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Open Meteorological and Climate Data

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Julia Wagemann
Geospatial data consultant,
Visiting Scientist @ECMWF,
PhD candidate @MarbugUniversity

Published in: Environment
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Open Meteorological and Climate Data

  1. 1. Open METEOROLOGICAL and CLIMATE DATA Julia Wagemann Geospatial data consultant, Visiting Scientist @ECMWF, PhD candidate @MarbugUniversity @JuliaWagemann jwagemann.github.io
  2. 2. CLIMATE ERA5 reanalysis ● 1979 - almost Near-Real-Time ○ (soon from 1950 onwards) ● Temporal resolution: hourly ● Spatial resolution: ~ 30 km (ERA5-Land: 9 km) Seasonal forecasts ● monthly forecasts up to 6 months ahead ● Spatial resolution: 10 km
  3. 3. CAMS reanalysis ● 2003 - 2016 (will be extended ● Spatial resolution: 80 km CAMS Forecasts ● 3-hourly forecasts up to 5 days in advance ● Spatial resolution: 80 km Parameters: Ozone, CO2, SO2, NO2, ... AIR QUALITY
  4. 4. Fire danger indices ● Fire-Weather Index ● Fine Fuel Moisture Code ● Duff Moisture Code ● Drought Code ● Build-Up Index ● Initial Spread Index ● Daily Severity Rating Time period: 1 Jan 1980 - 31 Dec 2018 Temporal resolution: daily Spatial resolution: 80 km FIRE DANGER
  5. 5. FLOOD River discharge ● GloFAS 30-day forecast ○ 1 Jan 2018 - realtime ○ Temporal resolution: daily ○ Spatial resolution: 10 km ● GloFAS 30-day reanalysis ○ 1981-2017 ○ Temporal resolution: daily ○ Spatial resolution: 10 km
  6. 6. Copernicus FULL, FREE and OPEN data policy
  7. 7. https://pypi.org/project/ cdsapi/ import cdsapi c = cdsapi.Client() c.retrieve( 'reanalysis-era5-single-levels', { 'product_type':'reanalysis', 'format':'netcdf', 'variable':'2m_temperature', 'year':'2019', 'month':'05', 'day':'01', ‘area’:’90/-180/-90/179.75 'time':[ '00:00','01:00','02:00', '03:00','04:00','05:00', '06:00','07:00','08:00', '09:00','10:00','11:00', '12:00','13:00','14:00', '15:00','16:00','17:00', '18:00','19:00','20:00', '21:00','22:00','23:00' ] }, 'download.nc') Python libraries to handle NetCDF / GRIB files: ● xarray ● cfgrib ● netCDF4 https://cran.r-project.org/web /packages/ecmwfr/index.html R package to handle NetCDF / raster files: ● Raster
  8. 8. Some resources: ● Climate Data Store | https://cds.climate.copernicus.eu/#!/home ● ECMWF Public Datasets | https://apps.ecmwf.int/datasets/ ● Global Flood Awareness System | http://www.globalfloods.eu/ ● Fire danger forecasts | https://zenodo.org/communities/wildfire/ ● ECMWF WMS Service endpoint | http://apps.ecmwf.int/wms/?token=public&request=GetCapabilities&version=1.3.1 ● Example notebooks | https://github.com/jwagemann/2019_egu_workshop_jupyter_notebooks/blob/maste r/02_Geospatial_Data_Access.ipynb

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