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The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface and root-zone soil moisture from April 2015 to the present with a mean latency of 2.5 days from the time of observation. The L4_SM algorithm assimilates SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observation-based precipitation. This paper describes and evaluates the use of satellite- and gauge-based precipitation from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products in the L4_SM algorithm beginning with L4_SM Version 6. Specifically, IMERG is used in two ways: (i) The L4_SM precipitation reference climatology is primarily based on IMERG-Final (Version 06B) data, replacing the Global Precipitation Climatology Project Version 2.2 data used in previous L4_SM versions, and (ii) the precipitation forcing outside of North America and the high latitudes is corrected to match the daily totals from IMERG, replacing the gauge-only, daily product or uncorrected weather analysis precipitation used there in earlier L4_SM versions. The use of IMERG precipitation improves the anomaly time series correlation coefficient of L4_SM surface soil moisture (versus independent satellite estimates) by 0.03 in the global average and by up to ∼0.3 in parts of South America, Africa, Australia, and East Asia, where the quality of the gauge-only precipitation product used in earlier L4_SM versions is poor. The improvements also reduce the time series standard deviation of the Tb observation-minus-forecast residuals from 5.5 K in L4_SM Version 5 to 5.1 K in Version 6. Significance Statement: Soil moisture links the land surface water, energy, and carbon cycles. NASA Soil Moisture Active Passive (SMAP) satellite observations and observation-based precipitation data are merged into a numerical model of land surface water and energy balance processes to generate the global, 9-km resolution, 3-hourly Level-4 Soil Moisture (L4_SM) data product. The product is available with ∼2.5-day latency to support Earth science research and applications, such as flood prediction and drought monitoring. We show that a recent L4_SM algorithm update using satellite- and gauge-based precipitation inputs from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products improves the temporal variations in the estimated soil moisture, particularly in otherwise poorly instrumented regions in South America, Africa, Australia, and East Asia. [ABSTRACT FROM AUTHOR]

In the last years, ensemble methods have been widely popular in atmospheric, climate, and ocean dynamics investigations and forecasts as convenient methods to obtain statistical information on these systems. In many cases, ensembles have been used as an approximation to the probability distribution that has acquired more and more a central role, as the importance of a single trajectory, or member, was recognized as less informative. This paper shows that using results from the dynamical systems and more recent results from the machine learning and AI communities, we can arrive at a direct estimation of the probability distribution evolution and also at the formulation of predictor systems based on a nonlinear formulation. The paper introduces the theory and demonstrates its application to two examples. The first is a one-dimensional system based on the Niño-3 index; the second is a multidimensional case based on time series of monthly mean SST in the Pacific. We show that we can construct the probability distribution and set up a system to forecast its evolution and derive various quantities from it. The objective of the paper is not strict realism, but the introduction of these methods and the demonstration that they can be used also in the complex, multidimensional environment typical of atmosphere and ocean applications. [ABSTRACT FROM AUTHOR]

Global dynamical reanalyses of the atmosphere and ocean fundamentally rely on observations, not just for the assimilation (i.e., for the definition of the state of the Earth system components) but also in many other steps along the production chain. Observations are used to constrain the model boundary conditions, for the calibration or uncertainty determination of other observations, and for the evaluation of data products. This requires major efforts, including data rescue (for historical observations), data management (including metadatabases), compilation and quality control, and error estimation. The work on observations ideally occurs one cycle ahead of the generation cycle of reanalyses, allowing the reanalyses to make full use of it. In this paper we describe the activities within ERA-CLIM2, which range from surface, upper-air, and Southern Ocean data rescue to satellite data recalibration and from the generation of snow-cover products to the development of a global station data metadatabase. The project has not produced new data collections. Rather, the data generated has fed into global repositories and will serve future reanalysis projects. The continuation of this effort is first contingent upon the organization of data rescue and also upon a series of targeted research activities to address newly identified in situ and satellite records. [ABSTRACT FROM AUTHOR]

The European Reanalysis of Global Climate Observations 2 (ERA-CLIM2) is a European Union Seventh Framework Project started in January 2014 and due to be completed in December 2017. It aims to produce coupled reanalyses, which are physically consistent datasets describing the evolution of the global atmosphere, ocean, land surface, cryosphere, and the carbon cycle. ERA-CLIM2 has contributed to advancing the capacity for producing state-of-the-art climate reanalyses that extend back to the early twentieth century. ERA-CLIM2 has led to the generation of the first European ensemble of coupled ocean, sea ice, land, and atmosphere reanalyses of the twentieth century. The project has funded work to rescue and prepare observations and to advance the data-assimilation systems required to generate operational reanalyses, such as the ones planned by the European Union Copernicus Climate Change Service. This paper summarizes the main goals of the project, discusses some of its main areas of activities, and presents some of its key results. [ABSTRACT FROM AUTHOR]

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. presented here are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop-specific measurement tool. [ABSTRACT FROM AUTHOR]

The transient climate response to cumulative CO2 emissions (TCRE) is a useful metric of climate warming that directly relates the cause of climate change (cumulative carbon emissions) to the most used index of climate change (global mean near-surface temperature change). In this paper, analytical reasoning is used to investigate why TCRE is near constant over a range of cumulative emissions up to 2000 Pg of carbon. In addition, a climate model of intermediate complexity, forced with a constant flux of CO2 emissions, is used to explore the effect of terrestrial carbon cycle feedback strength on TCRE. The analysis reveals that TCRE emerges from the diminishing radiative forcing from CO2 per unit mass being compensated for by the diminishing ability of the ocean to take up heat and carbon. The relationship is maintained as long as the ocean uptake of carbon, which is simulated to be a function of the CO2 emissions rate, dominates changes in the airborne fraction of carbon. Strong terrestrial carbon cycle feedbacks have a dependence on the rate of carbon emission and, when present, lead to TRCE becoming rate dependent. Despite these feedbacks, TCRE remains roughly constant over the range of the representative concentration pathways and therefore maintains its primary utility as a metric of climate change. [ABSTRACT FROM AUTHOR]

Water scarcity threatens agriculture in California. During the last two decades, historically severe droughts have led to severe water shortages. Under projected changes in climate, droughts of greater severity and duration will exacerbate this situation. California produces 80% of the world's almonds, which require consistent water supplies for irrigation. Almonds are the most commonly grown crop in California, covering nearly 1.4 million acres over about 8,000 farms. In response to these challenges, almond growers are considering a myriad of management strategies to save water and mitigate climate change. The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX) aims to identify water and orchard management opportunities to maximize water use efficiency and carbon sequestration in almonds and other woody perennial tree crops. The project combines satellite, uncrewed aerial vehicles, and proximal sensing technologies to retrieve key variables used to model surface fluxes and biophysical properties. We aim to advance our understanding of water management and cultural practices on water-carbon relationships in tree-perennial agroecosystems. Through new methods, such as evapotranspiration-based irrigation scheduling, even a modest 10% decrease in almond orchard irrigation across the state equates to about a third of the water in Lake Oroville, California's second-largest reservoir, at average levels. From a carbon perspective, almond orchards could sequester 8% of the state's current greenhouse gas emissions by transitioning toward climate-smart practices. As such, the almond industry is uniquely positioned to curb water use and contribute to climate change mitigation while maintaining economic viability of almond production. An overview of initial results related to evapotranspiration observational and modeling uncertainty and carbon sequestration potential are presented in this article. [ABSTRACT FROM AUTHOR]

Carbon uptake by land and ocean as a biogeochemical response to increasing atmospheric CO2 concentration is called concentration-carbon feedback and is one of the carbon cycle feedbacks of the global climate. This feedback can have a major impact on climate projections with an uncertain magnitude. This paper focuses on the concentration-carbon feedback in terrestrial ecosystems, analyzing the mechanisms and strength of the feedback reproduced by Earth system models (ESMs) participating in phase 5 of the Coupled Model Intercomparison Project. It is confirmed that multiple ESMs driven by a common scenario show a large spread of concentration-carbon feedback strength among models. Examining the behavior of the carbon fluxes and pools of the models showed that the sensitivity of plant productivity to elevated CO2 is likely the key to reduce the spread, although increasing CO2 stimulates other carbon cycle processes. Simulations with a single ESM driven by different CO2 pathways demonstrated that carbon accumulation increases in scenarios with slower CO2 increase rates. Using both numerical and analytical approaches, the study showed that the difference among CO2 scenarios is a time lag of terrestrial carbon pools in response to atmospheric CO2 increase-a high rate of CO2 increase results in smaller carbon accumulations than that in an equilibrium state of a given CO2 concentration. These results demonstrate that the current quantities for concentration-carbon feedback are incapable of capturing the feedback dependency on the carbon storage state and suggest that the concentration feedback can be larger for future scenarios where the CO2 growth rate is reduced. [ABSTRACT FROM AUTHOR]

In the context of phase 5 of the Coupled Model Intercomparison Project, most climate simulations use prescribed atmospheric CO2 concentration and therefore do not interactively include the effect of carbon cycle feedbacks. However, the representative concentration pathway 8.5 (RCP8.5) scenario has additionally been run by earth system models with prescribed CO2 emissions. This paper analyzes the climate projections of 11 earth system models (ESMs) that performed both emission-driven and concentration-driven RCP8.5 simulations. When forced by RCP8.5 CO2 emissions, models simulate a large spread in atmospheric CO2; the simulated 2100 concentrations range between 795 and 1145 ppm. Seven out of the 11 ESMs simulate a larger CO2 (on average by 44 ppm, 985 ± 97 ppm by 2100) and hence higher radiative forcing (by 0.25 W m−2) when driven by CO2 emissions than for the concentration-driven scenarios (941 ppm). However, most of these models already overestimate the present-day CO2, with the present-day biases reasonably well correlated with future atmospheric concentrations' departure from the prescribed concentration. The uncertainty in CO2 projections is mainly attributable to uncertainties in the response of the land carbon cycle. As a result of simulated higher CO2 concentrations than in the concentration-driven simulations, temperature projections are generally higher when ESMs are driven with CO2 emissions. Global surface temperature change by 2100 (relative to present day) increased by 3.9° ± 0.9°C for the emission-driven simulations compared to 3.7° ± 0.7°C in the concentration-driven simulations. Although the lower ends are comparable in both sets of simulations, the highest climate projections are significantly warmer in the emission-driven simulations because of stronger carbon cycle feedbacks. [ABSTRACT FROM AUTHOR]

This paper presents a detailed quality assessment of a novel underwater sensor for the measurement of CO2 partial pressure ( pCO2) based on surface water field deployments carried out between 2008 and 2011. The commercially available sensor, which is based on membrane equilibration and nondispersive IR (NDIR) spectrometry is small and can be integrated into mobile platforms. It is calibrated in water against a proven flow-through pCO2 instrument within a custom-built calibration setup. The aspect of highest concern with respect to achievable data quality of the sensor is the compensation for signal drift inevitably connected to absorption measurements. Three means are used to correct for drift effects: (i) a filter correlation or dual-beam setup, (ii) regular zero gas measurements realized automatically within the sensor, and (iii) a zero-based transformation of two sensor calibrations flanking the time of sensor deployment. Three sensors were tested against an underway pCO2 system during two major research cruises, providing an in situ temperature range from 7.4° to 30.1°C and pCO2 values between 289 and 445 μatm. The average difference between sensor and reference pCO2 was found to be −0.6 ±3.0 μatm with an RMSE of 3.7 μatm. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. [ABSTRACT FROM AUTHOR]

Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model-Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north-south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north-south gradient increase due to fossil fuel emissions, but east-west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2-10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations. [ABSTRACT FROM AUTHOR]

This paper presents the fossil fuel-derived CO2 emissions simulated by the Hadley Centre Global Environmental Model, version 2, Earth System (HadGEM2-ES) to be compatible with four representative concentration pathways (RCPs) from 2006 to 2100. For three of the four RCPs, the analysis is extended to 2300. The compatible emissions compare well with those generated by integrated assessment models from which the RCPs were constructed. Historical compatible emissions are also presented, which closely match observation-based estimates from 1860 to 2005 (cumulatively 330 and 319 GtC, respectively). Simulated land and ocean carbon uptake, which determines the compatible emissions, is examined, with an emphasis on changes in vegetation carbon. In addition, historical land and ocean carbon uptake is compared with observations. The influences of climate change and the carbon cycle on compatible emissions are investigated individually through two additional experiments in which either aspect is decoupled from the CO2 pathway. Exposure of the biogeochemical components of the Earth system to increasing CO2 is found to be responsible for 68% of the compatible emissions of the fully coupled simulation, while increased radiative forcing from the CO2 pathway reduces its compatible emissions by 11%. The importance of dynamic vegetation to compatible emissions is investigated and discussed. Two different methods of determining emissions from land use and land-use change are compared; differencing the land-atmosphere CO2 exchange of two experiments, one with fixed land use and the other variable, results in historical land-use emissions within the uncertainty range of observed estimates, while those simulated directly by the model are well below the lower limit of the observations. [ABSTRACT FROM AUTHOR]

Net primary productivity (NPP) is an important component of the carbon cycle and a key indicator of ecosystem performance. The aim of this study is to construct a more accurate regional vegetation NPP estimation model and explore the relationship between NPP and climatic factors (air temperature, rainfall, sunshine hours, relative humidity, air pressure, global radiation, and surface net radiation). As a key variable in NPP modeling, photosynthetically active radiation (PAR) was obtained by finding a linear relationship between PAR and horizontal direct radiation, scattered radiation, and net radiation with high accuracy. The fraction of absorbed photosynthetically active radiation (FPAR) was estimated by enhanced vegetation index (EVI) instead of the widely used normalized difference vegetation index (NDVI). Stress factors of temperature/humidity for different types of vegetation were also considered in the simulation of light use efficiencies (LUE). The authors used EVI datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2011 and geographic information techniques to reveal NPP variations in Wuhan. Time lagged serial correlation analysis was employed to study the delayed and continuous effects of climatic factors on NPP. The results showed that the authors' improved model can simulate vegetation NPP in Wuhan effectively, and it may be adopted or used in other regions of the world that need to be further tested. The results indicated that air temperature and air pressure contributed significantly to the interannual changes of plant NPP while rainfall and global radiation were major climatic factors influencing seasonal NPP variations. A significant positive 32-day lagged correlation was observed between seasonal variation of NPP and rainfall (P , 0.01); the influence of changing climate on NPP lasted for 64 days. The impact of air pressure, global radiation, and net radiation on NPP persisted for 48 days, while the effects of sunshine hours and air temperature on NPP only lasted for 16 and 32 days, respectively. [ABSTRACT FROM AUTHOR]

Projections of greenhouse gas concentrations over the twenty-first century generally rely on two optimistic, but questionable, assumptions about the carbon cycle: 1) that elevated atmospheric CO2 concentrations will enhance terrestrial carbon storage and 2) that plant migration will be fast relative to climate changes. This paper demonstrates that carbon cycle uncertainty is considerably larger than currently recognized and that plausible carbon cycle responses could strongly amplify climate warming. This has important implications for societal decisions that relate to climate change risk management because it implies that a given level of human emissions could result in much larger climate changes than we now realize or that stabilizing atmospheric greenhouse gas concentrations at a 'safe' level could require lower human emissions than currently understood. These results also suggest that terrestrial carbon cycle responses could be sufficiently strong to account for the changes in atmospheric carbon dioxide that occurred during transitions between ice age and interglacial periods. [ABSTRACT FROM AUTHOR]

The dynamic vegetation and carbon cycling component, LM3V, of the Geophysical Fluid Dynamics Laboratory (GFDL) prototype Earth system model (ESM2.1), has been designed to simulate the effects of land use on terrestrial carbon pools, including secondary vegetation regrowth. Because of the long time scales associated with the carbon adjustment, special consideration is required when initializing the ESM when historical simulations are conducted. Starting from an equilibrated, preindustrial climate and potential vegetation state in an offline land-only model (LM3V), estimates of historical land use are instantaneously applied in five experiments beginning in the following calendar years: 1500, 1600, 1700, 1750, and 1800. This application results in the land carbon pools experiencing an abrupt change-a carbon shock-and the secondary vegetation needs time to regrow into consistency with the harvesting history. The authors find that it takes approximately 100 years for the vegetation to recover from the carbon shock, whereas soils take at least 150 years to recover. The vegetation carbon response is driven primarily by land-use history, whereas the soil carbon response is affected by both land-use history and the geographic pattern of soil respiration rates. Based on these results, the authors recommend the application of historical land-use scenarios in 1700 to provide sufficient time for the land carbon in ESMs with secondary vegetation to equilibrate to adequately simulate carbon stores at the start of the historical integrations (i.e., 1860) in a computationally efficient manner. [ABSTRACT FROM AUTHOR]

Scaling up of observed point data to estimate regional carbon fluxes is an important issue in the context of the global terrestrial carbon cycle. In this study, the authors proposed a new model to scale up the eddy covariance data to estimate regional carbon fluxes using satellite-derived data. Gross primary productivity (GPP) and ecosystem respiration (RE) were empirically calculated using the normalized difference vegetation index (NDVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS). First, the model input is evaluated by comparing with the field data, then established and tested the model at the point scale, and then extended it into a regional scale. At the point scale, the empirical model could reproduce the seasonal and interannual variations in the carbon budget of the mature black spruce forests in Alaska and Canada sites, suggesting that seasonality of the NDVI and LST could explain the carbon fluxes and that the model is robust within mature black spruce forests in North America. Regional-scale analysis showed that the total GPP and RE between 2003 and 2006 were 1.76 ± 0.28 and 1.86 ± 0.26 kg CO2 m−2 yr−1, respectively, in mature black spruce forests in Alaska, indicating that these forests were almost carbon neutral. The authors' model analysis shows that the proposed method is effective in scaling up point observations to estimate the regional-scale carbon budget and that the mature black spruce forests increased in sink strength during spring warming and decreased in sink strength during summer and autumn warming. [ABSTRACT FROM AUTHOR]

Uncertainty about biases common across models and about unknown and unmodeled feedbacks is important for the tails of temperature change distributions and thus for climate risk assessments. This paper develops a hierarchical Bayes framework that explicitly represents these and other sources of uncertainty. It then uses models’ estimates of albedo, carbon cycle, cloud, and water vapor–lapse rate feedbacks to generate posterior probability distributions for feedback strength and equilibrium temperature change. The posterior distributions are especially sensitive to prior beliefs about models’ shared structural biases: nonzero probability of shared bias moves some probability mass toward lower values for climate sensitivity even as it thickens the distribution’s positive tail. Obtaining additional models of these feedbacks would not constrain the posterior distributions as much as narrowing prior beliefs about shared biases or, potentially, obtaining feedback estimates having biases uncorrelated with those impacting climate models. Carbon dioxide concentrations may need to fall below current levels to maintain only a 10% chance of exceeding official 2°C limits on global average temperature change. [ABSTRACT FROM AUTHOR]

Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time. [ABSTRACT FROM AUTHOR]

The Amazon rain forest constitutes one of the major global stocks of carbon. Recent studies, including the last Intergovernmental Panel on Climate Change report and the Coupled Climate Carbon Cycle Model Intercomparison Project, have suggested that it may reduce in size and lose biomass during the twenty-first century through a savannization process. A better understanding of how this ecosystem structure, dynamics, and carbon balance may respond to future climate changes is needed. This article investigates how well a fully coupled atmosphere–biosphere model can reproduce vegetation structure and dynamics in Amazonia to the extent permitted by available data. The accurate representation of the coupled climate–biosphere dynamics requires the accurate representation of climate, net primary production (NPP), and its partition among the several carbon pool components. The simulated climate is validated against precipitation (within 5% of four datasets) and incident solar radiation (within 7% of observations). The authors also validate (i) simulated land cover, which reproduces well the observed patterns; (ii) NPP, within 5% of observations; and (iii) respiration rates, within 15% of observations. The performance of simulated variables that depend on carbon allocation, like NPP partitioning, leaf area index, and aboveground live biomass, although good on a regional mean, is significantly low when spatial patterns are considered. These errors may be attributed to fixed carbon allocation and residence time parameters assumed by the model. Carbon allocation apparently varies spatially, and to simulate this spatial variability is quite a challenge. [ABSTRACT FROM AUTHOR]

Eight earth system models of intermediate complexity (EMICs) are used to project climate change commitments for the recent Intergovernmental Panel on Climate Change’s (IPCC’s) Fourth Assessment Report (AR4). Simulations are run until the year 3000 a.d. and extend substantially farther into the future than conceptually similar simulations with atmosphere–ocean general circulation models (AOGCMs) coupled to carbon cycle models. In this paper the following are investigated: 1) the climate change commitment in response to stabilized greenhouse gases and stabilized total radiative forcing, 2) the climate change commitment in response to earlier CO2 emissions, and 3) emission trajectories for profiles leading to the stabilization of atmospheric CO2 and their uncertainties due to carbon cycle processes. Results over the twenty-first century compare reasonably well with results from AOGCMs, and the suite of EMICs proves well suited to complement more complex models. Substantial climate change commitments for sea level rise and global mean surface temperature increase after a stabilization of atmospheric greenhouse gases and radiative forcing in the year 2100 are identified. The additional warming by the year 3000 is 0.6–1.6 K for the low-CO2 IPCC Special Report on Emissions Scenarios (SRES) B1 scenario and 1.3–2.2 K for the high-CO2 SRES A2 scenario. Correspondingly, the post-2100 thermal expansion commitment is 0.3–1.1 m for SRES B1 and 0.5–2.2 m for SRES A2. Sea level continues to rise due to thermal expansion for several centuries after CO2 stabilization. In contrast, surface temperature changes slow down after a century. The meridional overturning circulation is weakened in all EMICs, but recovers to nearly initial values in all but one of the models after centuries for the scenarios considered. Emissions during the twenty-first century continue to impact atmospheric CO2 and climate even at year 3000. All models find that most of the anthropogenic carbon emissions are eventually taken up by the ocean (49%–62%) in year 3000, and that a substantial fraction (15%–28%) is still airborne even 900 yr after carbon emissions have ceased. Future stabilization of atmospheric CO2 and climate change requires a substantial reduction of CO2 emissions below present levels in all EMICs. This reduction needs to be substantially larger if carbon cycle–climate feedbacks are accounted for or if terrestrial CO2 fertilization is not operating. Large differences among EMICs are identified in both the response to increasing atmospheric CO2 and the response to climate change. This highlights the need for improved representations of carbon cycle processes in these models apart from the sensitivity to climate change. Sensitivity simulations with one single EMIC indicate that both carbon cycle and climate sensitivity related uncertainties on projected allowable emissions are substantial. [ABSTRACT FROM AUTHOR]

Northern ecosystems contain much of the global reservoir of terrestrial carbon that is potentially reactive in the context of near-term climate change. Annual variability and recent trends in vegetation productivity across Alaska and northwest Canada were assessed using a satellite remote sensing–based production efficiency model and prognostic simulations of the terrestrial carbon cycle from the Terrestrial Ecosystem Model (TEM) and BIOME–BGC (BioGeoChemical Cycles) model. Evidence of a small, but widespread, positive trend in vegetation gross and net primary production (GPP and NPP) is found for the region from 1982 to 2000, coinciding with summer warming of more than 1.8°C and subsequent relaxation of cold temperature constraints to plant growth. Prognostic model simulation results were generally consistent with the remote sensing record and also indicated that an increase in soil decomposition and plant-available nitrogen with regional warming was partially responsible for the positive productivity response. Despite a positive trend in litter inputs to the soil organic carbon pool, the model results showed evidence of a decline in less labile soil organic carbon, which represents approximately 75% of total carbon storage for the region. These results indicate that the regional carbon cycle may accelerate under a warming climate by increasing the fraction of total carbon storage in vegetation biomass and more rapid turnover of the terrestrial carbon reservoir. [ABSTRACT FROM AUTHOR]

Climate, vegetation cover, and management create finescale heterogeneity in unirrigated agricultural regions, with important but not well-quantified consequences for spatial and temporal variations in surface CO2, water, and heat fluxes. Eddy covariance fluxes were measured in seven agricultural fields—comprising winter wheat, pasture, and sorghum—in the U.S. Southern Great Plains (SGP) during the 2001–03 growing seasons. Land cover was the dominant source of variation in surface fluxes, with 50%–100% differences between fields planted in winter–spring versus fields planted in summer. Interannual variation was driven mainly by precipitation, which varied more than twofold between years. Peak aboveground biomass and growing season net ecosystem exchange (NEE) of CO2 increased in rough proportion to precipitation. Based on a partitioning of gross fluxes with a regression model, ecosystem respiration increased linearly with gross primary production, but with an offset that increased near the time of seed production. Because the regression model was designed for well-watered periods, it successfully retrieved NEE and ecosystem parameters during the peak growing season and identified periods of moisture limitation during the summer. In summary, the effects of crop type, land management, and water limitation on carbon, water, and energy fluxes were large. Capturing the controlling factors in landscape-scale models will be necessary to estimate the ecological feedbacks to climate and other environmental impacts associated with changing human needs for agricultural production of food, fiber, and energy. [ABSTRACT FROM AUTHOR]

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of the conterminous United States over the period 2001–04. Predicted net ecosystem production (NEP) flux for atmospheric CO2 in the United States was estimated as annual net sink of about +0.2 Pg C in 2004. Regional climate patterns were reflected in the predicted annual NEP flux from the model, which showed extensive carbon sinks in ecosystems of the southern and eastern regions in 2003–04, and major carbon source fluxes from ecosystems in the Rocky Mountain and Pacific Northwest regions in 2003–04. As demonstrated through tower site comparisons, net primary production (NPP) modeled with monthly MODIS enhanced vegetation index (EVI) inputs closely resembles both the measured high- and low-season carbon fluxes. Modeling results suggest that the capacity of the NASA Carnegie Ames Stanford Approach (CASA) model to use 8-km resolution MODIS EVI data to predict peak growing season uptake rates of CO2 in irrigated croplands and moist temperate forests is strong. [ABSTRACT FROM AUTHOR]

As part of the Western Arctic Linkage Experiment (WALE), simulations of carbon dynamics in the western Arctic (WALE region) were conducted during two recent decades by driving the Terrestrial Ecosystem Model (TEM) with three alternative climate datasets. Among the three TEM simulations, we compared the mean monthly and interannual variability of three carbon fluxes: 1) net primary production (NPP), 2) heterotrophic respiration (Rh), and 3) net ecosystem production (NEP). Cumulative changes in vegetation, soil, and total carbon storage among the simulations were also compared. This study supports the conclusion that the terrestrial carbon cycle is accelerating in the WALE region, with more rapid turnover of carbon for simulations driven by two of the three climates. The temperature differences among the climate datasets resulted in annual estimates of NPP and Rh that varied by a factor of 2.5 among the simulations. There is much spatial variability in the temporal trends of NPP and Rh across the region in the simulations driven by different climates, and the spatial pattern of trends is quite different among simulations. Thus, this study indicates that the overall response of NEP in simulations with TEM across the WALE region depends substantially on the temporal trends in the climate dataset used to drive the model. Similar to the recommendations of other studies in the WALE project, this study indicates that coupling methodologies should use anomalies of future climate model simulations to alter the climate of more trusted datasets for purposes of driving ecosystem models of carbon dynamics. [ABSTRACT FROM AUTHOR]

A review is presented of soil properties and litter fauna of an experimental site in the Caxiuanã forest, eastern Amazonia, as a contribution to the Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA). This study’s main scientific goal is to compare some biogeochemical soil properties of an undisturbed forest ecosystem with those of an experimental (1 ha) plot in which rainfall was artificially excluded to simulate drought [the Efeitos da Seca da Floresta (ESECAFLOR) experiment]. A second scientific objective is to investigate the space variability of soil profile characteristics in the experimental sites, particularly organic carbon concentration, moisture, and texture. It is expected that such soil property variability influences greatly the distribution of several biological species such as spiders. To investigate such effects in the litter spider community, we applied percentual complementarity and Simpson diversity index to available data. Our results suggest that a faunal transition was under way in the treatment plot, shifting from a rich and even community to a less diverse one. [ABSTRACT FROM AUTHOR]

Seventeen years (1982?98) of net carbon flux predictions from a simulation model based on satellite observations of monthly vegetation cover have been analyzed. The NASA-CASA model was driven by vegetation cover properties derived from the Advanced Very High Resolution Radiometer and radiative transfer algorithms that were developed for the Moderate Resolution Imaging Spectroradiometer (MODIS). It is found that although the terrestrial ecosystem sink for atmospheric CO[sub2] on the North American continent has been fairly consistent at between +0.2 and +0.3 Pg C yr[sup-1], high interannual variability in net ecosystem production (NEP) fluxes can be readily identified at locations across the continent. Five major areas having the highest variability were detected: 1) along the extreme northern vegetated zones of Canada and Alaska, 2) the northern Rocky Mountains, 3) the central-western U.S. Great Plains and central farming region, 4) across the southern United States and Mexico, and 5) in coastal forest areas of the United States and Canada. Analysis of climate anomalies over this 17-yr time period suggests that variability in precipitation and surface solar irradiance could be associated with trends in carbon sink fluxes within regions of high NEP variability. [ABSTRACT FROM AUTHOR]

Tipping points in the Earth system describe critical thresholds beyond which a single component, part of the system, or the system as a whole changes from one stable state to another. In the present-day Southern Ocean, the Weddell Sea constitutes an important dense-water formation site, associated with efficient deep-ocean carbon and oxygen transfer and low ice-shelf basal melt rates. Here, a regime shift will occur when continental shelves are continuously flushed with warm, oxygen-poor offshore waters from intermediate depth, leading to less efficient deep-ocean carbon and oxygen transfer and higher ice-shelf basal melt rates. We use a global ocean–biogeochemistry model including ice-shelf cavities and an eddy-permitting grid in the southern Weddell Sea to address the susceptibility of this region to such a system change for four twenty-first-century emission scenarios. Assessing the projected changes in shelf–open-ocean density gradients, bottom-water properties, and on-shelf heat transport, our results indicate that the Weddell Sea undergoes a regime shift by 2100 in the highest-emission scenario, SSP5–8.5, but not yet in the lower-emission scenarios. The regime shift is imminent by 2100 in the scenarios SSP3–7.0 and SSP2–4.5, but avoidable under the lowest-emission scenario SSP1–2.6. While shelf-bottom waters freshen and acidify everywhere, bottom waters in the Filchner Trough undergo accelerated warming and deoxygenation following the system change, with implications for local ecosystems and ice-shelf basal melt. Additionally, deep-ocean carbon and oxygen transfer decline, implying that the local changes ultimately affect ocean circulation, climate, and ecosystems globally. [ABSTRACT FROM AUTHOR]

For modern Earth, the annual-mean equatorial winds in the upper troposphere are flowing from east to west (i.e., easterly winds). This is mainly due to the deceleration effect of the seasonal cross-equatorial Hadley cells, against the relatively weaker acceleration effect of coupled Rossby and Kelvin waves excited from tropical convection and latent heat release. In this work, we examine the evolution of equatorial winds during the past 250 million years using one global Earth system model, the Community Earth System Model version 1.2.2 (CESM1.2.2). Three climatic factors different from the modern Earth—solar constant, atmospheric CO2 concentration, and land–sea configuration—are considered in the simulations. We find that the upper-tropospheric equatorial winds change sign to westerly flows (called equatorial superrotation) in certain eras, such as 250–230 and 150–50 Ma. The strength of the superrotation is below 4 m s−1, comparable to the magnitude of the present-day easterly winds. In general, this phenomenon occurs in a warmer climate within which the tropical atmospheric circulation shifts upward in altitude, stationary and/or transient eddies are relatively stronger, and/or the Hadley cells are relatively weaker, which in turn are due to the changes of the three factors, especially CO2 concentration and land–sea configuration. [ABSTRACT FROM AUTHOR]

Multiple stable equilibria are intrinsic to many complex dynamical systems, and have been identified in a hierarchy of climate models. Motivated by the idea that the Quaternary glacial–interglacial cycles could have resulted from orbitally forced transitions between multiple stable states mediated by internal feedbacks, this study investigates the existence and mechanisms of multiple equilibria in an idealized, energy-conserving atmosphere–ocean–sea ice general circulation model with a fully coupled carbon cycle. Four stable climates are found for identical insolation and global carbon inventory: an ice-free Warm climate, two intermediate climates (Cold and Waterbelt), and a fully ice-covered Snowball climate. A fifth state, a small ice cap state between Warm and Cold, is found to be barely unstable. Using custom radiative kernels and a thorough sampling of the model's internal variability, three equilibria are investigated through the state dependence of radiative feedback processes. For fast feedbacks, the systematic decrease in surface albedo feedback from Cold to Warm states is offset by a similar increase in longwave water vapor feedback. At longer time scales, the key role of the carbon cycle is a dramatic lengthening of the adjustment time comparable to orbital forcings near the Warm state. The dynamics of the coupled climate–carbon system are thus not well separated in time from orbital forcings, raising interesting possibilities for nonlinear triggers for large climate changes. Significance Statement: How do carbon cycle and other physical processes affect the physical and mathematical properties of the climate system? We use a complex climate model coupled with a carbon cycle to simulate the climate evolution under different initial conditions. Four stable climate states are possible, from the Snowball Earth, in which ice covers the whole planet, to the Warm state, an ice-free world. The carbon cycle drives the global climate change at an extremely slower pace after sea ice retreats. Sea ice and water vapor, on the other hand, constitute the major contributing factors that accelerate faster climate change. [ABSTRACT FROM AUTHOR]

The spatial and temporal variations in terrestrial carbon storage play a pivotal role in regulating future climate change. However, Earth system models (ESMs), which have coupled the terrestrial biosphere and atmosphere, show great uncertainty in simulating the global land carbon storage. Here, based on multiple global datasets and a traceability analysis, we diagnosed the uncertainty source of terrestrial carbon storage in 22 ESMs that participated in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). The modeled global terrestrial carbon storage has converged among ESMs from CMIP5 (1936.9 ± 739.3 PgC) to CMIP6 (1774.4 ± 439.0 PgC) but is persistently lower than the observation-based estimates (2285 ± 669 PgC). By further decomposing terrestrial carbon storage into net primary production (NPP) and ecosystem carbon residence time (τE), we found that the decreased intermodel spread in land carbon storage primarily resulted from more accurate simulations on NPP among ESMs from CMIP5 to CMIP6. The persistent underestimation of land carbon storage was caused by the biased τE. In CMIP5 and CMIP6, the modeled τE was far shorter than the observation-based estimates. The potential reasons for the biased τE could be the lack of or incomplete representation of nutrient limitation, vertical soil biogeochemistry, and the permafrost carbon cycle. Moreover, the modeled τE became the key driver for the intermodel spread in global land carbon storage in CMIP6. Overall, our study indicates that CMIP6 models have greatly improved the terrestrial carbon cycle, with a decreased model spread in global terrestrial carbon storage and less uncertain productivity. However, more efforts are needed to understand and reduce the persistent data-model disagreement on carbon storage and residence time in the terrestrial biosphere. [ABSTRACT FROM AUTHOR]

Large-scale changes in the state of the land surface affect the circulation of the atmosphere and the structure and function of ecosystems alike. As global temperatures increase and regional climates change, the timing of key plant phenophase changes are likely to shift as well. Here we evaluate a suite of phenometrics designed to facilitate an "apples to apples" comparison between remote sensing products and climate model output. Specifically, we derive day-of-year (DOY) thresholds of leaf area index (LAI) from both remote sensing and the Community Land Model (CLM) over the Northern Hemisphere. This systematic approach to comparing phenologically relevant variables reveals appreciable differences in both LAI seasonal cycle and spring onset timing between model simulated phenology and satellite records. For example, phenological spring onset in the model occurs on average 30 days later than observed, especially for evergreen plant functional types. The disagreement in phenology can result in a mean bias of approximately 5% of the total estimated Northern Hemisphere NPP. Further, while the more recent version of CLM (v5.0) exhibits seasonal mean LAI values that are in closer agreement with satellite data than its predecessor (CLM4.5), LAI seasonal cycles in CLM5.0 exhibit poorer agreement. Therefore, despite broad improvements for a range of states and fluxes from CLM4.5 to CLM5.0, degradation of plant phenology occurs in CLM5.0. Therefore, any coupling between the land surface and the atmosphere that depends on vegetation state might not be fully captured by the existing generation of the model. We also discuss several avenues for improving the fidelity between observations and model simulations. [ABSTRACT FROM AUTHOR]

NASA's Student Airborne Research Program (SARP) has completed 13 years of airborne student research since its inception in 2009. The 8-week summer internship program provides students, typically rising undergraduate seniors, with an opportunity to get hands-on experience in making Earth system measurements using NASA's airborne science platforms. Students also make complementary surface-based measurements, analyze airborne and surface data in the context of related data (e.g. coincident satellite measurements or prior-year SARP data), and present results to peers, program leadership, agency management, and the community. The program splits its time between the NASA Armstrong flight facility in Palmdale, California, and the University of California, Irvine. It is implemented with participation of faculty advisors (who provide many of the instruments used) and graduate student mentors, under the overall leadership of the NASA Earth Science Division. Disciplinary foci include atmospheric gases and aerosols, ocean biology, and terrestrial ecology using both in situ and remote sensing instruments. Students are also taken on site visits to nearby laboratories and facilities and attend lectures from visiting faculty and NASA agency personnel. The program engages approximately 30 students per year, with overall approximate gender balance. The program has a high rate of STEM retention, and its alumni are actively engaged in graduate and postgraduate programs in Earth system science and other disciplines. A summary of scientific and programmatic outcomes and a description of how the program has evolved will be presented. [ABSTRACT FROM AUTHOR]

It is increasingly evident that climate sustainability depends not only on societal actions and responses, but also on ecosystem functioning and responses. The capacity of global ecosystems to provide services such as sequestering carbon and regulating hydrology is being strongly reduced both by climate change itself and by unprecedented rates of ecosystem degradation. These services rely on functional aspects of ecosystems that are causally linked—the same ecosystem components that efficiently sequester and store carbon also regulate hydrology by sequestering and storing water. This means that climate change adaptation and mitigation must involve not only preparing for a future with temperature and precipitation anomalies, but also actively minimizing climate hazards and risks by conserving and managing ecosystems and their fundamental supporting and regulating ecosystem services. We summarize general climate–nature feedback processes relating to carbon and water cycling on a broad global scale before focusing on Norway to exemplify the crucial role of ecosystem regulatory services for both carbon sequestration and hydrological processes and the common neglect of this ecosystem–climate link in policy and landscape management. We argue that a key instrument for both climate change mitigation and adaptation policy is to take advantage of the climate buffering and regulative abilities of a well-functioning natural ecosystem. This will enable shared benefits to nature, climate, and human well-being. To meet the global climate and nature crises, we must capitalize on the importance of nature for buffering climate change effects, combat short-term perspectives and the discounting of future costs, and maintain or even strengthen whole-ecosystem functioning at the landscape level. Significance Statement: Natural ecosystems such as forests, wetlands, and heaths are key for the cycling and storage of water and carbon. Preserving these systems is essential for climate mitigation and adaptation and will also secure biodiversity and associated ecosystem services. Systematic failure to recognize the links between nature and human well-being underlies the current trend of accelerating loss of nature and thereby nature's ability to buffer climate changes and their impacts. Society needs a new perspective on spatial planning that values nature as a sink and store of carbon and a regulator of hydrological processes, as well as for its biodiversity. We need policies that fully encompass the role of nature in preventing climate-induced disasters, along with many other benefits for human well-being. [ABSTRACT FROM AUTHOR]

Wetlands are an important natural source of methane to theatmosphere. The amounts of methane emitted from inundated ecosystems in the United States can vary greatly from area to area. Seasonal temperature, water table dynamics, and carbon content of soils are principal controlling factors. To calculate the effect of wetlands (and their potential conversion to other land uses) on global greenhouse gas emissions, information on area covered by various wetland types is needed, along with verified projections of spatial variation in net methane emissions. Both of these variables are poorly known, and estimates are largely unavailable at the country level. Nationwide satellite datasets for the coterminous United States (excluding Alaska) have been combined with ecosystem model predictions of monthly net carbon exchange with the atmosphere to produce the first detailed mapping of methane fluxes from natural wetlands on a monthly and annual basis. The Carnegie¿Ames¿Stanford Approach (CASA) model¿s predicted mean emission flux of methane from wetlands of the continental United States totaled 5.5 Tg CH4 per year. Ranked in terms of total annual flux, the 10 states with the highest predicted emissions (not considering Alaska) are all located in the Great Lakes region and the southern coastal regions of the country. [ABSTRACT FROM AUTHOR]

Anthropogenic CO2-emission-induced feedbacks between the carbon cycle and the climate system perturb the efficiency of atmospheric CO2 uptake by land and ocean carbon reservoirs. The Southern Ocean is a region where these feedbacks can be largest and differ most among Earth system model projections of twenty-first-century climate change. To improve our mechanistic understanding of these feedbacks, we develop an automated procedure that tracks changes in the positions of Southern Ocean water masses and their carbon uptake. In an idealized ensemble of climate change projections, we diagnose two carbon–concentration feedbacks driven by atmospheric CO2 (due to increasing air–sea CO2 partial pressure difference, dpCO2, and reducing carbonate buffering capacity) and two carbon–climate feedbacks driven by climate change (due to changes in the water mass surface outcrop areas and local climate impacts). Collectively these feedbacks increase the CO2 uptake by the Southern Ocean and account for almost one-fourth of the global uptake of CO2 emissions. The increase in CO2 uptake is primarily dpCO2 driven, with Antarctic Intermediate Waters making the largest contribution; the remaining three feedbacks partially offset this increase (by ~25%), with maximum reductions in Subantarctic Mode Waters. The process dominating the decrease in CO2 uptake is water mass dependent: reduction in carbonate buffering capacity in Subtropical and Subantarctic Mode Waters, local climate impacts in Antarctic Intermediate Waters, and reduction in outcrop areas in Circumpolar Deep Waters and Antarctic Bottom Waters. Intermodel variability in the feedbacks is predominately dpCO2 driven and should be a focus of efforts to constrain projection uncertainty. [ABSTRACT FROM AUTHOR]

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts. [ABSTRACT FROM AUTHOR]

We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs' diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs' CO2 concentration pathways were constructed; the simpler IAMs' emissions lie within the ESMs' spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs' FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models' ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two. [ABSTRACT FROM AUTHOR]

The Global Land Surface Satellite (GLASS) product suite currently contains 12 products, including leaf area index, fraction of absorbed photosynthetically active radiation, fraction of green vegetation coverage, gross primary production, broadband albedo, broadband longwave emissivity, downward shortwave radiation and photosynthetically active radiation, land surface temperature, downward and upwelling thermal radiation, all-wave net radiation, and evapotranspiration. These products are generated from the Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer satellite data. Their unique features include long-term temporal coverage (many from 1981 to the present), high spatial resolutions of the surface radiation products (1 km and 0.05°), spatial continuities without missing pixels, and high quality and accuracy based on extensive validation using in situ measurements and intercomparisons with other existing satellite products. Moreover, the GLASS products are based on robust algorithms that have been published in peer-reviewed literature. Herein, we provide an overview of the algorithm development, product characteristics, and some preliminary applications of these products. We also describe the next steps, such as improving the existing GLASS products, generating more climate data records (CDRs), broadening product dissemination, and fostering their wider utilization. The GLASS products are freely available to the public. [ABSTRACT FROM AUTHOR]

Increasing concentrations of CO2 in the atmosphere influence climate both through CO2's role as a greenhouse gas and through its impact on plants. Plants respond to atmospheric CO2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded inmost Earth systemmodels, and a robust literature demonstrates that they can affect global-scale temperature.However, the physiological contribution to transient warming has yet to be assessed systematically in Earth system models. Here this gap is addressed using carbon cycle simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-yr window centered on the time of CO2 doubling relative to preindustrial CO2 concentrations. In CMIP6 models, the physiological effect contributes 0.128C (σ: 0.09°C; range: 0.02°-0.29°C) of warming to the TCR, corresponding to 6.1%of the full TCR (σ: 3.8%; range: 1.4%-13.9%).Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the intermodel spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO2-forced warming-and the intermodel spread in warming-occurs over land, especially in forested regions. [ABSTRACT FROM AUTHOR]

Where does the carbon released by burning fossil fuels go? Currently, ocean and land systems remove about half of the CO2 emitted by human activities; the remainder stays in the atmosphere. These removal processes are sensitive to feedbacks in the energy, carbon, and water cycles that will change in the future. Observing how much carbon is taken up on land through photosynthesis is complicated because carbon is simultaneously respired by plants, animals, and microbes. Global observations from satellites and air samples suggest that natural ecosystems take up about as much CO2 as they emit. To match the data, our land models generate imaginary Earths where carbon uptake and respiration are roughly balanced, but the absolute quantities of carbon being exchanged vary widely. Getting the magnitude of the flux is essential to make sure our models are capturing the right pattern for the right reasons. Combining two cutting-edge tools, carbonyl sulfide (OCS) and solar-induced fluorescence (SIF), will help develop an independent answer of how much carbon is being taken up by global ecosystems. Photosynthesis requires CO2, light, and water. OCS provides a spatially and temporally integrated picture of the "front door" of photosynthesis, proportional to CO2 uptake and water loss through plant stomata. SIF provides a high-resolution snapshot of the "side door," scaling with the light captured by leaves. These two independent pieces of information help us understand plant water and carbon exchange. A coordinated effort to generate SIF and OCS data through satellite, airborne, and ground observations will improve our process-based models to predict how these cycles will change in the future. [ABSTRACT FROM AUTHOR]

Current carbon measurement strategies leave spatiotemporal gaps that hinder the scientific understanding of the oceanic carbon biogeochemical cycle. Data products and models are subject to bias because they rely on data that inadequately capture mesoscale spatiotemporal (kilometers and days to weeks) changes. Highresolution measurement strategies need to be implemented to adequately evaluate the global ocean carbon cycle. To augment the spatial and temporal coverage of ocean-atmosphere carbon measurements, an Autonomous Surface Vehicle CO2 (ASVCO2) system was developed. From 2011 to 2018, ASVCO2 systems were deployed on seven Wave Glider and Saildrone missions along the U.S. Pacific and Australia's Tasmanian coastlines and in the tropical Pacific Ocean to evaluate the viability of the sensors and their applicability to carbon cycle research. Here we illustrate that the ASVCO2 systems are capable of long-term oceanic deployment and robust collection of air and seawater pCO2 within ±2 µatm based on comparisons with established shipboard underway systems, with previously described Moored Autonomous pCO2 (MAPCO2) systems, and with companion ASVCO2 systems deployed side by side. [ABSTRACT FROM AUTHOR]

Under the Paris Agreement (PA), progress of emission reduction efforts is tracked on the basis of regular updates to national greenhouse gas (GHG) inventories, referred to as bottomup estimates. However, only top-down atmospheric measurements can provide observation-based evidence of emission trends. Today, there is no internationally agreed, operational capacity to monitor anthropogenic GHG emission trends using atmospheric measurements to complement national bottom-up inventories. The European Commission (EC), the European Space Agency, the European Centre for Medium-Range Weather Forecasts, the European Organisation for the Exploitation of Meteorological Satellites, and international experts are joining forces to develop such an operational capacity for monitoring anthropogenic CO2 emissions as a new CO2 service under the EC's Copernicus program. Design studies have been used to translate identified needs into defined requirements and functionalities of this anthropogenic CO2 emissions Monitoring and Verification Support (CO2MVS) capacity. It adopts a holistic view and includes components such as atmospheric spaceborne and in situ measurements, bottom-up CO2 emission maps, improved modeling of the carbon cycle, an operational data-assimilation system integrating top-down and bottom-up information, and a policy-relevant decision support tool. The CO2MVS capacity with operational capabilities by 2026 is expected to visualize regular updates of global CO2 emissions, likely at 0.05° x 0.05°. This will complement the PA's enhanced transparency framework, providing actionable information on anthropogenic CO2 emissions that are the main driver of climate change. This information will be available to all stakeholders, including governments and citizens, allowing them to reflect on trends and effectiveness of reduction measures. The new EC gave the green light to pass the CO2MVS from exploratory to implementing phase. [ABSTRACT FROM AUTHOR]

Given their high carbon uptake, the terrestrial ecosystems in the East Asia summer monsoon (EASM) region play an irreplaceable role in the global carbon cycle. Because the rich vegetation growth over East Asia benefits mainly from the sufficient water supply brought by the EASM, which is characterized by a strong intraseasonal oscillation (ISO), the intraseasonal spatiotemporal variations and underlying drivers of photosynthesis activity over East Asia have been comprehensively investigated using the daily gross primary productivity (GPP) and meteorological data. Strong intraseasonal fluctuations of GPP have been identified over the area between the Yangtze and Yellow Rivers (YYR) with a magnitude of 0.4 gC m−2 day−1. The mean power spectrum suggests that 20–50-day variation is the major component of the intraseasonal GPP anomalies over the YYR during the summers of 1980–2013. The 20–50-day ISO of YYR GPP anomalies is modulated by the local 20–50-day precipitation variation via soil moisture, with precipitation (soil moisture) leading GPP by 10 (7) days. The 20–50-day YYR precipitation anomalies are in turn controlled by tropical ISO signals, particularly the convective activity over the western North Pacific. This leading relationship between the 20–50-day atmospheric ISO and GPP suggests a potential for extended-range predictability of vegetation growth. [ABSTRACT FROM AUTHOR]

Aerosols alter Earth's radiative budget both directly and indirectly through interaction with clouds. Continuous observations are required to reduce the uncertainties in climate models associated with atmospheric processing and the interactions between aerosols and clouds. Field observations of aerosols are a central component of the Atmospheric Radiation Measurement (ARM) Facility's global measurements. The ARMmission goal is to ''provide the climate research community with strategically located in situ and remote sensing observatories designed to improve the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their interactions and coupling with the Earth's surface.'' Since 1996, ARM has met this goal by operating Aerosol Observing Systems (AOS) for in situ measurement of aerosols. Currently the five ARM AOSs are the most comprehensive field deployable aerosol systems in the United States. The AOS suite includes seven measurement classes: number concentration, size distribution, chemical composition, radiative and optical properties, hygroscopicity, trace gases, and supporting meteorological conditions. AOSs are designed as standardized measurement platforms to enable intercomparison across the ARM Facility for regional process studies within a global context. The instrumentation and measurement capabilities of the ARMAOSs, along with a history of their design and field deployments are presented here. [ABSTRACT FROM AUTHOR]

Carbon balance of terrestrial ecosystems in the northern high latitudes (NHL) is sensitive to climate change. It remains uncertain whether current regional carbon uptake capacity can be sustained under future warming. Here the atmospheric CO2 drawdown rate (CDR) between 1974 and 2014, defined as the CO2 decrease in ppm over the number of days in spring or summer, is estimated using atmospheric CO2 observations at Barrow (now known as Utqiaġvik), Alaska. We found that the sensitivity of CDR to interannual seasonal air temperature anomalies has trended toward less carbon uptake for a given amount of warming over this period. Changes in interannual temperature sensitivity of CDR suggest that relatively warm springs now result in less of a carbon uptake enhancement. Similarly, relatively warm summers now result in greater carbon release. These results generally agree with the sensitivity of net carbon exchange (NCE) estimated by atmospheric CO2 inversion. When NCE was aggregated over North America (NA) and Eurasia (EA), separately, the temperature sensitivity of NCE in NA has changed more than in EA. To explore potential mechanisms of this signal, we also examine trends in interannual variability of other climate variables (soil temperature and precipitation), satellite-derived gross primary production (GPP), and Trends in Net Land–Atmosphere Carbon Exchanges (TRENDY) model ensemble results. Our analysis suggests that the weakened spring sensitivity of CDR may be related to the slowdown in seasonal soil thawing rate, while the summer sensitivity change may be caused by the temporally coincident decrease in temperature sensitivity of photosynthesis. This study suggests that the current NHL carbon sink may become unsustainable as temperatures warm further. We also found that current carbon cycle models do not represent the decrease in temperature sensitivity of net carbon flux. We argue that current carbon–climate models misrepresent important aspect of the carbon–climate feedback and bias the estimation of warming influence on NHL carbon balance. [ABSTRACT FROM AUTHOR]

The Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration's (NASA) next investment in satellite ocean color and the study of Earth's ocean–atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth's biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean–atmosphere–land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products. [ABSTRACT FROM AUTHOR]

The surface warming response to carbon emissions is affected by how the ocean sequesters excess heat and carbon supplied to the climate system. This ocean uptake involves the ventilation mechanism, where heat and carbon are taken up by the mixed layer and transferred to the thermocline and deep ocean. The effect of ocean ventilation on the surface warming response to carbon emissions is explored using simplified conceptual models of the atmosphere and ocean with and without explicit representation of the meridional overturning. Sensitivity experiments are conducted to investigate the effects of (i) mixed layer thickness, (ii) rate of ventilation of the ocean interior, (iii) strength of the meridional overturning, and (iv) extent of subduction in the Southern Ocean. Our diagnostics focus on a climate metric, the transient climate response to carbon emissions (TCRE), defined by the ratio of surface warming to the cumulative carbon emissions, which may be expressed in terms of separate thermal and carbon contributions. The variability in the thermal contribution due to changes in ocean ventilation dominates the variability in the TCRE on time scales from years to centuries, while that of the carbon contribution dominates on time scales from centuries to millennia. These ventilated controls are primarily from changes in the mixed layer thickness on decadal time scales, and in the rate of ventilated transfer from the mixed layer to the thermocline and deep ocean on centennial and millennial time scales, which is itself affected by the strength of the meridional overturning and extent of subduction in the Southern Ocean. [ABSTRACT FROM AUTHOR]

Interannual variability of air–sea CO2 exchange is an important metric that represents the interaction between the carbon cycle and climate change. Although previous studies report a large bias in the CO2 flux interannual variability in many Earth system models (ESMs), the reason for this bias remains unclear. In this study, the performance of ESMs in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is assessed in the context of the variability of air–sea CO2 flux over the tropical Pacific related to El Niño–Southern Oscillation (ENSO) using an emission-driven historical experiment. Using empirical orthogonal function (EOF) analysis, the first principal component of air–sea CO2 flux shows a significant relationship with the Niño-3.4 index in both the observation-based product and models. In the observation-based product, the spatial pattern of EOF1 shows negative anomalies in the central Pacific, which is, however, in contrast to those in several ESMs, and even opposite in sign to those in HadGEM2-ES and MPI-ESM-LR. The unrealistic response of the air–sea CO2 flux to ENSO mainly originates from the biases in the anomalous surface-water CO2 partial pressure (). A linear Taylor expansion by decomposing the anomalous into contributions from salinity, sea surface temperature, dissolved inorganic carbon (DIC), and alkalinity is applied to diagnose the biases. The results show that decreased during El Niño results from reduced upwelling of high-concentration DIC from deeper layers that overwhelms the increasing caused by warmer sea surface temperature. Overly weak reduction of vertical motion during El Niño and weak vertical gradients of climatological DIC concentration are the main reasons for biases in the negative surface DIC anomalies and eventually the anomalies. This study highlights the importance of both physical ocean responses to El Niño and climatological distributions of carbon-related tracers in the simulation of the interannual variability of air–sea CO2 fluxes. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is an important driver of climate and carbon cycle variability in the Amazon. Sea surface temperature (SST) anomalies in the equatorial Pacific drive teleconnections with temperature directly through changes in atmospheric circulation. These circulation changes also impact precipitation and, consequently, soil moisture, enabling additional indirect effects on temperature through land–atmosphere coupling. To separate the direct influence of ENSO SST anomalies from the indirect effects of soil moisture, a mechanism-denial experiment was performed to decouple their variability in the Energy Exascale Earth System Model (E3SM) forced with observed SSTs from 1982 to 2016. Soil moisture variability was found to amplify and extend the effects of SST forcing on eastern Amazon temperature and carbon fluxes in E3SM. During the wet season, the direct, circulation-driven effect of ENSO SST anomalies dominated temperature and carbon cycle variability throughout the Amazon. During the following dry season, after ENSO SST anomalies had dissipated, soil moisture variability became the dominant driver in the east, explaining 67%–82% of the temperature difference between El Niño and La Niña years, and 85%–91% of the difference in carbon fluxes. These results highlight the need to consider the interdependence between temperature and hydrology when attributing the relative contributions of these factors to interannual variability in the terrestrial carbon cycle. Specifically, when offline models are forced with observations or reanalysis, the contribution of temperature may be overestimated when its own variability is modulated by hydrology via land–atmosphere coupling. [ABSTRACT FROM AUTHOR]