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Global Climate [in “State of the Climate in 2019"] / A. Ades in Bulletin of the American Meteorological Society, vol 101 n° 8 (August 2020)  

Public [article]  inBulletin of the American Meteorological Society > vol 101 n° 8 (August 2020) . - pp S9 - S128 Titre : Global Climate [in “State of the Climate in 2019"] Type de document : Article/Communication Auteurs : A. Ades, Auteur ; R. Adler, Auteur ; et al., Auteur ; Olivier Bock , Auteur Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : pp S9 - S128 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Atmosphère [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] circulation atmosphérique [Termes descripteurs IGN] climat terrestre [Termes descripteurs IGN] cryosphère [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] gaz à effet de serre [Termes descripteurs IGN] humidité de l'air [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] température de l'air Résumé : (auteur) [introduction] The assessments and analyses presented in this chapter focus predominantly on the measured differences of climate and weather observables from previous conditions, years, and decades to place 2019 in context. Many of these differences have direct impacts on people, for example, their health and environment, as well as the wider biosphere, but are beyond the scope of these analyses. For the last few State of the Climate reports, an update on the number of warmer-than-average years has held no surprises, and this year is again no different. The year 2019 was among the three warmest years since records began in the mid-to-late 1800s. Only 2016, and for some datasets 2015, were warmer than 2019; all years after 2013 have been warmer than all others back to the mid-1800s. Each decade since 1980 has been successively warmer than the preceding decade, with the most recent (2010–19) being around 0.2°C warmer than the previous (2000–09). This warming of the land and ocean surface is reflected across the globe. For example, lake and permafrost temperatures have increased; glaciers have continued to lose mass, becoming thinner for the 32nd consecutive year, with the majority also becoming shorter during 2019. The period during which Northern Hemisphere (NH) lakes were covered in ice was seven days shorter than the 1981–2010 long-term average, based on in situ phenological records. There were fewer cool extremes and more warm extremes on land; regions including Europe, Japan, Pakistan, and India all experienced heat waves. More strong than moderate marine heat waves were recorded for the sixth consecutive year. And in Australia (discussed in more detail in section 7h4), moisture deficits and prolonged high temperatures led to severe impacts during late austral spring and summer, including devastating wildfires. Smoke from these wildfires was detected across large parts of the Southern Hemisphere (SH). [...] Numéro de notice : A2020-798 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1175/BAMS-D-20-0104.1 date de publication en ligne : 12/08/2020 En ligne : https://doi.org/10.1175/BAMS-D-20-0104.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96582 [article]

Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)  

Public [article]  inForest ecology and management > Vol 466 (15 June 2020) Titre : Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada Type de document : Article/Communication Auteurs : Wushuang Li, Auteur ; John A. Kershaw, Auteur ; Kara K. L. Costanza, Auteur ; Anthony R. Taylor, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] azote [Termes descripteurs IGN] Canada [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] Picea rubens [Termes descripteurs IGN] température de l'air [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Numéro de notice : A2020-407 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118139 date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118139 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95464 [article]

Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 88 (June 2020) . - 10 p. Titre : Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data Type de document : Article/Communication Auteurs : Rochelle Schneider dos Santos, Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme du gradient [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] chaleur [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] Londres [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] politique publique [Termes descripteurs IGN] Python (langage de programmation) [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] santé [Termes descripteurs IGN] station météorologique [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] température de l'air [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Urbanisation generates greater population densities and an increase in anthropogenic heat generation. These factors elevate the urban–rural air temperature (Ta) difference, thus generating the Urban Heat Island (UHI) phenomenon. Ta is used in the fields of public health and epidemiology to quantify deaths attributable to heat in cities around the world: the presence of UHI can exacerbate exposure to high temperatures during summer periods, thereby increasing the risk of heat-related mortality. Measuring and monitoring the spatial patterns of Ta in urban contexts is challenging due to the lack of a good network of weather stations. This study aims to produce a parsimonious model to retrieve maximum Ta (Tmax) at high spatio-temporal resolution using Earth Observation (EO) satellite data. The novelty of this work is twofold: (i) it will produce daily estimations of Tmax for London at 1 km2 during the summertime between 2006 and 2017 using advanced statistical techniques and satellite-derived predictors, and (ii) it will investigate for the first time the predictive power of the gradient boosting algorithm to estimate Tmax for an urban area. In this work, 6 regression models were calibrated with 6 satellite products, 3 geospatial features, and 29 meteorological stations. Stepwise linear regression was applied to create 9 groups of predictors, which were trained and tested on each regression method. This study demonstrates the potential of machine learning algorithms to predict Tmax: the gradient boosting model with a group of five predictors (land surface temperature, Julian day, normalised difference vegetation index, digital elevation model, solar zenith angle) was the regression model with the best performance (R² = 0.68, MAE = 1.60 °C, and RMSE = 2.03 °C). This methodological approach is capable of being replicated in other UK cities, benefiting national heat-related mortality assessments since the data (provided by NASA and the UK Met Office) and programming languages (Python) sources are free and open. This study provides a framework to produce a high spatio-temporal resolution of Tmax, assisting public health researchers to improve the estimation of mortality attributable to high temperatures. In addition, the research contributes to practice and policy-making by enhancing the understanding of the locations where mortality rates may increase due to heat. Therefore, it enables a more informed decision-making process towards the prioritisation of actions to mitigate heat-related mortality amongst the vulnerable population. Numéro de notice : A2020-448 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2020.102066 date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102066 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95524 [article]

Impact of precipitation, air temperature and abiotic emissions on gross primary production in Mediterranean ecosystems in Europe / S. Bartsch in European Journal of Forest Research, vol 139 n° 1 (February 2020)  

Public [article]  inEuropean Journal of Forest Research > vol 139 n° 1 (February 2020) Titre : Impact of precipitation, air temperature and abiotic emissions on gross primary production in Mediterranean ecosystems in Europe Type de document : Article/Communication Auteurs : S. Bartsch, Auteur ; A.I. Stegehuis, Auteur ; C. Boissard, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] climat méditerranéen [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] Europe (géographie politique) [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] puits de carbone [Termes descripteurs IGN] température de l'air [Termes descripteurs IGN] teneur en carbone [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Mediterranean ecosystems are significant carbon sinks and are particularly sensitive to climate change. However, the carbon dynamics in such ecosystems are still not fully understood. An improved understanding of the drivers of carbon fixation by vegetation is needed to better predict how these ecosystems will respond to climate change. In this study, a large dataset collected through the FLUXNET network is used to estimate how the gross primary production (GPP) of different Mediterranean ecosystems was affected by air temperature and precipitation between 1996 and 2013. We showed that annual precipitation and temperature were not significant drivers of annual GPP. However, inter-annual variations of GPP seemed largely controlled by the precipitation during early spring (March–April). Late spring and early summer temperature also had a positive effect on annual GPP. We furthermore show that GPP may also have been influenced by both summer rainfall pulses and abiotic emissions due to carbonates precipitation/dissolution. Finally, the sensitivity of GPP in the Mediterranean region to climate drivers seemed not to be ecosystem-type dependent. Our results can provide general information for modeling exercises and improve future biomass projections on a regional scale. Numéro de notice : A2020-228 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-019-01246-7 date de publication en ligne : 30/11/2019 En ligne : https://doi.org/10.1007/s10342-019-01246-7 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94965 [article]

Co-visualization of air temperature and urban data for visual exploration / Jacques Gautier (2020) 

Public Titre : Co-visualization of air temperature and urban data for visual exploration Type de document : Article/Communication Auteurs : Jacques Gautier , Auteur ; Mathieu Brédif , Auteur ; Sidonie Christophe , Auteur Congrès : Congrès: IEEE VIS 2020, (VAST, INFOVIS, SCIVIS) premier forum for advances in visualization and visual analytics (25 - 30 October 2020; Virtuel) , Commanditaire Editeur : New-York : IEEE Computer society Année de publication : 2020 Projets : URCLIM / Masson, Valéry Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] exploration de données géographiques [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] modèle 3D de l'espace urbain [Termes descripteurs IGN] morphologie urbaine [Termes descripteurs IGN] rendu (géovisualisation) [Termes descripteurs IGN] représentation graphique [Termes descripteurs IGN] température de l'air [Termes descripteurs IGN] visualisation 3D [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Urban climate data remain complex to analyze regarding their spatial distribution. The co-visualization of simulated air temperature into urban models could help experts to analyze horizontal and vertical spatial distributions. We design a co-visualization framework enabling simulated air temperature data exploration, based on the graphic representation of three types of geometric proxies, and their co-visualization with a 3D urban model with various possible rendering styles. Through this framework, we aim at allowing meteorological researchers to visually analyze and interpret the relationships between simulated air temperature data and urban morphology. Numéro de notice : C2020-005 Affiliation des auteurs : LaSTIG (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : en attente Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96161

Documents numériques

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Visualizing 3D climate data in urban 3D models / Jacques Gautier (2020)  

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Increasing temperatures over an 18-year period shortens growing season length in a beech (Fagus sylvatica L.)-dominated forest / Quentin Hurdebise in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)  

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Couplings in cell differentiation kinetics mitigate air temperature influence on conifer wood anatomy / Henri Cuny in Plant, cell & environment, vol 42 n° 4 (April 2019)  

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Impact of humidity biases on light precipitation occurrence: observations versus simulations / Sophie Bastin in Atmospheric chemistry and physics, vol 19 n° 3 (February 2019)  

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A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis / Xiya Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)  

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La combinaison de l'image satellitaire avec les données citoyennes pour la mesure de l'ïlot de chaleur urbain : Premiers résultats sur la métropole de Lyon / Florent Renard in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 22 n° 5 (septembre - octobre 2017)  

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Displacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data / Qihuan Huang in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

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Statistical atmospheric parameter retrieval largely benefits from spatial–spectral image compression / Joaquín García-Sobrino in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)  

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Previous growing season climate controls the occurrence of black spruce growth anomalies in boreal forests of Eastern Canada / Clémentine Ols in Canadian Journal of Forest Research, vol 46 n° 5 (May 2016)  

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Modeling of the permittivity of holly leaves in frozen environments / Xiaokang Kou in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)  

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