Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000

Sánchez-Gómez, Emilia; Somot, Samuel; Déqué, Michel

doi:10.1007/s00382-008-0502-7

Cited by 111 publications

(99 citation statements)

References 30 publications

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“…This pattern is characterized by a stronger anticyclone circulation centered over the north of the domain, which reduces the strength of the North Atlantic westerly flow. Similar results were found for the European domain in Sanchez-Gomez et al (2008), by using the EU-FP6 ENSEMBLES multi-model database. They identified the Scandinavian Blocking as the atmospheric pattern excited in those periods in which the different RCMs, forced by the same LBCs, showed the largest discrepancies.…”

Section: Discussionsupporting

confidence: 84%

“…This SLP spatial pattern is similar to the Scandinavian Blocking (Barston and Livezey 1987), which exhibits a more zonal and weaker westerly atmospheric flow, leading to a weakening of the ERAI forcing at the ALADIN boundaries. The Blocking pattern was also documented in Sanchez-Gomez et al (2008) as being strongly related to large IV. Figure 11c, d shows the same composite patterns for the ensembles mean of ALADIN.…”

Section: Internal Variability and Large-scale Atmospheric Circulationmentioning

confidence: 80%

“…This has been previously addressed for an ensemble of RCMs operating over the European domain from the EU-FP6 ENSEMBLES project, by using four North Atlantic weather regimes (Sanchez-Gomez et al 2008); and over the South Africa domain by Cré-tat et al (2011), through a weather type approach. For Europe, Sanchez-Gomez et al (2008) found that Blocking In the present case, we analyse the atmospheric circulation related to highest RIV by conducting a composite approach, which differs from the weather typing methodologies mentioned above. This consists of selecting first those days where the RIV values exceed the 90 % percentile of RIV of the precipitation time-series from Fig.…”

Section: Internal Variability and Large-scale Atmospheric Circulationmentioning

confidence: 99%

See 2 more Smart Citations

Impact of the internal variability on the cyclone tracks simulated by a regional climate model over the Med-CORDEX domain

Sánchez-Gómez

Somot

2016

Clim Dyn

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Section: Discussionsupporting

confidence: 84%

Section: Internal Variability and Large-scale Atmospheric Circulationmentioning

confidence: 80%

Section: Internal Variability and Large-scale Atmospheric Circulationmentioning

confidence: 99%

See 1 more Smart Citation

Impact of the internal variability on the cyclone tracks simulated by a regional climate model over the Med-CORDEX domain

Sánchez-Gómez

Somot

2016

Clim Dyn

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“…All RCMs have been driven at the lateral boundaries by the meteorological fields from the ERA40 re-analysis, thereby forc-ing the atmospheric motions to be close to the observations (Sanchez-Gomez et al 2009). Most models use an identical grid with a rotated pole at a 0.22°resolution.…”

Section: Observations and Modelsmentioning

confidence: 99%

Exploring metrics of extreme daily precipitation in a large ensemble of regional climate model simulations

Lenderink¹

2010

Clim. Res.

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The ability of a large ensemble of 15 state-of-the-art regional climate models (RCMs) to simulate precipitation extremes was investigated. The 99th, 99.9th and 99.99th percentiles of daily precipitation in the models were compared with those in the recently released E-OBS observational database for winter, spring, summer and autumn. The majority of the models overestimated the values of the precipitation extremes compared with E-OBS, on average by approximately 38%, but some models exceeded 50%. To measure model performance, a simple metric is proposed that averages a nonlinear function of the seasonal biases over the European area. The sensitivity of the metric to different assumptions in the construction and the quality of the observational data was explored. Generally, low sensitivities of the metric to spatial and seasonal averaging were found. However, large sensitivities to potential biases in the observational database were found. An alternative metric that measures the spatial pattern of the extremes (which is not sensitive to a potential constant offset in the observational data) was further explored. With this metric, the ranking between the models changed substantially. However, the 2 models with the worst score in the standard metric also displayed the worst scores with this alternative metric. Finally, the regional climate models displayed the largest biases compared with E-OBS in areas where the underlying station density used in E-OBS is low, thus suggesting that data quality is indeed an important issue. In summary, the results show that: (1) there is no metric that guarantees an objective and precise ranking or weighting of the models, (2) by exploring different metrics it nevertheless appears possible to indentify models that perform consistently worse than other models, and (3) the observational data quality should be considered when designing and interpreting metrics.

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“…In recent years, however, the AV problem received increased attention and become the main subject of several studies (Castro et al 2005;Sotillo et al 2005;Duffy et al 2006;Feser 2006;Kanamitsu and Kanamaru 2007;Rauscher et al 2007;Sanchez-Gomez et al 2009;Winterfeldt and Weisse 2009;De Sales and Xue 2010;Prömmel et al 2010) and a central topic in a number of workshops (Bärring and Laprise 2005;Rockel et al 2010). Although some authors (e.g.…”

Section: Introductionmentioning

confidence: 99%

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

2011

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Regional Climate Models (RCMs) constitute the most often used method to perform affordable highresolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

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Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000

Cited by 111 publications

References 30 publications

Impact of the internal variability on the cyclone tracks simulated by a regional climate model over the Med-CORDEX domain

Impact of the internal variability on the cyclone tracks simulated by a regional climate model over the Med-CORDEX domain

Exploring metrics of extreme daily precipitation in a large ensemble of regional climate model simulations

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

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