A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates

Abstract. Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing withPublished by Copernicus Publications on behalf of the European Geosciences Union. observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

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“…The increase in resolution also improves the simulated temporal variability, including simulation of extremes (Durman et al, 2001). …”

Section: Hadrm3bmentioning

confidence: 97%

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

et al. 2017

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“…For this variable it has been shown that RCMs are able to add significant information to the driving global simulations, both in space and time (e.g., Jones et al 1995;Durman et al 2001;Jones et al 2004). In general terms, the RCMs produce an intensification of precipitation with respect to the driving global climate model (GCM), related to the intensification of the hydrological cycle (Jones et al 1995;Durman et al 2001;Buonomo et al 2007). Lynn et al (2010) tested a regional climate model with different physics components at two different spatial resolutions.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

et al. 2013

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Daily summer precipitation over Belgium from the Aire Limitee Adaptation Dynamique Developpement International (ALADIN) model and a version of the model that has been updated with physical parameterizations, the so-called ALARO-0 model [ALADIN and AROME (Application de la Recherche a l'Operationnel a Meso-Echelle) combined model, first baseline version released in 1998], are compared with respect to station observations for the period 1961-90. The 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) is dynamically downscaled using both models on a horizontal resolution of 40 km, followed by a one-way nesting on high spatial resolutions of 10 and 4 km. This setup allows us to explore the relative importance of spatial resolution versus parameterization formulation on the model skill to correctly simulate extreme daily precipitation. Model performances are assessed through standard statistical errors and density, frequency, and quantile distributions as well as extreme value analysis, using the peak-over-threshold method and generalized Pareto distribution. The 40-km simulations of ALADIN and ALARO-0 show similar results, both reproducing the observations reasonably well. For the high-resolution simulations, ALARO-0 at both 10 and 4 km is in better agreement with the observations than ALADIN. The ALADIN model consistently produces too high precipitation rates. The findings demonstrate that the new parameterizations within the ALARO-0 model are responsible for a correct simulation of extreme summer precipitation at various horizontal resolutions. Moreover, this study shows that ALARO-0 is a good candidate model for regional climate modeling.

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“…Maraun et al (2010) reviewed the situation with regard to RCM-simulated precipitation. Compared with their driving GCMs, RCMs tend to better reproduce the daily distribution of precipitation, including extreme events, and also spatial features of the field over regions of complex topography (Durman, Gregory, Hassell, Jones, & Murphy, 2001;Frei, Schöll, Fukutome, Schmidli, & Vidale, 2006;Maraun et al, 2010). The characteristic length scale at which the largest improvement in model skill occurs for precipitation tends to be smaller than that for temperature, often not occurring until below 12 km or so (Flato et al, 2013;Maraun et al, 2010).…”

Section: Introductionmentioning

confidence: 95%

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada

et al. 2016

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We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45 km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973-1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10 km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX > 25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45 km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability. RÉSUMÉ [Traduit par la rédaction] Nous évaluons la capacité d'un modèle régional de climat à représenter des conditions observées de température et de précipitations extrêmes. Nous examinons aussi l'impact d'une résolution accrue, afin d'en déterminer la plus-value dans ce cas. Nous avons mené deux simulations du climat pour l'ouest du Canada, avec le Modèle régional canadien du climat (version 4), à une résolution horizontale de 15 km (MRCC15) et de 45 km (MRCC45). Les conditions limites provenaient des réanalyses de 40 ans (ERA-40) du Centre européen pour les prévisions météorologiques à m...

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A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates

Cited by 184 publications

References 12 publications

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada

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