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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle

Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes

Rising atmospheric carbon dioxide due to human activities through fossil fuel emissions and land use changes have increased climate extremes such as heat waves and droughts that have led to and are expected to increase the occurrence of carbon cycle extremes. Carbon cycle extremes represent large anomalies in the carbon cycle that are associated with gains or losses in carbon uptake. Carbon cycle extremes could be continuous in space and time and cross political boundaries. Here, we present a methodology to identify large spatiotemporal extremes (STEs) in the terrestrial carbon cycle using image processing tools for feature detection. We characterized the STE events based on neighborhood structures that are three-dimensional adjacency matrices for the detection of spatiotemporal manifolds of carbon cycle extremes. We found that the area affected and carbon loss during negative carbon cycle extremes were consistent with continuous neighborhood structures. In the gross primary production data we used, 100 carbon cycle STEs accounted for more than 75% of all the negative carbon cycle extremes. This paper presents a comparative analysis of the magnitude of carbon cycle STEs and attribution of those STEs to climate drivers as a function of neighborhood structures for two observational datasets and an Earth system model simulation.

Sharma, Bharat↗
NASA NTRS2022

Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean 149^(+29)_(−23) Pg C/yr) are significantly higher than most GPP estimates reported in the literature (113^(+18)_(−18) Pg C/yr). Similarly, historical GPP estimates imply a soil respiration flux (Rs(_GPP), bootstrap mean of 68^(+10)_(−8) Pg C/yr) statistically inconsistent with most published RS values (87^(+9)_(−8) Pg C/yr), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R_(S):GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.

Jinshi Jian↗
NASA NTRS2018

Future of the North American Carbon Cycle: Chapter - 19

Rising atmospheric carbon dioxide (CO2) concentrations, primarily due to fossil fuel emissions and land-use change, are expected to continue to drive changes in both climate and the terrestrial and ocean carbon cycles. Over the past two-to-three decades, there has been considerable effort to understand how terrestrial and oceanic systems behave (in response to rising atmospheric CO2 and changing climate conditions), quantify the dynamics of system responses to environmental change, and project how the ocean and terrestrial carbon cycle will interact with, and influence, future atmospheric CO2 concentrations and climate. In this presentation, we will summarize key findings related to projected changes to the North American carbon cycle and drivers and associated consequences of these changes, as reported in Chapter 19 of the Second State of the Carbon Cycle Report (SOCCR-2). The findings not only capture projections of emissions from fossil fuel and changes in land cover and land use, but also highlight the decline in future carbon uptake capacity of North American carbon reservoirs and soil carbon losses from the Northern high-latitudes. Such a discussion of future carbon cycle changes is new in SOCCR-2, yet timely. It underlines the progress made since the release of the First State of the Carbon Cycle Report (SOCCR-1) in 2007 in identifying the vulnerability of key carbon pools and their co-evolution with changing climatic conditions. We will also discuss key knowledge gaps and outline a set of future research priorities, including both monitoring and modeling activities, that are necessary to improve projections of future changes to the North American carbon cycle and associated adaptation and resource-management decisions.

North America↗
NASA NTRS1992

Modelling the Phanerozoic carbon cycle and climate: constraints from the 87Sr/86Sr isotopic ratio of seawater

A numerical model describing the coupled evolution of the biogeochemical cycles of carbon, sulfur, calcium, magnesium, phosphorus, and strontium has been developed to describe the long-term changes of atmospheric carbon dioxide and climate during the Phanerozoic. The emphasis is on the effects of coupling the cycles of carbon and strontium. Various interpretations of the observed Phanerozoic history of the seawater 87Sr/86Sr ratio are investigated with the model. More specifically, the abilities of continental weathering, volcanism, and surface lithology in generating that signal are tested and compared. It is suggested that the observed fluctuations are mostly due to a changing weatherability over time. It is shown that such a conclusion is very important for the modelling of the carbon cycle. Indeed, it implies that the conventional belief that the evolution of atmospheric carbon dioxide and climate on a long time scale is governed by the balance between the volcanic input of CO2 and the rate of silicate weathering is not true. Rather carbon exchanges between the mantle and the exogenic system are likely to have played a key role too. Further, the increase of the global weathering rates with increasing surface temperature and/or atmospheric CO2 pressure usually postulated in long-term carbon cycle and climate modelling is also inconsistent with the new model. Other factors appear to have modulated the weatherability of the continents through time, such as mountain building and the existence of glaciers and ice sheets. Based on these observations, a history of atmospheric carbon dioxide and climate during Phanerozoic time, consistent with the strontium isotopic data, is reconstructed with the model and is shown to be compatible with paleoclimatic indicators, such as the timing of glaciation and the estimates of Cretaceous paleotemperatures.

NASA Discipline Number 52-30↗
DOE OSTI2024

Temporal Error Correlations in a Terrestrial Carbon Cycle Model Derived by Comparison to Carbon Dioxide Eddy Covariance Flux Tower Measurements

Abstract Atmospheric CO 2 flux inversions require as input an estimate of spatial and temporal correlations of errors in their estimate of the prior mean. Some previous studies have used the differences in CO 2 daily average flux estimates produced by terrestrial carbon cycle models and eddy covariance measurements to constrain the flux error correlations. Since inversions are starting to resolve the daily cycle, we set out to examine the correlations at sub‐daily time scales, as well as the correlations across years. To this end, we examine the autocorrelations in the difference between net ecosystem‐atmosphere exchange measurements from 75 AmeriFlux towers and temporally downscaled high‐spatial‐resolution flux estimates from the Carnegie‐Ames‐Stanford Approach (CASA) terrestrial carbon cycle model. We find that the daily cycle is prominent in these hourly autocorrelations and that these autocorrelations persist across years. We propose a family of functions to model these temporal correlations in atmospheric inversions, and use cross validation to determine which of the correlation functions best fits autocorrelation data from towers not in the training set. Correlation functions with a component that attempts to model the daily cycle in the differences match correlations from other towers better than those without. Those models that reproduce the same correlation structures at 1‐year intervals while modulating the amplitudes of the correlations between those intervals improve the fit still further.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

The Ocean’s Breath: How Autonomous Robotic Vehicles at Sea and Super Computers are Helping us Understand the Carbon Cycle in the Ocean

Carbon dioxide due to human activities such as fossil fuel burning has well-known and concerning implications for global temperatures as well as terrestrial and marine ecosystems. Hence, an important objective of NASA Earth science is to observe and understand the variations in the global carbon cycle and the associated climate and ecosystem impacts in the context of past and projected anthropogenic emissions. In my presentation, I will tell the story of how some of my collaborators and I are using autonomous robotic vehicles and super computers to try to untangle the mysteries of the carbon cycle in the ocean, which depends in fascinating ways on atmospheric and ocean physics, marine ecosystem dynamics, as well as the chemistry of the seawater.

Ocean's breath↗
DOE OSTI2022

Carbon acquisition ecological strategies to connect soil microbial biodiversity and carbon cycling

Soil carbon feedbacks to global change are uncertain, and the biological processes that govern soil organic matter decomposition are not resolved in current ecosystem models. Though it is recognized that microbial biodiversity influences decomposition rates, incorporating this relationship into ecosystem models is challenging because microbial communities are prohibitively diverse. It is likely necessary to distill microbial biodiversity by focusing on functional groups or ecological strategies. The ecological strategies that currently dominate the microbial ecology literature derive from macroecological theory, have clear weaknesses, and have had limited success when applied to predict soil carbon dynamics. Here, we present a new framework for soil microorganisms: Carbon Acquisition Ecological Strategies (CAES), and we outline a path toward incorporating microbial biodiversity into ecosystem models using this framework to enhance predictions of soil carbon feedbacks to global change. Because a microorganism's diet is central to its ecological niche and likely to covary with other ecologically significant traits, we posit that carbon acquisition may serve as a tractable foundation for developing ecological strategies. Further, we describe four candidate ecological strategies for soil microorganisms: 1° decomposers that assimilate complex plant polymers, 2° decomposers that assimilate microbial necromass, passive consumers that assimilate dissolved organic carbon, and predatory microbes that assimilate live microbial biomass. These strategies are directly linked to soil carbon pools currently represented in ecosystem models and may provide a foundation for greater integration of microbial community dynamics into ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Matrix Approach to Land Carbon Cycle Modeling

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Impacts of Disturbance History on Forest Carbon Stocks and Fluxes: Merging Satellite Disturbance Mapping with Forest Inventory Data in a Carbon Cycle Model Framework

Forest carbon stocks and fluxes are highly dynamic following stand-clearing disturbances from severe fire and harvest and this presents a significant challenge for continental carbon budget assessments. In this work we use forest inventory data to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for specific forest types growing in high and low site productivity class settings. We then apply these trajectories to landscapes and regions based on forest age distributions derived from either the FIA data or from Landsat time series stacks (1985-2006) for 54 representative scenes throughout most of the conterminous United States. We estimate the net carbon uptake in forests caused by post-disturbance growth and decomposition ("regrowth sink") for forested regions across the country. At the landscape scale, the prevailing condition of positive net ecosystem productivity (NEP) is in stark contrast to local patches with large sources, particularly in the west where fires and clear cuts create contiguous disturbed patches. At the continental scale, regional differences in disturbance rates reflect management patterns of high disturbance rates in the Southeastern and South Central states, and lower disturbance rates in the Northeast and Northern Lakes States. Despite low contemporary disturbance rates in the Northeast and Northern Lakes States (0.61 and 0.74% y(exp −1)), the regrowth sink there remains of moderate to large strength (88 and 57 g C m(exp −2) y(exp −1)) owing to the continued legacy from historical clearing. Large regrowth sinks are also found in the Southeast, South Central, and Pacific Southwest regions (85, 86, and 95 g C m(exp −2) y(exp −1)) where disturbance rates also tend to be higher (1.59, 1.38, and 0.93% y(exp −1)). Overall, the Landsat-derived disturbance rates are elevated relative to FIA-derived rates (1.19 versus 0.93% y(exp −1)) particularly for western regions. The differences only modestly adjust regional- and continental-scale carbon budgets, reducing NEP from forest regrowth by about 8%.

carbon↗
DOE OSTI2026

A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management

Greenhouse gas (GHG) emissions continue to grow, while natural carbon reservoirs are becoming increasingly vulnerable to anthropogenic pressures, climate extremes, and disturbance. These changes are impacting humans, ecosystems, and natural resources worldwide. Tracking and mitigating GHG emissions require a pivot to operational monitoring of regional carbon flux and stock changes. The current GHG observing system is addressing needs at two distinct scales: 1) Local scale (< 1 km), related to anthropogenic point source emissions, and 2) global scales (> 1000 km), related to land and ocean carbon sinks. More focus on intermediate (10–1000 km) scales is needed to more effectively monitor progress in reducing carbon emissions, enhancing removals, and maintaining sinks. Representatives from carbon cycle biomass and flux communities across United States government agencies and academic institutions met in September 2024 to discuss the rationale and scientific context for more effectively implementing an operational system for GHG monitoring in support of urban and national carbon management needs. To guide development of this system, we propose a multi-tiered global spaceborne observing framework for carbon flux and stock, prioritizing: 1) frequent GHG partial columns for carbon emissions and removals; 2) continuous time series and data fusion of biomass from Lidar and Synthetic Aperture Radar (SAR) for carbon stocks, and 3) expanded coverage of tropical, high latitude, and oceanic regions to monitor carbon cycle tipping points and feedbacks. This system should be complemented by expanded surface and airborne networks for oceanic and terrestrial/aquatic ecosystems for calibration, ground truthing, and study of under-sampled regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Climate model↗
DOE OSTI2022

Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300

The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Gregg, W. W.↗
DOE OSTI2024

The Four-Dimensional Carbon Cycle of the Southern Ocean

The Southern Ocean plays a fundamental role in the global carbon cycle, dominating the oceanic uptake of heat and carbon added by anthropogenic activities and modulating atmospheric carbon concentrations in past, present, and future climates. However, the remote and extreme conditions found there make the Southern Ocean perpetually one of the most difficult places on the planet to observe and to model, resulting in significant and persistent uncertainties in our knowledge of the oceanic carbon cycle there. The flow of carbon in the Southern Ocean is traditionally understood using a zonal mean framework, in which the meridional overturning circulation drives the latitudinal variability observed in both air–sea flux and interior ocean carbon concentration. However, recent advances, based largely on expanded observation and modeling capabilities in the region, reveal the importance of processes acting at smaller scales, including basin-scale zonal asymmetries in mixed-layer depth, mesoscale eddies, and high-frequency atmospheric variability. Assessing the current state of knowledge and remaining gaps emphasizes the need to move beyond the zonal mean picture and embrace a four-dimensional understanding of the carbon cycle in the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

The Ocean Carbon States Database: A Proof-of-Concept Application of Cluster Analysis in the Ocean Carbon Cycle

In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.

carbon cycle↗
NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗