VALUE WG2 Benchmark data set & pseudo-reality (year 1-2) Report, Trieste Meeting Sep.12 Sven Kotlarski, José Gutiérrez

Slide 2 of Members Chair / co-Chair: Kotlarski (CH) Gutiérrez (E) WG Members:Bärring (S) Bosshard (CH) Brands (E) Brzóska (PL) J.H. Christensen (DK) Coppola (I) Jaczewski (PL) Jones (UK) Maraun (D) Pagé (FR) Pianko (PL)

Slide 3 of 13 Overview (MoU) “Observational benchmark data sets and pseudo realities will be set up for the validation by WG2. These will comprise climatically distinct regions, e.g., maritime, continental, alpine and Mediterranean climates. The daily station data set will build upon the ECA&D data set publicly available from the Dutch weather service KNMI. Sub-daily station data will be provided by the Swedish Meteorological and Hydrological Institute SMHI for Sweden, MeteoSwiss for the Alps and the Regional Agency for Prevention and Environment ARPA of the Emilia Romagna for a Mediterranean climate. Station data may require the user to individually sign an agreement with the data provider to use the data for scientific purposes only. Additionally, the benchmark data set will contain daily gridded observations for the validation of SDS and in particular RCMs. The latter simulate area averages and are not directly comparable with station observations. As gridded observations, the EOBS data set will be employed, which is the gridded version of the ECA&D station data set developed within the ENSEMBLES project. Several researchers have noted potential weaknesses of the EOBS data set in regions of sparse data (e.g., Herrera et al, 2010), such that the validation will be restricted to selected regions, where a high data quality is ensured. Currently, a gridded precipitation data set with sub- daily resolution for the Alps, based on a combination of station and radar data, is under development by MeteoSwiss and might be used in a later stage of VALUE. Further data sets which might be available in the future or by further partners joining VALUE at a later stage will be considered additionally. The pseudo reality …”

Slide 4 of 13 Tasks, Milestones, Deliverables T5: compile benchmark data set; upload benchmark data set to website 1 st half of year 2 T6: compile pseudo reality; upload pseudo reality to website 1 st half of year 2 D3: observational benchmark data set and a pseudo reality for the validation (upload to website) 1 st half of year 2 M3: observational benchmark data set and pseudo reality compiled 1 st half of year 2

Slide 5 of 13 Observational Benchmark Dataset (1) Regions Station-based obs. data (e.g. ECA&D) Validation SD Parameters and required temporal resolution depend on target (i.e. on WG) Gridded obs. data (e.g. EOBS) Validation SD and DD Parameters and required temporal resolution depend on target (i.e. on WG)

Slide 6 of 13 Depends on target / WG Which pilot regions? Example: maritime -> UK, continental -> PL, alpine -> CH, Mediterrenean -> E / IP Is quality of observational data appropriate? Is temporal resolution appropriate? Is spatial coverage appropriate? Concerns especially network density for gridded observations Are all required parameters available? Is length of observed period appropriate? 30 years at least? Observational Benchmark Dataset (2) Open issues (to be discussed this meeting)

Slide 7 of 13 Dataset inventory Compiled by WG2 with input from further WGs But: Not much feedback, inventory probably not complete yet (especially wrt. regional/national station data sets) Please add data from your country! Data availability and terms of use still need to be checked

Slide 8 of 13 E-OBS (1) Standard reference data set for RCM evaluation Entire European land surface, present, daily resolution, available on standard RCM grids Would allow for a “fair” comparison of SD and DD performance BUT Poor data quality in regions of low network density (over-smoothing of the spatial field) Smoothing particularly affects tails of dictribution (reduction of daily extremes) Temporal inhomogeneities due to changes in contributing station network Hofstra et al. 2009, Hofstra et al. 2010, Kysely and Plavcova 2010, Maraun et al. 2012, Herrera et al. 2012

Slide 9 of 13 E-OBS (2)

Slide 10 of 13 E-OBS (3) ? ? ? ? Restrict validation exercise to regions of high network density or apply different regional / national gridded datasets

Slide 11 of 13 Suggestions for pilot regions Covers both atlantic and mediterranean climates Publicly available high-quality datasets at daily resolution Spain02: daily P, T max, T min at 0.2° for Several downscaling studies already exist, including validation of E-OBS and ENSEMBLES RCMs Besides daily data: hourly data available for some stations Spain / IB Alpine climate High-quality gridded (2 km) and station-based data available Gridded hourly precipitation up from 2003, sub-daily station data available Large number of previous downscaling studies (SD and DD) Switzerland Continental climate Gridded 25km daily data, quality probably superior to E-OBS Poland Maritime to alpine climate Safran analysis available (8 km res., , hourly to daily) France (?) Open for discussion!

Slide 12 of 13 Further Issues Selection of predictors (ERA40? Identical for each SD method? Include predictors with high uncertainty, e.g. humidity?) Data distribution / data server Santander group set up a THREDDS data server that could host observational reference data and predictor datasets Involvement of WGs 3 to 5 Selection of reference data and selection of predictors: This meeting? Further discussions: One / two representatives of each WG? Scenarios − Downscale CMIP5 projections? − Data server could host GCM predictors − GCM selection -> Paper Brands et al. Median of the absolute SLP bias/std values along the lateral boundaries of the Euro-CORDEX domains (1 Re-analysis and 7 CMIP5 GCMs)

Thanks …

Slide 14 of 13 Publicly available high-quality datasets at daily resolution (> 100 stations, Spain02 / IB02 gridded datasets) Spain02: daily P, Tmax, Tmin at 0.2° for Covers both atlantic and mediterranean climates Several downscaling studies already exist, including validation of E-OBS and ENSEMBLES RCMs Besides daily data: hourly data available for some stations Suggestion for pilot region Spain / IP Herrera et al. 2012

Slide 15 of 13 E-OBS: Temporal coverage

Slide 16 of 13 E-OBS: Distribution of T stations (1)

Slide 17 of 13 E-OBS: Distribution of T stations (2)