Meeting Summaries

Leung, L. Ruby; Mearns, Linda O.; Giorgi, Filippo; Wilby, Robert L.

doi:10.1175/bams-84-1-89

Cited by 165 publications

(37 citation statements)

References 5 publications

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“…Part of the difficulty in exploring the dynamic downscaling ability issue is rooted in the lack of validation data for small scale features (e.g., Leung et al, 2003a). Simply applying low resolution global reanalyses as climate reference for comparison is inadequate because the small scale features are absent in the global reanalyses.…”

Section: Introductionmentioning

confidence: 99%

A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability

Xue

Janjić

Dudhia

et al. 2014

Atmospheric Research

212

135

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Regional climate models (RCMs) have been developed and extensively applied for dynamically downscaling coarse resolution information from different sources, such as general circulation models (GCMs) and reanalyses, for different purposes including past climate simulations and future climate projection. Thus far, the nature, the methods, and a number of crucial issues concerning the use of dynamic downscaling are still not well understood. The most important issue is whether, and if so, under what conditions dynamic downscaling is really capable of adding more information at different scales compared to the GCM or reanalysis that imposes lateral boundary conditions (LBCs) to the RCMs. There are controversies regarding the downscaling ability. In this review paper we present several factors that have consistently demonstrated strong impact on dynamic downscaling ability in intraseasonal and seasonal simulations/predictions and future projection. Those factors include setting of the RCM experiment (e.g. imposed LBC quality, domain size and position, LBC coupling, and horizontal resolution); as well as physical processes, mainly convective schemes and vegetation and soil processes that include initializations, vegetation specifications, and planetary boundary layer and surface coupling. These studies indicate that RCMs have downscaling ability in some aspects but only under certain conditions. Any significant weaknesses in one of these aspects would cause an RCM to lose its dynamic downscaling ability. This paper also briefly presents challenges faced in current RCM dynamic downscaling and future prospective, which cover the application of coupled ocean-atmosphere RCMs, ensemble applications, and future projections.

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Section: Introductionmentioning

confidence: 99%

A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability

Xue

Janjić

Dudhia

et al. 2014

Atmospheric Research

212

135

View full text Add to dashboard Cite

show abstract

“…One distinct advantage of RCM application is its high horizontal resolution, which enables the RCM to provide additional details beyond global reanalysis or global climate simulations (Liang et al 2004;Feser et al 2011) and realistically describe certain critically important climate processes, such as clouds and land-surface processes/features (Leung et al 2003;1 3 of coarse-resolution gridded data from various reanalysis datasets and/or forecast products of general circulation models (GCMs). RCMs have also been increasingly used to meet the demand of forecast (e.g.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of a regional climate model to land surface parameterization schemes for East Asian summer monsoon simulation

Guo

Xue

et al. 2015

Clim Dyn

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“…One of the well-established techniques to obtain high-resolution information adequate for impact studies is dynamical downscaling through regional climate modeling [6] [7]. Relatively coarse data derived from global models are used as initial and boundary conditions to drive the higher resolution limited-area models.…”

Section: Introductionmentioning

confidence: 99%