The GEOS-Carb project seeks to make high quality, data-driven products that support NASA's Carbon Monitoring System Program. These include bottom-up land and ocean flux estimates along with fossil fuel emissions, all informed by satellite data and the MERRA-2 reanalysis. These flux data support atmospheric carbon products that include both simulations and data assimilation products. We show examples of this work and discuss applications to future mission planning.

The precise contribution of the two major sinks for anthropogenic CO2 emissions, terrestrial vegetation and the ocean, and their location and year-to-year variability are not well understood. Top-down estimates of the spatiotemporal variations in emissions and uptake of CO2 are expected to benefit from the increasing measurement density brought by recent in situ and remote CO2 observations. We uniquely apply a batch Bayesian synthesis inversion at relatively high resolution to in situ surface observations and bias-corrected GOSAT satellite column CO2 retrievals to deduce the global distributions of natural CO2 fluxes during 2009-2010. Our objectives include evaluating bottom-up prior flux estimates, assessing the value added by the satellite data, and examining the impacts of inversion technique and assumptions on posterior fluxes and uncertainties. The GOSAT inversion is generally better constrained than the in situ inversion, with smaller posterior regional flux uncertainties and correlations, because of greater spatial coverage, except over North America and high-latitude ocean. Complementarity of the in situ and GOSAT data enhances uncertainty reductions in a joint inversion; however, spatial and temporal gaps in sampling still limit the ability to accurately resolve fluxes down to the sub-continental scale. The GOSAT inversion produces a shift in the global CO2 sink from the tropics to the north and south relative to the prior, and an increased source in the tropics of ~2 Pg C y-1 relative to the in situ inversion, similar to what is seen in studies using other inversion approaches. This result may be driven by sampling and residual retrieval biases in the GOSAT data, as suggested by significant discrepancies between posterior CO2 distributions and surface in situ and HIPPO mission aircraft data. While the shift in the global sink appears to be a robust feature of the inversions, the partitioning of the sink between land and ocean in the inversions using either in situ or GOSAT data is found to be sensitive to prior uncertainties because of negative correlations in the flux errors. The GOSAT inversion indicates significantly less CO2 uptake in summer of 2010 than in 2009 across northern regions, consistent with the impact of observed severe heat waves and drought. However, observations from an in situ network in Siberia imply that the GOSAT inversion exaggerates the 2010-2009 difference in uptake in that region, while the prior CASA-GFED model of net ecosystem production and fire emissions reasonably estimates that quantity. The prior, in situ posterior, and GOSAT posterior all indicate greater uptake over North America in spring to early summer of 2010 than in 2009, consistent with wetter conditions. The GOSAT inversion does not show the expected impact on fluxes of a 2010 drought in the Amazon; evaluation of posterior mole fractions against local aircraft profiles suggests that time-varying GOSAT coverage can bias estimation of flux interannual variability in this region.

Abstract. Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long term fire records are needed that fuse information from different satellite and in-situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2015. The modeling system, based on the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include: 1) new burned area estimates with contributions from small fires, 2) a revised fuel consumption parameterization optimized using field observations, 3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and 4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2 x 1015 grams carbon per year (Pg C yr-1) during 1997–2015, with a maximum in 1997 (3.0 Pg C yr-1) and minimum in 2013 (1.8 Pg C yr-1). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (–19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the "s" for small fires), average emissions were 1.5 Pg C yr-1. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. Our improved dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth System. GFED data is available from http://www.globalfiredata.org.

Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.

Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2 × 1015 grams of carbon per year (Pg C yr−1) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr−1) and minimum in 2013 (1.8 Pg C yr−1). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr−1. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org.

The El Niño Modoki in 2010 led to historic droughts in Brazil. In order to understand its impact on carbon cycle variability, we derive the 2011–2010 annual carbon flux change ( δ F ↑ ) globally and specifically to Brazil using the NASA Carbon Monitoring System Flux (CMS‐Flux) framework. Satellite observations of CO 2 , CO, and solar‐induced fluorescence (SIF) are ingested into a 4D‐variational assimilation system driven by carbon cycle models to infer spatially resolved carbon fluxes including net ecosystem production, biomass burning, and gross primary productivity (GPP). The global 2011–2010 net carbon flux change was estimated to be δ F ↑ =−1.60 PgC, while the Brazilian carbon flux change was −0.24 ± 0.11 PgC. This estimate is broadly within the uncertainty of previous aircraft‐based estimates restricted to the Amazon basin. The 2011–2010 biomass burning change in Brazil was −0.24 ± 0.036 PgC, which implies a near‐zero 2011–2010 change of the net ecosystem production (NEP): The near‐zero NEP change is the result of quantitatively comparable increases GPP (0.31 ± 0.20 PgC) and respiration in 2011. Comparisons between Brazilian and global component carbon flux changes reveal complex interactions between the processes controlling annual land‐atmosphere CO 2 exchanges. These results show the potential of multiple satellite observations to help quantify and spatially resolve the response of productivity and respiration fluxes to climate variability.

Disturbances are a major determinant of forest carbon stocks and uptake. They generally reduce land carbon stocks but also initiate a regrowth legacy that contributes substantially to the contemporary rate of carbon stock increase in US forestlands. As managers and policy makers increasingly look to forests for climate protection and mitigation, and because of increasing concern about changes in disturbance intensity and frequency, there is a need for synthesis and integration of current understanding about the role of disturbances and other processes in governing forest carbon cycle dynamics, and the likely future of this and other sinks for atmospheric carbon. This paper aims to address that need by providing a quantitative review of the distribution, extent and carbon impacts of the major disturbances active in the US. We also review recent trends in disturbances, climate, and other global environmental changes and consider their individual and collective contributions to the US carbon budget now and in the likely future. Lastly, we identify some key challenges and opportunities for future research needed to improve current understanding, advance predictive capabilities, and inform forest management in the face of these pressures.Harvest is found to be the most extensive disturbance both in terms of area and carbon impacts, followed by fire, windthrow and bark beetles, and lastly droughts. Collectively these lead to the gross loss of about 200 Tg C y(-1) in live biomass annually across the conterminous US. At the same time, the net change in forest carbon stocks is positive (190 Tg C y(-1)), indicating not only forest resilience but also an apparently large response to growth enhancements such as fertilization by CO2 and nitrogen. Uncertainty about disturbance legacies, disturbance interactions, likely trends, and global change factors make the future of the US forest carbon sink unclear. While there is scope for management to enhance carbon sinks in US forests, tradeoffs with other values and uses are likely to significantly limit practical implementation. Continued and expanded remote sensing and field-based monitoring capabilities and manipulative experimentation are needed to improve understanding of the US forest carbon sink, and assess how disturbance processes are responding to the pressures of global environmental change. In addition, continued development and application of holistic, decision support tools that consider a range of forest values are needed to enable managers and policy makers to use the best available information for guiding forest resources now and into the future. (C) 2016 Elsevier B.V. All rights reserved.

Terrestrial ecosystems play a significant role in the global carbon cycle and offset a large fraction of anthropogenic CO 2 emissions. The terrestrial carbon sink is increasing, yet the mechanisms responsible for its enhancement, and implications for the growth rate of atmospheric CO 2 , remain unclear. Here using global carbon budget estimates, ground, atmospheric and satellite observations, and multiple global vegetation models, we report a recent pause in the growth rate of atmospheric CO 2 , and a decline in the fraction of anthropogenic emissions that remain in the atmosphere, despite increasing anthropogenic emissions. We attribute the observed decline to increases in the terrestrial sink during the past decade, associated with the effects of rising atmospheric CO 2 on vegetation and the slowdown in the rate of warming on global respiration. The pause in the atmospheric CO 2 growth rate provides further evidence of the roles of CO 2 fertilization and warming-induced respiration, and highlights the need to protect both existing carbon stocks and regions, where the sink is growing rapidly.

The spatial pattern across the continental United States of the interannual variance of warm-season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water-dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, streamflow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent – they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budyko’s hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009.

Warmer conditions over the past two decades have contributed to rapid expansion of bark beetle outbreaks killing millions of trees over a large fraction of western United States ( US ) forests. These outbreaks reduce plant productivity by killing trees and transfer carbon from live to dead pools where carbon is slowly emitted to the atmosphere via heterotrophic respiration which subsequently feeds back to climate change. Recent studies have begun to examine the local impacts of bark beetle outbreaks in individual stands, but the full regional carbon consequences remain undocumented for the western US . In this study, we quantify the regional carbon impacts of the bark beetle outbreaks taking place in western US forests. The work relies on a combination of postdisturbance forest regrowth trajectories derived from forest inventory data and a process‐based carbon cycle model tracking decomposition, as well as aerial detection survey ( ADS ) data documenting the regional extent and severity of recent outbreaks. We find that biomass killed by bark beetle attacks across beetle‐affected areas in western US forests from 2000 to 2009 ranges from 5 to 15 Tg C yr −1 and caused a reduction of net ecosystem productivity ( NEP ) of about 6.1–9.3 Tg C y −1 by 2009. Uncertainties result largely from a lack of detailed surveys of the extent and severity of outbreaks, calling out a need for improved characterization across western US forests. The carbon flux legacy of 2000–2009 outbreaks will continue decades into the future (e.g., 2040–2060) as committed emissions from heterotrophic respiration of beetle‐killed biomass are balanced by forest regrowth and accumulation.

Quantification of biogenic carbon fluxes from agricultural lands is needed to generate comprehensive bottom-up estimates of net carbon exchange for global and regional carbon monitoring. We estimated global agricultural carbon fluxes associated with annual crop net primary production (NPP), harvested biomass, and consumption of biomass by humans and livestock. These estimates were combined for a single estimate of net carbon exchange and spatially distributed to 0.05° resolution usingModerate Resolution Imaging Spectroradiometer satellite land cover data. Global crop NPP in 2011 was estimated at 5.25± 0.46 PgC yr , of which 2.05± 0.05 PgCyr 1 was harvested and 0.54 PgC yr 1 was collected from crop residues for livestock fodder. Total livestock feed intake in 2011 was 2.42± 0.21 PgC yr , of which 2.31± 0.21 PgCyr 1 was emitted as CO2, 0.07± 0.01 PgC yr 1 was emitted as CH4, and 0.04 PgC yr 1 was contained within milk and egg production. Livestock grazed an estimated 1.27 PgC yr 1 in 2011, which constituted 52.4% of total feed intake. Global human food intake was 0.57± 0.03 PgCyr 1 in 2011, the majority of which was respired as CO2. Completed global cropland carbon budgets accounted for the ultimate use of approximately 80% of harvested biomass. The spatial distribution of these fluxes may be used for global carbon monitoring, estimation of regional uncertainty, and for use as input to Earth system models.

Recent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2-D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U. S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U. S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with different models and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.