Abstract
There are well-known difficulties to run numerical weather prediction (NWP) and climate models at resolutions traditionally referred to as ‘grey-zone’ (~3–8 km) where deep convection is neither completely resolved by the model dynamics nor completely subgrid. In this study, we describe the performance of an operational NWP model, HARMONIE, in a climate setting (HCLIM), run at two different resolutions (6 and 15 km) for a 10-yr period (1998–2007). This model has a convection scheme particularly designed to operate in the ‘grey-zone’ regime, which increases the realism and accuracy of the time and spatial evolution of convective processes compared to more traditional parametrisations. HCLIM is evaluated against standard observational data sets over Europe as well as high-resolution, regional, observations. Not only is the regional climate very well represented but also higher order climate statistics and smaller scale spatial characteristics of precipitation are in good agreement with observations. The added value when making climate simulations at ~5 km resolution compared to more typical regional climate model resolutions is mainly seen for the very rare, high-intensity precipitation events. HCLIM at 6 km resolution reproduces the frequency and intensity of these events better than at 15 km resolution and is in closer agreement with the high-resolution observations.
Highlights
Accurate and reliable projections of future precipitation distributions remain one of the greatest challenges in the climate model community
L can have values between zero and two, the former indicating a perfect match. This is the first time HCLIM has been used as a climate model and one of few studies where an regional climate models (RCMs) has been run in climate mode at grey-zone resolution at this spatial scale
After establishing the general performance in a standard setting, we address the impact of higher model resolution by examining the HCLIM6 and HCLIM15 simulated climate in more detail focussing on precipitation
Summary
Accurate and reliable projections of future precipitation distributions remain one of the greatest challenges in the climate model community. Global and regional, struggle to accurately capture the observed intensity and frequency of precipitation, deviating from observations most radically at the extreme high- and/or low-intensity tails of the distribution (e.g. Kjellström et al, 2010; Wehner, 2013), lowering the confidence in models projections of changes in these features under climate change scenarios. One important reason for this discrepancy is likely the low resolution presently used in climate models, an issue which has been extensively discussed and studied With the use of an atmosphere-only global climate model (GCM) run in an aqua-planet configuration, Li et al. The result emphasised the importance of model resolution for simulating higher order statistics of rainfall
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