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The global and multi-annual MUSICA IASI {H2O, δD} pair dataset
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dc.contributor.authorDiekmann, Christopheres_ES
dc.contributor.authorSchneider, Matthiases_ES
dc.contributor.authorErtl, Benjamines_ES
dc.contributor.authorHase, Frankes_ES
dc.contributor.authorGarcía Rodríguez, Omaira Elenaes_ES
dc.contributor.authorKhosrawi, Farahnazes_ES
dc.contributor.authorSepúlveda Hernández, Eliezeres_ES
dc.contributor.authorKnippertz, Peteres_ES
dc.contributor.authorBraesicke, Peteres_ES
dc.date.accessioned2022-02-16T12:51:08Z-
dc.date.available2022-02-16T12:51:08Z-
dc.date.issued2021-
dc.identifier.citationEarth System Science Data. 2021, 13(1), p. 5273–5292es_ES
dc.identifier.issn1866-3508-
dc.identifier.issn1866-3516-
dc.identifier.urihttp://hdl.handle.net/20.500.11765/13439-
dc.description.abstractWe present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions.es_ES
dc.description.sponsorshipThis research has been supported by the Deutsche Forschungsgemeinschaft (grant no. 290612604, project MOTIV and grant no. 416767181, project TEDDY), the European Research Council, FP7 Ideas: European Research Council (MUSICA, grant no. 256961), the Bundesministerium für Bildung und Forschung (ForHLR supercomputer), the Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg (ForHLR supercomputer), and the Ministerio de Economía y Competitividad (grant no. CGL2016-80688-P, project INMENSE).es_ES
dc.language.isoenges_ES
dc.publisherCopernicus Publicationses_ES
dc.rightsLicencia CC: Reconocimiento CC BYes_ES
dc.subjectRadiance measurementses_ES
dc.subjectCycle of Atmospheric wateres_ES
dc.subjectIsotopologueses_ES
dc.subjectDatasetes_ES
dc.subjectIASIes_ES
dc.titleThe global and multi-annual MUSICA IASI {H2O, δD} pair datasetes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.5194/essd-13-5273-2021es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
Colecciones: Artículos científicos 2019-2022


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