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Effect of climate change on the growth of tree species: Dendroclimatological analysis / Archana Gauli in Forests, vol 13 n° 4 (April 2022)  

Public [article]  inForests > vol 13 n° 4 (April 2022) . - n° 496 Titre : Effect of climate change on the growth of tree species: Dendroclimatological analysis Type de document : Article/Communication Auteurs : Archana Gauli, Auteur ; Prem Raj Neupane, Auteur ; Philip Mundhenk, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne [Termes IGN] analyse diachronique [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] dendrologie [Termes IGN] données météorologiques [Termes IGN] échantillonnage [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] prévision météorologique [Termes IGN] Pseudotsuga menziesii [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree ring analyses can assist in revealing the effect of gradual change in climatic variables on tree growth. Dendroclimatic analyses are of particular importance in evaluating the climate variables that affect growth significantly and in determining the relative strength of different climatic factors. In this study, we investigated the growth performance of Pinus sylvestris, Picea abies, and Pseudotsuga menziesii in northern Germany using standard dendrochronological methods. The study further analyzed tree growth responses to different climatic variables over a period of a hundred years. Both response function analysis and moving correlation analysis confirmed that the climate and growth relationship is species-specific and variable and inconsistent over time. Scots pine and Douglas fir growth were stimulated mainly by the increase in winter temperatures, particularly the January, February, and March temperatures of the current year. In contrast, Norway spruce growth was stimulated mainly by the increase in precipitation in May, June, and July and the increase in temperature in March of the current year. Climate projections for central Europe foresee an increase in temperature and a decrease in the amount of summer precipitation. In a future, warmer climate with drier summers, the growth of Norway spruce might be negatively affected. Numéro de notice : A2022-259 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f13040496 Date de publication en ligne : 22/03/2022 En ligne : https://doi.org/10.3390/f13040496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100237 [article]

Assessing ZWD models in delay and height domains using data from stations in different climate regions / Thainara Munhoz Alexandre de Lima in Applied geomatics, vol 14 n° 1 (March 2022)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 93 - 103 Titre : Assessing ZWD models in delay and height domains using data from stations in different climate regions Type de document : Article/Communication Auteurs : Thainara Munhoz Alexandre de Lima, Auteur ; Marcelo Santos, Auteur ; Daniele Barroca Marra Alves, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 93 - 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] climat [Termes IGN] correction du signal [Termes IGN] données GNSS [Termes IGN] modèle atmosphérique [Termes IGN] modèle empirique [Termes IGN] modèle météorologique [Termes IGN] positionnement ponctuel précis [Termes IGN] prévision météorologique [Termes IGN] radiosondage [Termes IGN] retard troposphérique zénithal Résumé : (auteur) Global Navigation Satellite System (GNSS) has revolutionized activities involving geodetic positioning. To achieve a desired accuracy, it is essential to model the atmosphere in an appropriate way. With respect to the neutral atmosphere, the signal sent by the satellite suffers a delay when crossing this layer during its travel to the receiver on the surface, the so-called neutral atmospheric delay. Although empirical models exist, they may not be suitable to represent microclimatic variations in different regions of the globe due to peculiarities that exist in diverse areas. To minimize this limitation, correction models based on numerical weather prediction (NWP) emerge. They allow the assessment of the delay from local atmospheric parameters and the evaluation of atmospheric particularities of each region. In addition, another way to obtain neutral atmosphere delay is by making use of data from radiosondes, which measure atmospheric data at various altitude levels. The main objective of this article is to investigate the performance of different models using GNSS data collected in countries with different climatic conditions. Assessment is performed on the positioning domain using the precise point positioning (PPP) technique. The results show that the proximity between the NWP-based models and radiosondes was approximately 3 cm, and that between empirical models was 5 cm, with variations that depended on the model and the region. Regarding the impact on the height component, the difference between the accuracy of the empirical and NWP models was approximately 16 cm. Numéro de notice : A2022-219 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s12518-021-00414-y En ligne : https://doi.org/10.1007/s12518-021-00414-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100088 [article]

Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan / Eunbeen Park in GIScience and remote sensing, vol 59 n° 1 (2022)  

Public [article]  inGIScience and remote sensing > vol 59 n° 1 (2022) . - pp 36 - 53 Titre : Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan Type de document : Article/Communication Auteurs : Eunbeen Park, Auteur ; Hyun-Woo Jo, Auteur ; Sujong Lee, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 36 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] changement temporel [Termes IGN] image Terra-MODIS [Termes IGN] Indice de précipitations antérieures [Termes IGN] indice de végétation [Termes IGN] Kirghizistan [Termes IGN] message d'alerte [Termes IGN] modèle de simulation [Termes IGN] plan de prévention des risques [Termes IGN] prévision météorologique [Termes IGN] sécheresse Résumé : (auteur) Drought is a natural disaster that occurs globally and is a main trigger of secondary environmental and socio-economic damages, such as food insecurity, land degradation, and sand-dust storms. As climate change is being accelerated by human activities and environmental changes, both the severity and uncertainties of drought are increasing. In this study, a diagnostic drought prediction model (DDPM) was developed to reduce the uncertainties caused by environmental diversity at the regional level in Kyrgyzstan, by predicting drought with meteorological forecasts and satellite image diagnosis. The DDPM starts with applying a prognostic drought prediction model (PDPM) to 1) estimate future agricultural drought by explaining its relationship with the standardized precipitation index (SPI), an accumulated precipitation anomaly, and 2) compensate for regional variances, which were not reflected sufficiently in the PDPM, by taking advantage of preciseness in the time-series vegetation condition index (VCI), a satellite-based index representing land surface conditions. Comparing the prediction results with the monitored VCI from June to August, it was found that the DDPM outperformed the PDPM, which exploits only meteorological data, in both spatiotemporal and spatial accuracy. In particular, for June to August, respectively, the results of the DDPM (coefficient of determination [R2] = 0.27, 0.36, and 0.4; root mean squared error [RMSE] = 0.16, 0.13, and 0.13) were more effective in explaining the spatial details of drought severity on a regional scale than those of the PDPM (R2 = 0.09, 0.10, and 0.11; RMSE = 0.17, 0.15, and 0.16). The DDPM revealed the possibility of advanced drought assessment by integrating the earth observation big data comprising meteorological and satellite data. In particular, the advantage of data fusion is expected to be maximized in areas with high land surface heterogeneity or sparse weather stations by providing observational feedback to the PDPM. This research is anticipated to support policymakers and technical officials in establishing effective policies, action plans, and disaster early warning systems to reduce disaster risk and prevent environmental and socio-economic damage. Numéro de notice : A2022-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2021.2012370 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1080/15481603.2021.2012370 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99720 [article]

La campagne Caddiwa dans la région des îles du Cap-Vert / Cyrille Flamant in La Météorologie, n° 115 (2021)  

Public [article]  inLa Météorologie > n° 115 (2021) . - pp 2 - 5 Titre : La campagne Caddiwa dans la région des îles du Cap-Vert Type de document : Article/Communication Auteurs : Cyrille Flamant, Auteur ; Julien Delanoë, Auteur ; Jean-Pierre Chaboureau, Auteur ; Christophe Lavaysse, Auteur ; Marco Gaetani, Auteur ; Olivier Bock , Auteur Année de publication : 2021 Projets : 3-projet - voir note / Article en page(s) : pp 2 - 5 Note générale : bibliographie Le projet Clouds-Atmospheric Dynamics-Dust Interactions in West Africa (Caddiwa) est d’étudier les interactions « systèmes convectifs de méso-échelle-pousières-ondes tropicales » dans la zone de l’Atlantique Nord tropical située au large de l’Afrique de l’Ouest. Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] aérosol [Termes IGN] campagne d'observations [Termes IGN] Cap-Vert [Termes IGN] convection [Termes IGN] image MSG [Termes IGN] lidar atmosphérique [Termes IGN] positionnement par GPS [Termes IGN] poussière [Termes IGN] prévision météorologique [Termes IGN] télédétection spatiale [Termes IGN] tempête Numéro de notice : A2021-978 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.37053/lameteorologie-2021-0081 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.37053/lameteorologie-2021-0081 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100756 [article]

A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models / Victoria Sol Galligani in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 8968 - 8977 Titre : A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models Type de document : Article/Communication Auteurs : Victoria Sol Galligani, Auteur ; Die Wang, Auteur ; Paola Belen Corales, Auteur ; Catherine Prigent, Auteur Année de publication : 2021 Article en page(s) : pp 8968 - 8977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image GPM [Termes IGN] image radar [Termes IGN] latitude [Termes IGN] modèle atmosphérique [Termes IGN] modèle de transfert radiatif [Termes IGN] nuage [Termes IGN] polarisation [Termes IGN] prévision météorologique [Termes IGN] radiomètre à hyperfréquence [Termes IGN] reconstruction du signal [Termes IGN] variation saisonnière Résumé : (auteur) Microwave cloud polarized observations have shown the potential to improve precipitation retrievals since they are linked to the orientation and shape of ice habits. Stratiform clouds show larger brightness temperature (TB) polarization differences (PDs), defined as the vertically polarized TB (TBV) minus the horizontally polarized TB (TBH), with ~10 K PD values at 89 GHz due to the presence of horizontally aligned snowflakes, while convective regions show smaller PD signals, as graupel and/or hail in the updraft tend to become randomly oriented. The launch of the global precipitation measurement (GPM) microwave imager (GMI) has extended the availability of microwave polarized observations to higher frequencies (166 GHz) in the tropics and midlatitudes, previously only available up to 89 GHz. This study analyzes one year of GMI observations to explore further the previously reported stable relationship between the PD and the observed TBs at 89 and 166 GHz, respectively. The latitudinal and seasonal variability is analyzed to propose a cloud scattering polarization parameterization of the PD-TB relationship, capable of reconstructing the PD signal from simulated TBs. Given that operational radiative transfer (RT) models do not currently simulate the cloud polarized signals, this is an alternative and simple solution to exploit the large number of cloud polarized observations available. The atmospheric radiative transfer simulator (ARTS) is coupled with the weather research and forecasting (WRF) model, in order to apply the proposed parameterization to the RT simulated TBs and hence infer the corresponding PD values, which show to reproduce the observed GMI PDs well. Numéro de notice : A2021-886 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3049921 Date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3049921 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98871 [article]

Precipitable water vapor fusion based on a generalized regression neural network / Bao Zhang in Journal of geodesy, vol 95 n° 4 (April 2021)  

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Assessment of renewable energy resources with remote sensing / Fernando Ramos Martins (2021)  

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Copula-based modeling of dependence structure in geodesy and GNSS applications: case study for zenith tropospheric delay in complex terrain / Roya Mousavian in GPS solutions, vol 25 n° 1 (January 2021)  

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Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Homogenizing GPS integrated water vapor time series: Benchmarking break detection methods on synthetic data sets / Roeland Van Malderen in Earth and space science, vol 7 n° 5 (May 2020)  

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Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica [en ligne], vol 24 n° 2 (April 2020)  

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Improving operational radar rainfall estimates using profiler observations over complex terrain in Northern California / Haonan Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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Typology of meteorological weather forecast maps printed in world newspapers / Jaromir Kolejka in Cartographic journal (the), Vol 57 n° 1 (February 2020)  

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High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)  

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