12 research outputs found

    RĂŽle de la vapeur d'eau dans le cycle hydrologique en Arctique

    No full text
    Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Arctic water vapor is characterized by a spatial and temporal variability which is not completely understood yet. Its mass integrated in the atmospheric column (TCWV) is studied in this thesis. TCWV seasonal cycle at 18 polar stations is examined following the effect of latitude, longitude in addition to the continental effect. The measurements used in this thesis were validated at three polar stations, the satellites measurements of TCWV in the NIR/VIS/IR bands by MODIS/ SCIAMACHY/ AIRS sensors are compared to those obtained from ground based GPS signals delay. Their uncertainties and limitations are evaluated in season and month scales especially their sensitivities to the clouds presence. In NIR and VIS, the measurements undergo increased sensitivity to the presence of clouds at high latitudes in summer. In addition, albedo estimation is still a challenge to their TCWV inversion models, especially where canopies are snow-covered. Following the validation results, the distribution and seasonal trends of the TCWV over the entire Arctic was assessed via MODIS. Trends and anomalies are discussed mainly in response to changes in the Arctic vegetation, snow cover, and sea ice during 2001-2015. Increased trends in TCWV may be related to local increase of vegetated areas coincidently to snow cover decrease during transient seasons. Increased trends in TCWV were observed by MODIS, forced by local summer warming from many warm waves. A dramatic decline in sea ice near the Siberian and Beaufort coasts led to an observed local increase in TCWV in early fall. A warm-up phase in the Svalbard archipelago, persisting in all seasons except summer, also resulted in additional quantities of TCWV. The detection and justification of trends is a task still far from being accomplished. Arctic TCWV measurements are in question, TCWV measurements over green areas in winter, or through cloudy skies in summer are the major challenges.La vapeur d'eau atmosphĂ©rique joue un rĂŽle clĂ© dans le budget radiatif en Arctique, le cycle hydrologique et donc le climat. Mais sa mesure avec une prĂ©cision reste un dĂ©fi. La vapeur d'eau en Arctique se caractĂ©rise par une variabilitĂ© spatiale et temporelle qui n'est pas complĂštement comprise. Sa colonne atmosphĂ©rique total intĂ©grĂ©e (TCWV) est Ă©tudiĂ©e dans cette thĂšse. Trois mĂ©thodes de mesures de la TCWV Ă  distance sont testĂ©es et validĂ©es pour la rĂ©gion polaire. Cela inclut les mesures de TCWV aux bandes NIR/VIS/IR par les capteurs MODIS, SCIAMACHY, et AIRS embarquĂ©s sur satellites. Le cycle saisonnier de la TCWV Ă  19 stations polaires de rĂ©fĂ©rence est examinĂ© suite Ă  l'effet de la latitude, de la longitude en plus de l'effet continental/ocĂ©anique. Les mesures utilisĂ©es ont Ă©tĂ© validĂ©es aux trois stations polaires via la comparaison Ă  une base de donnĂ©es rĂ©fĂ©rentielle de TCWV convertis de retards de signaux GPS basĂ©s au sol. Les incertitudes et limites de mesures satellitaires sont Ă©valuĂ©es par saison et par mois. ParticuliĂšrement, nous avons Ă©tudiĂ© l’effet de la prĂ©sence de nuages sur les mesures des TCWV par satellites. Dans le NIR et dans le VIS, les mesures subissent une sensibilitĂ© accrues Ă  la prĂ©sence de nuages aux latitudes hautes en Ă©tĂ©. En plus, l’estimation de l’albĂ©do est toujours un dĂ©fi aux modĂšles d’inversion de la TCWV, surtout en prĂ©sence de neige en rĂ©gions cultivĂ©es. Suite aux rĂ©sultats de la validation, la distribution et les tendances saisonniĂšres de la TCWV au-dessus de toute l'Arctique ont Ă©tĂ© Ă©valuĂ©s via MODIS. Les tendances et anomalies accrues sont discutĂ©es principalement en rĂ©ponse aux changements observĂ©s en Arctique au cours des 2001-2015 annĂ©es, celles qui concernent la vĂ©gĂ©tation, la couverture de neige, et la glace de mer. Les tendances accrues de la TCWV peuvent ĂȘtre liĂ©es Ă  l’augmentation locale de surfaces vertes relative Ă  la neige pendant les saisons transitoires. Des tendances augmentĂ©es de la TCWV Ă©taient observables par MODIS, forcĂ© par le rĂ©chauffement estival local pendant les vagues de chaleurs au temps de ciels clairs. Un dĂ©clin dramatique de la glace de mer prĂšs des cĂŽtes SibĂ©riennes et de la cote du Beaufort a entraĂźnĂ© une augmentation locale observĂ©e de la TCWV en dĂ©but d’automne. Une phase de rĂ©chauffement au niveau de l’archipel du Svalbard, persistant en toutes saisons sauf l’étĂ©, a entrainĂ© Ă©galement des quantitĂ©s supplĂ©mentaires de la TCWV. La dĂ©tection et justification de tendances est une tache toujours loin d’ĂȘtre accomplie. Les mesures en Arctique sont toujours en question, les mesures de la TCWV au-dessus de surfaces vertes en hiver, ou Ă  travers du ciel nuageux en Ă©tĂ© sont des dĂ©fis majeurs

    The role of water vapor on the hydrologic cycle in the polar regions

    No full text
    La vapeur d'eau atmosphĂ©rique joue un rĂŽle clĂ© dans le budget radiatif en Arctique, le cycle hydrologique et donc le climat. Mais sa mesure avec une prĂ©cision reste un dĂ©fi. La vapeur d'eau en Arctique se caractĂ©rise par une variabilitĂ© spatiale et temporelle qui n'est pas complĂštement comprise. Sa colonne atmosphĂ©rique total intĂ©grĂ©e (TCWV) est Ă©tudiĂ©e dans cette thĂšse. Trois mĂ©thodes de mesures de la TCWV Ă  distance sont testĂ©es et validĂ©es pour la rĂ©gion polaire. Cela inclut les mesures de TCWV aux bandes NIR/VIS/IR par les capteurs MODIS, SCIAMACHY, et AIRS embarquĂ©s sur satellites. Le cycle saisonnier de la TCWV Ă  19 stations polaires de rĂ©fĂ©rence est examinĂ© suite Ă  l'effet de la latitude, de la longitude en plus de l'effet continental/ocĂ©anique. Les mesures utilisĂ©es ont Ă©tĂ© validĂ©es aux trois stations polaires via la comparaison Ă  une base de donnĂ©es rĂ©fĂ©rentielle de TCWV convertis de retards de signaux GPS basĂ©s au sol. Les incertitudes et limites de mesures satellitaires sont Ă©valuĂ©es par saison et par mois. ParticuliĂšrement, nous avons Ă©tudiĂ© l’effet de la prĂ©sence de nuages sur les mesures des TCWV par satellites. Dans le NIR et dans le VIS, les mesures subissent une sensibilitĂ© accrues Ă  la prĂ©sence de nuages aux latitudes hautes en Ă©tĂ©. En plus, l’estimation de l’albĂ©do est toujours un dĂ©fi aux modĂšles d’inversion de la TCWV, surtout en prĂ©sence de neige en rĂ©gions cultivĂ©es. Suite aux rĂ©sultats de la validation, la distribution et les tendances saisonniĂšres de la TCWV au-dessus de toute l'Arctique ont Ă©tĂ© Ă©valuĂ©s via MODIS. Les tendances et anomalies accrues sont discutĂ©es principalement en rĂ©ponse aux changements observĂ©s en Arctique au cours des 2001-2015 annĂ©es, celles qui concernent la vĂ©gĂ©tation, la couverture de neige, et la glace de mer. Les tendances accrues de la TCWV peuvent ĂȘtre liĂ©es Ă  l’augmentation locale de surfaces vertes relative Ă  la neige pendant les saisons transitoires. Des tendances augmentĂ©es de la TCWV Ă©taient observables par MODIS, forcĂ© par le rĂ©chauffement estival local pendant les vagues de chaleurs au temps de ciels clairs. Un dĂ©clin dramatique de la glace de mer prĂšs des cĂŽtes SibĂ©riennes et de la cote du Beaufort a entraĂźnĂ© une augmentation locale observĂ©e de la TCWV en dĂ©but d’automne. Une phase de rĂ©chauffement au niveau de l’archipel du Svalbard, persistant en toutes saisons sauf l’étĂ©, a entrainĂ© Ă©galement des quantitĂ©s supplĂ©mentaires de la TCWV. La dĂ©tection et justification de tendances est une tache toujours loin d’ĂȘtre accomplie. Les mesures en Arctique sont toujours en question, les mesures de la TCWV au-dessus de surfaces vertes en hiver, ou Ă  travers du ciel nuageux en Ă©tĂ© sont des dĂ©fis majeurs.Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Arctic water vapor is characterized by a spatial and temporal variability which is not completely understood yet. Its mass integrated in the atmospheric column (TCWV) is studied in this thesis. TCWV seasonal cycle at 18 polar stations is examined following the effect of latitude, longitude in addition to the continental effect. The measurements used in this thesis were validated at three polar stations, the satellites measurements of TCWV in the NIR/VIS/IR bands by MODIS/ SCIAMACHY/ AIRS sensors are compared to those obtained from ground based GPS signals delay. Their uncertainties and limitations are evaluated in season and month scales especially their sensitivities to the clouds presence. In NIR and VIS, the measurements undergo increased sensitivity to the presence of clouds at high latitudes in summer. In addition, albedo estimation is still a challenge to their TCWV inversion models, especially where canopies are snow-covered. Following the validation results, the distribution and seasonal trends of the TCWV over the entire Arctic was assessed via MODIS. Trends and anomalies are discussed mainly in response to changes in the Arctic vegetation, snow cover, and sea ice during 2001-2015. Increased trends in TCWV may be related to local increase of vegetated areas coincidently to snow cover decrease during transient seasons. Increased trends in TCWV were observed by MODIS, forced by local summer warming from many warm waves. A dramatic decline in sea ice near the Siberian and Beaufort coasts led to an observed local increase in TCWV in early fall. A warm-up phase in the Svalbard archipelago, persisting in all seasons except summer, also resulted in additional quantities of TCWV. The detection and justification of trends is a task still far from being accomplished. Arctic TCWV measurements are in question, TCWV measurements over green areas in winter, or through cloudy skies in summer are the major challenges

    Trends of total water vapor column above the Arctic from satellites observations

    No full text
    International audienceAtmospheric water vapor (H2O) is the most important natural (as opposed to man-made) greenhouse gas, accounting for about two-thirds of the natural greenhouse effect. Despite this importance, its role in climate and its reaction to climate change are still difficult to assess.Many details of the hydrological cycle are poorly understood, such as the process of cloud formation and the transport and release of latent heat contained in the water vapor.In contrast to other important greenhouse gases like carbon dioxide (CO2) and methane, water vapor has a much higher temporal and spatial variability.Total precipitable water (TPW) or the total column of water vapor (TCWV) is the amount of liquid water that would result if all the water vapor in the atmospheric column of unit area were condensed. TCWV distribution contains valuable information on the vigor of the hydrological processes and moisture transport in the atmosphere. Measurement of TPW can be obtained based on atmospheric water vapor absorption or emission of radiation in the spectral range from UV to MW.TRENDS were found over the terrestrial Arctic by means of TCWV retrievals (using Moderate Resolution Imaging Spectro-radiometer (MODIS) near-infrared (2001-2015) records).More detailed approach was made for comparisons with ground based instruments over Sodankyla – Finland (TCWV from: SCIAMACHY 2003-2011, GOME-2A 2007-2011, SAOZ 2003-2011, GPS 2003-2011, MODIS 2003-2011

    Total Column Water Vapor Trends from 15 Years of MODIS/NIR above the Arctic

    No full text
    International audienceWater vapor is defined as a major climate indicator at many occasions, highly variable spatially and temporarily, water vapor has the most important natural GHG effect, through his high infra-red absorption capacity, and temperature changes sensitivity, water vapor affects the Earth radiative budget and energy transfer, evolved at many atmospheric dynamics including the cloud formation and the aerosols composition. As a consequence to the accelerated transition towards the new climate especially above the arctic, and to investigate the feedback to the arctic amplification and the global warming, we study the water vapor variability and trends on a relatively long term above the arctic region, using the Total Column Water Vapor retrieval from MODIS/NIR spectro-radiometer on board of TERRA satellite. These 15 Years monthly daytime satellite data were compared to GPS integrated water vapor over four selected NDACC polar stations: Sodankyla-Finland, Ny-Alesund –Svalbard, Thule-Greenland, Scoresbysund-Greenland. GPS data are calculated with the temperature and pressure profile of the nearest coastal ERA-Interim station. These data were filtered for nearly coincident time to satellite over pass in order to exclude the timing effects. Errors, relative biases and RMSE at both monthly and seasonally scales will be presented and discussed. Then the MODIS 15 years linear trends and anomalies above the whole Arctic will be shown with a special focus on sea ice extent decline feed-back and hydrologic cycle connections with respect to heat waves. Results show wetter trends on the Mackenzie and mid-Siberia at September, unlike the European arctic summer which is getting drier, while Svalbard is getting wetter almost all the year. Conclusion and perspectives are also presented

    Enhanced MODIS Atmospheric Total Water Vapour Content Trends in Response to Arctic Amplification

    No full text
    International audienceIn order to assess the strength of the water vapour feedback within Arctic climate change, 15 years of the total column-integrated density of water vapour (TCWV) from the moderate resolution imaging spectrometer (MODIS) are analysed. Arctic TCWV distribution, trends, and anomalies for the 2001–2015 period, broken down into seasons and months, are analysed. Enhanced local spring TCWV trends above the terrestrial Arctic regions are discussed in relation to land snow cover and vegetation changes. Upward TCWV trends above the oceanic areas are discussed in lien with sea ice extent and sea surface temperature changes. Increased winter TCWV (up to 40%) south of the Svalbard archipelago are observed; these trends are probably driven by a local warming and sea ice extent decline. Similarly, the Barents/Kara regions underwent wet trends (up to 40%), also associated with winter/fall local sea ice loss. Positive late summer TCWV trends above the western Greenland and Beaufort seas (about 20%) result from enhanced upper ocean warming and thereby a local coastal decline in ice extent. The Mackenzie and Siberia enhanced TCWV trends (about 25%) during spring are found to be associated with coincident decreased snow cover and increased vegetation, as a result of the earlier melt onset. Results show drier summers in the Eurasia and western Alaska regions, thought to be affected by changes in albedo from changing vegetation. Other TCWV anomalies are also presented and discussed in relation to the dramatic decline in sea ice extent and the exceptional rise in sea surface temperature

    Evaluation du module de transfert des pesticides PeStics sur diffĂ©rents sites expĂ©rimentaux et acquisition de donnĂ©es Ă  la parcelle en vue de l’application du modĂšle sur le bassin de l’Orgeval

    No full text
    Le transfert des pesticides dans les bassins versants est difficile Ă  apprĂ©hender, tant au niveau de l’évaluation des molĂ©cules susceptibles d’ĂȘtre dĂ©tectĂ©es que des concentrations mesurĂ©es. La diversitĂ© des molĂ©cules utilisĂ©es en agriculture et les doses d’application de plus en plus faibles rendent leur dĂ©tection au-dessus de la limite de quantification incertaine. La modĂ©lisation du transfert des pesticides permettrait d’évaluer la prĂ©sence de ces molĂ©cules. La rĂšglementation des traitements a considĂ©rablement Ă©voluĂ© ces derniĂšres annĂ©es, notamment avec la mise en place du plan Ecophyto 2018 qui s’est accompagnĂ©e d’un retrait d’homologation des principales substances rĂ©guliĂšrement dĂ©tectĂ©es dans les eaux. Dans le cadre du Piren Seine, le couplage du modĂšle agronomique STICS avec la chaine de modĂ©lisation hydrogĂ©ologique MODCOU avait permis de montrer qu’il Ă©tait possible de modĂ©liser le transfert des nitrates sur tout le territoire du bassin versant de la Seine (Gomez et al., 2003). Les dĂ©veloppements au sein de la plateforme de modĂ©lisation Eau-dyssĂ©e ainsi que ceux apportes dans la derniĂšre version de STICS pour la rendre modularisable ont oriente le choix d’y intĂ©grer un module de transfert dĂ©diĂ© aux pesticides : Pestics. Les processus affectant le transfert dans les sols des pesticides ont Ă©tĂ© implĂ©mentĂ©s au sein de Pestics dans le modĂšle agronomique STICS. Bien que les premiĂšres applications de ce modĂšle donnent des rĂ©sultats sensĂ©s, des travaux supplĂ©mentaires Ă©taient nĂ©cessaires pour une Ă©valuation plus prĂ©cise. Pour cela, un effort a Ă©tĂ© effectue pour obtenir de nouveaux jeux de donnĂ©es expĂ©rimentaux auprĂšs de partenaires scientifiques. En parallĂšle, un travail expĂ©rimental a Ă©tĂ© mis en place sur le bassin versant de l’Orgeval pour acquĂ©rir des donnĂ©es sur une parcelle agricole durant la saison 2012

    Evaluation du module de transfert des pesticides PeStics sur diffĂ©rents sites expĂ©rimentaux et acquisition de donnĂ©es Ă  la parcelle en vue de l’application du modĂšle sur le bassin de l’Orgeval

    No full text
    Le transfert des pesticides dans les bassins versants est difficile Ă  apprĂ©hender, tant au niveau de l’évaluation des molĂ©cules susceptibles d’ĂȘtre dĂ©tectĂ©es que des concentrations mesurĂ©es. La diversitĂ© des molĂ©cules utilisĂ©es en agriculture et les doses d’application de plus en plus faibles rendent leur dĂ©tection au-dessus de la limite de quantification incertaine. La modĂ©lisation du transfert des pesticides permettrait d’évaluer la prĂ©sence de ces molĂ©cules. La rĂšglementation des traitements a considĂ©rablement Ă©voluĂ© ces derniĂšres annĂ©es, notamment avec la mise en place du plan Ecophyto 2018 qui s’est accompagnĂ©e d’un retrait d’homologation des principales substances rĂ©guliĂšrement dĂ©tectĂ©es dans les eaux. Dans le cadre du Piren Seine, le couplage du modĂšle agronomique STICS avec la chaine de modĂ©lisation hydrogĂ©ologique MODCOU avait permis de montrer qu’il Ă©tait possible de modĂ©liser le transfert des nitrates sur tout le territoire du bassin versant de la Seine (Gomez et al., 2003). Les dĂ©veloppements au sein de la plateforme de modĂ©lisation Eau-dyssĂ©e ainsi que ceux apportes dans la derniĂšre version de STICS pour la rendre modularisable ont oriente le choix d’y intĂ©grer un module de transfert dĂ©diĂ© aux pesticides : Pestics. Les processus affectant le transfert dans les sols des pesticides ont Ă©tĂ© implĂ©mentĂ©s au sein de Pestics dans le modĂšle agronomique STICS. Bien que les premiĂšres applications de ce modĂšle donnent des rĂ©sultats sensĂ©s, des travaux supplĂ©mentaires Ă©taient nĂ©cessaires pour une Ă©valuation plus prĂ©cise. Pour cela, un effort a Ă©tĂ© effectue pour obtenir de nouveaux jeux de donnĂ©es expĂ©rimentaux auprĂšs de partenaires scientifiques. En parallĂšle, un travail expĂ©rimental a Ă©tĂ© mis en place sur le bassin versant de l’Orgeval pour acquĂ©rir des donnĂ©es sur une parcelle agricole durant la saison 2012

    Evolutions and Improvements in CFOSAT SWIM Products

    No full text
    International audienceThe Chinese-French oceanography satellite, CFOSAT, was launched on October 2018. Two Ku-band scatterometers are on-board: SCAT for the wind observation and SWIM for the wave observation. After a first phase mainly dedicated to validation and identification of improvement possibilities, the ground processing and products generated were upgraded. This paper presents the main evolutions implemented and their positive impacts on the SWIM data quality

    CFOSAT: Latest Improvements in the Swim Products and Contributions in Oceanography

    No full text
    International audienceFor the first time, co-located wind vectors and wave spectral characteristics are available thanks to the French/Chinese CFOSAT mission, which includes a wind scatterometer SCAT and a wave scatterometer SWIM. Three years after its launch, CFOSAT data is thoroughly qualified and various scientific work has been undertaken. This paper focuses on CFOSAT SWIM data, its performance and scientific contribution to oceanography, coastal and sea ice study
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