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1. Climate-driven variability of the Southern Ocean CO 2 sink

Author

N. Mayot, C. Le Quéré, C. Rödenbeck, R. Bernardello, L. Bopp, L. M. Djeutchouang, M. Gehlen, L. Gregor, N. Gruber, J. Hauck, Y. Iida, T. Ilyina, R. F. Keeling, P. Landschützer, A. C. Manning, L. Patara, L. Resplandy, J. Schwinger, R. Séférian, A. J. Watson, R. M. Wright, J. Zeng, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), National Oceanic and Atmospheric Administration, NOAA: NA20OAR4320278, OPP-1922922, Horizon 2020 Framework Programme, H2020: 820989, 821003, Natural Environment Research Council, NERC: NE/P021417/1, Royal Society: RPR1191063, University of East Anglia, UEA, European Commission, EC, Deutsche Forschungsgemeinschaft, DFG: PA 3075/2-1, Eidgenössische Technische Hochschule Zürich, ETH: 101003536, Norges Forskningsråd: 270061, Helmholtz Association: VH-NG-1301, Neurosciences Foundation, NSF, N.M., C.L.Q., R.B., N.G., L.G. and A.C.M. acknowledge the funding from the European Commission through the H2020 project 4C (grant no. 821003). J.H., L.G., M.G. and N.G. acknowledge the funding from the European Commission through the H2020 project COMFORT project (grant no. 820989). C.L.Q. was funded by the UK Royal Society (grant no. RPR1191063). N.M. and R.M.W. were funded by UK's Natural Environment Research Council (SONATA: grant no. NE/P021417/1). J.S. received funding from the Research Council of Norway through project INES (grant no. 270061) and HPC resources provided by the National Infrastructure for HPC and Data Storage in Norway, UNINETT Sigma2 (grant no. nn/ns2980k). L.R. acknowledges the Princeton University Catalysis Initiative. N.G. and L.G. acknowledge funding from ETH Zürich. M.G. and R.S. acknowledge the ESM2025 project under the grant agreement number 101003536. M.G. also acknowledges funding from the European Union's Horizon 2020 Blue Growth research and innovation programme under grant agreement number 862923 (project AtlantECO). J.H. acknowledges support by the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem Feedbacks in the Earth System [MarESys], grant number VH-NG-1301). The integration of the ORCA025-GEOMAR experiment was performed at the North German Supercomputing Alliance (HLRN) and was financially supported by the German Research Foundation (project PA 3075/2-1). The APO measurements were supported by a series of grants to the Scripps Institution of Oceanography from the US NSF and NOAA, most recently OPP-1922922 and NA20OAR4320278. Acknowledgements, and Thanks to Erik Buitenhuis and David Willis for their work on the NEMO-PlankTOM12 model development. The research presented in this paper was carried out on the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia.

Subjects
[PHYS]Physics [physics], carbon sink, General Mathematics, General Engineering, General Physics and Astronomy, Southern ocean, Carbon sink, Climate, Oxygen, Interannual, interannual, Southern Ocean, decadal, climate, oxygen
Abstract

The Southern Ocean is a major sink of atmospheric CO2, but the nature and magnitude of its variability remains uncertain and debated. Estimates based on observations suggest substantial variability that is not reproduced by process-based ocean models, with increasingly divergent estimates over the past decade. We examine potential constraints on the nature and magnitude of climate-driven variability of the Southern Ocean CO2 sink from observation-based air-sea O2 fluxes. On interannual time scales, the variability in the air-sea fluxes of CO2 and O2 estimated from observations is consistent across the two species and positively correlated with the variability simulated by ocean models. Our analysis suggests that variations in ocean ventilation related to the Southern Annular Mode are responsible for this interannual variability. On decadal time scales, the existence of significant variability in the air-sea CO2 flux estimated from observations also tends to be supported by observation-based estimates of O2 flux variability. However, the large decadal variability in air-sea CO2 flux is absent from ocean models. Our analysis suggests that issues in representing the balance between the thermal and non-thermal components of the CO2 sink and/or insufficient variability in mode water formation might contribute to the lack of decadal variability in the current generation of ocean models. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'., Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 381 (2249), ISSN:1364-503X, ISSN:1471-2962

Published
2023

2. Correlating Indoor and Outdoor Temperature and Humidity in a Sample of Buildings in Tropical Climates

Author

Linsey C. Marr, Miguela A. Caniza, Hong Kai Lee, Alejandra Nava Ruiz, Yuguo Li, Julian Tang, Chun Kiat Lee, Carlos Francisco Santillan-Salas, Jean-Michel Heraud, Jin Pan, Evelyn Siew-Chuan Koay, Virginia Tech [Blacksburg], University of Leicester, St Jude Children's Research Hospital, Unité de Virologie [Antananarivo, Madagascar] (IPM), Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), National University of Singapore (NUS), Agency for science, technology and research [Singapore] (A*STAR), National University Health System [Singapore] (NUHS), The University of Hong Kong (HKU), Hospital de Especialidades Pediátricas, Instituto Nacional de Salud del Niño San Borja, This research was supported by a grant from the Alfred P. Sloan Foundation as part of its Microbiology of the Built Environment program. The authors thank Kaisen Lin for helpful discussions, Julia Gohlke, Archit Manuja, and AJ Prussin II for handling sensors, and and the reviewers for their detailed feedback that helped strengthen this paper.

Subjects
Wet season, bepress|Engineering|Civil and Environmental Engineering|Environmental Engineering, Environmental Engineering, 010504 meteorology & atmospheric sciences, bepress|Engineering, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, complex mixtures, outdoor, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, engrXiv|Engineering|Civil and Environmental Engineering, medicine, Temperate climate, Relative humidity, indoor, climate, 0105 earth and related environmental sciences, Tropical Climate, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, engrXiv|Engineering|Civil and Environmental Engineering|Environmental Engineering, business.industry, Public Health, Environmental and Occupational Health, humidity, Humidity, Tropics, temperature, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, Building and Construction, Seasonality, medicine.disease, respiratory virus, engrXiv|Engineering, bepress|Engineering|Civil and Environmental Engineering, 13. Climate action, Air conditioning, Air Pollution, Indoor, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Respiratory virus, Environmental science, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Seasons, business
Abstract

Posté sur engrXiv le 13 juin 2021.; The incidence of several respiratory viral infections has been shown to be related to climate. Because humans spend most of their time indoors, measures of indoor climate, rather than outdoor climate, may be better predictors of disease incidence and transmission. Therefore, understanding the relationship between indoor and outdoor climate will help illuminate their influence on the seasonality of diseases caused by respiratory viruses. Indoor-outdoor relationships between temperature and humidity have been documented in temperate regions, but little information is available for tropical regions, where seasonal patterns of respiratory viral diseases differ. We have examined indoor-outdoor correlations of temperature, relative humidity (RH), and absolute humidity (AH) over a 1-year period in each of seven tropical cities. Across all cities, the average monthly indoor temperature was 25±3°C (mean ± standard deviation) with a range of 20–30°C. The average monthly indoor RH was 669% with a range of 50–78%, and the average monthly indoor AH was 153 g/m3 with a range of 10–23 g/m3. Indoor AH and RH were linearly correlated with outdoor AH when the air-conditioning (AC) was off, suggesting that outdoor AH may be a good proxy of indoor humidity in the absence of AC. All indoor measurements were more strongly correlated with outdoor measurements as distance from the equator increased. Such correlations were weaker during the wet season, especially when AC was in operation. These correlations will provide insight for assessing the seasonality of respiratory viral infections using outdoor climate data, which is more widely available than indoor data, even though transmission of these diseases mainly occurs indoors.

Published
2021

3. Diversity of leaf unfolding dynamics among tree species: New insights from a study along an altitudinal gradient

Author

Hendrik Davi, M. Gillmann, Aurore Bontemps, François Lefèvre, Thomas Ibanez, Maxime Cailleret, Bruno Fady, Ecologie des Forêts Méditerranéennes (URFM), Institut National de la Recherche Agronomique (INRA), and We thank the INRA Experimental Unit UEFM (UE348) for the field work, in particular: Frederic Jean, Norbert Turion, Olivier Gilg and Franck Rei. We also thank Julia Fady, our American proof-reader and the two anonymous reviewers that have helped us to clarify the paper. We also thank the editor and ECOGER fundings and the Isabelle Chuine who drives the GDR SIP-GECC.

Subjects
0106 biological sciences, Atmospheric Science, budburst, Quercus pubescens, 010603 evolutionary biology, 01 natural sciences, phenology, leaf unfolding, Fagus sylvatica, meteorology and atmospheric sciences, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, Botany, Sorbus aria, Shade tolerance, climate, Global and Planetary Change, biology, Phenology, Ecology, agronomy, forestry, temperature, 15. Life on land, Evergreen, biology.organism_classification, Abies alba, tree, Deciduous, altitudinal gradient, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

Leaf unfolding is a key ecosystem parameter controlling carbon and water fluxes and affecting forest dynamics. This parameter is highly sensitive to temperature and, consequently, often used as an indicator of global change. In this paper, we analyzed weekly leaf unfolding dynamics for seven temperate species ( Fagus sylvatica L., Acer opalus Mill., Sorbus aria L., Quercus pubescens Willd. Abies alba Mill., Pinus sylvestris L., Pinus nigra Arnold). The effects of temperature on leaf unfolding were studied in situ using several methods and proxies. First, in a spatial approach, leaf unfolding dates were measured along two altitudinal gradients situated on the north and south face of the Mont Ventoux to test altitudinal and slope effects. Second, in a temporal approach, the year effect was analyzed on the north face by comparing two contrasted years (2006 and 2007). Finally, the role of temperature was investigated directly by linking leaf unfolding patterns and temperatures recorded during the leaf unfolding process itself. Two major conclusions were obtained. First, three distinct leaf unfolding patterns were revealed: a rapid sigmoid pattern for the deciduous species group, a slow kinetic pattern for the pines and an intermediate pattern for A. alba . Second, we found an unexpected pattern of variation in the response to spatial or temporal variation of temperature. The more sensitive a species was to temperature variations between years, the less sensitive it was to temperature variations due to altitude. Finally, we discuss that these results can be correlated to two major life history traits: evergreen vs. deciduous and shade tolerant vs. shade intolerant.

Published
2011