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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Influence of Anomalous Biomass Emissions on ENSO in CESM2

Abstract The influence of biomass burning (BB) aerosols arising from wildfires and agricultural fires on the transient coupled evolution of El Niño–Southern Oscillation (ENSO) is explored in Community Earth System Model, version 2 (CESM2). For both El Niño and La Niña, two 20-member ensembles are generated from initial states that are predisposed to evolve into ENSO events. For each ENSO phase, one ensemble is forced with the observed BB emissions during satellite-era ENSO events while the other is forced with a climatological annual cycle, with the responses to anomalous BB emissions estimated from interensemble differences. It is found that the regional responses to anomalous BB emissions occur mainly during boreal fall, which is also the time of the climatological seasonal maximum in emissions. Transient responses are identified in precipitation, clouds, and radiation in both the tropics and extratropics. At the onset of El Niño, these include increased precipitation in the northern branch of the intertropical convergence zone (ITCZ) and an enhancement of cloud albedo and amount across the Maritime Continent and eastern subtropical Pacific Ocean. Additional responses are identified through the course of El Niño and successive La Niña events, the net effect of which is to strengthen sea surface temperature (SST) anomalies in the eastern Pacific Ocean during El Niño and warm the tropical Pacific Ocean during La Niña. These responses improve the simulation of ENSO power, diversity, and asymmetry in CESM2. Significance Statement Biomass burning emissions from both wildfires and agricultural fires during ENSO act as a climate feedback, as they are both driven by fire weather anomalies tied to ENSO and influence clouds, radiation, and precipitation on a global scale. While the largest biomass burning (BB) emissions emanate mainly from Indonesia, other regions also exhibit systematic responses. When simulated in CESM2, the emissions collectively impact the flows of energy across the tropical Pacific Ocean in a spatially and temporally complex fashion, with the net effect of improving CESM2’s simulation of ENSO events.

Fasullo, John T. [National Center for Atmospheric ↗
DOE OSTI2024

Influence of open ocean biogeochemistry on aerosol and clouds: Recent findings and perspectives

Aerosols and clouds are key components of the marine atmosphere, impacting the Earth’s radiative budget with a net cooling effect over the industrial era that counterbalances greenhouse gas warming, yet with an uncertain amplitude. Here we report recent advances in our understanding of how open ocean aerosol sources are modulated by ocean biogeochemistry and how they, in turn, shape cloud coverage and properties. We organize these findings in successive steps from ocean biogeochemical processes to particle formation by nucleation and sea spray emissions, further particle growth by condensation of gases, the potential to act as cloud condensation nuclei or ice nucleating particles, and finally, their effects on cloud formation, optical properties, and life cycle. We discuss how these processes may be impacted in a warming climate and the potential for ocean biogeochemistry—climate feedbacks through aerosols and clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

G-Band Radar Demonstration for Microphysics Field Campaign Report

The G-Band Radar Demonstration for Microphysics (GRDM) campaign took place at the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) from March 15 to April 30, 2024. This was a deployment of two of NASA’s Jet Propulsion Laboratory (JPL) radars and one radar from Brookhaven National Laboratory to demonstrate the utility of high-frequency millimeter-wave radars for remote sensing of stratocumulus microphysical properties. The radars were deployed on the Ellen Browning Scripps Memorial Pier alongside the AMF instruments (Figure 1). The radars include a Ka-band (35 GHz), W-band (94 GHz), and four G-band (158, 165, 174, and 240 GHz) channels. The 240 GHz and W-band channels provide complete Doppler spectra, which are useful for advanced analysis. The 158-175 GHz channels are sensitive to the water vapor profile and are useful for attenuation correction. These radars complement the high-sensitivity ARM KAZR. The goal of the deployment was to observe drizzling stratocumulus and demonstrate the capabilities of the multifrequency radar data set to constrain profiles of liquid water content and drizzle drop characteristic size. The data are still being analyzed. The methodology to derive the cloud and precipitation parameters will exploit differential attenuation and differential reflectivity between low-frequency (Ka-band) and high-frequency (G-band) channels. The method will also exploit the capability of the G-band observations to constrain the attenuation due to water vapor. These observations will quantify the capabilities and limitations of the emerging technology of G-band radars for constraint stratocumulus cloud microphysics, which are key to constraining aerosol-cloud-precipitation interactions and low-cloud climate feedback.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Panama Rainforest Changes with Experimental Drought (PaRChED): Initial Effects of Partial Throughfall Exclusion on Soil Dynamics in Lowland Forests Across Variation in Rainfall and Soil Fertility

Changes in rainfall are predicted across tropical regions, with effects on nutrient, water, and carbon cycling. This chapter summarizes results from the first two years of a throughfall exclusion experiment in four lowland Panamanian forests that span a 1,000-mm change in rainfall and variation in soil fertility. Soil respiration (i.e., soil carbon dioxide [CO2 ] flux) declined with throughfall exclusion, with a site*season interaction, and the radiocarbon age of respired carbon was older in exclusion versus control plots. The decline in soil CO2 flux could be related to reduced fine root production and soil microbial biomass. Microbial community composition also changed with throughfall exclusion in infertile soils, and soil nutrients accumulated more in exclusion versus control plots during the dry season. The net effects on soil carbon storage will depend on the relative strengths of these effects over time. Continued research could improve predictions of tropical forest-climate feedbacks with changes in precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Nonlocal, Pattern-Aware Response and Feedback Framework for Regional Climate Response

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green’s function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) for important climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green’s function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing–response mode pairs, which are in turn used to construct a reduced-order model describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus make the reduced-order model apt for capturing regional features of climate response. A key observation is that the CLRF captures the polar-amplified response as the most excitable mode of the climate system, and this mode is explainable in the data-learned pattern-aware feedback framework. The reduced-order model can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for multiple independent forcing scenarios.

Feedback↗
DOE OSTI2024

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗
DOE OSTI2024

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗
DOE OSTI2026

Recent Weakening of the Global Radiative Feedback

Earth's climate stability, characterized by the global radiative feedback parameter (𝜆), varies decadally due to changing surface temperature patterns. Recent variations in 𝜆 are poorly understood as coordinated model simulations typically end in 2014. We apply a convolutional neural network trained on climate model simulations to observation-based surface temperature reconstructions to estimate variations in 𝜆 up to 2025. We find that 𝜆 reached a minimum (maximum stability) around the mid 1990s (𝜆 ≃ −3 Wm −2 /K), but has since weakened significantly (𝜆 ≃ −2 Wm −2 /K). We confirm these results with climate model simulations extended to 2022. The recent 𝜆 weakening is not significantly affected by El Niño Southern Oscillation or Pacific Decadal Oscillation. Attribution reveals that warming in the subtropical Northeast Pacific is an important driver of the recently weakened feedback, confirmed by targeted experiments in E3SMv2. Our approach enables near real-time monitoring of Earth's climate stability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Post-fire soil respiration in late growing season (2023 and 2024), Kougarok Fire Complex, Seward Peninsula, Alaska

Field soil respiration data collected in 2023 and 2024 from burned and unburned tussock tundra sites in the Kougarok Fire Complex, near Nome, on the Seward Peninsula of Alaska. Specifically, we measured soil properties and late-growing season CO2 fluxes in patches of unique plant functional types (forbs, shrubs, and graminoids) across two years in tundra recovering from repeated wildfires over the decade. The goal was to identify the main drivers of soil respiration in Arctic tundra underlain by discontinuous permafrost that is recovering from two recent, repeated wildfires that differed in fire age and number of times burned, thereby resulting in different levels of vegetation and subsurface property changes (i.e., successional trajectories). There are five files in *.csv format with one data file and four data description files including data, dictionary, methods, terminology, and file-level metadata. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), is a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic Phase 3 project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Santos, Fernanda [ORNL] (ORCID:0000000191555623)↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2024

Multisystem feedbacks from a changing climate: Do altered hydrological dynamics control vadose zone carbon nutrient cycling and storage in shallow aquifer systems?

The vadose zone, which extends from upper soils to the subsurface water table, consists of many distinct habitats (including the critical zone), each with its own physical characteristics. Upper soils are typically richer in organic carbon chemical diversity and concentration, while deeper portions near the water table have less labile carbon and a greater percentage of humic acids and other long-lived organics. The availability of carbon and oxygen constrain the habitability of these zones. Typically, microorganisms (bacteria, archaea, and fungi) extend throughout the vadose zone and potentially deeper into the bedrock, while higher eukaryotes (i.e., arthropods and plants) are limited to the surficial soils. An exception to this is deep taproots of some tree species that can extend tens of meters into the subsurface. In subsurface systems, microbial metabolisms are constrained by the availability of carbon (organic and inorganic) and electron acceptors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain. The global annual mean GPP is historically thought to be around 120 PgC yr −1 , which is about 30–50 PgC yr −1 lower than GPP inferred from the oxygen-18 ( 18 O) isotope and soil respiration. This disparity is a source of uncertainty in predicting climate–carbon cycle feedbacks. Here, in this study, we infer GPP from carbonyl sulfide, an innovative tracer for CO 2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr −1 , which is consistent with estimates from 18 O (150–175 PgC yr −1 ) and soil respiration ($149^{+29}_{-23}$) PgC yr −1 ), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120–140 PgC yr –1 ) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories, our findings lay a physiological foundation on which the understanding and prediction of carbon–climate feedbacks can be advanced.

Lai, Jiameng↗