A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges

Prein, Andreas F.; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; Lipzig, Nicole Van; Leung, Ruby

doi:10.1002/2014rg000475

Cited by 1,067 publications

(1,093 citation statements)

References 377 publications

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“…GCMs also remain important for providing initial and boundary conditions for RCMs (e.g. Kendon et al, 2010), which now yield kilometre-scale climate simulations (Hohenegger et al, 2008;Kendon et al, 2014;Prein et al, 2015), allowing for convection-permitting simulations crucial for representing, in particular, sub-daily precipitation extremes Kendon et al, 2017) and the soil moistureprecipitation feedback (Hohenegger et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

Schiemann

Vidale

Shaffrey

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25 km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25 km model is about 25 % smaller than in the 135 km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50 000 km 2 . GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10 % in summer and around 20 % in the other seasons. For some river basins, however, these biases can be much larger and take values between 50 % and 100 %. Extreme precipitation is better simulated in the 25 km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation.

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Section: Introductionmentioning

confidence: 99%

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

Schiemann

Vidale

Shaffrey

et al. 2018

Hydrol. Earth Syst. Sci.

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“…The spatial resolution of these numerical experiments is an important aspect of the successful simulation of regional-scale precipitation (e.g., Sato et al 2008;Prein et al 2015). When computational resources are limited, a spatial resolution of coarser than 10 km is commonly used to obtain the climatological ensemble mean of physical variables, in which case a cumulus parameterization (CP) should be used to represent sub-grid-scale precipitation (e.g., Cruz et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…When computational resources are limited, a spatial resolution of coarser than 10 km is commonly used to obtain the climatological ensemble mean of physical variables, in which case a cumulus parameterization (CP) should be used to represent sub-grid-scale precipitation (e.g., Cruz et al 2016). In contrast, a microphysical process and a triggering of cloud convection are explicitly calculated in experiments using a fine mesh size (e.g., Prein et al 2015), resulting in an improvement in the thermodynamical processes associated with cumulus convection. A finer mesh size also improves the computation of orographic precipitation because it can resolve the dynamical effect of mountains on heavy precipitation (Leung and Qian 2003;Langhans et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Effect of Spatial Resolution and Cumulus Parameterization on Simulated Precipitation over South Asia

Sugimoto

Takahashi

2016

SOLA

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This paper evaluates the ability of a regional-scale climate model to simulate precipitation over the South Asian tropical region. Experiments were conducted using three different spatial resolutions, with and without cumulus parameterization (CP), to assess the influence of horizontal mesh size and the CP on regional-scale precipitation. The experiments that used a finer mesh size but no CP improved the spatial distribution of monthly precipitation relative to that in the experiments based on a coarser spatial resolution. Meanwhile, the impact of horizontal mesh size was much less in the experiments that included the CP because an overestimation of precipitation caused by the CP strongly affected the simulation accuracy in these experiments. Regional differences in diurnal variations in precipitation intensity and frequency were captured reasonably well in the pre-monsoon season regardless of the spatial resolution, and both with and without the CP. In contrast, the diurnal characteristics of precipitation were difficult to simulate during the mature monsoon season. During both seasons, those experiments that incorporated the CP tended to predicted a continuous weak precipitation due to the excessive release of convective instability; accordingly, precipitation intensity was weaker, and precipitation frequency greater than in those experiments that did not use the CP.(Citation: Sugimoto, S., and H. G. Takahashi, 2016: Effect of spatial resolution and cumulus parameterization on simulated precipitation over South Asia. SOLA, 12A, 7−12,

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“…Katragkou et al (2015), Kotlarski et al (2014) and Prein et al (2016). The model configurations for the convection-permitting (3 km grid spacing) simulations in the GAR 15 are based on experiences from previous sensitivity experiments (Suklitsch et al 2011;Awan et al 2011;Prein et al 2013;Prein et al 2015). Our RCMs differ from their coarser resolved counterparts (EURO-CORDEX) insofar that the parametrization for deep-convection has been turned off in the GAR.…”

Section: Study Area and Observation Data 20mentioning

confidence: 99%

“…Two major advantages of CPCSs concerning precipitation extremes are: (1) deep moist convection, which is the most important process in the majority of extreme precipitation events, are physically resolved by the RCM and (2) the representation of orography and surface fields is 20 improved. Multiple studies have already demonstrated the added value of convection-permitting models (CPMs, Prein et al, 2015) in capturing extreme precipitation (e.g., Chan et al 2013;Chan et al, 2014;Meredith et al, 2015;Chan et al, 2017;Zittis et al, 2017). However, there are only a few future projections that use CPCSs (e.g., Prein et al, 2017;Ban et al, 2015;Kendon et al, 2014).…”

mentioning

confidence: 99%

Convection-permitting regional climate simulations for representing floods in small and medium sized catchments in the Eastern Alps

Reszler¹,

Switanek²,

Truhetz³

2018

Preprint

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Abstract. Small scale floods are a consequence of high precipitation rates in small areas that can occur along frontal activity and convective storms. This situation is expected to become more severe due to a warming climate, when single precipitation events resulting from deep convection become more intense ("Super Clausius-Clapeyron effect"). Regional climate model (RCM) evaluations and inter-comparisons have shown that there is evidence that an increase in regional climate model 10 resolution and in particular, at the convection permitting scale, will lead to a better representation of the spatial and temporal characteristics of heavy precipitation at small and medium scales. In this paper, the benefit of grid size reduction and bias correction in climate models are evaluated in their ability to properly represent flood generation in small and medium sized catchments. The climate models are coupled with a distributed hydrological model. The study area is the Eastern Alps, where small scale storms often occur along with heterogeneous rainfall distributions leading to a very local flash flood 15 generation. The work is carried out in a small multi-model (ensemble) framework using two different RCMs (CCLM and WRF) in different grid sizes. Bias correction is performed by the use of the novel Scaled Distribution Mapping (SDM) method. The results show, that for small catchments (< 200 km²) a resolution of 3 km is essential to accurately simulate the magnitude of flood events. Flood frequency and seasonality are both represented well in all catchments. In the larger catchments resolutions of 12.5 km and 50 km already yield statistically satisfying results, but poor results regarding 20 seasonality. Also, due to the short response times in the small sub-catchments a time step of 1 hour is required. In all setups a bias still exists in precipitation and temperature, which sometimes leads to unrealistic hydrological conditions demonstrating the necessity of bias correction. The results show the added value of reducing grid size and bias correction in climate models that can be used to model flood mechanisms in small and medium sized catchments.

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A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges

Cited by 1,067 publications

References 377 publications

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

Effect of Spatial Resolution and Cumulus Parameterization on Simulated Precipitation over South Asia

Convection-permitting regional climate simulations for representing floods in small and medium sized catchments in the Eastern Alps

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