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The combination of a sparse dataset and possible outliers in
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The E-OBSpre1950 dataset is based on a considerably sparser network ofĭata than the datasets that cover the post 1950 period despite someĭata rescue efforts in the ERA4CS project INDECIS and a query at the European In-situ observations, where the in-situ observations are the 'anchor Theĭimension reduced satellite data is used to interpolate between the Interpolated using Multiple Adaptive Regression Splines (MARS). Spatially and temporally highly variable. On daily time-scales the global radiation is mainlyĭependent on cloud patterns. Product and includes elevation and distance-to-coast as spatial It also incorporates the CERES global radiation satellite derived Observations, but, in order to properly estimate spatial variability, The global radiation dataset not only uses ground-based in-situ
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Throughīootstrapping, a 20-member ensemble is created. The dailyĪnomaly are then gridded using kriging regression. For wind speedĪnd some of the covariates, a log-transform is applied. Windspeed, altitude, slope, topographic position index (TPI, theĭifference between a central pixel and the mean of its surroundingĬells), distance to coast and surface roughness length. TheseĬovariates are: latitude, longitude, ERA5 800 hPa monthly averaged Various covariates to compute an monthly background grid. The dataset for wind speed is also based on the in-situ data holdings This also ensures thatĪll interpolated values, when converted back to the unit of %, are Transformed by \(\sqrt\) prior to fitting. (and the background field used in the gridding method) were Remove some of the skewness in the data, the relative humidity values One used for temperature, precipitation and sea level pressure. The gridding method used for this element is the same as the Holdings of the ECA&D dataset similar as the other E-OBSĭatasets. The dataset for relative humidity is based on the in-situ data
#Obs download and guide how to#
(2018) and the guidance on how to use ensemble datasets. The spread is calculated as the difference between the 5th and 95th percentiles over the ensemble to provide a measure indicate of the 90% uncertainty range. The mean across the members is calculated and is provided as the "best-guess" fields. For each of the members of the ensemble a spatially correlated random field is produced using a pre-calculated spatial correlation function. The ensemble dataset is constructed through a conditional simulation procedure.
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The Global 30 Arc-Second Elevation Data Set ( GTOPO30), a global raster Digital Elevation Model (DEM) with a horizontal grid spacing of 30 arc seconds (approximatelyġ kilometer) developed by USGS is used for the elevation file as well. Sum RR, daily mean sea level pressure PP, daily mean wind speed FG, daily mean relative humidity HU and global radiation QQ. Temperature TN, daily maximum temperature TX, daily precipitation
#Obs download and guide update#
Bookmark this page for future direct access!ĮCA&D staff will maintain and update the E-OBS gridded dataset.Į-OBS comes as an ensemble dataset and is available on a 0.1 and 0.25 degree regular grid for the elements daily mean temperature TG, daily minimum This is the download page for the ENSEMBLES daily gridded observational dataset for precipitation, temperature and sea level pressure in Europe called E-OBS.