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For this quantification, we use long-term measurements of CO 2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature.
The results help us to understand the mechanisms of CO 2 exchange. The estimate of monthly emission budgets is largely improved in high emitting regions.
The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO 2 emissions.
Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. Chini, Philippe Ciais, Catherine E.
Houghton, Christopher W. Monteiro, David R. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu. The Global Carbon Budget describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties.
It is the 12th annual update and the 6th published in this journal. Gerard Spain, and Christophe Ampe. Urbanized and industrialized areas are the largest source of fossil CO 2.
This work analyses the atmospheric CO 2 variability observed from the first in situ network deployed in the Paris megacity area.
Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO 2 records.
Koch, and Martin Heimann. Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon—Cerrado border, followed by nutrient limitation and interannual climate variability.
The accurate representation of the transition is important for understanding the savannization of the Amazon. This study assesses the potential of space-borne imagery of CO 2 atmospheric concentrations for monitoring the emissions from the Paris area.
Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO 2 emissions for urban areas with CO 2 observations from satellites, and calls for more technological innovations in the remote sensing of CO 2 and in the models that exploit it.
Ivar R. Miller, Michiel K. Tans, Bruce H. Vaughn, James W. White, Kevin Schaefer, and Wouter Peters. This study highlights the importance of improving the representation of the biosphere in carbon—climate models, in particular in a world where droughts become more extreme and more frequent.
Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes.
These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module.
We quantified in detail the P budgets in agricultural systems and PUE on global, regional, and national scales from to Globally, half of the total P inputs into agricultural systems accumulated in agricultural soils, with the rest lost to bodies of water.
There are great differences in P budgets and PUE in agricultural systems on global, regional, and national scales. International trade played a significant role in P redistribution and P in fertilizer and food among countries.
The year appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since according to satellite observation, but the atmospheric CO 2 growth rate is also the highest since Liu, Julia E.
We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models.
Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies. Sterk, Arjan Hensen, and Wouter Peters.
In this research we examined the use of different models to simulate CO 2 concentrations in and around urban areas. We find that in the presence of large stack emissions in a gridded model is insufficient to represent the small dimensions of the CO 2 plumes.
A plume model improves this representation up to 10—14 km from the stack. Better model results can improve the estimate of CO 2 emissions from urban areas and assist in identifying efficient emission reduction policies.
Andreas Krause, Thomas A. Pugh, Anita D. Bayer, Jonathan C. Many climate change mitigation scenarios require negative emissions from land management.
However, environmental side effects are often not considered. Here, we use projections of future land use from two land-use models as input to a vegetation model.
We show that carbon removal via bioenergy production or forest maintenance and expansion affect a range of ecosystem functions. Largest impacts are found for crop production, nitrogen losses, and emissions of biogenic volatile organic compounds.
Hutley, Gabriel Abramowitz, Martin G. This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems.
We provide a particular focus on three dynamic processes phenology, root-water access, and fire that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models.
We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Daniel S. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition.
However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.
Calibration of terrestrial ecosystem models TEMs is important but challenging. This study applies an advanced sampling technique for parameter estimation of a TEM.
The results improve the model fit and predictive performance. We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Consistencies and discrepancies in the temporal and spatial patterns and in the climatic and physiological controls of the inter-annual variability were investigated for the three data sources.
Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate.
We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing.
We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches.
The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.
Ingrid T. Masarie, Maarten C. Krol, and Wouter Peters. We present and document CTDAS and demonstrate its ability to estimate global carbon sources and sinks.
We present the latest CTE results including the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans.
The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales.
Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.
Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates.
Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa.
We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.
The present study 1 evaluates land—atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and 2 refines the model ensemble using a land—atmosphere coupling diagnostic as constraint.
Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season moisture-limited climate regimes in midlatitude regions.
This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble. Land-use change is still overly simplistically implemented in global ecosystem and climate models.
We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models.
We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use—climate interactions and feedback.
Goll, Alexander J. The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate.
In the model JSBACH carbon—nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect.
The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model. The inverse modelling approach for estimating surface fluxes is based on transport models that have an imperfect representation of atmospheric processes like vertical mixing.
In this paper, we show how assimilating commercial aircraft-based vertical profiles of CO 2 into inverse models can help reduce error due to the transport model, thus providing more accurate estimates of surface fluxes.
Further, the reduction in flux uncertainty due to aircraft profiles from the IAGOS project is quantified. Modelling seasonal cycle at the coniferous forests poses a challenge.
It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region. SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.
The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere MOPITT satellite retrievals and surface in-situ measurements.
Rabin, Joe R. Ward, Chao Yue, Vivek K. Kelley, I. Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include.
A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance.
It also includes equations for all models. Surface ozone harms vegetation, which can influence not only climate but also ozone air quality itself.
We implement a scheme for ozone damage on vegetation into an Earth system model, so that for the first time simulated vegetation and ozone can coevolve in a fully coupled simulation.
Reduced dry deposition and enhanced isoprene emission contribute to most of these increases. Bayer, Mats Lindeskog, Thomas A. Pugh, Peter M.
Anthoni, Richard Fuchs, and Almut Arneth. We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model.
Different historical reconstructions yielded an uncertainty of ca. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level tropical shifting cultivation substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.
Otto, and Markus Reichstein. The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years.
Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to 1 the choice of dryness definition and 2 statistical data processing.
In fact, we find only minor and only some significant increases if 1 dryness is based on aridity and 2 statistical artefacts are accounted for.
Earth's terrestrial surface influences climate by exchanging carbon and water with the atmosphere through stomatal pores. However, most land-surface models, used to predict global carbon and water fluxes, estimate that water lost through stomata is less than what observations show.
In this study, we integrate plant water loss data from species into a global land surface model, finding that global estimates of plant water loss increase, soil moisture decreases, and carbon gain also decreases.
Michalak, and Prabir Patra. The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements.
It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed.
We apply it to estimate monthly ratios between CO 2 , CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between and We find that this approach is little sensitive to the regional background level definition.
With this new method, we may reveal spatial and seasonal variability in the ratios in Paris. Semi-arid ecosystems in Australia are responsible for a significant part of the variability in global atmospheric carbon dioxide.
Here we use Australian observations to estimate parameters in a land surface model of carbon and water cycles. We quantify the variability in Australian carbon fluxes between and , including the large uptake in associated with exceptionally wet conditions following a prolonged drought.
We estimate the effect of parameter uncertainty on these estimates. Andrew, Josep G. Peters, Andrew C. Manning, Thomas A. Tans, Richard A.
Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Stocker, Adrienne J. The Global Carbon Budget is the 11th annual update of emissions of carbon dioxide CO 2 and their partitioning among the atmosphere, land, and ocean.
This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years to , with a projection for year Evans, Anne Griebel, Lindsay B.
Prober, and Richard Silberstein. Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial.
We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia.
Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.
Jason Beringer, Lindsay B. Arndt, David Campbell, Helen A. Phillips, Suzanne M. We describe the evolution, design, and status as well as an overview of data processing.
We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.
Sylvia S. Nyawira, Julia E. We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses.
The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions.
The evaluation offers an opportunity for identifying causes of model—data discrepancies. Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model.
Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context.
This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO 2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model.
The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.
Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. Marked improvements in predictions of evaporation are demonstrated globally.
Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation. Gregor J.
The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting or assimilating the model with observations of atmospheric CO 2 and fractions of absorbed photosynthetically active radiation.
Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types.
Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.
In this study, we found that methane emission estimates, driven by the CTE-CH 4 model, depend on model setups and inputs, especially for regional estimates.
An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role.
The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
This paper presents a method to adjust the sinks and sources of CO 2 associated with land ecosystems within a global atmospheric CO 2 forecasting system in order to reduce the errors in the forecast.
This is done by combining information on 1 retrospective fluxes estimated by a global flux inversion system, 2 land-use information, and 3 simulated fluxes from the model.
Because the method is simple and flexible, it can easily run in real time as part of a forecasting system. To understand the role of fires in the Earth system, global fire models are required.
It follows a reduced complexity approach using mainly temperature, humidity and precipitation. INFERNO was found to perform well on a global scale and to maintain regional patterns over the — period of study, despite regional biases particularly linked to fuel consumption.
Lisa R. Welp, Prabir K. Piper, and Ralph F. Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO 2 over the last decades.
It is not clear if these ecosystems are sequestering more carbon or possibly becoming sources. This is an important feedback of the carbon cycle to global warming.
We studied monthly biological land CO 2 fluxes inferred from atmospheric CO 2 concentrations using inverse models and found that net summer CO 2 uptake increased, resulting in a small increase in annual CO 2 uptake.
Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network.
Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.
Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom.
Dynamic global vegetation models DGVMs are used to predict the response of vegetation to climate change.
We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base.
The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly.
We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs.
We show here that the many methods for doing this are special cases of underlying statistics. This provides a unified way of comparing and contrasting such methods.
Christian Frankenberg, Susan S. Kulawik, Steven C. Olsen, and Gregory Osterman. This paper advances atmospheric inversion of city CO 2 emissions as follows: 1 illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO 2 concentrations; 2 demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification MRV of city CO 2 emissions; 3 clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO 2 emissions.
Harrison, Douglas I. Colin Prentice, Sam S. Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes.
A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales.
In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project — FireMIP.
We measured carbon dioxide and methane concentrations at four near-ground sites located in London, We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions.
Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications.
A gradient approach was found to be beneficial to reduce model—data errors. Hutley, Gab Abramowitz, Martin G. In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems.
We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. On average, we found the models as a group display only moderate levels of performance.
Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. We apply the ratio inversion method described in Pandey et al. We propose insights based on atmospheric observations around the Arctic circle to evaluate estimates of methane emissions to the atmosphere from the East Siberian Arctic Shelf.
Based on a comprehensive statistical analysis of the observations and of high-resolution transport simulations, annual methane emissions from ESAS are estimated to range from 0.
This paper evaluates the model predictions of leaf area index in the current climate, compared against satellite observations. It also summarizes the predicted changes in leaf area index in the future, and identifies whether some of the uncertainty in future predictions can be decreased.
Miller, Paul O. Dubey, Nicholas M. Feist, Laura T. Iraci, and Joyce Wolf. To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized.
We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability.
Our findings are useful for assimilation of satellite data. Burrows, Nicholas M. Dubey, David W. We show that the modelled CO 2 has a better precision than standard CO 2 satellite products compared to ground-based measurements.
We also present the CO 2 forecast based on our best knowledge of the atmospheric CO 2 distribution. We show that it has skill to forecast the largest scale CO 2 patterns up to day 5.
Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. Trudinger, and J. We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network.
Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence.
Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
Wagner, I. Kolari, J. Kurbatova, A. Varlagin, T. Maximov, A. Kononov, T. Ohta, A. Kotani, M. Krol, and W. Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle.
Droughts can modify this cycle considerably, although very few ground-based observations are available in the region.
We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best.
The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
Sippel, F. Otto, M. Forkel, M. Allen, B. Guillod, M. Heimann, M. Reichstein, S. Seneviratne, K. Thonicke, and M. We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure.
The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere—atmosphere carbon and water fluxes with a biosphere model LPJmL show that the novel technique can be usefully applied to drive climate impact models.
Ryder, J. Polcher, P. Peylin, C. Chen, E. Haverd, M. McGrath, K. Naudts, J. Otto, A. Valade, and S. Murray-Tortarolo, P. Friedlingstein, S.
Sitch, V. Jaramillo, F. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. Stocker, A.
Wiltshire, S. Zaehle, and N. We modelled the carbon C cycle in Mexico for three different time periods: past 20th century , present and future We used different available products to estimate C stocks and fluxes in the country.
Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century unless the most extreme climate-change scenarios are reached.
Rödenbeck, D. Bakker, N. Gruber, Y. Iida, A. Jacobson, S. Jones, P. Landschützer, N. Metzl, S. Nakaoka, A.
Olsen, G. Park, P. Peylin, K. Rodgers, T. Sasse, U. Schuster, J. Shutler, V. Valsala, R. Wanninkhof, and J. This study investigates variations in the CO2 uptake of the ocean from year to year.
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Frank Griebe born 28 August is a German cinematographer.. Griebe was born in Hamburg. He is most popular for his work with German director Tom Tykwer.
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We present the concept of Earth system data cubes to study the complex dynamics of multiple climate and ecosystem variables across space and time.
Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Scott, and Sebastian Wolf.
Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales.
To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Teuling, and Markus Reichstein. This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration.
We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation.
Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
We explored the timing of the peak of the short annual growing season in tundra ecosystems as indicated by an extensive suite of satellite indicators of vegetation productivity.
Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. Plants also experience growth after optimal conditions for assimilation regarding light and temperature have passed.
Our results have implications for the modelling of the circumpolar carbon balance. In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage.
We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis.
While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Mahecha, and Markus Reichstein. We provide continuous half-hourly carbon and energy fluxes for to at 0.
In addition, we provide a derived product that only contains monthly average diurnal cycles but which also enables us to study the important characteristics of subdaily patterns at a global scale.
Jacob A. Plants have typical daily carbon uptake and water loss cycles. However, these cycles may change under periods of duress, such as water limitation.
Here we identify two types of patterns in response to water limitations: a tendency to lose more water in the morning than afternoon and a decoupling of the carbon and water cycles.
The findings show differences in responses by trees and grasses and suggest that morning shifts may be more efficient at gaining carbon per unit water used.
Scott, Francesco P. Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity GPP and ecosystem respiration globally across a wide range of ecosystems.
We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Model Dev. Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO 2 fluxes to climate often remain uncertain.
The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach.
When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Jakob Zscheischler, Miguel D. West, Julie E. Wolf, and Markus Reichstein. Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere.
A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. For plants, the ratio of carbon uptake to water loss by transpiration is usually thought to depend on characteristic properties their adaption to water scarcity and the dryness of the atmosphere at any given moment.
We show that, on the ecosystem scale, radiation has an independent effect on this ratio that had not been previously considered. When including this variable in models, predictions of transpiration improve considerably.
We have evaluated 11 machine learning ML methods and two complementary drivers' setup to estimate the carbon dioxide CO 2 and energy exchanges between land ecosystems and atmosphere.
Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes.
The results were good for all the ecosystems, with limitations to the ones in the extreme environments cold, hot or less represented in the training data tropics.
Miralles, C. Jung, D. Michel, A. Ershadi, M. McCabe, M. Hirschi, B. Martens, A. Dolman, J. Fisher, Q. Mu, S. Seneviratne, E. Wood, and D. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components.
Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
Michel, C. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. McCabe, J. In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration ET algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product.
More articles 9. Remote Sens. Spatial Inf. Getachew Agmuas Adnew, Thijs L. We measured the effect of photosynthesis, the largest flux in the carbon cycle, on the triple oxygen isotope composition of atmospheric CO 2 at the leaf level during gas exchange using three plant species.
The main factors that limit the impact of land vegetation on the triple oxygen isotope composition of atmospheric CO 2 are identified, characterized and discussed.
It has undergone rapid development since the first release in and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Yan Sun, Daniel S. We find that the simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates.
However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes, as well as model development priorities are discussed.
The Cryosphere Discuss. Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs.
Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the s at two of the sites.
Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Sehgal, and Rajkumar Dhakar. Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing environmental and management factors.
These effects vary across the country, thereby affecting production at regional scales. Andrew J. Wiltshire, Eleanor J.
Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Harper, Spencer Liddicoat, Stephen A. Sitch, and Sonke Zaehle. Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon.
It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle which is included within the UK Earth System model to improve projections of cliamte change and impacts on ecosystems.
Given the self-reporting nature of this system, it is critical to evaluate the emission reports with independent observation systems.
Here we present the direct observations of city CO 2 plumes from space and the quantification of CO 2 emissions from these observations over the largest emitter country China.
Data Discuss. To understand the carbon cycle better, we generated a global dataset of forest aboveground biomass, i. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests although for dense forests in the tropics values are somewhat underestimated.
This dataset will have considerable impact on climate, carbon and socio-economic modelling schemes. Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P.
Melton, Lars Nieradzik, Sam S. Rabin, I. Global fire—vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes.
Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks.
While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Lei Ma, George C. Hurtt, Louise P. Earth system models require information on historical land cover change.
We present transition rules to generate land cover change from newly developed land use dataset Land-use Harmonization, LUH2.
The resulting forest cover, vegetation carbon, and emissions from land use and land cover change are simulated and evaluated against remote sensing data and other studies.
The rules can guide the incorporation of land-cover information within earth system models for CMIP6. Dlugokencky, and Christian Frankenberg.
The growth of methane, the second most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in the atmosphere in recent years.
Biogeosciences Discuss. We find a biogeophysically-induced global cooling with strong carbon losses after 20 million km 2 idealized deforestation experiment performed with nine CMIP6 Earth System Models.
It takes many decades for temperature signal to emerge, with non-local effects playing an important role. Despite a consistent experimental setup, models diverge substantially in climate response, especially in tropics.
This study offers unprecedented insights for understanding land-use change effects in CMIP6 models. Robert J. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G.
Feist, David W. Pollard, Coleen Roehl, Mahesh K. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch. This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset.
We detail the processing, validation and evaluation involved in producing this data and highlight its many applications.
With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Anita D. Verburg, Peter Anthoni, and Almut Arneth. We evaluate a number of these and determine the variability they cause in ecosystems and their services.
We found that projections differ a lot in regional patterns with some of them being at least questionable in a historical context.
Across ecosystem service indicators resulting variability until was highest in crop production. Results emphasize that such variabilities should be acknowledged in assessments of future ecosystem provisions.
Ingrid Super, Hugo A. Denier van der Gon, Michiel K. Dellaert, and Wouter Peters. Understanding urban CO 2 fluxes is increasingly important to support emission reduction policies.
In this work we extended an existing framework for emission verification to increase its suitability for urban areas and source-sector-based decision-making by using a dynamic emission model.
We find that the dynamic emission model provides a better understanding of emissions at small scales and their uncertainties. By including co-emitted species, emission can be related to specific source sectors.
Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites.
Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different time.
The new model has the potential to study large scale impacts of aerosol changes. Garry D. Harper, Tom Powell, Peter M.
House, Jonathan C. Doelman, Detlef P. Chadburn, Eleanor Burke, and Nicola Gedney. We investigate the regional effectiveness of lowering methane emissions from human activities, re afforestation, and growing bioenergy crops.
Methane reduction always helps, especially for major methane-emitting regions. However, the preferred land-management strategy and its effectiveness is more variable.
Charles D. Koven, Ryan G. Knox, Rosie A. Fisher, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Michael C.
McDowell, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Serbin, Jacquelyn K. Shuman, Abigail L. Swann, Charuleka Varadharajan, Anthony P.
Walker, S. Joseph Wright, and Chonggang Xu. Tropical forests play a crucial role in governing climate feedbacks, and are incredibly diverse ecosystems, yet most Earth system models do not take into account the diversity of plant traits in these forests and how this diversity may govern feedbacks.
We present an approach to represent diverse competing plant types within Earth system models, test this approach at a tropical forest site, and explore how the representation of disturbance and competition governs traits of the forest community.
Ainsworth, Timiothy Arkebauer, and David Scoby. Ground-level ozone O 3 is detrimental to plant productivity and crop yield. The result shows good performance for yield and it helps contribute to understanding of the impacts of climate and air pollution on food production.
This paper shows that a Neural Network approach can be used to process spaceborne observations from the OCO-2 satellite and retrieve both the surface pressure and the atmospheric CO 2 content.
The accuracy evaluation indicates that the retrievals have an accuracy that is at least as good as those of the operational approach that relies on complex algorithms and that is very computer intensive.
The approach is therefore a very promising alternative for the processing of CO 2 -monitoring missions. El-Madany, and Mirco Migliavacca.
Data Syst. Continuous data of soil CO 2 efflux can improve model prediction of climate warming, and automated data are becoming increasingly available.
However, aggregating chamber-based data to plot scale pose challenges. Therefore, we showed, using 1 year of half-hourly data, how using the lognormal assumption tackles several challenges.
We propose that plot-scale SO 2 efflux observations should be reported together with lognormally based uncertainties and enter model constraining frameworks at log scale.
Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO 2 to monitor anthropogenic emissions from regions, cities and large industrial plants.
The analysis, applied to a large ensemble of sources in Western Europe, shows a strong dependence of the results to different characteristics of the spaceborne instrument, to the source emission budgets and spreads, and to the wind conditions.
Sun-induced chlorophyll fluorescence is a valuable indicator of vegetation productivity, but our capacity to measure it from space using satellite remote techniques has been hampered by a lack of spatial detail.
Based on prior knowledge of how ecosystems should respond to growing conditions in some modelling along with ancillary satellite observations, we provide here a new enhanced dataset with higher spatial resolution that better represents the spatial patterns of vegetation growth over land.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Norby, Anthony P. The Sphagnum mosses are the important species of wetland ecosystem.
To better represent the peatland ecosystem, we introduced the moss species to the land model component ELM of the Energy Exascale Earth System Model E3SM , by developing water content dynamics and non-vascular photosynthetic processes for moss.
We tested the model against field observations and used the model to make projections of site carbon cycle under warming and atmospheric CO 2 concentration scenarios.
To closely monitor the state of our planet, we require systems that can monitor the observation of many different properties at the same time.
We create indicators that resemble the behavior of many different simultaneous observations. We apply the method to create indicators representing the Earth's biosphere.
The indicators show a productivity gradient and a water gradient. The resulting indicators can detect a large number of changes and extremes in the Earth system.
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up GHG anthropogenic emissions from agriculture, forestry and other land use AFOLU in the EU We provide comprehensive emission assessments in support to policy, facilitating real-time verification procedures.
This work investigates the sensitivity of terrestrial CO 2 fluxes to climate drivers. We observed that CO 2 flux is mostly controlled by temperature during the growing season and by radiation off season.
We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia.
Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
Sam S. Pugh, Mark Rounsevell, and Almut Arneth. We modeled how agricultural performance and demand will shift as a result of climate change and population growth, and how the resulting adaptations will affect aspects of the Earth system upon which humanity depends.
We found that the impacts of land use and management can have stronger impacts than climate change on some such ecosystem services.
Boysen, Pete Smith, and Daniel Goll. Many CO 2 uptake estimates do not include the effect of nutrient deficiencies in soils on biomass production.
We show that nutrients can be partly resupplied by enhanced weathering EW rock powder application, increasing the effectiveness of tNETs.
Depending on the deployed amounts of rock powder, EW could also improve soil hydrology, adding a new dimension to the coupling of tNETs with EW. George C.
Bodirsky, Katherine Calvin, Jonathan C. Tubiello, Detlef P. Evans, Flurin Babst, and Sebastiaan Luyssaert. ISAM model was used to estimate soybean and maize crop yields over — driven by changes in environmental factors and management factors.
Over the 20 th century, each of these factors contributes to the increase in global crop yield with increasing nitrogen fertilizer application the strongest of these drivers for maize and increasing [CO 2 ] the strongest for soybean.
Over the 21 st century, changing climate drives yield lower, while rising [CO 2 ] drives yield higher for both crops. Arora, Vanessa Haverd, Atul K.
Evapotranspiration ET links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET.
These three categories of approaches agreed well in terms of ET intensity. For —, all models showed that Earth greening enhanced terrestrial ET.
Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO 2 of different vegetation types at the global scale.
We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny.
This implies different water management strategies of forests, but also a lack of sensitivity in remote sensing derived vegetation activity.
We quantitatively examined the relative contributions of climate change, land use and land cover change, and elevated CO 2 to interannual variations and seasonal cycle amplitude of gross primary productivity GPP in China based on multi-model ensemble simulations.
The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
We explore ecosystem responses in China to 1. Our analyses suggest that an associated reduction of CO 2 and pollution emissions brings more benefits to ecosystems in China via 1.
Causal inference promises new insight into biosphere—atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data.
The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques.
Thus, causal inference allows to us gain well-constrained insights into processes and interactions. Nora Linscheid, Lina M. Sierra, and Miguel D.
Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems.
It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered.
This scale dependency should be considered for modeling land—atmosphere interactions. Tea Thum, Julia E. Dlugokencky, Jari Liski, Ingrid T.
Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of upmost importance, as its emissions to atmosphere will enhance atmospheric carbon dioxide concentration.
To evaluate the skill of the global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources.
We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations. Javier Pacheco-Labrador, Tarek S. El-Madany, M. The new generation of sensors on-board satellites have the potential to provide richer information about the function of vegetation than before.
This information, nowadays missing, is fundamental to improve our understanding and prediction of carbon and water cycles, and therefore to anticipate effects and responses to Climate Change.
In this manuscript we propose a method to exploit the data provided by these satellites to successfully obtain this information key to face Climate Change.
Thomas A. Pugh, Tim T. Rademacher, Sarah L. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle.
Estimates from six contemporary models found this time to range from Future projections do not give consistent results, but twelve model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce current large uncertainty.
Goll, and Emmanuel Frossard. In this article we provide estimates of mean residence times of phosphorus in inorganic soil phosphorus pools.
These values improve our understanding of the dynamics of phosphorus cycling and can be used to improve global land surface models. Alexander J.
Turner, Philipp Köhler, Troy S. We present the highest resolution solar-induced chlorophyll fluorescence SIF dataset from satellite measurements, providing previously unobservable phenomena related to plant photosynthesis.
We then observe a double peak in the seasonality of California's photosynthesis, not seen by traditional vegetation indices e.
Models need to account for forest age structures when investigating land use influences on land—atmosphere feedbacks.
We present a consolidated scheme to introduce forest age classes, combining age-dependent simulations of important processes with the possibility to trace forest age, and describe its implementation in JSBACH4, the land surface model of the ICON Earth system model.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. Tuinder, Abram F. Sanders, Willem W. Folkert Boersma. With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument.
The result is a coherent dataset of daily and monthly averaged fluorescence values for the period — to track worldwide changes in photosynthetic activity by vegetation.
In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale.
We developed a simple method to refine existing open ocean maps towards different coastal seas. Using a multi linear regression we produced monthly maps of surface ocean f CO 2 in the northern European coastal seas North Sea, Baltic Sea, Norwegian Coast and in the Barents Sea covering a time period from to Based on this f CO 2 map, we calculate trends in surface ocean f CO 2 , pH and the air-sea gas exchange.
Thompson, Ingrid T. The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups.
It aims at producing an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period —, based on constraints provided by observed CO 2 concentrations, and using inverse modelling technicuqes.
The use of six different models enables us to investigate the robustness of the results. Vivek K. Arora, Anna Katavouta, Richard G.
Williams, Chris D. Chamberlain, James R. Christian, Christine Delire, Rosie A. Law, David M. Since the pre-industrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans.
Comparison of different earth system models with carbon cycle allows to assess how carbon uptake by land and ocean differs among models.
This yields an estimate of uncertainty of our understanding of how land and ocean respond to increasing atmospheric CO 2.
This manuscript summarizes results from two such model intercomparisons projects. Pierre Friedlingstein, Matthew W.
Andrew, Judith Hauck, Glen P. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Chini, Kim I. Currie, Richard A.
Jain, Emilie Joetzjer, Jed O. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. Tubiello, Guido R.
Wiltshire, and Sönke Zaehle. The Global Carbon Budget describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean.
These living data are updated every year to provide the highest transparency and traceability in the reporting of CO 2 , the key driver of climate change.
We present a way to rate the CO 2 flux estimates made from inversion of a global atmospheric transport model. Our approach relies on accurate aircraft measurements in the free troposphere.
It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.
This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems. The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system.
The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism.
We present continuous in situ measurements of atmospheric CO 2 and CH 4 mole fractions at the new station Ambarchik, located in northeastern Siberia.
We describe the site, measurements and quality control, characterize the signals in comparison with data from Barrow, Alaska, and show which regions the measurements are sensitive to.
Ambarchik data are available upon request. Daniel E. Lina Teckentrup, Sandy P. We investigate the influence of five forcing factors: atmospheric CO 2 , population density, land—use change, lightning and climate.
We find that the anthropogenic factors lead to the largest spread between models. In these regions, microwave satellite observations indicate that soil moisture decreased from to Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend.
Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies.
Let us know how this access is important for you. Skip to main content. UC Irvine. Email Facebook Twitter. Recent decline in the global land evapotranspiration trend due to limited moisture supply.
Abstract More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Thumbnails Document Outline Attachments.
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