Articles | Volume 14, issue 8
https://doi.org/10.5194/tc-14-2673-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-2673-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Aug 2020
Research article |
| 21 Aug 2020
| 21 Aug 2020
Clouds damp the radiative impacts of polar sea ice loss
Ramdane Alkama
CORRESPONDING AUTHOR
European Commission – Joint Research Centre, Via Enrico Fermi, 2749,
21027 Ispra (VA), Italy
Patrick C. Taylor
CORRESPONDING AUTHOR
NASA Langley Research Center, Hampton, Virginia, USA
Lorea Garcia-San Martin
European Commission – Joint Research Centre, Via Enrico Fermi, 2749,
21027 Ispra (VA), Italy
Herve Douville
Centre National de Recherches Météorologiques, Météo-France/CNRS,
Toulouse, France
Gregory Duveiller
European Commission – Joint Research Centre, Via Enrico Fermi, 2749,
21027 Ispra (VA), Italy
Giovanni Forzieri
European Commission – Joint Research Centre, Via Enrico Fermi, 2749,
21027 Ispra (VA), Italy
Didier Swingedouw
EPOC, Université de Bordeaux, Allée Geoffroy Saint-Hilaire,
Pessac 33615, France
Alessandro Cescatti
European Commission – Joint Research Centre, Via Enrico Fermi, 2749,
21027 Ispra (VA), Italy
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A. Elia, M. Pickering, M. Girardello, G. Oton, G. Ceccherini, S. Capobianco, M. Piccardo, G. Forzieri, M. Migliavacca, and A. Cescatti
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Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
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Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
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Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
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This study explores two of the most recent products in carbon productivity estimation, FLUXCOM gross primary productivity (GPP), calculated by upscaling local measurements of CO2 exchange, and remotely sensed sun-induced chlorophyll a fluorescence (SIF). High-resolution SIF data are valuable in demonstrating similarity in the SIF–GPP relationship between vegetation covers, provide an independent probe of the FLUXCOM GPP model and demonstrate the response of SIF to meteorological fluctuations.
Aurélien Ribes, Julien Boé, Saïd Qasmi, Brigitte Dubuisson, Hervé Douville, and Laurent Terray
Earth Syst. Dynam., 13, 1397–1415, https://doi.org/10.5194/esd-13-1397-2022, https://doi.org/10.5194/esd-13-1397-2022, 2022
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We use a novel statistical method to combine climate simulations and observations, and we deliver an updated assessment of past and future warming over France. As a key result, we find that the warming over that region was underestimated in previous multi-model ensembles by up to 50 %. We also assess the contribution of greenhouse gases, aerosols, and other factors to the observed warming, as well as the impact on the seasonal temperature cycle, and we discuss implications for climate services.
Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 13, 1305–1350, https://doi.org/10.5194/esd-13-1305-2022, https://doi.org/10.5194/esd-13-1305-2022, 2022
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Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation, and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occurs and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Roberto Pilli, Ramdane Alkama, Alessandro Cescatti, Werner A. Kurz, and Giacomo Grassi
Biogeosciences, 19, 3263–3284, https://doi.org/10.5194/bg-19-3263-2022, https://doi.org/10.5194/bg-19-3263-2022, 2022
Short summary
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Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
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Sean Horvath, Linette Boisvert, Chelsea Parker, Melinda Webster, Patrick Taylor, and Robyn Boeke
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Preprint withdrawn
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Arctic sea ice has been experiencing a dramatic decline since the late 1970s. A database is presented that combines satellite observations with daily sea ice parcel drift tracks. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states. This has multiple applications for the scientific community that can shed light on the atmosphere-snow-sea ice interactions in the changing Arctic environment.
J. Brant Dodson, Patrick C. Taylor, Richard H. Moore, David H. Bromwich, Keith M. Hines, Kenneth L. Thornhill, Chelsea A. Corr, Bruce E. Anderson, Edward L. Winstead, and Joseph R. Bennett
Atmos. Chem. Phys., 21, 11563–11580, https://doi.org/10.5194/acp-21-11563-2021, https://doi.org/10.5194/acp-21-11563-2021, 2021
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Aircraft in situ observations of low-level Beaufort Sea cloud properties and thermodynamics from the ARISE campaign are compared with the Arctic System Reanalysis (ASR) to better understand deficiencies in simulated clouds. ASR produces too little cloud water, which coincides with being too warm and dry. In addition, ASR struggles to produce cloud water even in favorable thermodynamic conditions. A random sampling experiment also shows the effects of the limited aircraft sampling on the results.
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
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In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
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Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. 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 times. The new model has the potential to study large-scale impacts of aerosol changes.
Senna Bouabdelli, Ayoub Zeroual, Mohamed Meddi, Fateh Djelloul, and Ramdane Alkama
Proc. IAHS, 383, 315–318, https://doi.org/10.5194/piahs-383-315-2020, https://doi.org/10.5194/piahs-383-315-2020, 2020
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The temporal evolution of drought events characteristics is discussed.
Data from observations and simulations of the regional climate model RCA4 MPI-ESM-LR under two Representative Concentration Pathways (RCPs) scenarios for the period (1941–2100) are used. An amplification of drought frequencies is projected in the future under the RCP8.5 scenario. The maximum duration is expected to hardly change under the RCP8.5 scenario or even to decline.
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, Victor Estella-Perez, Christian Ethé, Frédéric Fluteau, Marie-Alice Foujols, Guillaume Gastineau, Josefine Ghattas, Didier Hauglustaine, Frédéric Hourdin, Masa Kageyama, Myriam Khodri, Olivier Marti, Yann Meurdesoif, Juliette Mignot, Anta-Clarisse Sarr, Jérôme Servonnat, Didier Swingedouw, Sophie Szopa, and Delphine Tardif
Geosci. Model Dev., 13, 3011–3053, https://doi.org/10.5194/gmd-13-3011-2020, https://doi.org/10.5194/gmd-13-3011-2020, 2020
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Our paper describes IPSL-CM5A2, an Earth system model that can be integrated for long (several thousands of years) climate simulations. We describe the technical aspects, assess the model computing performance and evaluate the strengths and weaknesses of the model, by comparing pre-industrial and historical runs to the previous-generation model simulations and to observations. We also present a Cretaceous simulation as a case study to show how the model simulates deep-time paleoclimates.
Gregory Duveiller, Federico Filipponi, Sophia Walther, Philipp Köhler, Christian Frankenberg, Luis Guanter, and Alessandro Cescatti
Earth Syst. Sci. Data, 12, 1101–1116, https://doi.org/10.5194/essd-12-1101-2020, https://doi.org/10.5194/essd-12-1101-2020, 2020
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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.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 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.
Simon Michel, Didier Swingedouw, Marie Chavent, Pablo Ortega, Juliette Mignot, and Myriam Khodri
Geosci. Model Dev., 13, 841–858, https://doi.org/10.5194/gmd-13-841-2020, https://doi.org/10.5194/gmd-13-841-2020, 2020
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Natural archives such as sediments, ice, tree rings or speleothems provide indirect observations of past climate at local and regional scales. In this paper, we provide a computational device to properly make evaluated reconstructions of climate indices using these paleo-data. It provides optimizing cross-validation algorithms and four regression methods that are applied to the reconstruction of the North Atlantic Oscillation index and compared in this study.
Giovanni Forzieri, Matteo Pecchi, Marco Girardello, Achille Mauri, Marcus Klaus, Christo Nikolov, Marius Rüetschi, Barry Gardiner, Julián Tomaštík, David Small, Constantin Nistor, Donatas Jonikavicius, Jonathan Spinoni, Luc Feyen, Francesca Giannetti, Rinaldo Comino, Alessandro Wolynski, Francesco Pirotti, Fabio Maistrelli, Ionut Savulescu, Stéphanie Wurpillot-Lucas, Stefan Karlsson, Karolina Zieba-Kulawik, Paulina Strejczek-Jazwinska, Martin Mokroš, Stefan Franz, Lukas Krejci, Ionel Haidu, Mats Nilsson, Piotr Wezyk, Filippo Catani, Yi-Ying Chen, Sebastiaan Luyssaert, Gherardo Chirici, Alessandro Cescatti, and Pieter S. A. Beck
Earth Syst. Sci. Data, 12, 257–276, https://doi.org/10.5194/essd-12-257-2020, https://doi.org/10.5194/essd-12-257-2020, 2020
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Strong winds may uproot and break trees and represent a risk for forests. Despite the importance of this natural disturbance and possible intensification in view of climate change, spatial information about wind-related impacts is currently missing on a pan-European scale. We present a new database of wind disturbances in European forests comprised of more than 80 000 records over the period 2000–2018. Our database is a unique spatial source for the study of forest disturbances at large scales.
Pierre Sabatier, Marie Nicolle, Christine Piot, Christophe Colin, Maxime Debret, Didier Swingedouw, Yves Perrette, Marie-Charlotte Bellingery, Benjamin Chazeau, Anne-Lise Develle, Maxime Leblanc, Charlotte Skonieczny, Yoann Copard, Jean-Louis Reyss, Emmanuel Malet, Isabelle Jouffroy-Bapicot, Maëlle Kelner, Jérôme Poulenard, Julien Didier, Fabien Arnaud, and Boris Vannière
Clim. Past, 16, 283–298, https://doi.org/10.5194/cp-16-283-2020, https://doi.org/10.5194/cp-16-283-2020, 2020
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High-resolution multiproxy analysis of sediment core from a high-elevation lake on Corsica allows us to reconstruct past African dust inputs to the western Mediterranean area over the last 3 millennia. Millennial variations of Saharan dust input have been correlated with the long-term southward migration of the Intertropical Convergence Zone, while short-term variations were associated with the North Atlantic Oscillation and total solar irradiance after and before 1070 cal BP, respectively.
Johannes Winckler, Christian H. Reick, Sebastiaan Luyssaert, Alessandro Cescatti, Paul C. Stoy, Quentin Lejeune, Thomas Raddatz, Andreas Chlond, Marvin Heidkamp, and Julia Pongratz
Earth Syst. Dynam., 10, 473–484, https://doi.org/10.5194/esd-10-473-2019, https://doi.org/10.5194/esd-10-473-2019, 2019
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For local living conditions, it matters whether deforestation influences the surface temperature, temperature at 2 m, or the temperature higher up in the atmosphere. Here, simulations with a climate model show that at a location of deforestation, surface temperature generally changes more strongly than atmospheric temperature. Comparison across climate models shows that both for summer and winter the surface temperature response exceeds the air temperature response locally by a factor of 2.
Patrick C. Taylor, Robyn C. Boeke, Ying Li, and David W. J. Thompson
Atmos. Chem. Phys., 19, 8759–8782, https://doi.org/10.5194/acp-19-8759-2019, https://doi.org/10.5194/acp-19-8759-2019, 2019
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Climate projections disagree more in the rapidly changing Arctic than anywhere else. The impact of a changing Arctic spans food and water security, economics, national security, etc. The representation of Arctic clouds within climate models is a critical roadblock towards improving Arctic climate projections. We explore the potential drivers of the diverse representation of the Arctic cloud annual cycle within climate models providing evidence that microphysical processes are a key driver.
Sophia Walther, Luis Guanter, Birgit Heim, Martin Jung, Gregory Duveiller, Aleksandra Wolanin, and Torsten Sachs
Biogeosciences, 15, 6221–6256, https://doi.org/10.5194/bg-15-6221-2018, https://doi.org/10.5194/bg-15-6221-2018, 2018
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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.
Gregory Duveiller, Giovanni Forzieri, Eddy Robertson, Wei Li, Goran Georgievski, Peter Lawrence, Andy Wiltshire, Philippe Ciais, Julia Pongratz, Stephen Sitch, Almut Arneth, and Alessandro Cescatti
Earth Syst. Sci. Data, 10, 1265–1279, https://doi.org/10.5194/essd-10-1265-2018, https://doi.org/10.5194/essd-10-1265-2018, 2018
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Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate. While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.
J. Brant Dodson, Patrick C. Taylor, and Mark Branson
Atmos. Chem. Phys., 18, 6493–6510, https://doi.org/10.5194/acp-18-6493-2018, https://doi.org/10.5194/acp-18-6493-2018, 2018
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The vertical profiles of convection in the Amazon are sampled using CloudSat, with particular emphasis on day–night contrast. Focusing on vigorous deep convective cores reveals a distinct, previously unreported double-arc reflectivity feature in the contoured frequency by altitude diagram, likely corresponding with two modes of ice hydrometeor phase: snow versus graupel/hail. Replicating this feature in cloud-resolving models requires further improvements in the microphysical parameterization.
Nathaelle Bouttes, Didier Swingedouw, Didier M. Roche, Maria F. Sanchez-Goni, and Xavier Crosta
Clim. Past, 14, 239–253, https://doi.org/10.5194/cp-14-239-2018, https://doi.org/10.5194/cp-14-239-2018, 2018
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Atmospheric CO2 is key for climate change. CO2 is lower during the oldest warm period of the last million years, the interglacials, than during the most recent ones (since 430 000 years ago). This difference has not been explained yet, but could be due to changes of ocean circulation. We test this hypothesis and the role of vegetation and ice sheets using an intermediate complexity model. We show that only small changes of CO2 can be obtained, underlying missing feedbacks or mechanisms.
Barbara Marcolla, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 14, 3815–3829, https://doi.org/10.5194/bg-14-3815-2017, https://doi.org/10.5194/bg-14-3815-2017, 2017
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Patterns and controls of the inter-annual variability of carbon net ecosystem exchange were analysed using three different data streams: ecosystem-level observations (FLUXNET database), a global upscaling of site-level fluxes (MPI-MTE), and a top–down estimate of fluxes (Jena CarboScope Inversion). 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.
Zhiyuan Zhang, Renduo Zhang, Yang Zhou, Alessandro Cescatti, Georg Wohlfahrt, Minmin Sun, Juan Zhu, Vincenzo Magliulo, Feng Tao, and Guanhong Chen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-345, https://doi.org/10.5194/bg-2017-345, 2017
Manuscript not accepted for further review
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This study highlight the key role of temperature as main controlling factor of the maximum respiration rates in most terrestrial ecosystems, while other driving forces reduce the maximum respiration rates and temperature sensitivity of the respiratory process. These findings are particularly relevant under the current scenario of rapid global warming, given that the potential climate-induced changes in ecosystem respiration may lead to substantial anomalies in terrestrial carbon budget.
Mélanie Wary, Frédérique Eynaud, Didier Swingedouw, Valérie Masson-Delmotte, Jens Matthiessen, Catherine Kissel, Jena Zumaque, Linda Rossignol, and Jean Jouzel
Clim. Past, 13, 729–739, https://doi.org/10.5194/cp-13-729-2017, https://doi.org/10.5194/cp-13-729-2017, 2017
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The last glacial period was punctuated by abrupt climatic variations, whose cold atmospheric phases have been commonly associated with cold sea-surface temperatures and expansion of sea ice in the North Atlantic and adjacent seas. Here we provide direct evidence of a regional paradoxical see-saw pattern: cold Greenland and North Atlantic phases coincide with warmer sea-surface conditions and shorter seasonal sea-ice cover durations in the Norwegian Sea as compared to warm phases.
Roberto Pilli, Giacomo Grassi, Werner A. Kurz, Giulia Fiorese, and Alessandro Cescatti
Biogeosciences, 14, 2387–2405, https://doi.org/10.5194/bg-14-2387-2017, https://doi.org/10.5194/bg-14-2387-2017, 2017
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We modeled, for 26 European countries, the C budget and fluxes of the main forest pools from 2000 to 2030 under different management scenarios. Our findings show an incipient aging process for the existing forests, but specific conditions, such as the harvest rate and the current age structure, may have different impacts on the country-specific evolution of biomass stock. This provides a useful framework for more detailed analyses of the mitigation potential of the forest sector.
Mark J. Webb, Timothy Andrews, Alejandro Bodas-Salcedo, Sandrine Bony, Christopher S. Bretherton, Robin Chadwick, Hélène Chepfer, Hervé Douville, Peter Good, Jennifer E. Kay, Stephen A. Klein, Roger Marchand, Brian Medeiros, A. Pier Siebesma, Christopher B. Skinner, Bjorn Stevens, George Tselioudis, Yoko Tsushima, and Masahiro Watanabe
Geosci. Model Dev., 10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, https://doi.org/10.5194/gmd-10-359-2017, 2017
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The Cloud Feedback Model Intercomparison Project (CFMIP) aims to improve understanding of cloud-climate feedback mechanisms and evaluation of cloud processes and cloud feedbacks in climate models. CFMIP also aims to improve understanding of circulation, regional-scale precipitation and non-linear changes. CFMIP is contributing to the 6th phase of the Coupled Model Intercomparison Project (CMIP6) by coordinating a hierarchy of targeted experiments with cloud-related model outputs.
Alessandro Cescatti, Barbara Marcolla, Ignacio Goded, and Carsten Gruening
Atmos. Meas. Tech., 9, 4665–4672, https://doi.org/10.5194/amt-9-4665-2016, https://doi.org/10.5194/amt-9-4665-2016, 2016
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Multi-point monitoring systems are required to measure atmospheric gas concentrations at tall towers and eddy covariance sites. The use of buffer volumes can reduce the uncertainty due to the discrete temporal sampling. We propose a processing scheme that accounts for the fraction of signal built up in the averaging period and reduces the error up to 80 % compared to the standard setup. A relationship is derived to estimate the optimal volume size given the specifications of the sampling system.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale
Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, https://doi.org/10.5194/bg-13-4291-2016, 2016
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We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) 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).
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
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This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, D. Carrer, H. Verbeeck, M. De Weirdt, and D. Bonal
Geosci. Model Dev., 8, 1709–1727, https://doi.org/10.5194/gmd-8-1709-2015, https://doi.org/10.5194/gmd-8-1709-2015, 2015
L. Alfieri, P. Burek, L. Feyen, and G. Forzieri
Hydrol. Earth Syst. Sci., 19, 2247–2260, https://doi.org/10.5194/hess-19-2247-2015, https://doi.org/10.5194/hess-19-2247-2015, 2015
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This work presents, to our best knowledge, the first pan-European assessment of the future hydro-meteorological hazard based on an ensemble of the new EURO-CORDEX regional climate scenarios.
We propose a novel approach, which shows how the change in the frequency of future floods in Europe is likely to have a larger impact on the overall flood hazard as compared to the change in their magnitude.
A consistent method is proposed to evaluate the agreement of ensemble projections.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir
Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, https://doi.org/10.5194/gmd-7-2933-2014, 2014
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014, https://doi.org/10.5194/gmd-7-2581-2014, 2014
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A consistent calibration of an advanced land surface model was performed by grouping in situ information on land-atmosphere exchanges of carbon and water using broad ecosystem and climate classes. Signatures of improved carbon cycle simulations were found across spatial and temporal scales, along with insights into current model limitations. These results hold promising perspectives within the ongoing efforts towards building robust model-data fusion frameworks for earth system models.
M. Verma, M. A. Friedl, A. D. Richardson, G. Kiely, A. Cescatti, B. E. Law, G. Wohlfahrt, B. Gielen, O. Roupsard, E. J. Moors, P. Toscano, F. P. Vaccari, D. Gianelle, G. Bohrer, A. Varlagin, N. Buchmann, E. van Gorsel, L. Montagnani, and P. Propastin
Biogeosciences, 11, 2185–2200, https://doi.org/10.5194/bg-11-2185-2014, https://doi.org/10.5194/bg-11-2185-2014, 2014
G. Forzieri, L. Feyen, R. Rojas, M. Flörke, F. Wimmer, and A. Bianchi
Hydrol. Earth Syst. Sci., 18, 85–108, https://doi.org/10.5194/hess-18-85-2014, https://doi.org/10.5194/hess-18-85-2014, 2014
E. Joetzjer, H. Douville, C. Delire, P. Ciais, B. Decharme, and S. Tyteca
Hydrol. Earth Syst. Sci., 17, 4885–4895, https://doi.org/10.5194/hess-17-4885-2013, https://doi.org/10.5194/hess-17-4885-2013, 2013
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-5475-2013, https://doi.org/10.5194/gmdd-6-5475-2013, 2013
Revised manuscript not accepted
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
R. Séférian, L. Bopp, D. Swingedouw, and J. Servonnat
Earth Syst. Dynam., 4, 109–127, https://doi.org/10.5194/esd-4-109-2013, https://doi.org/10.5194/esd-4-109-2013, 2013
M. Casado, P. Ortega, V. Masson-Delmotte, C. Risi, D. Swingedouw, V. Daux, D. Genty, F. Maignan, O. Solomina, B. Vinther, N. Viovy, and P. Yiou
Clim. Past, 9, 871–886, https://doi.org/10.5194/cp-9-871-2013, https://doi.org/10.5194/cp-9-871-2013, 2013
P. Ortega, M. Montoya, F. González-Rouco, H. Beltrami, and D. Swingedouw
Clim. Past, 9, 547–565, https://doi.org/10.5194/cp-9-547-2013, https://doi.org/10.5194/cp-9-547-2013, 2013
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Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, https://doi.org/10.5194/bg-9-5243-2012, 2012
Related subject area
Discipline: Sea ice | Subject: Climate Interactions
Forced and internal components of observed Arctic sea-ice changes
Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations
The contribution of melt ponds to enhanced Arctic sea-ice melt during the Last Interglacial
Analyzing links between simulated Laptev Sea sea ice and atmospheric conditions over adjoining landmasses using causal-effect networks
Jakob Simon Dörr, David B. Bonan, Marius Årthun, Lea Svendsen, and Robert C. J. Wills
The Cryosphere, 17, 4133–4153, https://doi.org/10.5194/tc-17-4133-2023, https://doi.org/10.5194/tc-17-4133-2023, 2023
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The Arctic sea-ice cover is retreating due to climate change, but this retreat is influenced by natural (internal) variability in the climate system. We use a new statistical method to investigate how much internal variability has affected trends in the summer and winter Arctic sea-ice cover using observations since 1979. Our results suggest that the impact of internal variability on sea-ice retreat might be lower than what climate models have estimated.
William Gregory, Julienne Stroeve, and Michel Tsamados
The Cryosphere, 16, 1653–1673, https://doi.org/10.5194/tc-16-1653-2022, https://doi.org/10.5194/tc-16-1653-2022, 2022
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This research was conducted to better understand how coupled climate models simulate one of the large-scale interactions between the atmosphere and Arctic sea ice that we see in observational data, the accurate representation of which is important for producing reliable forecasts of Arctic sea ice on seasonal to inter-annual timescales. With network theory, this work shows that models do not reflect this interaction well on average, which is likely due to regional biases in sea ice thickness.
Rachel Diamond, Louise C. Sime, David Schroeder, and Maria-Vittoria Guarino
The Cryosphere, 15, 5099–5114, https://doi.org/10.5194/tc-15-5099-2021, https://doi.org/10.5194/tc-15-5099-2021, 2021
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The Hadley Centre Global Environment Model version 3 (HadGEM3) is the first coupled climate model to simulate an ice-free summer Arctic during the Last Interglacial (LIG), 127 000 years ago, and yields accurate Arctic surface temperatures. We investigate the causes and impacts of this extreme simulated ice loss and, in particular, the role of melt ponds.
Zoé Rehder, Anne Laura Niederdrenk, Lars Kaleschke, and Lars Kutzbach
The Cryosphere, 14, 4201–4215, https://doi.org/10.5194/tc-14-4201-2020, https://doi.org/10.5194/tc-14-4201-2020, 2020
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To better understand the connection between sea ice and permafrost, we investigate how sea ice interacts with the atmosphere over the adjacent landmass in the Laptev Sea region using a climate model. Melt of sea ice in spring is mainly controlled by the atmosphere; in fall, feedback mechanisms are important. Throughout summer, lower-than-usual sea ice leads to more southward transport of heat and moisture, but these links from sea ice to the atmosphere over land are weak.
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Short summary
The amount of solar energy absorbed by Earth is believed to strongly depend on clouds. Here, we investigate this relationship using satellite data and 32 climate models, showing that this relationship holds everywhere except over polar seas, where an increased reflection by clouds corresponds to an increase in absorbed solar radiation at the surface. This interplay between clouds and sea ice reduces by half the increase of net radiation at the surface that follows the sea ice retreat.
The amount of solar energy absorbed by Earth is believed to strongly depend on clouds. Here, we...
