Relevant bibliographies by topics / Meteostat

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Meteostat'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Meteostat"

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Jobard, Isabelle, and Michel Desbois. "Satellite estimation of the tropical precipitation using the METEOSTAT and SSM/I data." Atmospheric Research 34, no. 1-4 (June 1994): 285–98. http://dx.doi.org/10.1016/0169-8095(94)90097-3.

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Deneke, H. M., and R. Roebling. "Downscaling of METEOSAT SEVIRI 0.6 and 0.8 micron channel radiances utilizing the high-resolution visible channel." Atmospheric Chemistry and Physics Discussions 10, no. 4 (April 23, 2010): 10707–40. http://dx.doi.org/10.5194/acpd-10-10707-2010.

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Abstract. An algorithm is introduced to downscale the 0.6 and 0.8 micron spectral channels of the METEOSTAT SEVIRI satellite imager from 3×3 km2 (LRES) to 1×1 km2 (HRES) resolution utilizing SEVIRI's high-resolution visible channel (HRVIS). Intermediate steps include the coregistration of low- and high-resolution images, lowpass filtering of the HRVIS channel with the spatial response function of the narrowband channels, and the estimation of a least-squares linear regression model for linking high-frequency variations in the HRVIS and narrowband images. The importance of accounting for the sensor spatial response function for matching reflectances at different spatial resolutions is demonstrated, and an estimate of the accuracy of the downscaled reflectances is provided. Based on a 1-year dataset of Meteosat SEVIRI images, it is estimated that on average, the reflectance of a HRES pixel differs from that of an enclosing LRES pixel by standard deviations of 0.049 and 0.052 in the 0.6 and 0.8 micron channels, respectively. By applying our downscaling algorithm, explained variance of 98.2 and 95.3 percent are achieved for estimating these deviations, corresponding to residual standard deviations of only 0.007 and 0.011 for the respective channels. For this dataset, a minor misregistration of the HRVIS channel relative to the narrowband channels of 0.36±0.11 km in East and 0.06±0.10 km in South direction is observed and corrected for, which should be negligible for most applications.
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Deneke, H. M., and R. A. Roebeling. "Downscaling of METEOSAT SEVIRI 0.6 and 0.8 μm channel radiances utilizing the high-resolution visible channel." Atmospheric Chemistry and Physics 10, no. 20 (October 18, 2010): 9761–72. http://dx.doi.org/10.5194/acp-10-9761-2010.

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Abstract. An algorithm is introduced to downscale the 0.6 and 0.8 μm spectral channels of the METEOSTAT SEVIRI satellite imager from 3×3 km2 (LRES) to 1×1 km2 (HRES) resolution utilizing SEVIRI's high-resolution visible channel (HRV). Intermediate steps include the coregistration of low- and high-resolution images, lowpass filtering of the HRV channel with the spatial response function of the narrowband channels, and the estimation of a least-squares linear regression model for linking high-frequency variations in the HRV and narrowband images. The importance of accounting for the sensor spatial response function for matching reflectances at different spatial resolutions is demonstrated, and an estimate of the accuracy of the downscaled reflectances is provided. Based on a 1-year dataset of Meteosat SEVIRI images, it is estimated that on average, the reflectance of a HRES pixel differs from that of an enclosing LRES pixel by standard deviations of 0.049 and 0.052 in the 0.6 and 0.8 μm channels, respectively. By applying our downscaling algorithm, explained variance of 98.2 and 95.3 percent are achieved for estimating these deviations, corresponding to residual standard deviations of only 0.007 and 0.011 for the respective channels. For this dataset, a minor misregistration of the HRV channel relative to the narrowband channels of 0.36±0.11 km in East and 0.06±0.10 km in South direction is observed and corrected for, which should be negligible for most applications.
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Seiz, Gabriela, Stephen Tjemkes, and Philip Watts. "Multiview Cloud-Top Height and Wind Retrieval with Photogrammetric Methods: Application to Meteosat-8 HRV Observations." Journal of Applied Meteorology and Climatology 46, no. 8 (August 1, 2007): 1182–95. http://dx.doi.org/10.1175/jam2532.1.

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Abstract The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) currently operates three geostationary satellites: Meteosat-5, Meteosat-7, and Meteosat-8. Observations by Meteosat-5 can be combined with observations from either Meteosat-7 or Meteosat-8 to allow geostationary stereo height retrievals within the overlap area over the Indian Ocean and east Africa. This paper aims to demonstrate the capabilities of the geostationary stereophotogrammetric cloud-top height retrieval—in particular, with the new high-resolution visible channel (HRV) of Meteosat-8. Conceived as a proof-of-concept study, the retrieval was limited to four distinct cloud areas in northeast Africa. The effects of the geolocation, spatial resolution, satellite position, and acquisition time on the cloud-top height accuracy were studied. It is demonstrated that the matching accuracy is sensitive to the acquisition-time difference and spatial resolution. As a result, there is only a marginal benefit from the good spatial resolution offered by the Meteosat-8 HRV channel because of the low spatial resolution of Meteosat-5 and the poor time synchronization between the observations of the two satellites. On the contrary, the good time synchronization between Meteosat-5 and Meteosat-7 observations offsets the errors in the height assignment resulting from the relatively coarse spatial resolution, if the geolocation accuracy is locally enhanced with additional landmarks from higher-resolution images. With the geolocation correction and the newly implemented time information in the Meteosat-5 and -7 header information, the stereo cloud-top height assignment for the Meteosat-5/-7 and Meteosat-5/-8 HRV combination resulted in about the same accuracy of approximately ±1 km. For the Meteosat-5/-8 HRV combination, the time differences of up to 7.5 min preclude higher accuracy. To validate the cloud-top heights, observations by the Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) were used.
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Le Borgne, Pierre, Gérard Legendre, and Anne Marsouin. "Meteosat and GOES-East Imager Visible Channel Calibration." Journal of Atmospheric and Oceanic Technology 21, no. 11 (November 1, 2004): 1701–9. http://dx.doi.org/10.1175/jtechjtech-1675.1.

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Abstract As a preliminary step to solar irradiance calculations, the Centre de Météorologie Spatiale (CMS) has developed a pragmatic approach to calibrate the visible channels of Meteosat and GOES-East imagers. The responsivity of the Meteosat visible channel has been monitored with three desert targets from 1989 to 2002. The annual degradation rate has been estimated to 1.8% for Meteosat-4, 1.4% for Meteosat-5, and 1.9% for Meteosat-7. A reference calibration coefficient for Meteosat-7 has been derived from a comparison with Clouds and Earth's Radiant Energy System (CERES) data in summer 1998. Meteosat and GOES-East data corresponding to homogenous pixels along longitude 37.5°W and around 1200 LST have been compared on a monthly basis, leading to a calibration of GOES-East visible channel. GOES-8 data have been processed from June 1998 to December 2002 and the annual degradation rate obtained during this period is 4.0%. GOES-12 data have been processed from April to August 2003. During this short period, no degradation rate can be estimated but only a mean value of the calibration coefficient, which corresponds to a 7% increase of the prelaunch coefficient.
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Messmer, Bettina, Leszek Kolendowicz, and Willi Schmid. "Detection and prediction of hail based on Meteosat data." Meteorologische Zeitschrift 4, no. 5 (November 8, 1995): 187–95. http://dx.doi.org/10.1127/metz/4/1995/187.

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Anonymous. "Meteosat-6 experiences anomaly." Eos, Transactions American Geophysical Union 75, no. 13 (1994): 147. http://dx.doi.org/10.1029/94eo00840.

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Cros, Sylvain, Michel Albuisson, and Lucien Wald. "Simulating Meteosat-7 broadband radiances using two visible channels of Meteosat-8." Solar Energy 80, no. 3 (March 2006): 361–67. http://dx.doi.org/10.1016/j.solener.2005.01.012.

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Campbell, G. G., and K. Holmlund. "Geometric cloud heights from Meteosat." International Journal of Remote Sensing 25, no. 21 (November 2004): 4505–19. http://dx.doi.org/10.1080/01431160410001726076.

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Turpeinen, Olli M. "Monitoring of precipitation with Meteosat." Advances in Space Research 9, no. 7 (January 1989): 347–53. http://dx.doi.org/10.1016/0273-1177(89)90183-x.

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Dissertations / Theses on the topic "Meteostat"

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Ramrani, Yasmina. "Interpolation spatio-temporelle combinée des images AVHRR et METEOSTAT dans l'infrarouge thermique." Grenoble 2 : ANRT, 1986. http://catalogue.bnf.fr/ark:/12148/cb376006392.

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Garland, A. C. "The use of Meteostat in the analysis of African armyworm outbreaks in East Africa." Thesis, University of Bristol, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356121.

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Cros, Sylvain. "Création d'une climatologie du rayonnement solaire incident en ondes courtes à l'aide d'images satellitales." Paris, ENMP, 2004. http://pastel.archives-ouvertes.fr/pastel-00949057.

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Hammer, Annette. "Anwendungsspezifische Solarstrahlungsinformationen aus Meteosat-Daten." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=960943188.

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Guéhenneux, Yannick. "Analyse thermique de l'activité volcanique par traitement des données à très haute résolution temporelle du satellite Meteosat Second Generation." Thesis, Clermont-Ferrand 2, 2013. http://www.theses.fr/2013CLF22361/document.

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Traore, Ahmed Faya. "Rainfall estimation by meteosat in west Africa." Thesis, University of Reading, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646000.

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Data from Meteosat thermal infrared (TIR) imagery are related to rainfall measured directly by gauges at meteorological stations in the Republic of Niger (West Africa), spanning between 0 and 14 °E and 12 and 18 ON. Quantitative physical parameters of 116 clouds from hourly TIR are then examined with the aim of establishing meaningful relations between them and ground observed rainfall.
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MAURY, ARNAUD. "Qualite image et rectification des images meteosat." Nice, 1993. http://www.theses.fr/1993NICE4654.

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Cette these traite de la rectification des images du satellite meteosat ; soit la methode d'allouer a chaque pixel de l'image sa localisation geographique. Meteosat est un satellite meteorologique geostationnaire manoeuvre par l'agence spatiale europeenne. Dans sa configuration nominale, le satellite meteosat permet la saisie d'images pour lesquelles les lignes sont orientees parfaitement en est-ouest et avec la terre parfaitement centree. De petites deviations de cette situation nominale induisent l'apparition de distorsions geometriques. L'ensemble des causes de ces distorsions sont decrites et definies. Afin de rectifier les images un modele de deformation est elabore, ses parametres etant estimes. Les images une fois rectifiees, l'erreur de rectification residuelle est quantifiee a partir de la localisation d'amers par un procede de correlation. L'ensemble des resultats et methodes ont ete valides a partir de donnees operationnelles au moyen de simulations informatiques; ce pour l'ensemble du processus de traitement image: des images brutes aux images rectifiees et re-echantillonnees
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Schmidt, Andreas. "Zeitreihen der Landoberflächentemperatur abgeleitet aus METEOSAT-7 Satellitendaten." [S.l. : s.n.], 2008. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000009865.

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Geer, Alan Jon. "Climate studies and model validation using satellite 6.7#mu#m water vapour data." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325605.

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Chadwick, Robin. "Multi-spectral satellite rainfall estimation over Africa using meteosat second generation data." Thesis, University of Reading, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.542062.

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Books on the topic "Meteostat"

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Brimacombe, C. A. Atlas de imágenes Meteosat. Espana: Centro de Publicaciones, Secretaría General Técnica, Ministerio de Obras Públicas y Transportes, 1991.

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2

Boekaerts, P. Autoadaptive cloud identification in Meteosat images. [Noordwijk, the Netherlands]: European Space Agency, 1995.

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Weydert, M. Data Collection from remote stations via Meteosat. Luxembourg: Commission of the European Communities, 1988.

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Huygen, J. Estimation of rainfall in Zambia using METEOSAT-TIR data. Wageningen (Netherlands): Winand Staring Centre, 1989.

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Versteeg, M. H. J. B. Implementation aspects of a decompressor for compressed METEOSAT data on a VME/68000 system. Amsterdam: National Aerospace Laboratory, 1986.

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MSG RAO Workshop (3rd 2006 Helsinki, Finland). Proceedings of the 3rd MSG RAO Workshop: 15 June 2006, Helsinki, Finland. Edited by Danesy D and European Space Agency. Noordwijk, The Netherlands: ESA Publications Division, 2006.

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Siyyid, Alward Nawazish. The use of Meteosat satellite data for spatial rainfall estimations and hydrological simulations. Birmingham: Aston University. Department of Civil Engineering, 1993.

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8

Scholl, Margit Christa. Fallstudie über die Kongruenz von Niederschlagsinformation aus SYNOP-, MODELL- und METEOSAT-Daten: (DK 001.8:551.5/167.7:551.5/519 ... Berlin: D. Reimer, 1991.

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MSG RAO Workshop (2nd 2004 Salzburg, Austria). Proceedings of the second MSG RAO Workshop: 9-10 September 2004, Salzburg, Austria. Noordwijk, The Netherlands: ESA Publications Division, 2004.

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Italy) MSG RAO Workshop (1st 2000 Bologna. First MSG RAO Workshop: 17-19 May 2000, CNR, Bologna, Italy. Noordwijk, the Netherlands: ESA Publications Division, 2000.

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Book chapters on the topic "Meteostat"

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Rao, P. Krishna, Susan J. Holmes, Ralph K. Anderson, Jay S. Winston, and Paul E. Lehr. "The European Meteosat." In Weather Satellites: Systems, Data, and Environmental Applications, 69–76. Boston, MA: American Meteorological Society, 1990. http://dx.doi.org/10.1007/978-1-944970-16-1_7.

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Schmetz, Johannes, Dieter Klaes, Alain Ratier, and Rolf Stuhlmann. "The Meteosat and EPS/Metop Satellite Series." In Measuring Precipitation From Space, 571–86. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5835-6_45.

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Göttsche, F., and F. S. Olesen. "Thermal Land-surface Variables From METEOSAT-IR Data." In Mediterranean Climate, 277–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55657-9_16.

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Macías-Macías, Miguel, Carlos J. García-Orellana, Horacio González-Velasco, and Ramón Gallardo-Caballero. "Independent Component Analysis for Cloud Screening of Meteosat Images." In Artificial Neural Nets Problem Solving Methods, 551–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44869-1_70.

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Hugentobler, U., T. Schildknecht, and G. Beutler. "Determination of Resonance Terms Using Optical Observations of Two Meteosat Satellites." In Dynamics and Astrometry of Natural and Artificial Celestial Bodies, 355–60. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5534-2_50.

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van Lammeren, André, and Arnout Feijt. "The Emissivity of Cirrus Clouds Derived from LITE and Meteosat Measurements." In Advances in Atmospheric Remote Sensing with Lidar, 201–4. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60612-0_50.

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Lafeuille, J. "Promoting the Use of Meteosat for Supporting Sustainable Development in Africa." In Space of Service to Humanity, 147–56. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5692-9_16.

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Feidas, H. "Study of a Mesoscale Convective Complex Over Balkans with Meteosat Data." In Advances in Meteorology, Climatology and Atmospheric Physics, 79–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_12.

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Bolla, Raffaele, Mario Marchese, Carlo Nobile, and Sandro Zappatore. "Prediction of short-term evolution of cloud formations based on Meteosat image sequences." In Image Analysis and Processing, 677–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_331.

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Reudenbach, Christoph, Thomas Nauss, and Jürg Bendix. "Retrieving Precipitation with GOES, Meteosat, and Terra/MSG at the Tropics and Mid-latitudes." In Measuring Precipitation From Space, 509–19. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5835-6_40.

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Conference papers on the topic "Meteostat"

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van't Klooster, Kees. "Antennas for Meteosat satellites." In 2010 20th International Crimean Conference "Microwave & Telecommunication Technology" (CriMiCo 2010). IEEE, 2010. http://dx.doi.org/10.1109/crmico.2010.5632849.

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Markland, Chris A. "METEOSAT second-generation program." In Orlando '91, Orlando, FL, edited by Philip N. Slater. SPIE, 1991. http://dx.doi.org/10.1117/12.46610.

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Dewitte, Steven, E. Nyssen, Dominique A. Crommelynck, and Jan P. Cornelis. "Multistage analysis of Meteosat images." In Satellite Remote Sensing II, edited by Jacky Desachy. SPIE, 1995. http://dx.doi.org/10.1117/12.226831.

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Hollier, Pierre A. "Imager of METEOSAT second generation." In Orlando '91, Orlando, FL, edited by Philip N. Slater. SPIE, 1991. http://dx.doi.org/10.1117/12.46613.

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Eichen, G., and P. Hollier. "Infrared Sounder For Second Generation Meteosat." In 1987 Symposium on the Technologies for Optoelectronics, edited by C. Stuart Bowyer and John S. Seeley. SPIE, 1988. http://dx.doi.org/10.1117/12.943601.

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Matheson, Lee. "METEOSAT Second Generation: Automated Procedures Execution Algorithms." In SpaceOps 2008 Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-3216.

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Lamarre, D., D. Aminou, P. van den Braembussche, P. Hallibert, B. Ahlers, M. Wilson, and H. J. Luhmann. "Meteosat Third Generation: The Infrared Sounder Instrument." In Fourier Transform Spectroscopy. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/fts.2011.jma2.

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Julien, Yves, Jose A. Sobrino, and Guillem Soria. "Phenology estimation from Meteosat Second Generation data." In IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6352735.

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Bosdogianni, P., D. Just, and C. Boukouvalas. "Image data resampling for Meteosat Second Generation." In IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174). IEEE, 1998. http://dx.doi.org/10.1109/igarss.1998.699556.

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Butterworth, James, Gérald Aigouy, Clement Chassaing, Benoı̂t Debray, and Alexandre Huguet. "Pulse tube coolers for Meteosat third generation." In ADVANCES IN CRYOGENIC ENGINEERING: Transactions of the Cryogenic Engineering Conference - CEC. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4860745.

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Reports on the topic "Meteostat"

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Habte, Aron, Manajit Sengupta, and Grant Buster. Estimating Surface Solar Irradiance Using Meteosat-8 Satellite for India and Surrounding Regions (2017-2019). Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1770886.

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