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dc.date.accessioned2020-11-27T20:15:46Z
dc.date.available2020-11-27T20:15:46Z
dc.date.created2020-10-08T16:53:13Z
dc.date.issued2020
dc.identifier.citationTegtmeier, Susann Anstey, James Davis, Sean Dragani, Rossana Harada, Yayoi Ivanciu, Ioana Pilch Kedzierski, Robin Krüger, Kirstin Legras, Bernard Long, Craig S. Wang, James S. Wargan, Krzysztof Wright, Jonathon S. . Temperature and tropopause characteristics from reanalyses data in the tropical tropopause layer. Atmospheric Chemistry and Physics. 2020, 20(2), 753-770
dc.identifier.urihttp://hdl.handle.net/10852/81179
dc.description.abstractThe tropical tropopause layer (TTL) is the transition region between the well-mixed convective troposphere and the radiatively controlled stratosphere with air masses showing chemical and dynamical properties of both regions. The representation of the TTL in meteorological reanalysis data sets is important for studying the complex interactions of circulation, convection, trace gases, clouds, and radiation. In this paper, we present the evaluation of climatological and long-term TTL temperature and tropopause characteristics in the reanalysis data sets ERA-Interim, ERA5, JRA-25, JRA-55, MERRA, MERRA-2, NCEP-NCAR (R1), and CFSR. The evaluation has been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The most recent atmospheric reanalysis data sets (ERA-Interim, ERA5, JRA-55, MERRA-2, and CFSR) all provide realistic representations of the major characteristics of the temperature structure within the TTL. There is good agreement between reanalysis estimates of tropical mean temperatures and radio occultation data, with relatively small cold biases for most data sets. Temperatures at the cold point and lapse rate tropopause levels, on the other hand, show warm biases in reanalyses when compared to observations. This tropopause-level warm bias is related to the vertical resolution of the reanalysis data, with the smallest bias found for data sets with the highest vertical resolution around the tropopause. Differences in the cold point temperature maximize over equatorial Africa, related to Kelvin wave activity and associated disturbances in TTL temperatures. Interannual variability in reanalysis temperatures is best constrained in the upper TTL, with larger differences at levels below the cold point. The reanalyses reproduce the temperature responses to major dynamical and radiative signals such as volcanic eruptions and the quasi-biennial oscillation (QBO). Long-term reanalysis trends in temperature in the upper TTL show good agreement with trends derived from adjusted radiosonde data sets indicating significant stratospheric cooling of around −0.5 to −1 K per decade. At 100 hPa and the cold point, most of the reanalyses suggest small but significant cooling trends of −0.3 to −0.6 K per decade that are statistically consistent with trends based on the adjusted radiosonde data sets. Advances of the reanalysis and observational systems over the last decades have led to a clear improvement in the TTL reanalysis products over time. Biases of the temperature profiles and differences in interannual variability clearly decreased in 2006, when densely sampled radio occultation data started being assimilated by the reanalyses. While there is an overall good agreement, different reanalyses offer different advantages in the TTL such as realistic profile and cold point temperature, continuous time series, or a realistic representation of signals of interannual variability. Their use in model simulations and in comparisons with climate model output should be tailored to their specific strengths and weaknesses.
dc.languageEN
dc.publisherCopernicus GmbH
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleTemperature and tropopause characteristics from reanalyses data in the tropical tropopause layer
dc.typeJournal article
dc.creator.authorTegtmeier, Susann
dc.creator.authorAnstey, James
dc.creator.authorDavis, Sean
dc.creator.authorDragani, Rossana
dc.creator.authorHarada, Yayoi
dc.creator.authorIvanciu, Ioana
dc.creator.authorPilch Kedzierski, Robin
dc.creator.authorKrüger, Kirstin
dc.creator.authorLegras, Bernard
dc.creator.authorLong, Craig S.
dc.creator.authorWang, James S.
dc.creator.authorWargan, Krzysztof
dc.creator.authorWright, Jonathon S.
cristin.unitcode185,15,22,70
cristin.unitnameMeteorologi og oseanografi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1838290
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Atmospheric Chemistry and Physics&rft.volume=20&rft.spage=753&rft.date=2020
dc.identifier.jtitleAtmospheric Chemistry and Physics
dc.identifier.volume20
dc.identifier.issue2
dc.identifier.startpage753
dc.identifier.endpage770
dc.identifier.doihttps://doi.org/10.5194/acp-20-753-2020
dc.identifier.urnURN:NBN:no-84278
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1680-7316
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/81179/1/acp-20-753-2020.pdf
dc.type.versionPublishedVersion


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