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At least 91 records · Page 5

Reimagining Earth in the Earth System

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.

Meteorology & Atmospheric Sciences↗

Earth System Model Improvement Pipeline via Uncertainty Attribution and Active Learning

Primary focal area: 2 (Predictive Modeling via AI): We develop methods to formally quantify uncertainties in Earth System models for the land-atmosphere coupled system. Science Challenge: Earth system models still have significant biases in historical predictions of the intensity and frequency of water cycling extremes (e.g., droughts and flood events), leading to low confidence in future projections. Uncertainties arise from incomplete understanding of land and atmospheric processes, and insufficient observational constraints on model parameters. Many observations, including those from key DOE investments such as ARM and AmeriFlux, are used to evaluate model performance but have not been used to formally quantify model uncertainty because of the expense of running ESM simulations. An efficient pipeline engaging cutting-edge machine learning (ML) and uncertainty quantification (UQ) methods is needed to improve the predictive understanding of water cycle extremes in the Earth system.

54 ENVIRONMENTAL SCIENCES↗

Climate-driven Chemistry and Aerosol Feedbacks in CMIP6 Earth System Models

Feedbacks play a fundamental role in determining the magnitude of the response of the climate system to external forcing, such as from anthropogenic emissions. The latest generation of Earth system models includes aerosol and chemistry components that interact with each other and with the biosphere. These interactions introduce a complex web of feedbacks that is important to understand and quantify. This paper addresses multiple pathways for aerosol and chemical feedbacks in Earth system models. These focus on changes in natural emissions (dust, sea salt, dimethyl sulfide, biogenic volatile organic compounds (BVOCs) and lightning) and changes in reaction rates for methane and ozone chemistry. The feedback terms are then given by the sensitivity of a pathway to climate change multiplied by the radiative effect of the change. We find that the overall climate feedback through chemistry and aerosols is negative in the sixth Coupled Model Intercomparison Project (CMIP6) Earth system models due to increased negative forcing from aerosols in a climate with warmer surface temperatures following a quadrupling of CO2 concentrations. This is principally due to increased emissions of sea salt and BVOCs which are sensitive to climate change and cause strong negative radiative forcings. Increased chemical loss of ozone and methane also contributes to a negative feedback. However, overall methane lifetime is expected to increase in a warmer climate due to increased BVOCs. Increased emissions of methane from wetlands would also offset some of the negative feedbacks. The CMIP6 experimental design did not allow the methane lifetime or methane emission changes to affect climate, so we found a robust negative contribution from interactive aerosols and chemistry to climate sensitivity in CMIP6 Earth system models.

Aerosol feedbacks↗

Sun, the Earth, and Near-Earth Space: A Guide to the Sun-Earth System

In a world of warmth and light and living things we soon forget that we are surrounded by a vast universe that is cold and dark and deadly dangerous, just beyond our door. On a starry night, when we look out into the darkness that lies around us, the view can be misleading in yet another way: for the brightness and sheer number of stars, and their chance groupings into familiar constellations, make them seem much nearer to each other, and to us, that in truth they are. And every one of them--each twinkling, like a diamond in the sky--is a white-hot sun, much like our own. The nearest stars in our own galaxy--the Milky Way-- are more than a million times further away from us than our star, the Sun. We could make a telephone call to the Moon and expect to wait but a few seconds between pieces of a conversation, or but a few hours in calling any planet in our solar system.

Sun↗

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

54 ENVIRONMENTAL SCIENCES↗

Human–Earth system interactions under climate change

This special issue, titled ‘Focus on human–Earth system interactions under climate change,’ compiles cutting-edge research that deepens our understanding of the complex feedback mechanisms between anthropogenic activities and Earth system processes in the context of a changing climate (figure 1). The featured articles employ a diverse array of methodologies—including field studies, remote sensing, modeling, and socio-ecological analyses—to explore these interconnections. A unifying theme across these contributions is the imperative to bridge disciplinary divides, integrating physical Earth sciences with social sciences to fully capture the spectrum of human-Earth system interactions. Key topics addressed the impacts of human activities on natural systems, encompassing land-use change and water resource management on biogeochemistry, climate dynamics, and feedback on the climate system and socioeconomics from local to global scales under a changing climate.

Li, Huidong [Vanderbilt Univ., Nashville, TN (Unit↗

Evaluation of Global Fire Simulations in CMIP6 Earth System Models

Fire is the primary form of terrestrial ecosystem disturbance on a global scale and an important Earth system process. Most Earth system models (ESMs) have incorporated fire modeling, with 19 of them submitting model outputs of fire-related variables to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study provides the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based historical reconstructions. Our results show that most CMIP6 models simulate the present-day global burned area and fire carbon emissions within the range of satellite-based products. They also capture the major features of observed spatial patterns and seasonal cycles, the relationship of fires with precipitation and population density, and the influence of the El Niño–Southern Oscillation (ENSO) on the interannual variability of tropical fires. Regional fire carbon emissions simulated by the CMIP6 models from 1850 to 2010 generally align with the charcoal-based reconstructions, although there are regional mismatches, such as in southern South America and eastern temperate North America prior to the 1910s and in temperate North America, eastern boreal North America, Europe, and boreal Asia since the 1980s. The CMIP6 simulations have addressed three critical issues identified in CMIP5: (1) the simulated global burned area being less than half of that of the observations, (2) the failure to reproduce the high burned area fraction observed in Africa, and (3) the weak fire seasonal variability. Furthermore, the CMIP6 models exhibit improved accuracy in capturing the observed relationship between fires and both climatic and socioeconomic drivers and better align with the historical long-term trends indicated by charcoal-based reconstructions in most regions worldwide. However, the CMIP6 models still fail to reproduce the decline in global burned area and fire carbon emissions observed over the past 2 decades, mainly attributed to an underestimation of anthropogenic fire suppression, and the spring peak in fires in the Northern Hemisphere midlatitudes, mainly due to an underestimation of crop fires. In addition, the model underestimates the fire sensitivity to wet–dry conditions, indicating the need to improve fuel wet-ness estimation. Based on these findings, we present specific guidance for fire scheme development and suggest a postprocessing methodology for using CMIP6 multi-model outputs to generate reliable fire projection products.

Wildfire, Earth system models↗

Evaluation of Flow Routing on the Unstructured Voronoi Meshes in Earth System Modeling

Flow routing is a fundamental process of Earth System Models' (ESMs) river component. Traditional flow routing models rely on Cartesian rectangular meshes, which exhibit limitations, particularly when coupled with unstructured mesh-based ocean components. They also lack the support for regionally refined models. While previous studies have highlighted the potential benefits of unstructured meshes for flow routing, their widespread application and comprehensive evaluation within ESMs remain limited. This study extends the river component of the Energy Exascale Earth System Model to unstructured Voronoi meshes. We evaluated the model's performance in simulating river discharge and water depth across three watersheds spanning the Arctic, temperate, and tropical regions. The results show that while providing several benefits, unstructured mesh-based flow routing can achieve comparable performance to structured mesh-based routing, and their difference is often less than 10%. Although the unstructured mesh-based method could address several existing limitations, this research also shows that additional improvements in the numerical method are needed to fully exploit the advantages of unstructured mesh for hydrologic and ESMs.

54 ENVIRONMENTAL SCIENCES↗

NASA’s Earth System Observatory Formulation Progress

The 2017 Earth Science Decadal Survey by the National Academies of Science, Engineering, and Medicine identified five foundational observations, or Designated Observables (DO), to be implemented as missions by NASA. To address these five DO areas – Surface Biology and Geology; Mass Change; Aerosols; Cloud, Convection, and Precipitation; and Surface Deformation and Change – NASA is developing the Earth System Observatory (ESO) as an array of Earth-focused, interconnected satellite missions. The ESO will build on the strong history of international partnerships in NASA Earth science, with initial participation and collaboration on these missions across space agency partners including the Japanese Aerospace Exploration Agency (JAXA), Centre National D'Etudes Spatiales (CNES), Canadian Space Agency (CSA), Deutsches Zentrum für Luft- und Raumfahrt (DLR), and Agenzia Spaziale Italiana (ASI). Targeting launch dates in the late 2020s and early 2030s, the ESO will work as a single observatory, with each satellite in the ESO delivering its own valuable information, but taken together, the data and imagery will provide the global community with a multidimensional, holistic view of the Earth. In addition to furthering the world’s scientific knowledge, data gathered by ESO missions will provide actionable science to inform decisions related to climate change, disaster mitigation, and wildfires, improve real-time agricultural processes, and many other applications. This paper will provide an overview of the ESO development activities, as well as an update on the individual ESO missions currently in formulation – Atmosphere Observing System, Gravity Recovery and Climate Experiment-Continuity, and Surface Biology and Geology – including current mission architectures and concepts, international partner collaboration, science community engagement, and applications efforts, as well as how ESO data will be freely open and accessible to users all over the world.

NASA Earth Science↗

Parallel Optimization of an Earth System Model (100 Gigaflops and Beyond?)

We are developing an Earth System Model (ESM) to be used in research aimed to better understand the interactions between the components of the Earth System and to eventually predict their variations. Currently, our ESM includes models of the atmosphere, oceans and the important chemical tracers therein.

Parallel Optimization Earth System Model↗

NASA’s Earth System Observatory Formulation Overview

NASA’s Earth System Observatory (ESO) is an array of Earth-focused, interconnected satellite missions focused on five core study areas: Surface Biology and Geology, Mass Change, Aerosols, Surface Deformation and Change, and Clouds, Convection, and Precipitation. Observatory development follows recommendations from the National Academies of Sciences, Engineering and Medicine’s 2017 Earth Science Decadal Survey. Data gathered by ESO missions will provide actionable science to inform decisions related to climate change, disaster mitigation, and wildfires, improve real-time agricultural processes, and many other applications. Targeting launch dates in the late 2020s and early 2030s, each ESO satellite will deliver valuable information, but by working together as a single observatory system, their combined data and imagery will provide the global community with a 4D, holistic view of Earth, from bedrock to atmosphere. The ESO is also building on the legacy of international collaboration in Earth science, with initial participation and collaboration on these missions across space agency partners, including the Japanese Aerospace Exploration Agency (JAXA), Centre National D'Etudes Spatiales (CNES), Canadian Space Agency (CSA), Deutsches Zentrum für Luft- und Raumfahrt (DLR), and Agenzia Spaziale Italiana (ASI). This paper provides an overview of ESO, as well as an update on ESO missions currently in formulation – the Atmosphere Observing System, Mass Change, and Surface Biology and Geology elements – including current mission architectures, international partner collaboration, science community engagement, and applications efforts, as well as how NASA and its partners will make ESO data accessible to users all over the world.

NASA Earth Science↗

Challenges to modeling the Sun-Earth System: A Workshop Summary

This special issue of the Journal of' Atmospheric and Solar-Terrestrial Physics is a compilation of 23 papers presented at The 2004 Huntsville Modeling Workshop: Challenges to Modeling thc San-Earth System held in Huntsville, AB on October 18-22, 2004. The title of the workshop appropriately captures the theme of what was presented and discussed by the 120 participants. Currently, end-to-end modeling of the Sun-Earth system is a major goal of the National Space Weather and NASA living with a star (LWS) programs. While profound advances have been made in modeling isolated regions of the Sun-Earth system, minimal progress has been achieved in modeling the end-to-end system. The transfer of mass, energy and momentum through the coupled Sun-Earth system spans a wide range of scales inn time and space. The uncertainty in the underlying physics responsible for coupling contiguous regions of the Sun-Earth system is recognized as a significant barrier to progress

Spann, James F.↗

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of dynamical downscaling in a fully coupled regional earth system model

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere–land–ocean–sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric river representation in the Energy Exascale Earth System Model (E3SM) version 1.0

Abstract. The Energy Exascale Earth System Model (E3SM) project is an ongoing, state-of-the-science Earth system modeling, simulation, and prediction project developed by the US Department of Energy (DOE). With an emphasis on supporting the DOE's energy mission, understanding and quantifying how well the model simulates water cycle processes is of particular importance. Here, we evaluate E3SM version 1.0 (v1.0) for its ability to represent atmospheric rivers (ARs), which play significant roles in water vapor transport and precipitation. The characteristics and precipitation associated with global ARs in E3SM at standard resolution (1∘ × 1∘) are compared to the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). Global patterns of AR frequencies in E3SM show high degrees of correlation (≥0.97) with MERRA2 and low mean absolute errors (MAEs; <1 %) annually, seasonally, and across different ensemble members. However, some large-scale condition biases exist, leading to AR biases – most significant of which are the double intertropical convergence zone (ITCZ), a stronger and/or equatorward-shifted subtropical jet during boreal and austral winters, and enhanced Northern Hemisphere westerlies during summer. By comparing atmosphere-only and fully coupled simulations, we attribute the sources of the biases to the atmospheric component or to a coupling response. Using relationships revealed in Dong et al. (2021), we provide evidence showing the stronger North Pacific jet in winter and the enhanced Northern Hemisphere westerlies during summer, associated with E3SM's double ITCZ and related weaker Atlantic meridional overturning circulation (AMOC), respectively, which are significant sources of the AR biases found in the coupled simulations.

58 GEOSCIENCES↗

NASA Earth System Digital Twins (ESDT) Use Cases

NASA AIST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. In order to define ESDT's benefits to Earth Science, as well as the AIST capabilities required to develop such systems, the AIST Program has been developed 6 science use cases corresponding to 6 of the main Earth Science domains.

J. Le Moigne↗

Nitrification, denitrification, and competition for soil N : Evaluation of two Earth System Models against observations

Abstract Earth System Models (ESMs) have implemented nitrogen (N) cycles to account for N limitation on terrestrial carbon uptake. However, representing inputs, losses, and recycling of N in ESMs is challenging. Here, we use global rates and ratios of key soil N fluxes, including nitrification, denitrification, mineralization, leaching, immobilization, and plant uptake (both NH 4 + and NO 3 − ), from the literature to evaluate the N cycles in the land model components of two ESMs. The two land models evaluated here, E3SM Land Model version 1 (ELMv1)‐ECA and CLM5.0, originated from a common model but have diverged in their representation of plant–microbe competition for soil N. The models predict similar global rates of gross primary productivity (GPP) but have approximately two‐fold to three‐fold differences in their underlying global mineralization, immobilization, plant N uptake, nitrification, and denitrification fluxes. Both models dramatically underestimate the immobilization of NO 3 − by soil bacteria compared with literature values and predict dominance of plant uptake by a single form of mineral nitrogen (NO 3 − for ELM, with regional exceptions, and NH 4 + for CLM5.0). CLM5.0 strongly underestimates the global ratio of gross nitrification:gross mineralization and both models are likely to substantially underestimate the ratio of nitrification:denitrification. Few experimental data exist to evaluate this last ratio, in part because nitrification and denitrification are quantified using different techniques and because denitrification fluxes are difficult to measure at all. More observational constraints on soil nitrogen fluxes such as nitrification and denitrification, as well as greater scrutiny of the functional impact of introducing separate NH 4 + and NO 3 − pools into ESMs, could help to improve confidence in present and future simulations of N limitation on the carbon cycle.

Nevison, Cynthia↗

Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2)

The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6-chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6-chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the volatility basis set (vbs) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ˜143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is -0.43 W/m2, mostly from the aerosol direct effect.

Tilmes, S↗