Sensitivity of a Spectrally Filtered and Nudged Limited-Area Model to Outer Model Options

Waldron, Kim M.; Paegle, Jan; Horel, John D.

doi:10.1175/1520-0493(1996)124<0529:soasfa>2.0.co;2

Cited by 169 publications

(149 citation statements)

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“…It might be possible to overcome this mathematically ill-posed boundary problem by framing the regional modeling as a state-space problem. Based on this concept, a dynamical model can augment existing knowledge about the regional state using the large-scale state of the atmosphere above a certain vertical level, where the influence of regional physiographic details is small (Kida et al 1991;Sasaki et al 1995;Waldron et al 1996;von Storch et al 2000). The spectral nudging technique, in which the regional model is exposed not only to lateral boundary values but also to scale-selective constraints in the interior that are considered well described by the global analysis or the global simulation, is based on this concept.…”

Section: Scale-selective Nudgingmentioning

confidence: 99%

Reconsidering the Quality and Utility of Downscaling

Takayabu¹,

Kanamaru

Dairaku

et al. 2016

Journal of the Meteorological Society of Japan

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Dynamical downscaling (DDS) is performed using regional climate models (RCMs) with global atmospheric states as the input, but there is no consensus among researchers on how to define and estimate the resolvable scale of the various climatic variables obtained by DDS. Sources of RCM uncertainties, including both internal model and intermodel variability, have been assessed by performing ensemble simulations and model intercomparisons, sometimes under the controversial assumption that model bias is independent of the climatic state. Compared with low-resolution global climate simulations, DDS can add value in several ways. For example, because they consider high-resolution topographic data, RCMs can often capture mesoscale phenomena and can better represent climate dynamics. Another downscaling method, empirical statistical downscaling (ESD), is complementary to DDS because it is based on a different philosophy (i.e., sources of information) and on a mostly different set of assumptions. More collaboration and communication should be encouraged among those who develop models, those who use models and perform downscaling, those who use downscaling data, and those who make decisions

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Section: Scale-selective Nudgingmentioning

confidence: 99%

Reconsidering the Quality and Utility of Downscaling

Takayabu¹,

Kanamaru

Dairaku

et al. 2016

Journal of the Meteorological Society of Japan

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“…The approach of analyzing complex models by resorting to synthetic models containing a few key ingredients with only a formal similarity with the original problem has a long history and has proven useful in the past. Actually Waldron et al (1996) use a linear wave model in order to compare the impact of indiscriminate and spectral nudging at the small and large scales, before turning to a realistic model. The approach used in this paper is quite similar.…”

Section: Rationalementioning

confidence: 99%

The effect of indiscriminate nudging time on large and small scales in regional climate modelling: Application to the Mediterranean basin

Salameh

Drobinski

Dubos

2010

Quart J Royal Meteoro Soc

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A regional climate model (RCM) is driven by the ERA-40 reanalyses produced by the ECMWF general circulation model (GCM) to simulate the winter 1998 climate over the Mediterranean basin. In this article, we consider the effects on internal variability of temporal nudging. This technique consists of relaxing the RCM's prognostic variables towards the GCM values within a predetermined time-scale, with the aim of disallowing large and unrealistic departures between driving and driven fields. To interpret the significant effect of time nudging on the regional climate prediction, we develop a 'toy model' basically consisting of resolving a linear transport equation with a Newtonian relaxation term. This model predicts the existence of an optimal nudging time which depends on the time-scale over which numerical errors affect significantly the accuracy of the 'regional' solution at the large spatial scales, and the typical time-scale of the small-scale phenomena that are not resolved by the GCM.

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“…In this technique, nudging is conducted in every grid cell. Another nudging technique that has gained interest is spectral nudging (Waldron et al, 1996;von Storch et al, 2000), in which the nudging term is spectrally expanded in both the zonal and meridional directions and only the waves under selected wave numbers are kept in the nudging term. All other waves are filtered out.…”

Section: Introductionmentioning

confidence: 99%

Differences between downscaling with spectral and grid nudging using WRF

et al. 2012

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Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

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Sensitivity of a Spectrally Filtered and Nudged Limited-Area Model to Outer Model Options

Cited by 169 publications

References 0 publications

Reconsidering the Quality and Utility of Downscaling

Reconsidering the Quality and Utility of Downscaling

The effect of indiscriminate nudging time on large and small scales in regional climate modelling: Application to the Mediterranean basin

Differences between downscaling with spectral and grid nudging using WRF

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