Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details

Laprise, René; Kornic, Dragana; Rapaić, Maja; Šeparović, Leo; Leduc, Martin; Nikiéma, Oumarou; Luca, Alejandro Di; Diaconescu, Emilia Paula; Alexandru, Adelina; Lucas‐Picher, Philippe; Elía, Ramón de; Caya, Daniel; Biner, S.B.

doi:10.1007/978-3-7091-0973-1_14

Cited by 41 publications

(38 citation statements)

References 72 publications

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“…The mean seasonal circulation is not substantially altered by REMO, indicating that it is mainly determined by the lateral GCM-forcing and, to a minor extent by the internal freedom of REMO in the center of the domain, (e.g., [66]). There are only minor temperature differences between MPI-ESM and REMO in the lower troposphere at 850 hPa.…”

Section: Discussionmentioning

confidence: 98%

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

et al. 2013

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Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM) chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM) is modified by dynamic downscaling with the regional model REMO in different world regions. The historical specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming, although somewhat less so by the RCM for certain regions and climate types. A common feature in regions of tropical climate types is that REMO shows dryer climate conditions than forMax Planck Institute for Meteorology-Earth System Model (MPI-ESM) for RCP 4.5 and RCP 8.5, leading to an opposing sign in the climate change signal. With an increase in radiative forcing from RCP 2.6 to RCP 8.5 and towards the end of the 21st century, some of the detected differences between GCM and RCM are more pronounced.

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Section: Discussionmentioning

confidence: 98%

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

et al. 2013

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“…A key component of the experimental design is a large domain (13,644 km × 8388 km or 379 × 233 grid points, shown in Figure ) to ensure full spin‐up of small scales and to minimize constraints on IV by the domain boundaries [ Laprise et al ., ]. Interior domain nudging is not applied to further minimize system constraints.…”

Section: Methodsmentioning

confidence: 99%

Internal variability of North Atlantic tropical cyclones

Done

Bruyère

et al. 2014

JGR Atmospheres

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Using a regional model initial condition ensemble, this study quantifies the magnitude of internal variability of North Atlantic tropical cyclone frequency for a case study year and identifies potential physical sources. For tropical cyclone formations from easterly waves, the simulated internal variability of tropical cyclone frequency for 1998 is approximately two fifths of the total (externally forced and internal) variability of observed tropical cyclone frequency. The simulated internal variability of tropical cyclone frequency is found to arise in approximately equal measure from variability of easterly wave occurrence and development and variability of the transition from incipient warm cores to tropical cyclones. Variable interaction between developing tropical cyclones and vertical wind shear associated with upper level cyclones is identified as a potentially important contributing factor to tropical cyclone internal variability.

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“…Laprise et al (2008) and Rummukainen (2010) described the RCM as a ''magnifying glass'' that reveals fine scales features that are latent, but are not present in the coarse-resolution driving fields. This also means that the small-scales features are closely related to the large scales, and therefore a good representation of the large scales is a prerequisite for well-simulating small-scales features (Diaconescu et al 2007;Laprise et al 2012).…”

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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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Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details

Cited by 41 publications

References 72 publications

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

Internal variability of North Atlantic tropical cyclones

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

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