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  • 7. Bennartz, Ralf
    et al.
    Hoschen, Heidrun
    Picard, Bruno
    Schroder, Marc
    Stengel, Martin
    Sus, Oliver
    Bojkov, Bojan
    Casadio, Stefano
    Diedrich, Hannes
    Eliasson, Salomon
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Fell, Frank
    Fischer, Jurgen
    Hollmann, Rainer
    Preusker, Rene
    Willén, Ulrika
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    An intercalibrated dataset of total column water vapour and wet tropospheric correction based on MWR on board ERS-1, ERS-2, and Envisat2017Inngår i: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 10, nr 4, s. 1387-1402Artikkel i tidsskrift (Fagfellevurdert)
    Fulltekst (pdf)
    fulltext
  • 8. Ning, T.
    et al.
    Elgered, G.
    Willén, Ulrika
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Johansson, J. M.
    Evaluation of the atmospheric water vapor content in a regional climate model using ground-based GPS measurements2013Inngår i: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 118, nr 2, s. 329-339Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Ground-based GPS measurements can provide independent data for the assessment of climate models. We use the atmospheric integrated water vapor (IWV) obtained from GPS measurements at 99 European sites to evaluate the regional Rossby Centre Atmospheric climate model (RCA) driven at the boundaries by the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA Interim). The GPS data were compared to the RCA simulation and the ERA Interim data. The comparison was first made using the monthly mean values. Averaged over the domain and the 14 years covered by the GPS data, IWV differences of about 0.47 kg/m(2) and 0.39 kg/m(2) are obtained for RCA-GPS and ECMWF-GPS, respectively. The RCA-GPS standard deviation is 0.98 kg/m(2) whereas it is 0.35 kg/m(2) for the ECMWF-GPS comparison. The IWV differences for RCA are positively correlated to the differences for ECMWF. However, this is not the case for two sites in Italy where a wet bias is seen for ECMWF, while a dry bias is seen for RCA, the latter being consistent with a cold temperature bias found for RCA in that region by other authors. Comparisons of the estimated diurnal cycle and the spatial structure function of the IWV were made between the GPS data and the RCA simulation. The RCA captures the geographical variation of the diurnal peak in the summer. Averaged over all sites, a peak at 17 local solar time is obtained from the GPS data while it appears later, at 18, in the RCA simulation. The spatial variation of the IWV obtained for an RCA run with a resolution of 11 km gives a better agreement with the GPS results than does the spatial variation from a 50 km resolution run. Citation: Ning, T., G. Elgered, U. Willen, and J. M. Johansson (2013), Evaluation of the atmospheric water vapor content in a regional climate model using ground-based GPS measurements, J. Geophys. Res. Atmos., 118, 329-339, doi: 10.1029/2012JD018053.

  • 9.
    Koenigk, Torben
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Brodeau, Laurent
    Graversen, Rune Grand
    Karlsson, Johannes
    Svensson, Gunilla
    Tjernstrom, Michael
    Willén, Ulrika
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Wyser, Klaus
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Arctic climate change in 21st century CMIP5 simulations with EC-Earth2013Inngår i: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 40, nr 11-12, s. 2719-2743Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.

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