which is 36%–48% lower than under RCP8.5. Ice lost across the grounding line under both G4 and RCP4.5 is reduced in the future as the termini of many southeast Greenland outlets retreat onto bedrock above sea level. Glaciers with large low‐lying catchments in the west, north, and northeast of Greenland (e.g., Jakobshavn, 79N, Zachariae Isstrøm, and Petermann glaciers) discharge more ice from the ice‐sheet interior under RCP4.5 than under G4. Although calving losses vary much more than the SMB difference between ice dynamic models, both models point to significant ice discharge losses of between 15% and 42% across the scenarios. Plain Language Summary: Sea level rise from Greenland over the next century may be around 10 cm by 2100. But the amount, and the long‐term stability of the ice sheet depend on the degree of summer warming it experiences. Limiting greenhouse gas emissions to the levels pledged by states under the 2015 Paris agreement cuts ice sheet losses by 1/3–1/2 of the losses under the business‐as usual‐emissions scenario. If further cooling is induced by aerosols put into the stratosphere at a rate of about 1/4 of the 1991 eruption of Mt Pinatubo, then the ice sheet loss is reduced by about 30% compared with Paris emissions. This specific aerosol geoengineering scenario maintains both the deep and fast‐flowing glaciers and the smaller mountain glaciers closer to present sizes than they would be under a greenhouse gas emission scenario similar to international pledges in the 2015 Paris agreement. Iceberg calving remains the most difficult to quantify aspect of Greenland ice loss. Key Points: Stratospheric aerosol injection at the rate of 5 Tg/yr (G4) lowers Greenland mass loss relative to RCP4.5 by 31%–38% by 2090Across four Earth System Model and two ice dynamic models (G4–RCP4.5) differences are 34%–40% in surface mass balance and 16%–34% in ice dischargeDynamic mass loss by calving from glaciers is the largest uncertainty between ice dynamics models [ABSTRACT FROM AUTHOR]

Sea‐level rise (SLR) projections by Earth System Models (ESMs) depend on ice sheet surface mass balances. Accurate, global atmosphere reanalyses would be ideal for providing equilibrated ice sheet model initial conditions in fully coupled ESM simulations. Here we present the first evaluation of 1980–1990 global reanalysis precipitation over Greenland and Antarctica that uses independent observations of net accumulation rates derived from shallow ice cores. Precipitation distributions from both the European Centre for Medium‐Range Weather Forecast's Reanalysis (ERA5) and the Modern‐Era Retrospective Analysis for Research and Applications (MERRA‐2) are highly correlated with contemporaneous co‐located net accumulation rates from Greenland (r2 > 0.95) and West Antarctica (r2 > 0.7). Three other commonly used reanalyses (WFDE5, CRUNCEP, and GSWP3) exhibit significantly weaker correlations on one or both ice sheets. Our findings imply that ESMs should use ERA5 or MERRA‐2 in data‐forced simulations to validate ice sheet model dynamics and precondition firn for SLR projections. Plain Language Summary: Because they assimilate observational data into self‐consistent models, atmospheric reanalyses are generally considered the best products for estimating the historical evolution of Earth's atmosphere. For this reason, their surface fields commonly provide land surface models with input data to study the impacts of climate change. To determine which reanalysis data set provides the best input data over Greenland and Antarctica, we compare precipitation from five reanalysis data sets to ice core measurements. We find that two reanalysis data sets provide accurate long‐term precipitation fields over Greenland, indicating their utility for ice sheet studies. Overall, we suggest the application of specific reanalysis data sets to improve future studies of sea‐level rise from ice sheets. Key Points: Net accumulation measured in shallow ice cores, adjusted for sublimation/deposition, constrains climatological precipitation over ice sheetsERA5 and MERRA‐2 precipitation fields over Greenland are highly correlated (r2 > 0.95) with in situ measurements of net accumulationOther widely used reanalyses (WFDE5, CRUNCEP, and GSWP3) are unfit for studies of ice sheet surface mass balance [ABSTRACT FROM AUTHOR]

Abstract The Paris Agreement plans for “net‐zero” carbon dioxide (CO2) emissions during the second half of the 21st century. However, reducing emissions from some sectors is challenging, and “net‐zero” permits carbon dioxide removal (CDR) activities. One CDR scheme is ocean alkalinity enhancement (OAE), which proposes dissolving basic minerals into seawater to increase its buffering capacity for CO2. While modeling studies have often investigated OAE at basin or global scale, some proposals focus on readily accessible coastal shelves, with TA added through the dissolution of seafloor olivine sands. Critically, by settling and dissolving sands on shallow seafloors, this retains the added TA in near‐surface waters in direct contact with atmospheric CO2. To investigate this, we add dissolved TA at a rate of ∼29 Teq y−1 to the global shelves (

Earth system models account for seasonal snow cover, but many do not accommodate the deeper snowpack on ice sheets (aka firn) that slowly transforms to ice under accumulating snowfall. To accommodate and resolve firn depths of up to 60 m in the Energy Exascale Earth System Model's land surface model (ELM), we add 11 layers to its snowpack and evaluate three dry snow compaction equations in multi-century simulations. After comparing results from ELM simulations (forced with atmospheric reanalysis) with empirical data, we find that implementing into ELM a two-stage firn densification model produces more accurate dry firn densities at intermediate depths of 20–60 m. Compared to modeling firn using the equations in the (12 layer) Community Land Model (version 5), switching to the two-stage firn densification model (with 16 layers) significantly decreases root-mean-square errors in upper 60 m dry firn densities by an average of 41 kg m−3 (31%). Simulations with three different firn density parameterizations show that the two-stage firn densification model should be used for applications that prioritize accurate upper 60 m firn air content (FAC) in regions where the mean annual surface temperature is greater than roughly −31°C. Because snow metamorphism, firn density, and FAC are major components in modeling ice sheet surface albedo, melt water retention, and climatic mass balance, these developments advance broader efforts to simulate the response of land ice to atmospheric forcing in Earth system models.

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve (Bsw), play crucial roles in controlling forest diversity, with higher Bsw values (>7) favoring late successional species in competition, and lower Bsw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry-season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.

The objective of the research is to explore the predictability of water resources directly with GCMs by analysing long-term effects of climate change on Northern Tunisia’s blue and green water. Hydrologic impacts rely on a rainfall-runoff lumped model using outputs of CMIP6 GCMs within the framework of the ssp2-45 scenario. Among the 30 CMIP6 models, the composite cnrm-esm2-1 and fgoals-g3 best restore observed runoff from 1995 to 2014 and give the best GCM. Hydrologic projections 2015–2100 show significant drops in rainfall (9%), runoff (21%), groundwater recharge (15%), as well as for green water (6%). The results show that the use of raw GCMs predictions on large basins is possible and provides precisions comparable to what is produced when using Regional Climate Models in medium size basins.

To project possible future climate change, it is important to understand Earth system response to CO2 removal, a potential key method to limit global warming. Previous studies examined some aspects of Earth system response to different scenarios of CO2 removal, but lacked a systematic analysis of the carbon cycle and climate system response in a consistent modeling framework. We expanded previous studies by using an Earth system model to examine the response of land and ocean carbon cycle, as well as a set of climate variables to idealized scenarios of atmospheric CO2 removal with different removal rates. In the scenarios considered, atmospheric CO2 increases at a rate of 1% per year to four times of its preindustrial level, and then decreases at a rate of 0.5%, 1%, and 2% per year to the preindustrial level. Simulation results show that a reduction of atmospheric CO2 induces CO2 release from both the ocean and terrestrial biosphere, and to keep atmospheric CO2 at a lower level requires the removal of anthropogenic CO2 not only from the atmosphere, but from the ocean and land carbon reservoirs as well. The response of many variables of the Earth system, including temperature, ocean heat content, sea level, deep ocean acidity, and permafrost area and carbon, lags the decrease in atmospheric CO2 ranging from a few years to many centuries. A few centuries after atmospheric CO2 returns to the preindustrial level, sea level is still substantially higher than the preindustrial level, and permafrost continues losing CO2 to the atmosphere. Our study demonstrates that to offset previous positive CO2 emissions by atmospheric CO2 removal does not mean to offset climate consequence of positive CO2 emissions. Rapid and deep reduction in CO2 emissions is key to prevent and limit increasing risks from further warming. Our study provides new insights into the carbon cycle and climate system response to CO2 removal, which would help to assess future climate change and the associated impacts.

Estimates of future changes in the characteristics of the air temperature regime in Northern Eurasia over a five-year time interval are presented. The estimates are based on the forecasts of the Earth climate model developed at Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences. The skill of the forecasts for the territory of Northern Eurasia is discussed using standard skill scores for long-range forecasts. Regions where surface air temperature anomalies are likely to exceed the threshold targets of the Paris Agreement are identified. The consequences of a possible change in the growing season and dates of the stable air temperature above 5°C for agriculture are analyzed. The presented estimates of possible changes in the air temperature characteristics in Northern Eurasia over a five-year interval provide a more objective pattern of expected climate change and can be useful to determine optimal solutions for the development of agricultural sector in the changing climate and to minimize possible negative consequences. [ABSTRACT FROM AUTHOR]

We have coupled the GEOS‐Chem tropospheric‐stratospheric chemistry mechanism and the Community Aerosol and Radiation Model for Atmospheres (CARMA), a sectional aerosol microphysics module, within the NASA Goddard Earth Observing System Chemistry‐Climate Model (GEOS CCM) in order to simulate the interactions between stratospheric chemistry and aerosol microphysics. We use observations of the 1991 Mount Pinatubo volcanic cloud to evaluate this new version of the GEOS CCM. The GEOS‐Chem chemistry module is used to simulate the oxidation of sulfur dioxide (SO2) more realistically than assuming hydroxyl radical (OH) fields are constant, as OH concentrations in the plume decrease dramatically in the weeks following the eruption. CARMA simulates sulfate aerosols with dynamic microphysical and optical properties. The CARMA‐calculated aerosol surface area is coupled to the chemistry module from GEOS‐Chem for the calculation of heterogeneous chemistry. We use a set of observational and theoretical constraints for Pinatubo to evaluate the performance of this new version of the GEOS CCM. These simulations are specifically compared with satellite and in‐situ observations and provide insights into the connections between the gas‐phase chemistry and the aerosol microphysics of the early plume and how they impact the climatic and chemical changes following a large volcanic eruption. A second, smaller eruption is also included in these simulations, the 15 August 1991, eruption of Cerro Hudson in Chile, which we find essential in explaining the aerosol optical depth in the Southern Hemisphere in 1991. Plain Language Summary: We have simulated two volcanic eruptions, the 1991 eruptions of Pinatubo and Cerro Hudson, using a new version of a computer program called the NASA GEOS Chemistry‐Climate Model. This model helps us understand how certain particles from volcanic eruptions, called sulfate aerosols, change sizes and impact the atmosphere. We have compared the results of this model with real‐world observations of the volcanic particles from these two eruptions. We show that the model is able to recreate similar conditions to those seen in 1991 by satellites and observations made from balloons. Additionally, the model shows that a chemical called hydroxyl radical, a key component in the development of volcanic sulfate aerosols, significantly decreases in the volcanic plume in the weeks after the eruption. Key Points: We developed and applied a setup of the NASA Goddard Earth Observing System (GEOS) Chemistry‐Climate Model (CCM) that simulates the 1991 Pinatubo aerosol loading and transportThe updated microphysics‐chemistry GEOS‐CCM realistically simulates aerosol optical depth (AOD) observations made following the 1991 eruptionsThe simulations also support the hypothesis that depletion of hydroxyl radical in volcanic plumes can slow the growth of sulfate aerosol [ABSTRACT FROM AUTHOR]

Abstract Sea‐level rise (SLR) projections by Earth System Models (ESMs) depend on ice sheet surface mass balances. Accurate, global atmosphere reanalyses would be ideal for providing equilibrated ice sheet model initial conditions in fully coupled ESM simulations. Here we present the first evaluation of 1980–1990 global reanalysis precipitation over Greenland and Antarctica that uses independent observations of net accumulation rates derived from shallow ice cores. Precipitation distributions from both the European Centre for Medium‐Range Weather Forecast's Reanalysis (ERA5) and the Modern‐Era Retrospective Analysis for Research and Applications (MERRA‐2) are highly correlated with contemporaneous co‐located net accumulation rates from Greenland (r2 > 0.95) and West Antarctica (r2 > 0.7). Three other commonly used reanalyses (WFDE5, CRUNCEP, and GSWP3) exhibit significantly weaker correlations on one or both ice sheets. Our findings imply that ESMs should use ERA5 or MERRA‐2 in data‐forced simulations to validate ice sheet model dynamics and precondition firn for SLR projections.

Abstract The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset.

Quantifying changes in oceanic aerobic respiration is essential for understanding marine deoxygenation. Here we use an Earth system model to investigate if and to what extent oxygen utilization rate (OUR) can be used to track the temporal change of true respiration (Rtrue). Rtrue results from the degradation of particulate and dissolved organic matter in the model ocean, acting as ground truth to evaluate the accuracy of OUR. Results show that in thermocline and intermediate waters of the North Atlantic Subtropical Gyre (200–1,000 m), vertically integrated OUR and Rtrue both decrease by 0.2 molO2/m2/yr from 1850 to 2100 under global warming. However, in the mesopelagic Tropical South Atlantic, integrated OUR increases by 0.2 molO2/m2/yr, while the Rtrue integral decreases by 0.3 molO2/m2/yr. A possible reason for the diverging OUR and Rtrue is ocean mixing, which affects water mass composition and maps remote respiration changes to the study region. Plain Language Summary: The ocean is losing oxygen due to an imbalance in oxygen supply and aerobic respiration. Therefore, monitoring temporal changes in the aerobic respiration rate contributes to understanding marine deoxygenation. Based on simulations of an Earth system model, we investigate an indirect diagnostic measure of the respiration rate (oxygen utilization rate, OUR), calculated as the slope of the least square regression of the apparent oxygen utilization (AOU, saturated oxygen concentration minus local oxygen concentration) and seawater age that can be computed from transient abiotic tracers. As the reference to OUR, true respiration (Rtrue) is the oxygen consumption rate resulting from the degradation of organic matter in the model ocean. Results show that in the North Atlantic Subtropical Gyre intermediate water (200–1000 m), both vertically integrated OUR and Rtrue decrease by 0.2 molO2/m2/yr from 1850 to 2100. However, in the Tropical South Atlantic intermediate water, the OUR integral increases by 0.2 molO2/m2/yr and the Rtrue integral decreases by 0.3 molO2/m2/yr. We hypothesize that changes in ocean mixing over time, which can affect water mass composition and map remote respiration changes to the study region, explain the discrepancy of OUR and Rtrue tendencies. Key Points: Our model study confirms earlier findings that oxygen utilization rate (OUR) underestimates true respiration (Rtrue) in mesopelagic oceanDespite OUR underestimate Rtrue, OUR can adequately estimate long‐term changes in Rtrue in the mesopelagic North Atlantic subtropical gyreOUR cannot adequately estimate climate‐driven changes in Rtrue in the mesopelagic tropical South Atlantic where different water masses mix [ABSTRACT FROM AUTHOR]

Impacts of the AMOC on the mean state of the North Atlantic sea surface temperature (SST) are investigated by implementing two seawater equations of state (EOS), the standard EOS and the "stiffened" EOS, into an earth system model (ESM). The ESM using the "stiffened" EOS improves the performance of the simulated AMOC. Moreover, the "stiffened" EOS significantly increases the SST in the northern tropical Atlantic (NTA) and northern North Atlantic (NNA) regions. Singular value decomposition analyses reveal that the AMOC changes exert important influences on the SST changes in the NTA and NNA regions. The enhanced AMOC intensifies the volume-integrated meridional heat transport, which dominates the SST warming in the NNA region. Physical processes responsible for the NTA SST changes are more complicated. Regarding the net surface heat flux, it plays an inverse role in modulating SST changes in the NTA region. The net surface heat flux dampens SST changes in the northern NTA region and favors SST changes in the southern NTA region. Influenced by the local and remote SST heating, we find that an anomalous southeasterly appears over the tropical North Atlantic in the simulation with the "stiffened" EOS, which increases the SST in the NTA region through the wind-evaporation-SST mechanism. Concerning the oceanic processes, the enhanced AMOC weakens the subtropical cell in the North Atlantic. Moreover, the enhanced deep convection downward transports the warm surface water in the NNA region to the deep ocean; then the well-mixed warm deep water is southward transported. When reaching the tropical North Atlantic the warm deep water is upward convected by the diapycnal mixing and is eventually upwelled to the sea surface by the enhanced cyclonic winds. The mixed-layer heat budget analysis shows that the NTA SST changes are mainly attributed to the changes in the zonal advection and vertical convection of the seawater temperature. [ABSTRACT FROM AUTHOR]

The ocean skin is composed of thin interfacial microlayers of temperature and mass of less than 1 mm where heat and chemical exchanges are controlled by molecular diffusion. It is characterized by a cooling of ∼−0.2 K and an increase in salinity of ∼0.1 g/kg (absolute salinity) relative to the water below. A surface observation‐based air‐sea CO2 flux estimate considering the variation of the CO2 concentration in these microlayers has been shown to lead to an increase in the global ocean sink of the anthropogenic CO2 by +0.4 PgC yr−1 (15% of the global sink). This study analyzes this effect in more details using a 15‐year (2000–2014) simulation from an Earth System Model (ESM) that incorporates a physical representation of the ocean surface layers (diurnal warm layer and rain lenses) and microlayers. Results show that considering the microlayers increases the simulated global ocean carbon sink by +0.26 to +0.37 PgC yr−1 depending on assumptions on the chemical equilibrium. This is indeed about 15% of the global sink (2.04 PgC yr−1) simulated by the ESM. However, enabling the ocean skin adjustment to feedback on ocean carbon concentrations reduces this increase to only +0.13 (±0.09) PgC y−1. Coupled models underestimate the ocean carbon sink by ∼5% if the ocean skin effect is not included. Plain Language Summary: The ocean skin is a thin layer of less than a millimeter that is in contact with the atmosphere, where the heat and chemical exchanges are controlled by molecular diffusion. It typically corresponds to a temperature at the ocean interface that is cooler by −0.2 K than the water at a depth of a millimeter. It also corresponds to a salinity that is slightly higher at the interface. Taking into account these temperature and salinity changes in this thin layer can change calculations of the global ocean carbon sink substantially. We use a global Earth System Model including a representation of the ocean skin to study this impact. We found an increase of 15% in the simulated global ocean carbon sink. This is consistent with past studies. Enabling the flux to feedback on the ocean carbon concentration significantly reduces its impact. We conclude by discussing the uncertainties in the global ocean carbon sink associated with the formulation of the carbon flux and the representation of the ocean skin. Key Points: Considering the ocean skin increases the global ocean CO2 sink by +0.26 to +0.37 PgC yr−1 (∼15% for 2000–2014) in an Earth System ModelEnabling the ocean skin adjustment to feedback on ocean carbon concentrations dampens this increase to +0.13 PgC y−1 (∼5% for 2000–2014)This global adjustment depends on the CO2 flux formulation and ultimately on the model capacity to transfer CO2 into the ocean interior [ABSTRACT FROM AUTHOR]

The Southern Hemisphere westerly winds influence deep ocean circulation and carbon storage. While the westerlies are hypothesized to play a key role in regulating atmospheric CO2 over glacial‐interglacial cycles, past changes in their position and strength remain poorly constrained. Here, we use a compilation of planktic foraminiferal δ18O from across the Southern Ocean and emergent relationships within an ensemble of climate models to reconstruct changes in the Southern Hemisphere surface westerlies over the last deglaciation. We infer a 4.8° (2.9–7.1°, 95% confidence interval) equatorward shift and about a 25% weakening of the westerlies during the Last Glacial Maximum (20 ka) relative to the mid‐Holocene (6.5 ka). Climate models from the Palaeoclimate Modeling Intercomparison Project substantially underestimate this inferred equatorward wind shift. According to our reconstruction, the poleward shift in the westerlies over deglaciation closely mirrors the rise in atmospheric CO2 (R2 = 0.98). Experiments with a 0.25° resolution ocean‐sea‐ice‐carbon model suggest that shifting the westerlies equatorward reduces the overturning rate of the ocean below 2 km depth, leading to a suppression of CO2 outgassing from the polar Southern Ocean. Our results support a role for the westerly winds in driving the deglacial CO2 rise, and suggest outgassing of natural CO2 from the Southern Ocean is likely to increase as the westerlies shift poleward due to anthropogenic warming. Plain Language Summary: The mid‐latitudes of the Southern Hemisphere are characterized by a band of strong westerly winds. These winds play an important role in driving the circulation of the deep ocean and are thought to influence the oceans' ability to store carbon. Understanding how the westerlies have varied in the past is challenging as we have few methods to track the winds directly. Here we use oxygen isotopes in foraminiferal shells to track changes in the broad‐scale pattern of sea surface temperature across the Southern Ocean, which we link to changes in the winds using climate models. We find the westerly winds were displaced around 5° equatorward during the cold climate of the last ice age, and that the poleward shift in the winds we observe as the earth warmed out of the ice age bears an uncanny resemblance to the increase in atmospheric CO2. We then force the winds in a climate model toward the equator in a similar manner to the shift we observe in the ice age, and find the model stores more carbon in the ocean. Our results support a link between shifts in the Southern Hemisphere westerly winds and atmospheric CO2. Key Points: We use planktic foraminiferal δ18O and climate models to infer deglacial changes in the Southern Hemisphere surface westerliesWe estimate the westerlies were ∼5° equatorward and ∼25% weaker at the LGM; their poleward shift over deglaciation mirrors the rise in CO2Experiments with a 1/4° ocean‐sea‐ice‐carbon model indicate increased oceanic carbon storage with equatorward shifted westerlies [ABSTRACT FROM AUTHOR]

Accurate estimation of gross primary production (GPP), the amount of carbon absorbed by plants via photosynthesis, is of great importance for understanding ecosystem functions, carbon cycling, and climate-carbon feedbacks. Remote sensing has been widely used to quantify GPP at regional to global scales. However, polar-orbiting satellites (e.g., Landsat, Sentinel, Terra, Aqua, Suomi NPP, JPSS, OCO-2) lack the capability to examine the diurnal cycles of GPP because they observe the Earth's surface at the same time of day. The Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), launched in June 2018, observes the land surface temperature (LST) at different times of day with high spatial resolution (70 m × 70 m) from the International Space Station (ISS). Here, we made use of ECOSTRESS data to predict instantaneous GPP with high spatial resolution for different times of day using a data-driven approach based on machine learning. The predictive GPP model used instantaneous ECOSTRESS LST observations along with the daily enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), land cover type from the National Land Cover Database (NCLD), and instantaneous meteorological data from the ERA5 reanalysis dataset. Our model estimated instantaneous GPP across 56 flux tower sites fairly well (R2 = 0.88, Root Mean Squared Error (RMSE) = 2.42 μmol CO2 m−2 s−1). The instantaneous GPP estimates driven by ECOSTRESS LST captured the diurnal variations of tower GPP for different biomes. We then produced multiple high resolution ECOSTRESS GPP maps for the central and northern California. We found distinct changes in GPP at different times of day (e.g., higher in late morning, peak around noon, approaching zero at dusk), and clear differences in productivity across landscapes (e.g., savannas, croplands, grasslands, and forests) for different times of day. ECOSTRESS GPP also captured the seasonal variations in the diurnal cycling of photosynthesis. This study demonstrates the feasibility of using ECOSTRESS data for producing instantaneous GPP (i.e., GPP for the acquisition time of the ECOSTRESS data) for different times of day. The ECOSTRESS GPP can shed light on how plant photosynthesis and water use vary over the course of the diurnal cycle and inform agricultural management and future improvement of terrestrial biosphere/land surface models.