Download or read book Estimating Terrestrial Carbon Fluxes Through an Optimal Combination of Models and Earth Observation Data written by and published by . This book was released on 2009 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Carbon Fluxes and Biophysical Variables from Earth Observation written by Manuel Campos-Taberner and published by Elsevier. This book was released on 2025-05-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon Fluxes and Biophysical Variables from Earth Observation: Methods for Ecosystem Assessment transforms the way remote sensing data can be used to approach monitoring of carbon fluxes (CF) and biophysical variables (BV) in ecosystem and global vegetation monitoring. In a field where these two subjects have traditionally been treated as distinct entities, this book offers an integrated exploration of CF and BV retrieval through remote sensing. It not only delves into a wide array of approaches and methodologies but also assists readers in selecting the most suitable models based on available inputs and spatiotemporal scales. Carbon Fluxes and Biophysical Variables from Earth Observation is a useful resource for Earth Observation specialists, particularly in Remote Sensing, machine learning, ecology, and plant physiology, to enhance and adapt their approaches and methodologies.
Download or read book Improving Terrestrial Carbon Modeling written by Brett Raczka and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. This dissertation evaluates ways to improve biosphere model performance by 1) evaluating short term (5 years) performance across a broad range of representation complexity, 2) identifying sources of parametric uncertainty for long term (~100 years) performance within a mechanistically detailed model (Ecosystem Demography) and 3) identifying observations that best constrain long term performance. Chapter 2 evaluates the performance of continental-scale carbon flux estimates from 17 models against carbon flux observations from 36 North American flux towers. On average the regional model runs overestimate the annual gross primary productivity (5%) and total respiration (15%), and significantly underestimate the annual net carbon uptake (64%) during the time period 2000-2005. Comparison with site-level simulations implicate choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models perform the best at simulating carbon exchange at deciduous broadleaf sites; likely because a number of models use prescribed phenology to simulate seasonal fluxes. In general, the models do not perform as well for crop, grass and evergreen sites in terms of bias, correlation and magnitude of variation. The regional models match the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but have very little skill at inter-annual correlation and minimal skill at inter-annual magnitude of variability. The comparison of site versus regional level model runs demonstrate that 1) the inter-annual correlation is higher for site-level model runs but the skill remains low, and 2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best performing regional models that do not use flux tower calibration are CLM-CN, CASA--GFEDv2 and SIB3. Two empirical models, calibrated with flux towers observations, EC-MOD and MOD17+, perform as well as the best process-based models. This suggests that 1) empirical, calibrated models can perform as well as complex, process-based models, and 2) combining process-based model structure with relevant constraining data could significantly improve model performance. Through a sensitivity analysis of the Ecosystem Demography model (version 2.1), Chapter 3 identifies quantum efficiency and leaf respiration rate parameters as the highest contributors to model uncertainty regardless of time frame (annual, decadal, centennial). This finding is sensitive to methodological choices within the meta-analysis process. Trait data provides relatively modest constraint upon the model simulation whereas integrative measurements of NEE and AGB provide strong constraints to the model and parameter uncertainty. Key actions for model improvement include 1) locating additional measurements related to quantum efficiency, leaf respiration rate and water fluxes (e.g. sap flux, soil moisture) and 2) implementing a more mechanistic representation of growth respiration within the model.
Download or read book Estimating Carbon Flux Phenology with Satellite Derived Land Surface Phenology and Climate Drivers for Different Biomes written by and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this paper, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptake (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. In conclusion, this methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.
Download or read book Terrestrial Carbon Observation written by Josef Cihlar and published by Food & Agriculture Org.. This book was released on 2002 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report summarises the discussions and recommendations of a workshop held in 2001, within the framework of the Terrestrial Carbon Observation (TCO) initiative. This workshop focused on the development of a systematic and collaborative approach to improving "in situ" or ground-based carbon data availability. The benefits of improved "in situ" terrestrial carbon observation will mean that countries can make more informed decisions related to the sustainable use and management of land resources.
Download or read book Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.
Download or read book Terrestrial Carbon Observation written by Global Terrestrial Observing System (Organization) and published by Food & Agriculture Org.. This book was released on 2002 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term 'terrestrial carbon' refers to carbon contained in vegetation or soil stocks. The global carbon cycle plays an important role in sustaining agricultural productivity, biodiversity and forest ecosystems processes. This report presents the results of a workshop, held in Canada in February 2000 and organised by the Global Terrestrial Observing System (GTOS) in collaboration with the International Geosphere-Biosphere Programme (IGBP). The workshop was designed to review existing data and observation requirements regarding terrestrial carbon, identify major gaps and propose solutions.
Download or read book Using Earth Observation and Ground based Data to Improve Modelled CO2 and CH4 Fluxes from Peatlands written by N. L. MacBean and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Peatlands are an important store of carbon; they contain ~15-30% of the world's soil C while covering only ~3% of the land area. They are also the largest natural source of methane (CH4), but the global estimate is highly uncertain. Here, this issue is addressed by developing a combined data - modelling framework to provide optimal estimates of CO2 and CH4 fluxes from an upland UK peat site. An Observing Systems Simulation Experiment (OSSE), using a Bayesian inversion method, is implemented to investigate the CH4, NEP and soil moisture observation temporal frequency and uncertainty required to accurately constrain model parameters and to estimate model predictive uncertainty. The OSSE is used to examine the impact of parameter correlations, bias in low-resolution observations, and unknown model error. The highly model-sensitive parameters are constrained by almost all observations, with a corresponding improvement in model predictive uncertainty. However there is high degree of model equifinality. Biased observations and unaccounted-for model error can result in false confidence in inaccurate model predictions. The OSSE results demonstrate the importance of performing a synthetic experiment prior to using actual data. Finally, real data are used to calibrate the model, which is then used to determine the net CO2 and CH4 flux for the site. The results highlight a possible source of error in the model. It is suggested this is because of an inaccurate representation of the coupling between CO2 and CH4, due to an unaccounted for lag in the methanotrophic activity. This has significant implications for CH4 flux modelling, as many models use a similar formulation for CH4 dynamics. Results are compared with satellite and ground-based measurement characteristics and recommendations are made for the observation and modelling of ecosystems at small spatial scales. This information is useful for modellers, space agencies and field biologists.
Download or read book Thriving on Our Changing Planet written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-01-20 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.
Download or read book Estimation of Net Ecosystem Carbon Exchange for the Conterminous United States by Combining MODIS and AmeriFlux Data written by and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p
Download or read book Land Carbon Cycle Modeling written by Yiqi Luo and published by CRC Press. This book was released on 2022-08-18 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon moves through the atmosphere, through the oceans, onto land, and into ecosystems. This cycling has a large effect on climate – changing geographic patterns of rainfall and the frequency of extreme weather – and is altered as the use of fossil fuels adds carbon to the cycle. The dynamics of this global carbon cycling are largely predicted over broad spatial scales and long periods of time by Earth system models. This book addresses the crucial question of how to assess, evaluate, and estimate the potential impact of the additional carbon to the land carbon cycle. The contributors describe a set of new approaches to land carbon cycle modeling for better exploring ecological questions regarding changes in carbon cycling; employing data assimilation techniques for model improvement; and doing real- or near-time ecological forecasting for decision support. This book strives to balance theoretical considerations, technical details, and applications of ecosystem modeling for research, assessment, and crucial decision making. Key Features Helps readers understand, implement, and criticize land carbon cycle models Offers a new theoretical framework to understand transient dynamics of land carbon cycle Describes a suite of modeling skills – matrix approach to represent land carbon, nitrogen, and phosphorus cycles; data assimilation and machine learning to improve parameterization; and workflow systems to facilitate ecological forecasting Introduces a new set of techniques, such as semi-analytic spin-up (SASU), unified diagnostic system with a 1-3-5 scheme, traceability analysis, and benchmark analysis, for model evaluation and improvement Related Titles Isabel Ferrera, ed. Climate Change and the Oceanic Carbon Cycle: Variables and Consequences (ISBN 978-1-774-63669-5) Lal, R. et al., eds. Soil Processes and the Carbon Cycle (ISBN 978-0-8493-7441-8) Windham-Myers, L., et al., eds. A Blue Carbon Primer: The State of Coastal Wetland Carbon Science, Practice and Policy (ISBN 978-0-367-89352-1)
Download or read book Toward Improved Regional Estimates of Carbon Dioxide Sources and Sinks Through Coupled Carbon atmospheric Data Assimilation written by Hans Weiteng Chen and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate estimates of regional carbon dioxide (CO2) sources and sinks are necessary to further our understanding of the carbon cycle and improve predictions of future climate change. CO2 surface fluxes can be constrained using atmospheric CO2 observations combined with atmospheric transport models through so-called top-down or inverse methods. At regional scales, however, inverse estimates of CO2 fluxes have been shown to be sensitive to errors in model representation of atmospheric transport. How to account for such atmospheric transport errors in inversions is currently not well understood.This dissertation examines the impact of atmospheric transport errors on simulated atmospheric CO2 mole fractions and inferred CO2 fluxes at subcontinental scales and hourly to monthly time scales. We first investigate how much space for improvement there is in two contemporary CO2 analysis datasets by comparing CO2 mole fractions from the analyses with airborne in situ measurements of CO2 from the Atmospheric Carbon and Transport - America field campaigns in summer 2016 and winter 2017. The analyses show an overall good agreement with observations except for large biases in near-surface CO2 mole fractions in the Mid-Atlantic region of the United States during summer, which suggests that CO2 fluxes can be further optimized in this region. Next, we quantify how transport errors due to uncertainties in meteorological initial conditions propagate to errors in atmospheric CO2 mole fractions through ensemble sensitivity experiments in a regional mesoscale model. Transport errors in CO2 are found to be of comparable magnitude and share similar spatiotemporal characteristics as errors due to uncertainties in CO2 fluxes on sub-monthly time scales. Finally, we present the development of a coupled carbon--atmospheric data assimilation system for regional CO2 flux inversion. This data assimilation system uses the ensemble Kalman Filter to optimize both meteorological variables and CO2 mole fractions and fluxes. Coupling the atmospheric and carbon states allows us to investigate the role of atmospheric transport errors in the CO2 flux optimization. The data assimilation system is tested in a series of perfect model experiments with synthetic observations to examine how well the CO2 flux inversion performs when different types of errors are introduced.
Download or read book Assessment of Uncertainties in Atmospheric Transport and Surface Flux of Carbon from the North American Terrestrial Biosphere written by Caroline Normile and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The North American terrestrial biosphere acts as a strong sink of atmospheric CO2 and therefore plays a key role in the global carbon cycle. The atmospheric inversion approach is used to quantify the magnitude and distribution land-atmosphere carbon exchange, and requires accurate atmospheric transport and surface flux prior. We evaluate the relative sensitivity of simulated atmospheric total, biological, and fossil fuel CO2 mole fractions in the atmospheric boundary layer and integrated column over North America to changes in transport model and surface fluxes. We run three versions of a mesoscale model that incorporate different physics parameterization schemes and identical surface fluxes; we run the same mesoscale transport model with two different surface fluxes. All simulations are conducted for North America during 2008. Observed CO2 mole fractions reveal that seasonal amplitude ranges from 13 ppm in the West to over 34 ppm in the Midcontinent, and the models tested match these amplitudes to within a few ppm. Biology drives both the magnitude of the seasonal amplitude and regional differences in amplitude. Fossil fuels exhibit a seasonal cycle that is smaller than biological CO2, but not trivial. During the growing season, variations in surface fluxes yield mean differences in regionally, seasonally averaged atmospheric boundary layer total CO2 mole fractions that are larger for all regions than those resulting from varied transport model. The relative contributions of biological and fossil fuel to total mean difference CO2 show distinct quantitative patterns for varied flux and transport, and can provide information for attributing model-model differences in total CO2. Seasonal amplitude is much greater in the ABL than in the integrated column. Simulated total biological, and fossil fuel integrated column XCO2 are about 1/10th the magnitude of their signal in the atmospheric boundary layer. Flux and transport differences are also found in the integrated column at approximately 1/10th their atmospheric boundary layer values. While transport error is a significant problem for identifying terrestrial carbon fluxes, it is not an overwhelming one. Our work indicates that there is potential for remotely sensed integrated column XCO2 to distinguish between the flux signal and transport errors. Understanding transport error deserves more study, motivating current and future observational campaigns and modeling.While reducing transport uncertainty in atmospheric inversions has received considerable attention in recent years, quantification of carbon surface flux uncertainty remains a challenge. Model-observation studies can help identify model temporal and spatial limitations. To this end, we organize 166 CO2 flux tower measurement sites across North America by region, climate, and vegetation type into 23 groupings. The data span from 2000 through 2014 and are compared to output from eight atmospheric inverse estimates and 17 terrestrial biosphere models. We generate a mean year of observed and simulated net ecosystem exchange for each regional vegetation group and for each model. The NOAA CarbonTracker inverse estimates, major carbon flux inverse products, almost always underestimate amplitude of the seasonal cycle (biased positive relative to observations) and have a small spread. Furthermore, the inversions dont typically improve upon the prior with respect to the observations. Groups characterized by large seasonal amplitudes are not well represented by the models. For these groups, drawdown is underestimated. The terrestrial biosphere models often encompass the observations, but may have too much model-model variability. No one model is best everywhere. Model performance varies by vegetation and location. Certain biomes are well represented, certain biomes are not, and some models are reliably better than others. In general, evergreen forests in the north and east are better represented by the models than grasslands or crops in the midcontinent and southwest. Our large-scale, regional approach to model-observation analyses provides insight into the vegetation- and location-dependent performance of many inverse and terrestrial biosphere model estimates of land-atmosphere carbon exchange. This can help inform selection and application of surface flux priors in future inversions.
Download or read book Atmospheric 14CO2 Constraints on and Modeling of Net Carbon Fluxes 06 ERD 031 An LLNL Exploratory Research in the Directorate s Final Report written by and published by . This book was released on 2009 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical scientific question is: 'what are the present day sources and sinks of carbon dioxide (CO2) in the natural environment, and how will these sinks evolve under rising CO2 concentrations and expected climate change and ecosystem response'? Sources and sinks of carbon dioxide impart their signature on the distribution, concentration, and isotopic composition of CO2. Spatial and temporal trends (variability) provide information on the net surface (atmosphere to ocean, atmosphere to terrestrial biosphere) fluxes. The need to establish more reliable estimates of sources and sinks of CO2 has lead to an expansion of CO2 measurement programs over the past decade and the development of new methodologies for tracing carbon flows. These methodologies include high-precision pCO2, [delta]13CO2, and [O2/N2] measurements on atmospheric constituents that, when combined, have allowed estimates of the net terrestrial and oceanic fluxes at decadal timescales. Major gaps in our understanding remain however, and resulting flux estimates have large errors and are comparatively unconstrained. One potentially powerful approach to tracking carbon flows is based on observations of the 14C/12C ratio of atmospheric CO2. This ratio can be used to explicitly distinguish fossil-fuel CO2 from other sources of CO2 and also provide constraints on the mass and turnover times of carbon in land ecosystems and on exchange rates of CO2 between air and sea. Here we demonstrated measurement of 14C/12C ratios at 1-2{per_thousand} on archived and currently collected air samples. In parallel we utilized the LLNL-IMPACT global atmospheric chemistry transport model and the TransCom inversion algorithm to utilize these data in inversion estimates of carbon fluxes. This project has laid the foundation for a more expanded effort in the future, involving collaborations with other air-sampling programs and modeling groups.
Download or read book Terrestrial Carbon Observation written by Josef Cihlar and published by Food & Agriculture Org.. This book was released on 2002 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term 'terrestrial carbon' refers to carbon contained in vegetation or soil stocks. The global carbon cycle plays an important role in sustaining agricultural productivity, biodiversity and forest ecosystems processes. This report identifies a framework for the systematic observation and assessment of carbon stocks on land and in the atmosphere, highlights a number of challenges that need to be addressed and outlines an approach to implement an initial observing system.
Download or read book Monitoring the Carbon Cycle written by Brendan Byrne and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliable projections of climate change will require terrestrial biosphere models (TBMs) that produce robust projections of changes in the exchange of CO2 between the atmosphere and terrestrial biosphere. In this thesis, atmospheric CO2 observations are used to evaluate TBMs. First, the sensitivity of several observing systems to surface fluxes of CO2 is characterized. This analysis identifies the spatiotemporal scales over which atmospheric CO2 observations provide significant constraints on net ecosystem exchange (NEE) fluxes. Second, constraints from atmospheric CO2 and solar-induced fluorescence (SIF) observations are combined to evaluate the seasonality of NEE, gross primary productivity (GPP) and ecosystem respiration (Re) fluxes over the northern mid-latitudes for a set of TBMs. It is shown that model-based seasonal cycles of Re exhibit systematic differences from optimized Re constrained by atmospheric CO2 and SIF measurements, with the models overestimating Re during June-July and underestimating Re during the fall. Further analysis suggests that the differences could be due to seasonal variations in the carbon use efficiency and to seasonal variations in the leaf litter and fine root carbon pool. Finally, the ability of TBMs to simulate interannual variability (IAV) in NEE is evaluated. IAV in NEE produced by a set of TBMs and CO2 flux inversions is compared to proxies of IAV in the carbon cycle, including temperature anomalies, SIF anomalies, and the Palmer drought index. It is shown that CO2 flux inversions that assimilate observations from the Greenhouse Gases Observing Satellite (GOSAT) out-perform most TBMs in recovering NEE anomalies driven by climate anomalies, suggesting that GOSAT CO2 flux inversions can be used to evaluate NEE anomalies produced by TBMs on large scales. This thesis also describes the installation of an open-path Fourier transform infrared spectroscopy (OP-FTIR) system in downtown Toronto. This system provides continuous observations of CO2, CO, CH4 and N2O, which, in combination with other observing stations, will provide valuable top-down constraints on GHG emissions from Toronto. An initial evaluation of this instrument is performed and comparisons of the observed gases with meteorological observations and CO2, CO, and CH4 measurements at a nearby site are presented.
Download or read book Proceedings of the International Symposium on Remote Sensing of Environment written by and published by . This book was released on 2009 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt:
