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Assessment of multiple daily precipitation statistics in ERA-Interim driven Med-CORDEX and EURO-CORDEX experiments against high resolution observations

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Abstract

We assess the statistics of different daily precipitation indices in ensembles of Med-CORDEX and EURO-CORDEX experiments at high resolution (grid spacing of ~0.11°, or RCM11) and medium resolution (grid spacing of ~0.44°, or RCM44) with regional climate models (RCMs) driven by the ERA-Interim reanalysis of observations for the period 1989–2008. The assessment is carried out by comparison with a set of high resolution observation datasets for nine European subregions. The statistics analyzed include quantitative metrics for mean precipitation, daily precipitation probability density functions (PDFs), daily precipitation intensity, frequency, 95th percentile and 95th percentile of dry spell length. We assess an ensemble including all Med-CORDEX and EURO-CORDEX models together and others including the Med-CORDEX and EURO-CORDEX separately. For the All Models ensembles, the RCM11 one shows a remarkable performance in reproducing the spatial patterns and seasonal cycle of mean precipitation over all regions, with a consistent and marked improvement compared to the RCM44 ensemble and the ERA-Interim reanalysis. A good consistency with observations by the RCM11 ensemble (and a substantial improvement compared to RCM44 and ERA-Interim) is found also for the daily precipitation PDFs, mean intensity and, to a lesser extent, the 95th percentile. A general improvement by the RCM11 models is also found when the data are upscaled and intercompared at the 0.44° and 1.5° resolutions. For some regions the RCM11 ensemble overestimates the occurrence of very high intensity events while for one region the models underestimate the occurrence of the most intense extremes. The RCM11 ensemble still shows a general tendency to underestimate the dry day frequency and 95th percentile of dry spell length over wetter regions, with only a marginal improvement compared to the lower resolution models. This indicates that the problem of the excessive production of low precipitation events found in many climate models persists also at relatively high resolutions, at least in wet climate regimes. Concerning the Med-CORDEX and EURO-CORDEX ensembles we find that their performance is of similar quality over the Mediterranean regions analyzed. Finally, we stress the need of consistent and quality checked fine scale observation datasets for the assessment of RCMs run at increasingly high horizontal resolutions.

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References

  • Adam JC, Lettenmaier DP (2003) Adjustment of global gridded precipitation for systematic bias. J Geophys Res 108:4257. doi:10.1029/2002JD002499

    Article  Google Scholar 

  • Adam JC, Clark EA, Lettenmaier DP, Wood EF (2006) Correction of global precipitation products for orographic effects. J Clim 19:15–38

    Article  Google Scholar 

  • Akhtar N, Brauch J, Dobler A, Berenger K, Ahrens B (2014) Medicanes in an ocean–atmosphere coupled regional climate model. Nat Hazards Earth Syst Sci 14:2189–2201. doi:10.5194/nhess-14-2189-2014

    Article  Google Scholar 

  • Ban N, Schmidli J, Schar C (2014) Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J Geophys Res 119:7889–7907. doi:10.1002/2014JD021478

    Google Scholar 

  • Casanueva A, Kotlarski S, Herrera S, Fernández J, Gutiérrez JM, Boberg F, Colette A, Christensen OB, Goergen K, Jacob D, Keuler K, Nikulin G, Teichmann C, Vautard R (2016) Daily precipitation statistics in a EURO-CORDEX RCM ensemble: added value of raw and bias-corrected high-resolution simulations. Clim Dyn 47:719–737. doi:10.1007/s00382-015-2865-x

    Article  Google Scholar 

  • Castro M, Fernández C, Gaertner MA (1993) Description of a meso-scale atmospheric numerical model. In: Díaz JI, Lions JL (eds) Mathematics, climate and environment. Recherches en Mathematics Appliques Series Mason, pp 230–253

  • Christensen OB, Drews M, Christensen JH, Dethloff K, Ketelsen K, Hebestadt I, Rinke A (2006) The HIRHAM regional climate model, version 5, Tech. Rep. Dan. Meteorol. Inst, Copenhagen, pp 06–17

    Google Scholar 

  • Colin J, Deque M, Radu R, Somot S (2010) Sensitivity study of heavy precipitation in limited area model climate simulations: influence of the size of the domain and the use of the spectral nudging technique. Tellus A 62:591–604

    Article  Google Scholar 

  • Dee DP et al (2011) The ERA Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Di Luca A, Flaounas E, Drobinski P, Brossier CL (2014) The atmospheric component of the Mediterranean Sea water budget in a WRF multi-physics ensemble and observations. Clim Dyn 43:2349–2375

    Article  Google Scholar 

  • Fita L, Romero R, Luque A, Emanuel K, Ramis C (2007) Analysis of the environments of seven Mediterranean storms using an axisymmetric, nonhydrostatic cloud model. Nat Hazards Earth Syst Sci 7:41–56

    Article  Google Scholar 

  • Flaounas E, Drobinski P, Vrac M, bastin S, Lebeaupin Brossier C et al (2013) Precipitation and temperature space-time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods. Clim Dyn 40:2687–2705

    Article  Google Scholar 

  • Gaertner MA, Jacob D, Gil V, Domınguez M, Padorno E, Sanchez E, Castro M (2007) Tropical cyclones over the Mediterranean Sea in climate change simulations. Geophys Res Lett. doi:10.1029/2007GL029977

    Google Scholar 

  • Gaertner MA, Gil V, Romera R, Domınguez M, Sanchez E, Gallardo C (2011) Climate change scenarios and risk of tropical cyclones over the Mediterranean Sea: analysis with ENSEMBLES data. Presented at the 3rd international summit on hurricanes and climate change. Rhodes

  • Giorgi F (1991) Sensitivity of summertime precipitation over the western United States to model physics parameterizations. Mon Weather Rev 119:2870–2888

    Article  Google Scholar 

  • Giorgi F, Jones C, Asrar G (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58:175–183

    Google Scholar 

  • Giorgi F, Coppola E, Solmon F, Mariotti L, Sylla MB, Bi X, Elguindi N, Diro GT, Nair V, Giuliani G, Turuncoglu UU, Cozzini S, Güttler I, O’Brien TA, Tawfik AB, Shalaby A, Zakey AS, Steiner AL, Stordal F, Sloan LC, Branković C (2012) RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim Res 52:7–29. doi:10.3354/cr01018

    Article  Google Scholar 

  • Giorgi F, Coppola E, Raffaele F, Diro GT, Fuentes-Franco R et al (2014) Changes in extremes and hydroclimatic regimes in the CREMA ensemble projections. Clim Change 125:39–51

    Article  Google Scholar 

  • Haylock MR, Hofstra N, Tank AMGK, Klok EJ, Jones PD et al (2008) A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J Geophys Res 113:D20119

    Article  Google Scholar 

  • Herrera S, Fernández J, Gutiérrez JM (2015) Update of the Spain02 gridded observational dataset for Euro-CORDEX evaluation: assessing the effect of the interpolation methodology. Int J Climatol. doi:10.1002/joc.4391

    Google Scholar 

  • Herrmann M, Somot S, Calmanti S, Dubois C, Sevault F (2011) Representation of daily wind speed spatial and temporal variability and intense wind events over the Mediterranean Sea using dynamical downscaling: impact of the regional climate model configuration. Nat. Hazards Earth Sys Sci 11:1983–2001

    Article  Google Scholar 

  • Isotta FA et al (2014) The climate of daily precipitation in the Alps: development and analysis of a high-resolution grid dataset from pan-Alpine raingauge data. Int J Climatol 34:1657–1675

    Article  Google Scholar 

  • Jacob D, Barring L, Christensen OB, Christensen JH, de Castro M et al (2007) An intercomparison of regional climate models for Europe: design of the experiments and model performance. Clim Change 81:31–52

    Article  Google Scholar 

  • Jacob D, Petersen J, Eggert B, Alias A, Christensen JH et al (2013) EURO-CORDEX: new high resolution climate change projections for European impact research. Reg Environ Change 14:563–578

    Article  Google Scholar 

  • Johansson B (2002) Estimation of areal precipitation for hydrological modelling, Ph.D. Thesis. Earth Sciences Centre, Göteborg University, Report nr. A76

  • Jones C, Giorgi F, Asrar G (2011) The coordinated regional downscaling experiment: CORDEX. An international downscaling link to CMIP5. CLIVAR Exch 16:34–40

    Google Scholar 

  • Kendon EJ, Roberts NM, Senior CA, Roberts mJ (2012) Realism of rainfall in a very-high resolution regional climate model. J Clim 25:5791–5806

    Article  Google Scholar 

  • Kotlarski S, Keuler K, Christensen OB, Colette A, Deque M et al (2014) Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci Model Dev 7:1297–1333

    Article  Google Scholar 

  • Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Stat 22:79–86

    Article  Google Scholar 

  • Kupiainen M, Samuelsson P, Jones C, Jansson C, Willén U, Hansson U, Ullerstig A, Wang S, Döscher R (2011) rossby centre regional atmospheric model, RCA4, Rossby Centre Newsletter

  • Lagouvardos K, Kotroni V, Nickovic S, Jovic D, Kallos G, Tremback CJ (1999) Observations and model simulations of a winter sub-synoptic vortex over the central Mediterranean. Meteorol Appl 6:371–383

    Article  Google Scholar 

  • Lionello P, Boldrin U, Giorgi F (2008) Future changes in cyclone climatology over Europe as inferred from a regional climate simulation. Clim Dyn 30:657–671

    Article  Google Scholar 

  • Matsuura K, Willmott C (2010) Terrestrial air temperature and precipitation: 1900–2008 gridded monthly time series (V 2.01). University of Delaware Department of Geography Center for Climatic Research. http://climate.geog.udel.edu/~climate/html_pages/archive.html

  • Mitchell T, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712

    Article  Google Scholar 

  • Mohr M (2009) Comparison of versions 1.1 and 1.0 of gridded temperature and precipitation data for Norway. Technical report Met.no note 19

  • Montani A, Marsigli C, Nerozzi F, Paccagnella T, Tibaldi S, Buizza R (2003) The Soverato flood in Southern Italy: performance of global and limited-area ensemble forecasts. Nonlinear Process Geophys 10:261–274

    Article  Google Scholar 

  • Perry M, Hollis D, Elms M (2009) The generation of daily gridded datasets of temperature and rainfall for the UK. Met Office Climate Memorandum No. 24

  • Porcú F, Caracciolo C, Prodi f (2003) Cloud systems leading to flood events in Europe: an overview and classification. Meteorol Appl 10:217–227. doi:10.1017/S1350482703003025

    Article  Google Scholar 

  • Prein AF, Gobiet A, Suklitsch M, Truhetz H, Awan NK et al (2013) Added value of convection permitting seasonal simulations. Clim Dyn 41:2577–2655

    Article  Google Scholar 

  • Prein AF, Gobiet A, Truhetz H, keuler K, Goergen K et al (2015) Precipitation in the EUOR-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits? Clim Dyn. doi:10.1007/s00382-015-2589-y

    Google Scholar 

  • Pytharoulis I, Craig GC, Ballard SP (2000) The hurricane-like Mediterranean cyclone of January 1995. Meteorol Appl 7:261–279

    Article  Google Scholar 

  • Rauscher SA, Coppola E, Piani C, Giorgi F (2010) Resolution effect of regional climate model simulation of precipitation over Europe part I: seasonal. Clim Dyn 35:685–711

    Article  Google Scholar 

  • Rauthe M, Steiner H, Riediger U, Mazurkiewicz A, Gratzki A (2013) A Central European precipitation climatology—part I: generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorol Z 22:235–256. doi:10.1127/0941-2948/2013/0436

    Article  Google Scholar 

  • Rockel B, Castro CL, Pielke RA Sr, von Storch H, Lencini G (2008) Special issue regional climate modelling with COSMO-CLM (CCLM). Meteorol Z 17:347–348

    Article  Google Scholar 

  • Ruti P, Somot S, Giorgi F, Dubois C, Calmanti S, Ahrens B et al (2016) The MED-CORDEX initiative for Mediterranean climate studies. Bull Am Meteorol Soc. doi:10.1175/BAMS-D-14-00176.1

    Google Scholar 

  • Sanchez E, Dominguez M, Romera R, Lopez de la Franca N, Gaertner MA, Gallardo C, Castro M (2011) Regional modeling of dry spells over the Iberian Peninsula for present climate and climate change conditions. Clim Change 107:625–634. doi:10.1007/s10584-011-0114-9

    Article  Google Scholar 

  • Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extreme indices in the CMIP5 multimodel ensemble: part 2. Future climate projections. J Geophys Res Atmos 118:2473–2493

    Article  Google Scholar 

  • Sun Y, Solomon S, Dai A, Portmann RW (2006) How often does it rain? J Clim 19:916–934

    Article  Google Scholar 

  • Szalai S et al (2013) Climate of the greater Carpathian region. Final Technical Report. www.carpatclim-eu.org

  • Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106:7183–7192

    Article  Google Scholar 

  • Torma C, Giorgi F, Coppola E (2015) Added value of regional climate modeling over areas characterized by complex terrain—precipitation over the Alps. J Geophys Res 120:3957–3972

    Google Scholar 

  • Tous M, Romero R (2013) Meteorological environments associated with medicane development. Int J Climatol 33:1–14

    Article  Google Scholar 

  • Tramblay Y, Ruelland D, Somot S, Bouaicha R, Servat E (2013) High resolution Med-CORDEX regional climate model simulations for hydrological impact studies: a first evaluation of the ALADIN-climate model in Morocco. Hydrol Earth Syst Sci 17:3721–3739

    Article  Google Scholar 

  • Meijgaard E van, Van Ulft LH, Lenderink G, de Roode SR, Wipfler L, Boers R, Timmermans RMA (2012) Refinement and application of a regional atmospheric model for climate scenario calculations of Western Europe. Climate Changes Spatial Planning Publications: KvR 054/12, p 44

  • Vautard R, Gobiet A, Jacob D, Belda M, Colette A et al (2013) The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project. Clim Dyn 41:1–21

    Article  Google Scholar 

  • Vidal JP, Martin E, Franchistéguy L, Baillonb M, Soubeyroux JM (2010) A 50-year high-resolution atmospheric reanalysis over France with the Safran system. Int J Climatol 30:1627–1644. doi:10.1002/joc.2003

    Article  Google Scholar 

  • Walsh K, Giorgi F, Coppola E (2014) Mediterranean warm-core cyclones in a warmer world. Clim Dyn 42(3–4):1053–1066

    Article  Google Scholar 

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Acknowledgements

We thank all the institutions in Table 2 for providing the observations and the Med-CORDEX and EURO-CORDEX groups. In particular, we thank the CETEMPS, University of L’Aquila for providing the Italian gridded data. We thank Fabio Di Sante and Graziano Giuliani, for helping in troubleshooting with the station data and other datasets. Bodo Ahrens acknowledges support by Senckenberg BiK-F, Germany. UCLM contribution has been partially funded by the Spanish Government and the European Regional Development Fund, through Grants CGL2007-66440-C04-02, CGL2010-18013 and CGL2013-47261-R.

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Correspondence to Adriano Fantini.

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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.

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Fig. S1

Taylor diagrams of the ensemble mean seasonal precipitation in the different analysis regions for the ERA-Interim, RCM44 and RCM11 (both EURO-CORDEX and Med-CORDEX models) ensembles with respect to the corresponding regional observation datasets, at the 0.44° resolution. (PDF 1787 kb)

Fig. S2

Mean precipitation Bias (model minus observations, % of observed values, upper panels) and RMSE (mm/day, lower panels) for December–January–February (DJF, on the left) and June–July–August (JJA, on the right) for the different analysis regions, the ERA-Interim, and the RCM44 and RCM11 ensemble average (EURO-CORDEX Models and Med-CORDEX models). All the values indicate Bias and RMSE obtained without the under-catch gauge correction (see text). (PDF 45 kb)

Fig. S3

Probability Density Function of daily precipitation intensity (mm/day) over the different analysis regions in the ERA-Interim reanalysis, regional observation datasets, RCM44 and RCM11 ensembles (All Models), all at the 0.44° resolution. For the RCM44 and RCM11 ensembles both the individual model values (circles) and their ensemble mean (continuous line) are shown. The PDFs include daily data for the different regional analysis periods (see Sect. 2). (PDF 75 kb)

Fig. S4

Same as Figure S3 but at the 1.5° resolution. (PDF 79 kb)

Fig. S5

Taylor diagrams of the ensemble mean values of the four indices described in Sect. 2 in the different analysis regions for the ERA-Interim, RCM44 and RCM11 (both EURO-CORDEX and Med-CORDEX models) ensembles with respect to the corresponding regional observation datasets, at the 0.44° resolution. (PDF 1773 kb)

Fig. S6

Ensemble mean precipitation over the analysis regions for ERA-Interim reanalysis, RCM44 and RCM11 (only Med-CORDEX models) ensembles, regional observations. Upper panels: December–January–February (DJF); Lower panels: June–July–August (JJA). The last column on the right shows the precipitation bias at each resolution. Units are mm/day and the mean is taken over the different regional analysis periods (see Sect. 2). (PDF 6430 kb)

(PDF 6620 kb)

Fig. S7

Same as Figure S6 but for EURO-CORDEX models ensembles. (PDF 17567 kb)

(PDF 18013 kb)

Fig. S8

Annual cycle of ensemble mean value of the SDII index over the different analysis regions for the RCM44 and RCM11 ensembles (EURO-CORDEX and Med-CORDEX models), along with the ERA-Interim and observed SDII, at the 1.50° resolution. For the model ensembles, both the mean (thick line) and intermodel standard deviations range (shaded area) are shown. Units are mm/day and the mean is taken over the different analysis periods (see Sect. 2). (PDF 13 kb)

Fig. S9

Same as Figure S8, but for the index Psum > R95-obs. Units are mm/year. (PDF 14 kb)

Fig. S10

Same as Figure S8, but for the index DDF. Units are % days/year. (PDF 13 kb)

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Fantini, A., Raffaele, F., Torma, C. et al. Assessment of multiple daily precipitation statistics in ERA-Interim driven Med-CORDEX and EURO-CORDEX experiments against high resolution observations. Clim Dyn 51, 877–900 (2018). https://doi.org/10.1007/s00382-016-3453-4

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