High-quality climate data ... ... accurate and representative - - PowerPoint PPT Presentation

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“High-quality” climate data ...

... “accurate and representative” measurements ... “efficient and reliable” data quality control ... “standardized and relevant” metadata ... “rational and efficient” homogenization procedures ... „???“ grid datasets

Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss

What does „high quality“ mean with regard to spatial climate datasets? Practice and experience at MeteoSwiss

Christoph Frei and Francesco Isotta Rebekka Erdin, Denise Keller, David Masson, Reinhard Schiemann, Raphaela Vogel, Bettina Weibel, Marco Willi (former collaborators) Data Management Workshop 28.-30.10.2015, St. Gallen, Switzerland

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Application and Users

Agriculture

Crop suitablity maps, Crop desease and pests, Subsidies, …

Snow & ice

Avalange risk, Slope stability, Glacier monitoring, …

Hydrology

Runoff forecasting, Flood protection, Land slide risks, …

Energy & Construction

Renewable energy, Heating/cooling design, …

Internal

Climate monitoring Model verification Local forecasts CC-Scenarios, …

Research

ETH, Univ., FHS

• Univ. outside CH

Agencies

Federal, Regional

Private Sector

Insurance Engineering

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User Requirements

high accuracy (small random errors) fine spatial resolution (km) high temporal resolution (1 day, 1 hour) multi-parameter – physically consistent multi-decadal – climate consistent timely – possibly real-time

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Trends in Viticulture

1981-2010 Trend in Huglin Index based on high-res daily grid data HI=sum((Tm+Tx)/2 – 10degC) April – September

change in station network

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Effects from network changes

Frei 2014

Interpolation Bias

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Purpose-Design Philosophy

Data products targeted to application groups Individual balance between method and data Methods depend on intended application Limitations / uncertainties are openly cummunicated

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The MCH Grid-Data Suite

~ 40 products, Temp (m, n, x), Precip, Sun, Radiation territory of Switzerland, 2 km norm, monthly, daily, (hourly), anomaly 1961-actual, 2004-actual (radar-gauge) automatic production and delivery web, reports

Temperature (degC) Precipitation (mm) Relative Sunshine Duration (%)

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Precipitation – Products

23.07.2009

Real-time (hourly)

Radar-Gauge combination, t-KED Erdin et al. 2012, Sideris et al. 2014

22.08.2005

Real-time (daily)

Statistical reconstruction (RSOI) Schiemann et al. 2012

• > talk by

Francesco

• n Friday

22.08.2005

High-resolution (daily, monthly, ...)

PRISM & SYMAP Schwarb et al. 2001, Frei et al. 1998, 2004

• Aug. 2005

Anomaly wrt Norm

>1960, SYMAP Shepard 1984, Frei et al. 1998

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Relative Sunshine Duration

Frei et al. 2015

High-resolution SSD

Merging satellite (MSG Clear-sky index) and in-situ data (Heliometer, ~75 stations) Non-contemporaneous, PCA & KED Frei et al. 2015, Stöckli 2013

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Relative Sunshine Duration

SS : Fraction of explained spatial variance (spatial Nash-Sutcliffe efficiency)

better

Leave-one-out crossvalidation all days 1998-2001

Frei et al. 2015

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Documentation for Users

www.meteoswiss.ch Search for „Gitterdaten“

Overview sheet with list of products

Underlying data Analysis method Applications and target users Accuracy and limitations Grid structures Update cycle Versions

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User Wishes (2013)

... higher spatial resolution ... finer time resolution (hourly) ... more parameters ... more real-time products ... uncertainty information (quantitative) ... longer time coverage (<1961) ... better long-term consistency ... areal extent beyond Swiss border Your applications could benefit from new products/developments with priority on ...

25% 50% 75%

Number of responses: 26

wind, humidity, snowfall, soil moisture, PET, soil moisture, ... „Hydrological“ Switzerland 250 m

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Our Experience

• “High quality” = USEFUL. Meeting the requirements of applications.
• Requirements are diverse. Products tailored for applications.
• There is not “a best method”.
• Users need to grapple with requirements and specifications.

User-friendly product information.

• Be honest about limitations.
• Improving through collaboration. Bridging producer – user gap.
• “High-quality climate services” is about sharing thought, not just data.

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Publications

Erdin, R., C. Frei, and H. R. Künsch, 2012: Data transformation and uncertainty in geostatistical combination of radar and rain gauges. J. Hydrometeorol., 13, 1332–1346, doi:10.1175/JHM-D-11-096.1. Frei, C., 2014: Interpolation of temperature in a mountainous region using nonlinear profiles and non-Euclidean

• distances. Int. J. Climatol., 34, 1585–1605, doi:10.1002/joc.3786.

Frei, C., M. Willi, R. Stöckli, and B. Dürr, 2015: Spatial analysis of sunshine duration in complex terrain by non- contemporaneous combination of station and satellite data. Int. J. Clim., doi:10.1002/joc.4322. Hiebl, J., and C. Frei, 2015: Daily temperature grids for Austria since 1961 - concept, creation and applicability.

• Theor. Appl. Clim., doi:10.1007/s00704-015-1411-4.

Isotta, F. A. and Coauthors, 2014: The climate of daily precipitation in the Alps: Development and analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data. Int. J. Clim., 34, 1657–1675, doi:10.1002/joc.3794. Isotta, F. A., R. Vogel, and C. Frei, 2015: Evaluation of European regional reanalyses and downscalings for precipitation in the Alpine region. Meteorol. Z., 24, 15-37. Masson, D., and C. Frei, 2014: Spatial analysis of precipitation in a high-mountain region: Exploring methods with multi-scale topographic predictors and circulation types. Hydrol. Earth Syst. Sci., 18, 4543–4563, doi:10.5194/hess-18-4543-2014. Masson, D., and C. Frei, 2015: Long-term variations and trends of mesoscale precipitation in the Alps: Recalculation and update for 1901-2008. Int. J. Clim., (in press). Vogel, R., 2013: Quantifying the uncertainty of spatial precipitation analyses with radar-gauge observation

• ensembles. Scientific Report MeteoSwiss, 95, 80 pp.

Willi, M., 2010: Gridding of daily sunshine duration by combination of station and satellite data. Technical Report MeteoSwiss, 232, 89 pp.