Testing E‐OBS European high‐resolution gridded data set of daily precipitation and surface temperature

Hofstra, Nynke; Haylock, M. R.; New, Mark; Jones, Phil

doi:10.1029/2009jd011799

Cited by 305 publications

(332 citation statements)

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“…A probability of exceedance of 0.001 corresponds to the 99.9th percentile precipitation could be considerably underestimated (by 15 to 51% in the grid boxes considered). Hofstra et al (2009) also found substantial differences between E-OBS and 3 other high-resolution data sets, in particular over topographically complex terrain such as the Alps. In agreement, we found differences between E-OBS and an alternative data set for the Rhine catchment area of approximately + 20%.…”

Section: Quality Of the Observations And Station Densitymentioning

confidence: 95%

“…This error mainly describes the error of the interpolation of the station observations to a very high resolution (0.1°base grid and the subsequent aggregation onto the 0.22°grid that is used here). In particular, the error related to spatial aggregation is difficult to assess because it is strongly dependent on estimates of the spatial correlation (shared variance), which is difficult to assess due to the low station density (see Hofstra et al 2009Hofstra et al , 2010. It is also not entirely clear whether this standard error should be interpreted as a random error or whether (in part) this error could be systematic.…”

Section: Sensitivity To Observation Datamentioning

confidence: 99%

“…As such, it is a very useful data set to evaluate the output of RCMs. Nevertheless, it is known that, in particular, the extremes in E-OBS are affected by station density (Haylock et al 2008, Hofstra et al 2009, 2010. For the construction of the E-OBS data set, approximately 2900 stations are used, whereas the number of grid cells in the 0.22°rotated model grid is approximately 16 000.…”

Section: Quality Of the Observations And Station Densitymentioning

confidence: 99%

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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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Section: Quality Of the Observations And Station Densitymentioning

confidence: 95%

Section: Sensitivity To Observation Datamentioning

confidence: 99%

Section: Quality Of the Observations And Station Densitymentioning

confidence: 99%

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

Lenderink¹

2010

Clim. Res.

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“…Frei and Schär, 1998, for an overview). A general dry bias, which can be exacerbated in mountainous terrain and for localised extremes, has been reported for E-OBS (Hofstra et al, 2009;Flaounas et al, 2012;Isotta et al, 2015).…”

Section: Observed Precipitationmentioning

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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“…E-OBS has been widely used for regional climate model evaluation (e.g. Lorenz and Jacob 2010;Nikulin et al 2011;Samuelsson et al 2011;Torma et al 2011;Flaounas et al 2013;Stéfanon et al 2014) and has been comprehensively evaluated in the literature (Hofstra et al 2009(Hofstra et al , 2010Kysel and Plavcov 2010;Flaounas et al 2012;Herrera et al 2012). In the E-OBS version 10 used here substantial improvements were realized, especially by increasing the station density (around 2000 for v1 and v2 vs. more than 4200 stations for temperature and more than 7300 for precipitation in v10).…”

Section: Observations: E-obs Datasetmentioning

confidence: 99%

Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios

et al. 2016

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temperature-precipitation extremes relationship displays a hook shape across the Mediterranean, with negative slope at high temperatures and a slope following Clausius-Clapeyron (CC)-scaling at low temperatures. The temperature at which the slope of the temperature-precipitation extreme relation sharply changes (or temperature break), ranges from about 20 °C in the western Mediterranean to <10 °C in Greece. In addition, this slope is always negative in the arid regions of the Mediterranean. The scaling of the simulated precipitation extremes is insensitive to oceanatmosphere coupling, while it depends very weakly on the resolution at high temperatures for short precipitation accumulation times. In future climate scenario simulations covering the 2070-2100 period, the temperature break shifts to higher temperatures by a value which is on average the mean regional temperature change due to global warming. AbstractIn this study we investigate the scaling of precipitation extremes with temperature in the Mediterranean region by assessing against observations the present day and future regional climate simulations performed in the frame of the HyMeX and MED-CORDEX programs. Over the 1979-2008 period, despite differences in quantitative precipitation simulation across the various models, the change in precipitation extremes with respect to temperature is robust and consistent. The spatial variability of the This paper is a contribution to the special issue on Med-CORDEX, an international coordinated initiative dedicated to the multi-component regional climate modelling (atmosphere, ocean, land surface, river) of the Mediterranean under the umbrella of HyMeX, CORDEX, and Med-CLIVAR and coordinated by Samuel Somot, Paolo Ruti, Erika Coppola, Gianmaria Sannino, Bodo Ahrens, and Gabriel Jordà. 3The slope of the simulated future temperature-precipitation extremes relationship is close to CC-scaling at temperatures below the temperature break, while at high temperatures, the negative slope is close, but somewhat flatter or steeper, than in the current climate depending on the model. Overall, models predict more intense precipitation extremes in the future. Adjusting the temperature-precipitation extremes relationship in the present climate using the CC law and the temperature shift in the future allows the recovery of the temperature-precipitation extremes relationship in the future climate. This implies negligible regional changes of relative humidity in the future despite the large warming and drying over the Mediterranean. This suggests that the Mediterranean Sea is the primary source of moisture which counteracts the drying and warming impacts on relative humidity in parts of the Mediterranean region.

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Testing E‐OBS European high‐resolution gridded data set of daily precipitation and surface temperature

Cited by 305 publications

References 32 publications

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

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

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

Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios

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