Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions

Christensen, Jens Hesselbjerg; Machenhauer, B.; Jones, Richard G.; Schär, Christoph; Ruti, Paolo; Castro, Manuel de; Visconti, Guido

doi:10.1007/s003820050178

Cited by 159 publications

(109 citation statements)

References 36 publications

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“…Jones et al 1995;Christensen et al 1997;Machenhauer et al 1998;Frei et al 2003;Rinke et al 2006;Jacob et al 2007), or under the idealised Big-Brother Experiment (e.g. Denis et al 2002bDenis et al , 2003Antic et al 2004;Dimitrijevic and Laprise 2005).…”

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confidence: 99%

Can added value be expected in RCM-simulated large scales?

Diaconescu

Laprise

2013

Clim Dyn

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Nested Limited-Area Models require driving data to define their lateral boundary conditions (LBC). The optimal choice of domain size and the repercussions of LBC errors on Regional Climate Model (RCM) simulations are important issues in dynamical downscaling work. The main objective of this paper is to investigate the effect of domain size, particularly on the larger scales, and to question whether an RCM, when run over very large domains, can actually improve the large scales compared to those of the driving data. This study is performed with a detailed atmospheric model in its global and regional configurations, using the ''Imperfect Big-Brother'' (IBB) protocol. The ERA-Interim reanalyses and five global simulations are used to drive RCM simulations for five winter seasons, on four domain sizes centred over the North American continent. Three variables are investigated: precipitation, specific humidity and zonal wind component. The results following the IBB protocol show that, when an RCM is driven by perfect LBC, its skill at reproducing the large scales decreases with increasing the domain of integration, but the errors remain small even for very large domains. On the other hand, when driven by LBC that contain errors, RCMs can bring some reduction of errors in large scales when very large domains are used. The improvement is found especially in the amplitude of patterns of both the stationary and the intra-seasonal transient components. When large errors are present in the LBC, however, these are only partly corrected by the RCM.Although results showed that an RCM can have some skill at improving imperfect large scales supplied as driving LBC, the main added value of an RCM is provided by its small scales and its skill to simulate extreme events, particularly for precipitation. Under the IBB protocol all RCM simulations were fairly skilful at reproducing small scales statistics, although the skill decreased with increasing LBC errors. Coarse-resolution model simulations have difficulties in simulating heavy precipitation events, and as a result their precipitation distributions are systematically shifted toward smaller intensity. Under the IBB protocol, all RCM simulations have distributions very similar to the reference field, being little affected by LBC errors, and no significant differences were found between the small scales statistics and the precipitation distributions obtained over different RCM domains.

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confidence: 99%

Can added value be expected in RCM-simulated large scales?

Diaconescu

Laprise

2013

Clim Dyn

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“…Recently, the model has been modified for use as a regional climate model, and has extensively been used for climate studies (Luthi et al, 1996;Schar et al, 1996. The regional climate model has also been featured in an international model intercomparison project (Christensen et al, 1997).…”

Section: Model Description and Setupmentioning

confidence: 99%

The Interannual Variability as a Test Ground for Regional Climate Simulations over Japan

Fukutome

Frei

Lüthi

et al. 1999

Journal of the Meteorological Society of Japan

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The validation of regional climate models is usually based on the intercomparison of the model's mean climate with the observed climatology. Albeit a prerequisite for the use of the model in a predictive mode, a successful validation of this type does not strictly test the model's ability to simulate anomalous conditions as might be associated with anthropogenic climate change. Here, we explore an alternate strategy, whereby the model's ability to reproduce the observed interannual variability is tested. The model utilized is an operational numerical weather prediction model of the German Weather Service, and it is tested for its use over East Asia and Japan in a series of 5 month-long January simulations. The model is used in a domain of 5100x5100km2, has a horizontal resolution of 56km, and 20 levels in the vertical. It is driven at its boundaries by the European Center for Medium-Range Weather Forecast (ECMWF) analysis.In validating the integrations, particular emphasis is put on the precipitation fields. For validation we use three different observational data sets: a terrestrial analysis from rain gauges, including the Automated Meteorological Data Acquisition System (AMeDAS) data of the Japan Meteorological Agency, the gridded data set of the Global Precipitation Climatology Project (GPCP), which over sea is largely based upon satellite information, and the ECMWF Re-Analysis (ERA) data set, which is produced by a model in an assimilation mode.It is demonstrated that the synoptic-scale evolution of individual low-pressure systems within the modeling domain is deterministically controlled by the lateral boundary conditions. Precipitation -spatially averaged over selected subdomains -compares remarkably well with the observations, both in terms of the monthly amounts and of the temporal evolution throughout the integration period. Using the strategy of a previous study, we analyze the year-to-year variations of the model results, both for the dynamical and precipitation fields. It is found that the modeling error is substantially smaller than the typical year-to-year fluctuations of the interannual variability. Implications of this result, concerning the model's use as a tool for down-scaling climate change, are also discussed.

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“…However, an important aspect of high resolution models is their spin-up time. When operated in climate mode they require simulation lengths exceeding the spinup time which is of the order of several days [10][11][12][13][14][15][16] Kain-Fritsch (KF) [8,9]. PBL scheme YSU scheme Explicit moisture scheme WSM 3-class Simple Ice…”

Section: Introductionmentioning

confidence: 99%

Numerical Modeling of the Severe Cold Weather Event over Central Europe (January 2006)

Dasari

Wibig

Rzepa

2010

Advances in Meteorology

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Cold waves commonly occur in higher latitudes under prevailing high pressure systems especially during winter season which cause serious economical loss and cold related death. Accurate prediction of such severe weather events is important for decision making by administrators and for mitigation planning. An Advanced high resolution Weather Research and Forecasting mesoscale model is used to simulate a severe cold wave event occurred during January 2006 over Europe. The model is integrated for 31 days starting from 00UTC of 1 January 2006 with 30 km horizontal resolution. Comparison of the model derived area averaged daily mean temperatures at 2m height from different zones over the central Europe with observations indicates that the model is able to simulate the occurrence of the cold wave with the observed time lag of 1 to 3days but with lesser intensity. The temperature, winds, surface pressure and the geopential heights at 500 hPa reveal that the cold wave development associates with the southward progression of a high pressure system and cold air advection. The results have good agreement with the analysis fields indicates that the model has the ability to reproduce the time evolution of the cold wave event.

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Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions

Cited by 159 publications

References 36 publications

Can added value be expected in RCM-simulated large scales?

Can added value be expected in RCM-simulated large scales?

The Interannual Variability as a Test Ground for Regional Climate Simulations over Japan

Numerical Modeling of the Severe Cold Weather Event over Central Europe (January 2006)

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