Evaluation of the mean and extreme precipitation regimes from the ENSEMBLES regional climate multimodel simulations over Spain

Herrera, Sixto; Fita, L.; Fernández, Jesús Fernández; Gutiérrez, José Manuel

doi:10.1029/2010jd013936

Cited by 129 publications

(183 citation statements)

References 47 publications

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“…R95pTOT and R99pTOT (Tank et al 2009;Herrera et al 2010) constitute the percentages of extreme events, exceeding the 95% and 99% percentiles of the reference period, on the total precipitation.…”

Section: Discussionmentioning

confidence: 99%

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Tölle

Schefczyk

Gutjahr

2017

Theor Appl Climatol

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A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5-and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 Max Planck Institute for Meteorology, Hamburg, Germany precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

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Section: Discussionmentioning

confidence: 99%

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Tölle

Schefczyk

Gutjahr

2017

Theor Appl Climatol

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“…8910 extreme value analysis show for ALARO-0 at the high resolutions of 4 and 10 km, as well as at 40-km horizontal resolution, a clear improvement in simulating extreme summer precipitation. Extreme events are also often investigated by means of climate indices (e.g., Herrera et al 2010;Domınguez et al 2013;Duliere et al 2011;Soares et al 2012b). To complete the extreme value analysis, two main precipitation indices have been calculated: the number of wet days and the number of very heavy precipitation days.…”

Section: ) Error Statisticsmentioning

confidence: 99%

“…Precipitation is thus an important meteorological variable in weather prediction and climate studies. Herrera et al (2010) studied the ability of regional climate models (RCMs) to reproduce the mean and extreme precipitation regimes over Spain using a state-of-the-art ensemble of RCM simulations. The RCMs show good agreement with the observed mean precipitation regime, but for the extreme regimes the models reveal important limitations.…”

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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“…Some researchers have noted potential weaknesses of the E-OBS data set in data-sparse regions (e.g. Herrera et al 2010). The MCYFS database has similar shortcomings with respect to the spatial density of weather stations and how these are interpolated to the grid.…”

Section: Discussionmentioning

confidence: 99%

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

Duveiller

Donatelli

Fumagalli

et al. 2015

Theor Appl Climatol

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Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near-and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

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Evaluation of the mean and extreme precipitation regimes from the ENSEMBLES regional climate multimodel simulations over Spain

Cited by 129 publications

References 47 publications

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Scale dependency of regional climate modeling of current and future climate extremes in Germany

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

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

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