Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4077-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4077-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
07 Sep 2022
Data description paper |
| 07 Sep 2022
| 07 Sep 2022
Global datasets of leaf photosynthetic capacity for ecological and earth system research
Jing M. Chen
CORRESPONDING AUTHOR
School of Geographical Sciences, Fujian Normal University, Fuzhou, China
Department of Geography and Planning, University of Toronto, Toronto, Canada
Rong Wang
School of Geographical Sciences, Fujian Normal University, Fuzhou, China
Yihong Liu
Department of Geography and Planning, University of Toronto, Toronto, Canada
Liming He
Canada Centre for Remote Sensing, Natural Resources Canada, Toronto, Canada
Holly Croft
School of Biosciences, University of Sheffield, Sheffield, UK
Xiangzhong Luo
Department of Geography, National University of Singapore, Singapore, Singapore
Han Wang
Department of Earth System Science, Tsinghua University, 100084 Beijing, China
Nicholas G. Smith
Department of Biological Sciences, Texas Tech University, Lubbock, TX, USA
Trevor F. Keenan
Climate and Ecosystem Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, CA, USA
Department of Environmental Science, Policy and Management, UC
Berkeley, Berkeley, CA, USA
I. Colin Prentice
Department of Life Sciences, Imperial College London, Silwood Park
Campus, Buckhurst Road, SL57PY Ascot, UK
Department of Earth System Science, Tsinghua University, 100084 Beijing, China
Department of Biological Sciences, Macquarie University, 2109 North Ryde, NSW, Australia
Yongguang Zhang
International Institute of Earth System Science, Nanjing University, Nanjing, China
Weimin Ju
International Institute of Earth System Science, Nanjing University, Nanjing, China
Ning Dong
Department of Life Sciences, Imperial College London, Silwood Park
Campus, Buckhurst Road, SL57PY Ascot, UK
Department of Biological Sciences, Macquarie University, 2109 North Ryde, NSW, Australia
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Soil water availability affects plant carbon uptake by reducing leaf area and/or by closing stomata, which reduces its efficiency. We present a new formulation of how climatic dryness reduces both maximum carbon uptake and the soil-moisture threshold below which it declines further. This formulation illustrates how plants adapt their water conservation strategy to thrive in dry climates, and is step towards a better representation of soil-moisture effects in climate models.
Mengmeng Liu, Yicheng Shen, Penelope González-Sampériz, Graciela Gil-Romera, Cajo J. F. ter Braak, Iain Colin Prentice, and Sandy P. Harrison
Clim. Past, 19, 803–834, https://doi.org/10.5194/cp-19-803-2023, https://doi.org/10.5194/cp-19-803-2023, 2023
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We reconstructed the Holocene climates in the Iberian Peninsula using a large pollen data set and found that the west–east moisture gradient was much flatter than today. We also found that the winter was much colder, which can be expected from the low winter insolation during the Holocene. However, summer temperature did not follow the trend of summer insolation, instead, it was strongly correlated with moisture.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
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A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Yicheng Shen, Luke Sweeney, Mengmeng Liu, Jose Antonio Lopez Saez, Sebastián Pérez-Díaz, Reyes Luelmo-Lautenschlaeger, Graciela Gil-Romera, Dana Hoefer, Gonzalo Jiménez-Moreno, Heike Schneider, I. Colin Prentice, and Sandy P. Harrison
Clim. Past, 18, 1189–1201, https://doi.org/10.5194/cp-18-1189-2022, https://doi.org/10.5194/cp-18-1189-2022, 2022
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We present a method to reconstruct burnt area using a relationship between pollen and charcoal abundances and the calibration of charcoal abundance using modern observations of burnt area. We use this method to reconstruct changes in burnt area over the past 12 000 years from sites in Iberia. We show that regional changes in burnt area reflect known changes in climate, with a high burnt area during warming intervals and low burnt area when the climate was cooler and/or wetter than today.
Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
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Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
Biogeosciences, 18, 3861–3879, https://doi.org/10.5194/bg-18-3861-2021, https://doi.org/10.5194/bg-18-3861-2021, 2021
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Along with current climate, vegetation, and human influences, long-term accumulation of biomass affects fires. Here, we find that including the influence of antecedent vegetation and moisture improves our ability to predict global burnt area. Additionally, the length of the preceding period which needs to be considered for accurate predictions varies across regions.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Douglas I. Kelley, Chantelle Burton, Chris Huntingford, Megan A. J. Brown, Rhys Whitley, and Ning Dong
Biogeosciences, 18, 787–804, https://doi.org/10.5194/bg-18-787-2021, https://doi.org/10.5194/bg-18-787-2021, 2021
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Initial evidence suggests human ignitions or landscape changes caused most Amazon fires during August 2019. However, confirmation is needed that meteorological conditions did not have a substantial role. Assessing the influence of historical weather on burning in an uncertainty framework, we find that 2019 meteorological conditions alone should have resulted in much less fire than observed. We conclude socio-economic factors likely had a strong role in the high recorded 2019 fire activity.
Yi Zheng, Ruoque Shen, Yawen Wang, Xiangqian Li, Shuguang Liu, Shunlin Liang, Jing M. Chen, Weimin Ju, Li Zhang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, https://doi.org/10.5194/essd-12-2725-2020, 2020
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Accurately reproducing the interannual variations in vegetation gross primary production (GPP) is a major challenge. A global GPP dataset was generated by integrating the regulations of several major environmental variables with long-term changes. The dataset can effectively reproduce the spatial, seasonal, and particularly interannual variations in global GPP. Our study will contribute to accurate carbon flux estimates at long timescales.
S. Wang, Z. Li, Y. Zhang, D. Yang, and C. Ni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 571–578, https://doi.org/10.5194/isprs-annals-V-3-2020-571-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-571-2020, 2020
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
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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.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Fortunat Joos, Renato Spahni, Benjamin D. Stocker, Sebastian Lienert, Jurek Müller, Hubertus Fischer, Jochen Schmitt, I. Colin Prentice, Bette Otto-Bliesner, and Zhengyu Liu
Biogeosciences, 17, 3511–3543, https://doi.org/10.5194/bg-17-3511-2020, https://doi.org/10.5194/bg-17-3511-2020, 2020
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Results of the first globally resolved simulations of terrestrial carbon and nitrogen (N) cycling and N2O emissions over the past 21 000 years are compared with reconstructed N2O emissions. Modelled and reconstructed emissions increased strongly during past abrupt warming events. This evidence appears consistent with a dynamic response of biological N fixation to increasing N demand by ecosystems, thereby reducing N limitation of plant productivity and supporting a land sink for atmospheric CO2.
Sean F. Cleator, Sandy P. Harrison, Nancy K. Nichols, I. Colin Prentice, and Ian Roulstone
Clim. Past, 16, 699–712, https://doi.org/10.5194/cp-16-699-2020, https://doi.org/10.5194/cp-16-699-2020, 2020
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We present geographically explicit reconstructions of seasonal temperature and annual moisture variables at the Last Glacial Maximum (LGM), 21 000 years ago. The reconstructions use existing site-based estimates of climate, interpolated in space and time in a physically consistent way using climate model simulations. The reconstructions give a much better picture of the LGM climate and will provide a robust evaluation of how well state-of-the-art climate models simulate large climate changes.
Benjamin D. Stocker, Han Wang, Nicholas G. Smith, Sandy P. Harrison, Trevor F. Keenan, David Sandoval, Tyler Davis, and I. Colin Prentice
Geosci. Model Dev., 13, 1545–1581, https://doi.org/10.5194/gmd-13-1545-2020, https://doi.org/10.5194/gmd-13-1545-2020, 2020
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Estimating terrestrial photosynthesis relies on satellite data of vegetation cover and models simulating the efficiency by which light absorbed by vegetation is used for CO2 assimilation. This paper presents the P-model, a light use efficiency model derived from a carbon–water optimality principle, and evaluates its predictions of ecosystem-level photosynthesis against globally distributed observations. The model is implemented and openly accessible as an R package (rpmodel).
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
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The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Xiaojin Qian, Liangyun Liu, Holly Croft, and Jingming Chen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-228, https://doi.org/10.5194/bg-2019-228, 2019
Preprint withdrawn
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The leaf maximum carboxylation rate (Vcmax) is a key photosynthesis parameter. We attempt to investigate whether a universal and stable relationship exists between leaf Vcmax25 and chlorophyll content across different C3 plant types from a plant physiological perspective and verify it using field experiments. The results confirm that leaf chlorophyll can be a reliable proxy for estimating Vcmax25, providing an operational approach for the global mapping of Vcmax25 across different plant types.
Guangqi Li, Sandy P. Harrison, and I. Colin Prentice
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-63, https://doi.org/10.5194/bg-2019-63, 2019
Publication in BG not foreseen
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Current methods of removing age effect from tree-ring are influenced by sampling biases – older trees are more abundantly sampled for recent decades, when the strongest environmental change happens. New technique of extracting environment-driven signals from tree ring is specifically designed to overcome this bias, drawing on theoretical tree growth. It removes sampling-bias effectively and shows consistent relationships between growth and climates through time and across two conifer species.
Dongyang Wei, Penélope González-Sampériz, Graciela Gil-Romera, Sandy P. Harrison, and I. Colin Prentice
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-16, https://doi.org/10.5194/cp-2019-16, 2019
Revised manuscript not accepted
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El Cañizar de Villarquemado provides a pollen record from semi-arid Spain since before the last interglacial. We use modern pollen–climate relationships to reconstruct changes in seasonal temperature and moisture, accounting for CO2 effects on plants, and show coherent climate changes on glacial–interglacial and orbital timescales. The low glacial CO2 means moisture changes are less extreme than suggested by the vegetation shifts, and driven by evapotranspiration rather than rainfall changes.
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
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We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Henrique Fürstenau Togashi, Iain Colin Prentice, Owen K. Atkin, Craig Macfarlane, Suzanne M. Prober, Keith J. Bloomfield, and Bradley John Evans
Biogeosciences, 15, 3461–3474, https://doi.org/10.5194/bg-15-3461-2018, https://doi.org/10.5194/bg-15-3461-2018, 2018
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Ecosystem models commonly assume that photosynthetic traits, such as carboxylation capacity measured at a standard temperature, are constant in time and therefore do not acclimate. Optimality hypotheses suggest this assumption may be incorrect. We investigated acclimation by carrying out measurements on woody species during distinct seasons in Western Australia. Our study shows evidence that carboxylation capacity should acclimate so that it increases somewhat with growth temperature.
Sandy P. Harrison, Patrick J. Bartlein, Victor Brovkin, Sander Houweling, Silvia Kloster, and I. Colin Prentice
Earth Syst. Dynam., 9, 663–677, https://doi.org/10.5194/esd-9-663-2018, https://doi.org/10.5194/esd-9-663-2018, 2018
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Temperature affects fire occurrence and severity. Warming will increase fire-related carbon emissions and thus atmospheric CO2. The size of this feedback is not known. We use charcoal records to estimate pre-industrial fire emissions and a simple land–biosphere model to quantify the feedback. We infer a feedback strength of 5.6 3.2 ppm CO2 per degree of warming and a gain of 0.09 ± 0.05 for a climate sensitivity of 2.8 K. Thus, fire feedback is a large part of the climate–carbon-cycle feedback.
Daniel S. Goll, Alexander J. Winkler, Thomas Raddatz, Ning Dong, Ian Colin Prentice, Philippe Ciais, and Victor Brovkin
Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, https://doi.org/10.5194/gmd-10-2009-2017, 2017
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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.
Yang Liu, Ronggao Liu, Jan Pisek, and Jing M. Chen
Biogeosciences, 14, 1093–1110, https://doi.org/10.5194/bg-14-1093-2017, https://doi.org/10.5194/bg-14-1093-2017, 2017
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Forest overstory and understory layers differ in carbon and water cycle regimes and phenology, as well as ecosystem functions. In this paper, overstory and understory LAI values were estimated separately for global needleleaf and deciduous broadleaf forests. This work would help us better understand the seasonal patterns of forest structure, evaluate the ecosystem functions and improve the modeling of the forest carbon and water cycles.
Tyler W. Davis, I. Colin Prentice, Benjamin D. Stocker, Rebecca T. Thomas, Rhys J. Whitley, Han Wang, Bradley J. Evans, Angela V. Gallego-Sala, Martin T. Sykes, and Wolfgang Cramer
Geosci. Model Dev., 10, 689–708, https://doi.org/10.5194/gmd-10-689-2017, https://doi.org/10.5194/gmd-10-689-2017, 2017
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This research presents a comprehensive description for calculating necessary, but sparsely observed, factors related to Earth's surface energy and water budgets relevant in, but not limited to, the study of ecosystems. We present the equations, including their derivations and assumptions, as well as example indicators relevant to plant-available moisture. The robustness of these relatively simple equations provides a tool to be used across broad fields of scientific research.
Ning Dong, Iain Colin Prentice, Bradley J. Evans, Stefan Caddy-Retalic, Andrew J. Lowe, and Ian J. Wright
Biogeosciences, 14, 481–495, https://doi.org/10.5194/bg-14-481-2017, https://doi.org/10.5194/bg-14-481-2017, 2017
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The nitrogen content of leaves is a key quantity for understanding ecosystem function. We analysed variations in nitrogen per unit leaf area among species at sites along a transect across Australia including many climates and ecosystem types. The data could be explained by the idea that leaf nitrogen comprises two parts, one proportional to leaf mass, the other (metabolic) part proportional to light intensity and declining with CO2 drawdown and temperature, as optimal allocation theory predicts.
Corinne Le Quéré, Erik T. Buitenhuis, Róisín Moriarty, Séverine Alvain, Olivier Aumont, Laurent Bopp, Sophie Chollet, Clare Enright, Daniel J. Franklin, Richard J. Geider, Sandy P. Harrison, Andrew G. Hirst, Stuart Larsen, Louis Legendre, Trevor Platt, I. Colin Prentice, Richard B. Rivkin, Sévrine Sailley, Shubha Sathyendranath, Nick Stephens, Meike Vogt, and Sergio M. Vallina
Biogeosciences, 13, 4111–4133, https://doi.org/10.5194/bg-13-4111-2016, https://doi.org/10.5194/bg-13-4111-2016, 2016
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We present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types, and use the model to assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean. Our results suggest that observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community, despite iron limitation of phytoplankton growth.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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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.
A. V. Gallego-Sala, D. J. Charman, S. P. Harrison, G. Li, and I. C. Prentice
Clim. Past, 12, 129–136, https://doi.org/10.5194/cp-12-129-2016, https://doi.org/10.5194/cp-12-129-2016, 2016
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It has become a well-established paradigm that blanket bog landscapes in the British Isles are a result of forest clearance by early human populations. We provide a novel test of this hypothesis using results from bioclimatic modelling driven by cimate reconstructions compared with a database of peat initiation dates. Both results show similar patterns of peat initiation over time and space. This suggests that climate was the main driver of blanket bog inception and not human disturbance.
B. A. A. Hoogakker, R. S. Smith, J. S. Singarayer, R. Marchant, I. C. Prentice, J. R. M. Allen, R. S. Anderson, S. A. Bhagwat, H. Behling, O. Borisova, M. Bush, A. Correa-Metrio, A. de Vernal, J. M. Finch, B. Fréchette, S. Lozano-Garcia, W. D. Gosling, W. Granoszewski, E. C. Grimm, E. Grüger, J. Hanselman, S. P. Harrison, T. R. Hill, B. Huntley, G. Jiménez-Moreno, P. Kershaw, M.-P. Ledru, D. Magri, M. McKenzie, U. Müller, T. Nakagawa, E. Novenko, D. Penny, L. Sadori, L. Scott, J. Stevenson, P. J. Valdes, M. Vandergoes, A. Velichko, C. Whitlock, and C. Tzedakis
Clim. Past, 12, 51–73, https://doi.org/10.5194/cp-12-51-2016, https://doi.org/10.5194/cp-12-51-2016, 2016
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In this paper we use two climate models to test how Earth’s vegetation responded to changes in climate over the last 120 000 years, looking at warm interglacial climates like today, cold ice-age glacial climates, and intermediate climates. The models agree well with observations from pollen, showing smaller forested areas and larger desert areas during cold periods. Forests store most terrestrial carbon; the terrestrial carbon lost during cold climates was most likely relocated to the oceans.
M. G. De Kauwe, S.-X. Zhou, B. E. Medlyn, A. J. Pitman, Y.-P. Wang, R. A. Duursma, and I. C. Prentice
Biogeosciences, 12, 7503–7518, https://doi.org/10.5194/bg-12-7503-2015, https://doi.org/10.5194/bg-12-7503-2015, 2015
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Future climate change has the potential to increase drought in many regions of the globe. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art models currently assume the same drought sensitivity for all vegetation. Our results indicate that models will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
T.-T. Meng, H. Wang, S. P. Harrison, I. C. Prentice, J. Ni, and G. Wang
Biogeosciences, 12, 5339–5352, https://doi.org/10.5194/bg-12-5339-2015, https://doi.org/10.5194/bg-12-5339-2015, 2015
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By analysing the quantitative leaf-traits along extensive temperature and moisture gradients with generalized linear models, we found that metabolism-related traits are universally acclimated to environmental conditions, rather than being fixed within plant functional types. The results strongly support a move towards Dynamic Global Vegetation Models in which continuous, adaptive trait variation provides the fundamental mechanism for changes in ecosystem properties along environmental gradients.
I. C. Prentice, X. Liang, B. E. Medlyn, and Y.-P. Wang
Atmos. Chem. Phys., 15, 5987–6005, https://doi.org/10.5194/acp-15-5987-2015, https://doi.org/10.5194/acp-15-5987-2015, 2015
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Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
S. Zhang, X. Zheng, J. M. Chen, Z. Chen, B. Dan, X. Yi, L. Wang, and G. Wu
Geosci. Model Dev., 8, 805–816, https://doi.org/10.5194/gmd-8-805-2015, https://doi.org/10.5194/gmd-8-805-2015, 2015
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A Global Carbon Assimilation System based on the Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
G. Li, S. P. Harrison, and I. C. Prentice
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-4769-2015, https://doi.org/10.5194/bgd-12-4769-2015, 2015
Revised manuscript has not been submitted
H. Zheng, Y. Li, J. M. Chen, T. Wang, Q. Huang, W. X. Huang, L. H. Wang, S. M. Li, W. P. Yuan, X. Zheng, S. P. Zhang, Z. Q. Chen, and F. Jiang
Biogeosciences, 12, 1131–1150, https://doi.org/10.5194/bg-12-1131-2015, https://doi.org/10.5194/bg-12-1131-2015, 2015
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Ecological models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) for an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state on 1 degree grid cells simultaneously.
G. Li, S. P. Harrison, I. C. Prentice, and D. Falster
Biogeosciences, 11, 6711–6724, https://doi.org/10.5194/bg-11-6711-2014, https://doi.org/10.5194/bg-11-6711-2014, 2014
M. Martin Calvo, I. C. Prentice, and S. P. Harrison
Biogeosciences, 11, 6017–6027, https://doi.org/10.5194/bg-11-6017-2014, https://doi.org/10.5194/bg-11-6017-2014, 2014
H. Wang, I. C. Prentice, and T. W. Davis
Biogeosciences, 11, 5987–6001, https://doi.org/10.5194/bg-11-5987-2014, https://doi.org/10.5194/bg-11-5987-2014, 2014
D. I. Kelley, S. P. Harrison, and I. C. Prentice
Geosci. Model Dev., 7, 2411–2433, https://doi.org/10.5194/gmd-7-2411-2014, https://doi.org/10.5194/gmd-7-2411-2014, 2014
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
I. Bistinas, S. P. Harrison, I. C. Prentice, and J. M. C. Pereira
Biogeosciences, 11, 5087–5101, https://doi.org/10.5194/bg-11-5087-2014, https://doi.org/10.5194/bg-11-5087-2014, 2014
P. N. Foster, I. C. Prentice, C. Morfopoulos, M. Siddall, and M. van Weele
Biogeosciences, 11, 3437–3451, https://doi.org/10.5194/bg-11-3437-2014, https://doi.org/10.5194/bg-11-3437-2014, 2014
Y. Liu, Y. Zhou, W. Ju, S. Wang, X. Wu, M. He, and G. Zhu
Biogeosciences, 11, 2583–2599, https://doi.org/10.5194/bg-11-2583-2014, https://doi.org/10.5194/bg-11-2583-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
Y. Liu, Y. Zhou, W. Ju, J. Chen, S. Wang, H. He, H. Wang, D. Guan, F. Zhao, Y. Li, and Y. Hao
Hydrol. Earth Syst. Sci., 17, 4957–4980, https://doi.org/10.5194/hess-17-4957-2013, https://doi.org/10.5194/hess-17-4957-2013, 2013
M. Liu, H. Wang, H. Wang, T. Oda, Y. Zhao, X. Yang, R. Zang, B. Zang, J. Bi, and J. Chen
Atmos. Chem. Phys., 13, 10873–10882, https://doi.org/10.5194/acp-13-10873-2013, https://doi.org/10.5194/acp-13-10873-2013, 2013
A. M. Ukkola and I. C. Prentice
Hydrol. Earth Syst. Sci., 17, 4177–4187, https://doi.org/10.5194/hess-17-4177-2013, https://doi.org/10.5194/hess-17-4177-2013, 2013
H. Wang, I. C. Prentice, and J. Ni
Biogeosciences, 10, 5817–5830, https://doi.org/10.5194/bg-10-5817-2013, https://doi.org/10.5194/bg-10-5817-2013, 2013
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
D. I. Kelley, I. C. Prentice, S. P. Harrison, H. Wang, M. Simard, J. B. Fisher, and K. O. Willis
Biogeosciences, 10, 3313–3340, https://doi.org/10.5194/bg-10-3313-2013, https://doi.org/10.5194/bg-10-3313-2013, 2013
F. J. Bragg, I. C. Prentice, S. P. Harrison, G. Eglinton, P. N. Foster, F. Rommerskirchen, and J. Rullkötter
Biogeosciences, 10, 2001–2010, https://doi.org/10.5194/bg-10-2001-2013, https://doi.org/10.5194/bg-10-2001-2013, 2013
D. J. Charman, D. W. Beilman, M. Blaauw, R. K. Booth, S. Brewer, F. M. Chambers, J. A. Christen, A. Gallego-Sala, S. P. Harrison, P. D. M. Hughes, S. T. Jackson, A. Korhola, D. Mauquoy, F. J. G. Mitchell, I. C. Prentice, M. van der Linden, F. De Vleeschouwer, Z. C. Yu, J. Alm, I. E. Bauer, Y. M. C. Corish, M. Garneau, V. Hohl, Y. Huang, E. Karofeld, G. Le Roux, J. Loisel, R. Moschen, J. E. Nichols, T. M. Nieminen, G. M. MacDonald, N. R. Phadtare, N. Rausch, Ü. Sillasoo, G. T. Swindles, E.-S. Tuittila, L. Ukonmaanaho, M. Väliranta, S. van Bellen, B. van Geel, D. H. Vitt, and Y. Zhao
Biogeosciences, 10, 929–944, https://doi.org/10.5194/bg-10-929-2013, https://doi.org/10.5194/bg-10-929-2013, 2013
Related subject area
Domain: ESSD – Global | Subject: Energy and Emissions
A global forest burn severity dataset from Landsat imagery (2003–2016)
A global surface CO2 flux dataset (2015–2022) inferred from OCO-2 retrievals using the GONGGA inversion system
Insights into the spatial distribution of global, national, and subnational greenhouse gas emissions in the Emissions Database for Global Atmospheric Research (EDGAR v8.0)
Estimating the uncertainty of the greenhouse gas emission accounts in global multi-regional input–output analysis
A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015
Temporal and spatial mapping of theoretical biomass potential across the European Union
Enhanced dataset of global marine isoprene emissions from biogenic and photochemical processes for the period 2001–2020
Quantifying greenhouse gas emissions from wood fuel use by households
Heat stored in the Earth system 1960–2020: where does the energy go?
Journals with open-discussion forums are excellent educational resources for peer review training exercises
Energy-related CO2 emission accounts and datasets for 40 emerging economies in 2010–2019
Natural gas supply from Russia derived from daily pipeline flow data and potential solutions for filling a shortage of Russian supply in the European Union (EU)
Kang He, Xinyi Shen, and Emmanouil N. Anagnostou
Earth Syst. Sci. Data, 16, 3061–3081, https://doi.org/10.5194/essd-16-3061-2024, https://doi.org/10.5194/essd-16-3061-2024, 2024
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Forest fire risk is expected to increase as fire weather and drought conditions intensify. To improve quantification of the intensity and extent of forest fire damage, we have developed a global forest burn severity (GFBS) database that provides burn severity spectral indices (dNBR and RdNBR) at a 30 m spatial resolution. This database could be more reliable than prior sources of information for future studies of forest burn severity on the global scale in a computationally cost-effective way.
Zhe Jin, Xiangjun Tian, Yilong Wang, Hongqin Zhang, Min Zhao, Tao Wang, Jinzhi Ding, and Shilong Piao
Earth Syst. Sci. Data, 16, 2857–2876, https://doi.org/10.5194/essd-16-2857-2024, https://doi.org/10.5194/essd-16-2857-2024, 2024
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An accurate estimate of spatial distribution and temporal evolution of CO2 fluxes is a critical foundation for providing information regarding global carbon cycle and climate mitigation. Here, we present a global carbon flux dataset for 2015–2022, derived by assimilating satellite CO2 observations into the GONGGA inversion system. This dataset will help improve the broader understanding of global carbon cycle dynamics and their response to climate change.
Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
Earth Syst. Sci. Data, 16, 2811–2830, https://doi.org/10.5194/essd-16-2811-2024, https://doi.org/10.5194/essd-16-2811-2024, 2024
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Knowing where emissions occur is essential for planning effective emission reduction measures and atmospheric modelling. Disaggregating national emissions over high-resolution grids requires spatial proxies that contain information on the location of different emission sources. This work incorporates state-of-the-art spatial information to improve the spatial representation of global emissions with the Emissions Database for Global Atmospheric Research (EDGAR).
Simon Schulte, Arthur Jakobs, and Stefan Pauliuk
Earth Syst. Sci. Data, 16, 2669–2700, https://doi.org/10.5194/essd-16-2669-2024, https://doi.org/10.5194/essd-16-2669-2024, 2024
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Greenhouse gas (GHG) emission accounts record emissions according to the economic boundary of a country, irrespective of whether they occur within national borders or not. In this study, we explore the accuracy of those GHG emission accounts. We find that the accuracy varies significantly depending on the country and economic sector. For example, small countries with extensive aviation or shipping activities show a high degree of uncertainty in their GHG emission accounts.
Kanishka B. Narayan, Brian C. O'Neill, Stephanie Waldhoff, and Claudia Tebaldi
Earth Syst. Sci. Data, 16, 2333–2349, https://doi.org/10.5194/essd-16-2333-2024, https://doi.org/10.5194/essd-16-2333-2024, 2024
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Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. We also present another version of this dataset aggregated from the country level to 32 geographical regions.
Susann Günther, Tom Karras, Friederike Naegeli de Torres, Sebastian Semella, and Daniela Thrän
Earth Syst. Sci. Data, 16, 59–74, https://doi.org/10.5194/essd-16-59-2024, https://doi.org/10.5194/essd-16-59-2024, 2024
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The following study was undertaken to provide a continuous open access dataset for 2010-2020 from country to local level. In order to understand the reliability of the final dataset and to enable further use, the modelled data were validated against statistics, which is a novelty in this field. The dataset has been shown to be in good agreement with the statistical data. Biomass potentials modelled in this study are published in an open access database.
Lehui Cui, Yunting Xiao, Wei Hu, Lei Song, Yujue Wang, Chao Zhang, Pingqing Fu, and Jialei Zhu
Earth Syst. Sci. Data, 15, 5403–5425, https://doi.org/10.5194/essd-15-5403-2023, https://doi.org/10.5194/essd-15-5403-2023, 2023
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Isoprene is a crucial non-methane biogenic volatile organic compound with the largest global emissions, which has high chemical reactivity and serves as the primary source of natural secondary organic aerosols. This study built a module to present a 20-year global hourly dataset of marine phytoplankton-generated biological and photochemistry-generated isoprene emissions in the sea microlayers based on the latest advancements in biological, physical, and chemical processes.
Alessandro Flammini, Hanif Adzmir, Kevin Karl, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 15, 2179–2187, https://doi.org/10.5194/essd-15-2179-2023, https://doi.org/10.5194/essd-15-2179-2023, 2023
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This paper estimates the share of greenhouse gas (GHG) emissions attributable to non-renewable wood fuel harvesting for use in residential food-related activities. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain and contributes to the development of the FAOSTAT climate change domain.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Nadine Borduas-Dedekind, Karen C. Short, and Samuel P. Carlson
Earth Syst. Sci. Data, 15, 1437–1440, https://doi.org/10.5194/essd-15-1437-2023, https://doi.org/10.5194/essd-15-1437-2023, 2023
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This article describes the use of the open-discussion manuscript review process as an educational exercise for early career scientists.
Can Cui, Shuping Li, Weichen Zhao, Binyuan Liu, Yuli Shan, and Dabo Guan
Earth Syst. Sci. Data, 15, 1317–1328, https://doi.org/10.5194/essd-15-1317-2023, https://doi.org/10.5194/essd-15-1317-2023, 2023
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Emerging economies face challenges regarding net-zero targets: inconsistencies in accounting calibers, missing raw data, non-transparent accounting methods, and a lack of detail about emissions. The authors established an accounting framework and compiled detailed inventories of energy-related CO2 emissions in 40 emerging economies, covering 47 sectors and eight energy types. The dataset will support emission reduction policymaking at global, national, and subnational levels.
Chuanlong Zhou, Biqing Zhu, Steven J. Davis, Zhu Liu, Antoine Halff, Simon Ben Arous, Hugo de Almeida Rodrigues, and Philippe Ciais
Earth Syst. Sci. Data, 15, 949–961, https://doi.org/10.5194/essd-15-949-2023, https://doi.org/10.5194/essd-15-949-2023, 2023
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Our work aims to analyze sectoral and country-based daily natural gas supply–storage–consumption based on ENTSOG, Eurostat, and multiple datasets in the EU27 and UK. We estimated the magnitude of the Russian gas gap if Russian gas imports were to stop as well as potential short-term solutions to fill this gap. Our datasets could be important in various fields, such as gas/energy consumption and market modeling, carbon emission and climate change research, and policy decision-making.
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Short summary
Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit...
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