Earth System Research Articles

Analysis of Uncertainties and Associated Convective Processes in Simulations of Extreme Precipitation Over Cities With a Regional Earth System Model: A Case Study

Analysis of Uncertainties and Associated Convective Processes in Simulations of Extreme Precipitation Over Cities With a Regional Earth System Model: A Case Study

Global Climatology of Low‐Level‐Jets: Occurrence, Characteristics, and Meteorological Drivers

AbstractLow‐level jets (LLJs), vertical profiles with a wind speed maxima in the lowest hundred meters of the troposphere, have multiple impacts in the Earth system, but a global present‐day climatology based on contemporary data does not exist. We use the spatially and temporally complete data set from ERA5 reanalysis to compile a global climatology of LLJs for studying the formation mechanisms, characteristics, and trends during the period of 1992–2021. In the global mean, LLJs are detected 21% of the time with more cases over land (32%) than over the ocean (15%). We classified the LLJs into three categories: non‐polar land (LLLJ), polar land (PLLJ), and coastal (CLLJ) LLJs. For LLLJ, the averaged frequency of occurrence is 20% and 75% of them are associated with a near‐surface temperature inversion as a prerequisite for an inertial oscillation. PLLJs are also associated with a temperature inversion and occur even more frequently with 59% of the time. These are also the lowest and the strongest LLJs among the three categories. CLLJs are particularly frequent in some marine hotspots, situated along the west coast of continents, with neutral to unstable stratification close to the surfaces and a stably stratified layer aloft. We found distinct regional trends in both the frequency and intensity of LLJs over the past decades, which can have implications for the emission and transport of aerosols, and the transport of atmospheric moisture. Future studies could address changes in LLJs and the associated implications in more detail, based on the here released ERA5‐based LLJ data.

Assessment of Storm‐Associated Precipitation and Its Extremes Using Observational Data Sets and Climate Model Short‐Range Hindcasts

AbstractHeavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio‐economic loss. In this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short‐range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short‐range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm‐associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon‐based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy‐precipitating storms.

The carbonate pump feedback on alkalinity and the carbon cycle in the 21st century and beyond

Abstract. Ocean acidification is likely to impact all stages of the ocean carbonate pump, i.e. the production, export, dissolution and burial of biogenic CaCO3. However, the associated feedback on anthropogenic carbon uptake and ocean acidification has received little attention. It has previously been shown that Earth system model (ESM) carbonate pump parameterizations can affect and drive biases in the representation of ocean alkalinity, which is critical to the uptake of atmospheric carbon and provides buffering capacity towards associated acidification. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show divergent responses of CaCO3 export at 100 m this century, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. The greatest export declines are projected by ESMs that consider pelagic CaCO3 production to depend on the local calcite/aragonite saturation state. Despite the potential effects of other processes on alkalinity, there is a robust negative correlation between anomalies in CaCO3 export and salinity-normalized surface alkalinity across the CMIP6 ensemble. Motivated by this relationship and the uncertainty in CaCO3 export projections across ESMs, we perform idealized simulations with an ocean biogeochemical model and confirm a limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification. However, we highlight a potentially abrupt shift, between 2100 and 2300, in the dissolution of CaCO3 from deep to subsurface waters when the global-scale mean calcite saturation state reaches about 1.23 at 500 m (likely when atmospheric CO2 reaches 900–1100 ppm). During this shift, upper ocean acidification due to anthropogenic carbon uptake induces deep ocean acidification driven by a substantial reduction in CaCO3 deep dissolution following its decreased export at depth. Although the effect of a diminished carbonate pump on global ocean carbon uptake and surface ocean acidification remains limited until 2300, it can have a large impact on regional air–sea carbon fluxes, particularly in the Southern Ocean.

Efficient spin-up of Earth System Models using sequence acceleration.

Marine and terrestrial biogeochemical models are key components of the Earth System Models (ESMs) used to project future environmental changes. However, their slow adjustment time also hinders effective use of ESMs because of the enormous computational resources required to integrate them to a pre-industrial equilibrium. Here, a solution to this "spin-up" problem based on "sequence acceleration", is shown to accelerate equilibration of state-of-the-art marine biogeochemical models by over an order of magnitude. The technique can be applied in a "black box" fashion to existing models. Even under the challenging spin-up protocols used for Intergovernmental Panel on Climate Change (IPCC) simulations, this algorithm is 5 times faster. Preliminary results suggest that terrestrial models can be similarly accelerated, enabling a quantification of major parametric uncertainties in ESMs, improved estimates of metrics such as climate sensitivity, and higher model resolution than currently feasible.

Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook

AbstractAs the Earth system is exposed to large anthropogenic interferences, it becomes ever more important to assess the resilience of natural systems, i.e., their ability to recover from natural and human-induced perturbations. Several, often related, measures of resilience have been proposed and applied to modeled and observed data, often by different scientific communities. Focusing on terrestrial ecosystems as a key component of the Earth system, we review methods that can detect large perturbations (temporary excursions from a reference state as well as abrupt shifts to a new reference state) in spatio-temporal datasets, estimate the recovery rate after such perturbations, or assess resilience changes indirectly from stationary time series via indicators of critical slowing down. We present here a sequence of ideal methodological steps in the field of resilience science, and argue how to obtain a consistent and multi-faceted view on ecosystem or climate resilience from Earth observation (EO) data. While EO data offers unique potential to study ecosystem resilience globally at high spatial and temporal scale, we emphasize some important limitations, which are associated with the theoretical assumptions behind diagnostic methods and with the measurement process and pre-processing steps of EO data. The latter class of limitations include gaps in time series, the disparity of scales, and issues arising from aggregating time series from multiple sensors. Based on this assessment, we formulate specific recommendations to the EO community in order to improve the observational basis for ecosystem resilience research.

Net primary production annual maxima in the North Atlantic projected to shift in the 21st century

Abstract. Shifts in the day of peak net primary production (NPP) were detected in different biogeochemical provinces of the North Atlantic (25–65° N). Most provinces displayed a shift toward earlier peak NPP, with the largest change points in the 21st century and in the northern parts of the domain. Furthermore, the occurrences of the first day with a mixed-layer depth (MLD) shallower than 40 m and the day of peak NPP are positively correlated over most of the domain. As was the case for the day of peak NPP, the largest change points for the day of MLD shallower than 40 m occur around or after the year 2000. Daily output from two fully coupled CMIP6 Earth system models, EC-Earth3-CC and NorESM2-LM, for the period 1750–2100 and under the SSP5-8.5 scenario, were used for the analysis. The ESM NPP data were compared with estimates derived from Carbon, Absorption and Fluorescence Euphotic-resolving (CAFE) satellite-based data. The ESMs showed significant differences from the CAFE model, though the timing of peak NPP was well captured for most provinces. The largest change points in the day of peak NPP occur earlier in EC-Earth3-CC than in NorESM2-LM. Although SSP5-8.5 is a scenario with very high warming, EC-Earth3-CC generates change points for most provinces in the early part of the 21st century, before the warming has deviated far from lower-emissions scenarios. NorESM2-LM displays the largest change points centered around the mid 21st century, with two out of eight provinces displaying the largest change point before the year 2050. The early timing of the detected shifts in some provinces in both ESMs suggests that similar shifts could already have been initiated or could start in the near future. This highlights the need for long-term monitoring campaigns in the North Atlantic.

Slow biological microplastics removal under ocean pollution phase-out trajectories

Abstract Microplastics are ubiquitous in marine environments and can be incorporated into biological aggregates including marine snows and faecal pellets. These aggregates are suspected to be a major removal mechanism for microplastics from the surface ocean, transporting them to deeper levels and the seafloor as they sink and remineralise. However, simple budget calculations, observations, and model parameter testing suggest that aggregation might also lead to retention of microplastics in the upper ocean, sustaining contamination in biologically-productive environments. The ability of the biological microplastic sink to reduce water column contamination has relevance to the setting of ocean plastics pollution reduction targets, as are currently under negotiation by the International Negotiating Committee of the United Nations Environment Assembly (UNEA). Here we apply 8 idealised global pollution reduction trajectories, from 1-100% per year, starting from the year 2026 and ending in the year 2100 to an Earth System Climate Model with a representation of ocean microplastics and their aggregation in biological particles. We find that the global ocean microplastic inventory and surface concentrations stabilize within this century for reduction rates exceeding 5% per year but the inventory does not substantially decrease under any trajectory. Furthermore, microplastics are retained by marine biology in the surface ocean, where concentrations stabilise to a non-zero value over decades. Lastly we find that irrespective of scenario, contamination of deeper ocean layers continues to increase for the duration of our simulations via the export of microplastics by biological aggregates. These results suggest that ambitious targets for pollution reduction exceeding 5\% per year will be required to progress the resolution of the UNEA to ``end plastic pollution'' in this century, and that ongoing microplastic contamination of the marine food web may be unavoidable.

First comprehensive assessment of industrial-era land heat uptake from multiple sources

Abstract. The anthropogenically intensified greenhouse effect has caused a radiative imbalance at the top of the atmosphere during the industrial period. This, in turn, has led to an energy surplus in various components of the Earth system, with the ocean storing the largest part. The land contribution ranks second with the latest observational estimates based on borehole temperature profiles, which quantify the terrestrial energy surplus to be 6 % in the last 5 decades, whereas studies based on state-of-the-art climate models scale it down to 2 %. This underestimation stems from land surface models (LSMs) having a subsurface that is too shallow, which severely constrains the land heat uptake simulated by Earth system models (ESMs). A forced simulation of the last 2000 years with the Max Planck Institute ESM (MPI-ESM) using a deep LSM captures 4 times more heat than the standard shallow MPI-ESM simulations in the historical period, well above the estimates provided by other ESMs. However, deepening the LSM does not remarkably affect the simulated surface temperature. It is shown that the heat stored during the historical period by an ESM using a deep LSM component can be accurately estimated by considering the surface temperatures simulated by the ESM using a shallow LSM and propagating them with a standalone forward model. This result is used to derive estimates of land heat uptake using all available observational datasets, reanalysis products, and state-of-the-art ESM experiments. This approach yields values of 10.5–16.0 ZJ for 1971–2018, which are 12 %–42 % smaller than the latest borehole-based estimates (18.2 ZJ).

Reflections on the past and future of whole Earth system science

Reflections on the past and future of whole Earth system science

Assessing acetone for the GISS ModelE2.1 Earth system model

Abstract. Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Rocks Really Rock: electronic field trips via Web Google Earth can generate positive impacts in attitudes toward Earth sciences in middle- and high-school students

Abstract. Earth sciences (ESs) are relevant to society and its relationship with the Earth system. However, ES education in K-12 environments in the United States faces several challenges, including limited exposure to ESs, lack of awareness of ES careers, and low ES literacy. International associations have recognized these challenges and recommended that Earth scientists improve the public's perception of the relevance of ES. In recent years, informal science communication and outreach platforms such as the Streaming Science model of electronic field trips (EFTs), which connect K-12 classrooms with science, engineering, technology, and mathematics (STEM) professionals, have gained popularity as an educational technology tool. EFTs are inexpensive, have spatiotemporal benefits, and have proven an effective informal science education pathway for introducing STEM content into formal classrooms to increase positive attitudes and interest in STEM careers. Nevertheless, EFTs in ES for K-12 environments have not been widely disseminated, and their impact on ES education has yet to be studied. This study presents the creation and implementation of an EFT in geology called “Rocks Really Rock: An Electronic Field Trip across Geological Time.” The program was implemented in seven schools in spring 2022. The EFT was built in Web Google Earth and had six stops that featured prerecorded videos recorded in different locations in Idaho (USA). The lead presenter or author used multimedia and science communication strategies such as storytelling to develop and teach concepts related to geological time, rock formation, and landscape-forming geological processes. The content aligned with four specific topics listed in the National Science Foundation's Earth Sciences Literacy Principles and intersected with the Next Generation Science Standards for middle-school classrooms. Participating students (n=120) completed a post-assessment after the program implementation to evaluate its impact. Results showed that the EFT positively impacted students' attitudes toward geology, geology careers, and perceptions of geology literacy. We identified the three main factors that determined a positive attitude change in K-12 students toward ES: (1) the use of videos and the Web Google Earth platform to create outreach materials for K-12 students, (2) the use of storytelling to craft the content of an EFT, and (3) the asynchronous interactions between teacher, student, and scientist. The results indicated a statistically significant positive change in attitudes toward geology, suggesting that participating in the EFT increased students' positive attitudes toward ES. These findings demonstrate the potential of expanding EFT to other ES fields and reaching middle- and high-school students. We suggest that EFTs are effective outreach tools that can address the challenges in ES education and that can be extended to other ES areas and distributed to students in middle, high, and home schools to support science educators in ES education.

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

Improving seasonal predictions of German Bight storm activity

Abstract. Extratropical storms are one of the major coastal hazards along the coastline of the German Bight, the southeastern part of the North Sea, and a major driver of coastal protection efforts. However, the predictability of these regional extreme events on a seasonal scale is still limited. We therefore improve the seasonal prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) large-ensemble decadal hindcast system for German Bight storm activity (GBSA) in winter. We define GBSA as the 95th percentiles of three-hourly geostrophic wind speeds in winter, which we derive from mean sea-level pressure (MSLP) data. The hindcast system consists of an ensemble of 64 members, which are initialized annually in November and cover the winters of 1960/61–2017/18. We consider both deterministic and probabilistic predictions of GBSA, for both of which the full ensemble produces poor predictions in the first winter. To improve the skill, we observe the state of two physical predictors of GBSA, namely 70 hPa temperature anomalies in September, as well as 500 hPa geopotential height anomalies in November, in areas where these two predictors are correlated with winter GBSA. We translate the state of these predictors into a first guess of GBSA and remove ensemble members with a GBSA prediction too far away from this first guess. The resulting subselected ensemble exhibits a significantly improved skill in both deterministic and probabilistic predictions of winter GBSA. We also show how this skill increase is associated with better predictability of large-scale atmospheric patterns.

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.

Projected poleward migration of the Southern Ocean CO2 sink region under high emissions

The Southern Ocean is a major region of ocean carbon uptake, but its future changes remain uncertain under climate change. Here we show the projected shift in the Southern Ocean CO2 sink using a suite of Earth System Models, revealing changes in the mechanism, position and seasonality of the carbon uptake. The region of dominant CO2 uptake shifts from the Subtropical to the Antarctic region under the high-emission scenario. The warming-driven sea-ice melt, increased ocean stratification, mixed layer shoaling, and a weaker vertical carbon gradient is projected to together reduce the winter de-gassing in the future, which will trigger the switch from mixing-driven outgassing to solubility-driven uptake in the Antarctic region during the winter season. The future Southern Ocean carbon sink will be poleward-shifted, operating in a hybrid mode between biologically-driven summertime and solubility-driven wintertime uptake with further amplification of biologically-driven uptake due to the increasing Revelle Factor.

The problems of the Anthropocene in the Geologic Time Scale, and beyond

The formalization of the Anthropocene in the Geologic Time Scale (GTS) is a matter of debate. An assessment of the two current options, one formalizing the Anthropocene as an Epoch and the other considering the Anthropocene as an informal event in the Earth's history that does not require formalization, are critically analyzed. The focus of the analysis is on the philosophical issues underlying these two options, which make them unsatisfactory for addressing the occurrence of humans on Earth and the evolution of the relationship between humans and nature. Essentially, the approach followed by these options is non-historical, and does not undertake a research on the structural socio-economic roots of the Anthropocene. As a result, the concept of the Anthropocene is unable to identify the particular and historical form of Anthropos underlying the ongoing environmental degradation. Some inconsistencies in the current configuration of the GTS and in the rules for formalizing units inherited from the historical tradition of the GTS are also highlighted. The current dualistic approach of the Earth system science community, including the two options analyzed for the Anthropocene, prevents a proper understanding of the relationship between humans and nature, which is fundamental to confront the Earth's habitability crisis of the Anthropocene.

History of human activity in South China since 7 cal ka BP: Evidence from a sediment record in the South China Sea

Human modifications of the Earth System have been getting increasing attention and this has resulted in the concept of the “Anthropocene”. A complete sequence of human-environment interactions needs to be reconstructed to define the onset of the Anthropocene. To address the chronological gaps and provide a general history of human impact in South China during the Holocene, we present a comprehensive reconstruction of the vegetation, chemical weathering, and heavy metal emissions in the Pearl River and Hainan catchments since 7.0 cal ka BP, using a continuous record of black carbon, clay minerals, and major and trace element concentrations of sediment in Core ZK001 taken from the northwestern South China Sea. Based on high-resolution sediment records, combined with archaeological and historical documents, we propose that human impact in South China can be divided into three stages: a hunting-gathering age (7.0–2.9 cal ka BP), a transitional period (2.9–2.0 cal ka BP) and an intensive farming age (<2.0 cal ka BP). Climate controlled both the vegetation and chemical weathering intensity before 2.9 cal ka BP, after which forest clearance by human-induced fire became significant. Along with population growth and technological progress, enhanced human activities including deforestation, cultivation, and metallurgical activities, gradually superseded natural processes and profoundly impacted the environment in South China, especially after 2.0 cal ka BP. Combined with previous studies from the Pearl River catchment, the Anthropocene likely commenced at 2−3 cal ka BP at least in South China.

Is Aromatic Plants Environmental Health Engineering (APEHE) a leverage point of the Earth system?

Is Aromatic Plants Environmental Health Engineering (APEHE) a leverage point of the Earth system?

Vertical Localization for Strongly Coupled Data Assimilation: Experiments in a Global Coupled Atmosphere‐Ocean Model

AbstractStrongly coupled data assimilation allows observations of one Earth system component (e.g., the ocean) to directly update another component (e.g., the atmosphere). The majority of the information transfer in strongly coupled atmosphere‐ocean systems is passed through vertical correlations between atmospheric boundary layer and ocean mixed layer fields. In this work we use correlations from a global, coupled model to study vertical observation‐space localization techniques for strongly coupled data assimilation. We generate target correlations using a bootstrapping approach from a single 24 hr forecast from a realistic global, weakly coupled atmosphere‐ocean cycling system with an 80‐member ensemble, which is the ensemble size currently used by the NOAA operational global data assimilation system. We compare data assimilation methods with different localization schemes using single‐update, offline experiments. We develop a new strategy for optimal observation space localization, called Empirical Optimal R‐localization (EORL), to give an upper bound on the improvement we can expect with any localization scheme. We then evaluate Gaspari‐Cohn localization, which is a commonly used parametric localization function and review its performance with respect to the optimal localization scheme. We investigate how the performance of these localization strategies changes with increasing ensemble sizes. Our results show that strongly coupled data assimilation has the potential to be an improvement over weakly coupled data assimilation when large ensembles are used. We also show that the Gaspari‐Cohn localization function does not appear to be a particularly good choice for cross‐fluid vertical localization.