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  • 1. Jacob, Daniela
    et al.
    Bärring, Lars
    SMHI, Research Department, Climate research - Rossby Centre.
    Christensen, Ole Bossing
    Christensen, Jens Hesselbjerg
    de Castro, Manuel
    Deque, Michel
    Giorgi, Filippo
    Hagemann, Stefan
    Hirschi, Martin
    Jones, Richard
    Kjellström, Erik
    SMHI, Research Department, Climate research - Rossby Centre.
    Lenderink, Geert
    Rockel, Burkhardt
    Sanchez, Enrique
    Schaer, Christoph
    Seneviratne, Sonia I.
    Somot, Samuel
    van Ulden, Aad
    van den Hurk, Bart
    An inter-comparison of regional climate models for Europe: model performance in present-day climate2007In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, Vol. 81, p. 31-52Article in journal (Refereed)
    Abstract [en]

    The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.

  • 2.
    Kjellström, Erik
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Boberg, Fredrik
    Castro, Manuel
    Christensen, Jens Hesselbjerg
    Nikulin, Grigory
    SMHI, Research Department, Climate research - Rossby Centre.
    Sanchez, Enrique
    Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models2010In: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 44, no 2-3, p. 135-150Article in journal (Refereed)
    Abstract [en]

    We evaluated daily and monthly statistics of maximum and minimum temperatures and precipitation in an ensemble of 16 regional climate models (RCMs) forced by boundary conditions from reanalysis data for 1961-1990. A high-resolution gridded observational data set for land areas in Europe was used. Skill scores were calculated based on the match of simulated and observed empirical probability density functions. The evaluation for different variables, seasons and regions showed that some models were better/worse than others in an overall sense. It also showed that no model that was best/worst in all variables, seasons or regions. Biases in daily precipitation were most pronounced in the wettest part of the probability distribution where the RCMs tended to overestimate precipitation compared to observations. We also applied the skill scores as weights used to calculate weighted ensemble means of the variables. We found that weighted ensemble means were slightly better in comparison to observations than corresponding unweighted ensemble means for most seasons, regions and variables. A number of sensitivity tests showed that the weights were highly sensitive to the choice of skill score metric and data sets involved in the comparison.

  • 3. Lenderink, G
    et al.
    Siebesma, A P
    Cheinet, S
    Irons, S
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Marquet, P
    Muller, F
    Olmeda, D
    Calvo, J
    Sanchez, E
    Soares, P M M
    The diurnal cycle of shallow cumulus clouds over land: A single-column model intercomparison study2004In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 130, no 604, p. 3339-3364Article in journal (Refereed)
    Abstract [en]

    An intercomparison study for single-column models (SCMs) of the diurnal cycle of shallow cumulus convection is reported. The case, based on measurements at the Atmospheric Radiation Measurement program Southern Great Plains site on 21 June 1997, has been used in a large-eddy simulation intercomparison study before. Results of the SCMs reveal the following general deficiencies: too large values of cloud cover and Cloud liquid water, unrealistic thermodynamic profiles, and high amounts of numerical noise. Results are also strongly dependent on vertical resolution. These results are analysed in terms of the behaviour of the different parametrization schemes involved: the convection scheme, the turbulence scheme, and the cloud scheme. In general the behaviour of the SCMs can be grouped in two different classes: one class with too strong mixing by the turbulence scheme, the other class with too strong activity by the convection scheme. The coupling between (subcloud) turbulence and the convection scheme plays a crucial role. Finally, (in part) motivated by these results several models have been successfully updated with new parametrization schemes and/or their present schemes have been successfully modified.

  • 4. Pessacg, Natalia L.
    et al.
    Solman, Silvina A.
    Samuelsson, Patrick
    SMHI, Research Department, Climate research - Rossby Centre.
    Sanchez, Enrique
    Marengo, Jose
    Li, Laurent
    Remedio, Armelle Reca C.
    da Rocha, Rosmeri P.
    Mourao, Caroline
    Jacob, Daniela
    The surface radiation budget over South America in a set of regional climate models from the CLARIS-LPB project2014In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 43, no 5-6, p. 1221-1239Article in journal (Refereed)
    Abstract [en]

    The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990-2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA.

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