Validation of mesoscale low-level winds obtained by dynamical downscaling
                        of ERA40 over complex terrain

Žagar, Nedjeljka; Žagar, Mark; Cedilnik, Jure; Gregorič, Gregor; Rakovec, Jože

doi:10.1111/j.1600-0870.2006.00186.x

Cited by 56 publications

(33 citation statements)

References 14 publications

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“…Initial and boundary conditions were provided by the global reanalysis of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis (ERA-40; Kållberg et al 2004), which is available at 125-km grid spacing with a 6-hourly frequency. Following the methods of Beck et al (2004) andŽ agar et al (2006), a direct nesting strategy was implemented. These authors showed that the dynamical downscaling of ERA-40 data with the ALADIN model to ;10-km grid spacing is equally accurate whether or not an intermediate domain is used.…”

Section: Methodsmentioning

confidence: 99%

Dynamical Downscaling of Wind Speed in Complex Terrain Prone To Bora-Type Flows

Horvath¹,

Bajić²,

Ivatek-Šahdan³

2011

Journal of Applied Meteorology and Climatology

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The results of numerically modeled wind speed climate, a primary component of wind energy resource assessment in the complex terrain of Croatia, are given. For that purpose, dynamical downscaling of 10 yr (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001) of the 40-yr ECMWF Re-Analysis (ERA-40) was performed to 8-km horizontal grid spacing with the use of a spectral, prognostic full-physics model Aire Limité e Adaptation Dynamique Dé veloppement International (ALADIN; the ''ALHR'' version). Then modeled data with a 60-min frequency were refined to 2-km horizontal grid spacing with a simplified and cost-effective model version, the so-called dynamical adaptation (DADA). The statistical verification of ERA-40-, ALHR-, and DADA-modeled wind speed on the basis of data from measurement stations representing different regions of Croatia suggests that downscaling was successful and that model accuracy generally improves as horizontal resolution is increased. The areas of the highest mean wind speeds correspond well to locations of frequent and strong bora flow as well as to the prominent mountain peaks. The best results are achieved with DADA and contain bias of 1% of the mean wind speed for eastern Croatia while reaching 10% for complex coastal terrain, mainly because of underestimation of the strongest winds. Root-mean-square errors for DADA are significantly smaller for flat terrain than for complex terrain, with relative values close to 12% of the mean wind speed regardless of the station location. Spectral analyses suggest that the shape of the kinetic energy spectra generally relaxes from k 23 at the upper troposphere to the shape of orographic spectra near the surface and shows no seasonal variability. Apart from the buildup of energy on smaller scales of motions, it is shown that mesoscale simulations contain a considerable amount of energy related to near-surface and mostly divergent meso-b-scale (20-200 km) motions. Spectral decomposition of measured and modeled data in temporal space indicates a reasonable performance of all model datasets in simulating the primary maximum of spectral power related to synoptic and larger-than-diurnal mesoscale motions, with somewhat increased accuracy of mesoscale model data. The primary improvement of dynamical adaptation was achieved for cross-mountain winds, whereas mixed results were found for along-mountain wind directions. Secondary diurnal and tertiary semidiurnal maxima are significantly better simulated with the mesoscale model for coastal stations but are somewhat more erroneous for the continental station. The mesoscale model data underestimate the spectral power of motions with less-than-semidiurnal periods.

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Section: Methodsmentioning

confidence: 99%

Dynamical Downscaling of Wind Speed in Complex Terrain Prone To Bora-Type Flows

Horvath¹,

Bajić²,

Ivatek-Šahdan³

2011

Journal of Applied Meteorology and Climatology

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“…The initial and boundary conditions necessary to perform the simulation are obtained from a general circulation model. The accuracy of the mesoscale model in representing the wind field can be evaluated by comparing the simulations with independent observational information (e.g., Mahrer et al 1985;Rife et al 2004;Zagar et al 2006). Additionally, hybrid approaches can enhance the spatial resolution of a mesoscale simulation using a diagnostic model (e.g., Ludwig et al 2006); however, their reliability is conditioned to that of the mesoscale simulation and the suitable representation of physical processes.…”

Section: Introductionmentioning

confidence: 99%

“…The value of the WRF simulation should be viewed in the context of the computational costs of running prognostic mesoscale models. Typically, short temporal periods of a few months or specifically the duration of an observational campaign are simulated to limit the computational requirements (Zhong and Fast 2003;Cairns and Corey 2003;Rife et al 2004;Zagar et al 2006). Although the computational power reached in the last years makes multiyear simulations feasible (Buckley et al 2004;Conil and Hall 2006;Walter et al 2006), long simulations at higher spatial resolutions that better capture the details of complex orography and allow for evaluations of variability at longer time scales are still computationally demanding and thus have not been so far extensively used.…”

Section: Introductionmentioning

confidence: 99%

Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation

Jiménez

González-Rouco²,

García‐Bustamante

et al. 2010

Journal of Applied Meteorology and Climatology

109

100

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This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992-2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999-2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one's understanding of the wind variability over the area. The subregions identified with the simulation during the 1992-2005 period are similar to those identified with observations (1999)(2000)(2001)(2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.

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“…This type of model behaviour, which could arise due to the used parameterisations of the model and information about the complex terrain characteristics, has already been observed so far in a large number of modelling studies (e.g. Žagar et al, 2006;Borge et al, 2008;Challa et al, 2009;Papanastasiou et al, 2010).…”

Section: Appendix a Model Verification By The Near-surface Measurementsmentioning

confidence: 99%

Wind patterns associated with the development of daytime thunderstorms over Istria

et al. 2014

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Abstract. The northeastern (NE) Adriatic in the northernMediterranean is the area with (i) the highest frequency of thunderstorms in Croatia, and (ii) frequent appearances of sea breeze (SB) along the coast. This study investigates the impact of the combined large-scale wind (associated with particular synoptic conditions) and the SB on the moist convection development over the NE Adriatic. The four selected cases were (i) chosen on the basis of a daytime moist convection; (ii) supplemented by one of the dominant large-scale winds with seaward (NE, NW) and landward (SW, SE) directions and (iii) simulated by WRF numerical model.The near-surface wind patterns consisted of SBs along the coastline, generated a narrow eastward-moving convergence zone (CZ) along the area if the large-scale wind was less than 9 m s −1 (below 500 hPa). Apart from the low-level CZ, the advection of large-scale wind influenced the lifetime and movement of the initial Cb cells. While the local front collision with the NE wind advection caused the thunderstorm to propagate southward, the CZ and fronts interaction determined the afternoon northwestward storm movement against the NW large-scale wind. Due to particular synoptic background, the thunderstorm event in SE case was the shortest with only a minor impact on the SB. While the origins and locations of storm cells were completely controlled by the low-level CZ and the upward advection of low-level moisture at the SB front, the most typical convective case with SW warm-wet wind only partially supported the SB-Cb interaction.

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Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA40 over complex terrain

Cited by 56 publications

References 14 publications

Dynamical Downscaling of Wind Speed in Complex Terrain Prone To Bora-Type Flows

Dynamical Downscaling of Wind Speed in Complex Terrain Prone To Bora-Type Flows

Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation

Wind patterns associated with the development of daytime thunderstorms over Istria

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