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  • 1. Decremer, Damien
    et al.
    Chung, Chul E.
    Ekman, Annica M. L.
    Brandefelt, Jenny
    KTH, School of Engineering Sciences (SCI), Mechanics, Turbulence.
    Which significance test performs the best in climate simulations?2014In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 66, no 1, p. 23139-Article in journal (Refereed)
    Abstract [en]

    Climate change simulated with climate models needs a significance testing to establish the robustness of simulated climate change relative to model internal variability. Student's t-test has been the most popular significance testing technique despite more sophisticated techniques developed to address autocorrelation. We apply Student's t-test and four advanced techniques in establishing the significance of the average over 20 continuous-year simulations, and validate the performance of each technique using much longer (375-1000 yr) model simulations. We find that all the techniques tend to perform better in precipitation than in surface air temperature. A sizable performance gain using some of the advanced techniques is realised in the model Ts output portion with strong positive lag-1 yr autocorrelation (> +/- 0.6), but this gain disappears in precipitation. Furthermore, strong positive lag-1 yr autocorrelation is found to be very uncommon in climate model outputs. Thus, there is no reason to replace Student's t-test by the advanced techniques in most cases.

  • 2.
    Hartung, Kerstin
    et al.
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden.;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.;Swedish E Sci Res Ctr, Stockholm, Sweden..
    Svensson, Gunilla
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden.;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.;Swedish E Sci Res Ctr, Stockholm, Sweden..
    Kjellstrom, Erik
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden.;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.;Swedish Meteorol & Hydrol Inst, Rossby Ctr, Norrkoping, Sweden..
    Resolution, physics and atmosphere-ocean interaction - How do they influence climate model representation of Euro-Atlantic atmospheric blocking?2017In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 69, article id 1406252Article in journal (Refereed)
    Abstract [en]

    Atmospheric blocking events are known to locally explain a large part of climate variability. However, despite their relevance, many current climate models still struggle to represent the observed blocking statistics. In this study, simulations of the global climate model EC-Earth are analysed with respect to atmospheric blocking. Seventeen simulations map the uncertainty space defined by the three-model characteristics: atmospheric resolution, physical parameterization and complexity of atmosphere-ocean interaction, namely an atmosphere coupled to an ocean model or forced by surface data. Representation of the real-world statistics is obtained from reanalyses ERA-20C, JRA-55 and ERA-Interim which agree on Northern Hemisphere blocking characteristics. Blocking events are detected on a central blocking latitude which is individually determined for each simulation. The frequency of blocking events tends to be underestimated relative to ERA-Interim over the Atlantic and western Eurasia in winter and overestimated during spring months. However, only few model setups show statistically significant differences compared to ERA-Interim which can be explained by the large inter-annual variability of blocking. Results indicate slightly larger biases relative to ERA-Interim in coupled than in atmosphere-only models but differences between the two are not statistically significant. Although some resolution dependence is present in spring, the signal is weak and only statistically significant if the physical parameterizations of the model are improved simultaneously. Winter blocking is relatively more sensitive to physical parameterizations, and this signal is robust in both atmosphere-only and coupled simulations, although stronger in the latter. Overall, the model can capture blocking frequency well despite biases in representing the mean state of geopotential height over this area. Blocking signatures of geopotential height are represented more similar to ERA-Interim and only weak sensitivities to model characteristics remain.

  • 3.
    Lindborg, Erik
    et al.
    KTH, School of Engineering Sciences (SCI), Mechanics, Turbulence.
    Riley, James J.
    A condition on the average Richardson number for weak non-linearity of internal gravity waves2007In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 59, no 5, p. 781-784Article in journal (Refereed)
    Abstract [en]

    A condition on the average Richardson number, Ri, for weak non-linearity of an internal gravity wavefield is derived using a quasi-normal assumption. For weak non-linearity to be satisfied it is required that Ri(-1) << 0.5. This condition is very rarely satisfied in the ocean at vertical scales up to the order of 100 m, for which it is often found that Ri(-1) similar to 1. The analysis suggests that non-linear effects are of no less importance than linear effects in the dynamics of the interior of the ocean at these scales.

  • 4. Strandberg, Gustav
    et al.
    Brandefelt, Jenny
    KTH, School of Engineering Sciences (SCI), Mechanics, Turbulence.
    Kjellstrom, Erik
    Smith, Benjamin
    High-resolution regional simulation of last glacial maximum climate in Europe2011In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 63, no 1, p. 107-125Article in journal (Refereed)
    Abstract [en]

    A fully coupled atmosphere-ocean general circulation model is used to simulate climate conditions during the last glacial maximum (LGM). Forcing conditions include astronomical parameters, greenhouse gases, ice sheets and vegetation. A 50-yr period of the global simulation is dynamically downscaled to 50 km horizontal resolution over Europe with a regional climate model (RCM). A dynamic vegetation model is used to produce vegetation that is consistent with the climate simulated by the RCM. This vegetation is used in a final simulation with the RCM. The resulting climate is 5-10 degrees C colder than the recent past climate (representative of year 1990) over ice-free parts of Europe as an annual average; over the ice-sheet up to 40 degrees C colder in winter." The average model-proxy error is about the same for summer and winter, for pollen-based proxies. The RCM results are within (outside) the uncertainty limits for winter (summer). Sensitivity studies performed with the RCM indicate that the simulated climate is sensitive to changes in vegetation, whereas the location of the ice sheet only affects the climate around the ice sheet. The RCM-simulated interannual variability in near surface temperature is significantly larger at LGM than in the recent past climate.

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