Earth System Research Articles

Evaluation of Leaf Phenology of Different Vegetation Types From Local to Hemispheric Scale in CLM

AbstractAccurate simulation of plant phenology is important in Earth system models as phenology modulates land‐atmosphere coupling and the carbon cycle. Evaluations based on grid cell average leaf area index (LAI) can be misleading because multiple plant functional types (PFTs) may be present in one model grid cell and PFTs with different phenology schemes have different LAI seasonal cycles. Here we examined PFT‐specific LAI magnitudes and seasonal cycles in the Community Land Model versions 5.0 and 4.5 (CLM5.0 and CLM4.5) and their relationship with the onset of growing season triggers in the Northern Hemisphere. LAI seasonal cycle and spring onset in CLM show the best agreement with Moderate Resolution Imaging Spectroradiometer (MODIS) for temperature‐dominated deciduous PFTs. Although the agreement in LAI magnitude between CLM5.0 and MODIS is better than CLM4.5, the agreement in seasonal cycles is worse in CLM5.0. Agreements between CLM and MODIS leaf phenology are primarily determined by the PFT and phenology scheme. While productivity depends on the environmental factors to which the plant is exposed during any given growing season, differences in phenology sensitivity to its environment necessitate a decoupling between the seasonality of LAI and GPP, which in turn could lead to biases in the carbon cycle as well as surface energy balance and hence land‐atmosphere interactions. Because the discrepancy not only depends on parameterizing phenology but phenology‐environment relationship, future improvements to other model components (e.g., soil moisture) could better align the seasonal cycle of LAI and GPP.

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

AbstractLakes are important sentinels of climate change and may contribute over 30% of natural methane (CH4) emissions; however, no earth system model (ESM) has represented lake CH4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH4 outgassing events in non‐floodplain lakes and the seasonal variability of CH4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH4 emissions and climate‐CH4 feedback.

A Method for Interpreting the Role of Parameterized Turbulence on Global Metrics in the Community Earth System Model

AbstractThe parameterization of subgrid‐scale processes such as boundary layer (PBL) turbulence introduces uncertainty in Earth System Model (ESM) results. This uncertainty can contribute to or exacerbate existing biases in representing key physical processes. This study analyzes the influence of tunable parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBBX) scheme. CLUBB is the operational PBL parameterization in the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community ESM version 2 (CESM2). We perform the Morris one‐at‐a‐time (MOAT) parameter sensitivity analysis using short‐term (3‐day), initialized hindcasts of CAM6‐CLUBBX with 24 unique initial conditions. Several input parameters modulating vertical momentum flux appear most influential for various regionally‐averaged quantities, namely surface stress and shortwave cloud forcing (SWCF). These parameter sensitivities have a spatial dependence, with parameters governing momentum flux most influential in regions of high vertical wind shear (e.g., the mid‐latitude storm tracks). We next evaluate several experimental 20‐year simulations of CAM6‐CLUBBX with targeted parameter perturbations. We find that parameter perturbations produce similar physical mechanisms in both short‐term and long‐term simulations, but these physical responses can be muted due to nonlinear feedbacks manifesting over time scales longer than 3 days, thus causing differences in how output metrics respond in the long‐term simulations. Analysis of turbulent fluxes in CLUBBX indicates that the influential parameters affect vertical fluxes of heat, moisture, and momentum, providing physical pathways for the sensitivities identified in this study.

Worldwide Rocket Launch Emissions 2019: An Inventory for Use in Global Models

AbstractThe rate of rocket launches is accelerating, driven by the rapid global development of the space industry. Rocket launches emit gases and particulates into the stratosphere, where they impact the ozone layer via radiative and chemical processes. We create a three‐dimensional per‐vehicle inventory of stratospheric emissions, accounting for flight profiles and all major fuel types in active use (solid, kerosene, cryogenic and hypergolic). In 2019, stratospheric (15–50 km) rocket launch emissions were 5.82 Gg , 6.38 Gg O, 0.28 Gg black carbon, 0.22 Gg nitrogen oxides, 0.50 Gg reactive chlorine and 0.91 Gg particulate alumina. The geographic locations of launch sites are preserved in the inventory, which covers all active launch sites in 2019. We also report the emissions data from contemporary vehicles that were not launched in 2019, so that users have freedom to construct their own launch activity scenarios. A subset of the inventory—stratospheric emissions for successful launches in 2019—is freely available and formatted for direct use in global chemistry‐climate or Earth system models.

Change in Wind Renewable Energy Potential Under Stratospheric Aerosol Injections

AbstractWind renewable energy (WRE) is an essential component of the global sustainable energy portfolio. Recently, there has been increasing discussion on the potential supplementation of this conventional mitigation portfolio with Solar Radiation Modification (SRM). However, the impact of SRM on conventional mitigation measures has received limited attention to date. In this study, we explore one part of this impact, the potential effect of one type of SRM, Stratospheric Aerosol Injections (SAI), on WRE. Using hourly output from the Earth System Model CNRM‐ESM2‐1, we compare WRE potential under a medium emission scenario (SSP245) and a high emission scenario (SSP585) with an SRM scenario that has SSP585 baseline conditions and uses SAI to offset warming to approximately SSP245 global warming levels. Our results suggest that SAI may affect surface wind resources by modifying large‐scale circulation patterns, such as a significant poleward jet‐shift in the Southern Hemisphere. The modeled total global WRE potential is negligibly reduced under SAI compared to the SSP‐scenarios. However, regional trends are highly variable, with large increases and decreases in WRE potential frequently reaching 12% across the globe with SAI. This study highlights potential downstream effects of SRM on climatic elements, such as wind patterns, and offers perspectives on its implications for our mitigation efforts.

The Rapid Response of Southern Ocean Biological Productivity to Changes in Background Small Scale Turbulence

AbstractBackground subsurface vertical mixing rates in the Southern Ocean (SO) are known to vary by an order of magnitude temporally and spatially, due to variability in their generating mechanisms, which include winds and shear instabilities at the surface, and the interaction of tides and lee waves with rough bottom topography. There is great uncertainty in the parameterization of this mixing in coarse resolution Earth System Models (ESM), and in the impact that this has on SO biological productivity on sub decadal timescales. Using a data assimilating biogeochemical ocean model we show that SO phytoplankton productivity is highly sensitive to differences in background diapycnal mixing over short timescales. Changes in the background vertical mixing rates alter key biogeochemical and physical conditions. The greatest changes to the distribution of physical and biogeochemical tracers occur in regions with very strong tracer vertical gradients. A combination of reduced nutrient limitation and reduced light limitation causes a strong increase in SO phytoplankton productivity with higher background mixing. This leads to increased summer carbon export but reduced wintertime export over the mixed layer depth, which could alter the strength of the SO biological carbon pump and atmospheric concentrations on centennial to millennial timescales. This study demonstrates the importance of accurately representing diapycnal mixing in ESM to predict SO biogeochemical dynamics and their broader climatic implications.

How Landmass Distribution Influences the Atmospheric Dynamics of Tidally Locked Terrestrial Exoplanets

Interpretation of the ongoing efforts to simulate the atmospheres of potentially habitable terrestrial exoplanets requires that we understand the underlying dynamics and chemistry of such objects to a much greater degree than 1D or even simple 3D models enable. Here, for the tidally locked habitable-zone planet TRAPPIST-1e, we explore one effect which can shape the dynamics and chemistry of terrestrial planets: the inclusion of an Earth-like land–ocean distribution with orography. To do this we use the Earth-system model WACCM6/CESM2 to run a pair of TRAPPIST-1e models with N2–O2 atmospheres and with the substellar point fixed over either land or ocean. The presence of orography shapes atmospheric transport, and in the case of Earth-like orography, breaks the symmetry between the Northern and Southern Hemispheres which was previously found in slab ocean models. For example, peak zonal jet speeds in the Southern Hemisphere are 50%–100% faster than similar jets in the Northern Hemisphere. This also affects the meridional circulation, transporting equatorial material toward the south pole. As a result we also find significant changes in the atmospheric chemistry, including the accumulation of potentially lethal quantities of ozone at both the south pole and the surface. Future studies which investigate the effects of landmass distribution on the dynamics of exoplanetary atmospheres should pay close attention to both the dayside land fraction as well as the orography of the land. Simply modeling a flat landmass will not give a complete picture of its dynamical impact.

Increasing Optimum Temperature of Vegetation Activity Over the Past Four Decades

AbstractOver the past four decades, global temperatures have increased more rapidly than before, potentially reducing vegetation activity if temperatures exceed the optimum temperature (Topt). However, plants have the capacity to acclimate to rising temperatures by adjusting Topt, thereby maintaining or even enhancing photosynthesis and carbon uptake. Despite this, it remains unclear how Topt of vegetation activity changes over time and to what extent global vegetation can acclimate to current temperature changes. In this study, we evaluated the temporal trends of Topt of vegetation activity and the thermal acclimation magnitudes globally using three remote‐sensed vegetation indices and eddy‐covariance observations of gross primary productivity from 1982 to 2020. We found that the global Topt of vegetation activity has increased at an average rate of 0.63°C per decade over the past four decades. The increase in Topt closely tracked the rise in annual maximum daily mean temperature (Tmax), indicating that thermal acclimation has occurred widely across the globe. Globally, we found an average thermal acclimation magnitude of 0.38°C per 1°C increase in Tmax. Notably, polar and continental regions exhibited the highest thermal acclimation magnitudes, while arid areas showed the lowest. Additionally, the thermal acclimation magnitude was positively affected by interannual temperature variability and negatively affected by soil moisture and vapor pressure deficits. Our findings indicate that terrestrial ecosystems have acclimated to current climate warming trends with varying degrees, suggesting a greater potential for land carbon uptake. Moreover, these results highlight the necessity for earth system models to integrate the thermal acclimation of Topt to better forecast the global carbon cycle.

Nutrient Addition Enhances the Temperature Sensitivity of Soil Carbon Decomposition Across Forest Ecosystems.

Atmospheric nitrogen (N) and phosphorus (P) depositions have been shown to alter nutrient availability in terrestrial ecosystems and thus largely influence soil carbon cycling processes. However, the general pattern of nutrient-induced changes in the temperature response of soil carbon decomposition is unknown. Yet, understanding this pattern is crucial in terms of its effect on soil carbon-climate feedback. Here, we report that N and P additions significantly increase the temperature sensitivity of soil organic carbon decomposition (Q10) by sampling soils from 36 sites across China's forests. We found that N, P, and their co-addition (NP) significantly increased the Q10 by 11.3%, 11.5%, and 23.9%, respectively. The enhancement effect of nutrient addition on Q10 was more evident in soils from warm regions than in those from cold regions. Moreover, we found that nutrient-induced changes in substrate availability and initial substrate and nutrient availability mainly regulated nutrient addition effects. Our findings highlight that N and P deposition enhances the temperature response of soil carbon decomposition, suggesting that N and P deposition should be incorporated into Earth system models to improve the projections of soil carbon feedback to climate change.

Advancing streamflow prediction in data-scarce regions through vegetation-constrained distributed hybrid ecohydrological models

Hybrid models that combine deep learning with physical principles have recently shown significant promise in improving streamflow prediction in data-scarce regions, achieving generally greater accuracy and reliability than either method alone. However, existing hybrid hydrological models underutilize the extensive and readily available remote sensing data on vegetation, which plays a critical role in hydrologic processes. Incorporating vegetation information can better constrain model processes by accounting for the interactions and feedbacks between vegetation and hydrology, thereby enabling more robust predictions. In this context, we present a novel distributed hybrid ecohydrological model that integrates dynamic vegetation processes into a distributed hybrid hydrological model, capable of simultaneously simulating leaf area index (LAI) and streamflow through multi-task learning. Our results indicate that in scenarios with limited available streamflow data, the combined constraint of LAI spatiotemporal patterns and streamflow significantly enhances the model’s ability to generalize streamflow simulation across space and time compared to models trained solely with either LAI or streamflow. Even with the increased availability of streamflow data, models utilizing both LAI and streamflow continue to exhibit superior robustness in streamflow prediction. The distributed ecohydrological model, which employs multi-process coupling and multi-source data constraints, accurately simulates the target variables (i.e., streamflow and LAI) while reliably capturing dynamic changes in other ecohydrological processes, such as evapotranspiration. This capability highlights its potential for multi-process diagnostics. Overall, our approach offers a new perspective for streamflow prediction in data-scarce regions and represents an important step towards integrating observational constraints from multiple subsystems into hybrid Earth system modeling

Persistently Elevated High‐Latitude Ocean Temperatures and Global Sea Level Following Temporary Temperature Overshoots

AbstractAs exceeding the 1.5°C level of global warming is likely to happen in the near future, understanding the response of the ocean‐climate system to temporarily overshooting this warming level is of critical importance. Here, we apply the Adaptive Emissions Reduction Approach to the Earth System Model GFDL‐ESM2M to conduct novel overshoot scenarios that reach 2.0, 2.5 and 3.0°C of global warming before returning to 1.5°C over the time period of 1861–2500. We also perform a complementary scenario that stabilizes global temperature at 1.5°C, allowing to isolate impacts caused by the temperature overshoots alone, both during their peaks and after their reversals. The simulations indicate that substantial residual ocean surface warming persists in the high latitudes after the overshoots, with most notable regional anomalies occurring in the North Atlantic (up to +3.1°C in the 3°C overshoot scenario compared to the 1.5°C stabilization scenario) and the Southern Ocean (+1.2°C). The residual warming is primarily driven by the recoveries of the Atlantic and Southern Ocean meridional overturning circulation and associated increases in ocean heat transport. Excess subsurface heat storage in low and mid‐latitudes prevents steric sea level rise (SLR) from reverting to 1.5°C stabilization levels in any overshoot scenario, with steric sea level remaining up to 32% higher in the 3°C overshoot scenario on centennial time scales. Both peak impacts and persistent changes after overshoot reversal bear significant implications for future assessments of coastlines, regional climates, marine ecosystems, and ice sheets.

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large‐Eddy Simulations of Low‐Level Warm Clouds

AbstractIn numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate , which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local is commonly parameterized as a function of DSD moments: cloud droplet number and mass concentrations. When applied in a large‐scale model, the grid‐mean must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large‐eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local , as well as its spatial variability. The analysis of an ensemble of warm low‐level cloud cases shows that the E3SMv2 formulation represents the reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM‐tuned local rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of and its co‐variability with in parameterizing the grid‐mean .

Gross Primary Production of Antarctic Landfast Sea Ice: A Model‐Based Estimate

AbstractMuch of the Antarctic coast is covered by seasonal landfast sea ice (fast ice), which serves as an important habitat for ice algae. Fast‐ice algae provide a key early season food source for pelagic and benthic food webs, and contribute to biogeochemical cycling in Antarctic coastal ecosystems. Summertime fast ice is undergoing a decline, leading to more seasonal fast ice with unknown impacts on interconnected Earth system processes. Our understanding of the spatiotemporal variability of Antarctic fast ice, and its impact on polar ecosystems is currently limited. Evaluating the overall productivity of fast‐ice algae has historically been hampered by limitations in observations and models. By linking new fast‐ice extent maps with a one‐dimensional sea‐ice biogeochemical model, we provide the first estimate of the spatio‐seasonal variability of Antarctic fast‐ice algal gross primary production (GPP) and its annual primary production on a circum‐Antarctic scale. Experiments conducted for the 2005–2006 season provide a mean fast ice‐algal production estimate of 2.8 Tg C/y. This estimate represents about 12% of overall Southern Ocean sea‐ice algae production (estimated in a previous study), with the mean fast‐ice algal production per area being 3.3 times higher than that of pack ice. Our Antarctic fast‐ice GPP estimates are probably underestimated in the Ross Sea and Weddell Sea sectors because the sub‐ice platelet layer habitats and their high biomass are not considered.

Groundwaterscapes: A Global Classification and Mapping of Groundwater's Large‐Scale Socioeconomic, Ecological, and Earth System Functions

AbstractGroundwater is a dynamic component of the global water cycle with important social, economic, ecological, and Earth system functions. We present a new global classification and mapping of groundwater systems, which we call groundwaterscapes, that represent predominant configurations of large‐scale groundwater system functions. We identify and map 15 groundwaterscapes which offer a new lens to conceptualize, study, model, and manage groundwater. Groundwaterscapes are derived using a novel application of sequenced self‐organizing maps that capture patterns in groundwater system functions at the grid cell level (∼10 km), including groundwater‐dependent ecosystem type and density, storage capacity, irrigation, safe drinking water access, and national governance. All large aquifer systems of the world are characterized by multiple groundwaterscapes, highlighting the pitfalls of treating these groundwater bodies as lumped systems in global assessments. We evaluate the distribution of Global Groundwater Monitoring Network wells across groundwaterscapes and find that industrial agricultural regions are disproportionately monitored, while several groundwaterscapes have next to no monitoring wells. This disparity undermines the ability to understand system dynamics across the full range of settings that characterize groundwater systems globally. We argue that groundwaterscapes offer a conceptual and spatial tool to guide model development, hypothesis testing, and future data collection initiatives to better understand groundwater's embeddedness within social‐ecological systems at the global scale.

Description and Evaluation of the CNRM‐Cerfacs Climate Prediction System (C3PS)

AbstractThe CNRM‐Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyzes and seasonal‐to‐multiannual predictions for a wide array of Earth system variables. C3PS is based on the CNRM‐ESM2‐1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to multiannual time‐scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP‐A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel Earth system‐based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialization procedure with the most up‐to‐date observations and reanalyzes over 1960–2021, and we discuss the overall performance of the system in the light of the lessons learned from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the multiannual scale, C3PS shows significant predictive skill in surface temperature during the first 2 years after initialization in several regions of the world. C3PS also exhibits potential predictive skill in Net primary production (NPP) and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multiannual predictions of marine ecosystems and carbon cycle.

Comparative field assessment of grounding enhancement material for electrical earthing system

Comparative field assessment of grounding enhancement material for electrical earthing system

The first satellite measurements of HFC-125 by the ACE-FTS: Long-term trends and distribution in the Earth’s upper troposphere and lower stratosphere

HFC-125 (CF3CHF2, pentafluoroethane) volume mixing ratios (VMRs) have been determined for the first time using infrared absorption spectra from the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) from 2004 to 2024. These VMRs provide global altitude-latitude VMR distributions. A VMR time series for HFC-125 has also been calculated and compared to values from in situ discrete flask measurements conducted by the National Oceanic and Atmospheric Administration Earth System Research Laboratory. The abundance of HFC-125 is currently experiencing exponential growth. ACE data shows a growth rate of 3.47 ± 0.05 ppt/year in the past six years.

Landslide Hazard Is Projected to Increase Across High Mountain Asia

AbstractHigh Mountain Asia has long been known as a hotspot for landslide risk, and studies have suggested that landslide hazard is likely to increase in this region over the coming decades. Extreme precipitation may become more frequent, with a nonlinear response relative to increasing global temperatures. However, these changes are geographically varied. This article maps probable changes to landslide hazard, as shown by a landslide hazard indicator (LHI) derived from downscaled precipitation and temperature. In order to capture the nonlinear response of slopes to extreme precipitation, a simple machine‐learning model was trained on a database of landslides across High Mountain Asia to develop a regional LHI. This model was applied to statistically downscaled data from the 30 members of the Seamless System for Prediction and Earth System Research large ensembles to produce a range of possible outcomes under the Shared Socioeconomic Pathways 2‐4.5 and 5‐8.5. The LHI reveals that landslide hazard will increase in most parts of High Mountain Asia. Absolute increases will be highest in already hazardous areas such as the Central Himalaya, but relative change is greatest on the Tibetan Plateau. Even in regions where landslide hazard declines by year 2100, it will increase prior to the mid‐century mark. However, the seasonal cycle of landslide occurrence will not change greatly across High Mountain Asia. Although substantial uncertainty remains in these projections, the overall direction of change seems reliable. These findings highlight the importance of continued analysis to inform disaster risk reduction strategies for stakeholders across High Mountain Asia.

Complexity science meets Earth system

Complexity science meets Earth system

Mesoscale eddies inhibit intensification of the Subantarctic Front under global warming

Abstract Oceanic mesoscale eddies are important dynamical processes in the Southern Ocean. Using high-resolution (~0.1○ for the ocean) Community Earth System Model (CESM-HR) simulations under a high-carbon emission scenario, we investigate the role of mesoscale eddies in regulating the response of the Subantarctic Front (SAF) to global warming. The CESM-HR simulates more realistic oceanic fronts and mesoscale eddies in the Southern Ocean than a coarse-resolution (~1○ for the ocean) CESM. Under global warming, the SAF is projected to intensify. The mean flow temperature advection intensifies the front, whereas the mesoscale-eddy-induced temperature advection and atmospheric dampening play primary (~67%) and secondary (~28%) roles in counteracting the effect of mean flow temperature advection. Our study suggests the importance of mesoscale eddies on inhibiting the SAF intensification under global warming and necessity of mesoscale-eddy-resolving simulations for faithful projection of future climate changes in the Southern Ocean.