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Published May 15, 2023 | Version 1.0.0
Dataset Open

SECURES-Met - A European wide meteorological data set suitable for electricity modelling (supply and demand) for historical climate and climate change projections

  • 1. University of Natural Resources and Life Sciences, Vienna
  • 2. International Water Management Institute: Lahore, Punjab, PK
  • 3. TU Wien, Institute of Energy Systems and Electrical Drives, Energy Economics Group
  • 4. AIT Austrian Institute of Technology

Description

For the modelling of electricity production and demand, meteorological conditions are becoming more relevant due to the increasing contribution from renewable electricity production. But the requirements on meteorological data sets for electricity modelling are quite high. One challenge is the high temporal resolution, since a typical time step for modelling electricity production and demand is one hour. On the other side the European electricity market is highly connected, so that a pure country based modelling does not make sense and at least the whole European Union area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21st century. Thus, we have developed an aggregated European wide data set that has a temporal resolution of one hour, covers the whole EU area, has a reasonable size but is considering the high spatial variability. This meteorological data set for Europe for the historical period and climate change projections fulfills all relevant criteria for energy modelling. It has a hourly temporal resolution, considers local effects up to a spatial resolution of 1 km and has a suitable size, as all variables are aggregated to NUTS regions. Additionally meteorological information from wind speed and river run-off is directly converted into power productions, using state of the art methods and the current information on the location of power plants. Within the research project SECURES (https://www.secures.at/) this data set has been widely used for energy modelling.

 

The SECURES-Met dataset provides variables visible in the table.

Variable Short name Unit Aggregation methods Temporal resolution
Temperature (2m) T2M

°C

°C

spatial mean

population weighted mean (recommended)

hourly
Radiation

GLO (mean global radiation)

BNI (direct normal irradiation)

Wm-2

Wm-2

spatial mean

population weighted mean (recommended)

hourly
Potential Wind Power WP 1 normalized with potentially available area hourly
Hydro Power Potential

HYD-RES (reservoir)

HYD-ROR (run-of-river)

MW

1

summed power production

summed power production normalized with average daily production

daily

 

 

 

 

 

 

 

 

 

 

 

 

 

SECURES-Met is available in a tabular csv format for the historical period (1981-2020, Hydro only until 2010) created from ERA5 and ERA5-Land and two future emission scenarios (RCP 4.5 and RCP 8.5, both 1951-2100, wind power starting from 1981, hydro power from 1971) created from one CMIP5 EUROCORDEX model (GCM:  ICHEC-EC-EARTH, RCM: KNMI-RACMO22E, ensemble run: r12i1p1) on the spatial aggregation level

  • NUTS0 (country-wide),
  • NUTS2 (province-wide),
  • NUTS3 (Austria only),
  • and EEZ (Exclusive Economic Zones, offshore only).

The data is divided into the historical (Historical.zip) and the two emission scenarios (Future_RCP45.zip and Future_RCP85.zip), a README file, which describes, how the files are organized,  and a folder (Meta.zip), which has information and shape files of the different NUTS levels. As population weighted temperature and radiation represent values in geographical areas more relevant for solar power, it is highly relevant to use population weighted files. Spatial mean should be used for reference only.

The project SECURES, in which this dataset was produced, was funded by the Climate and Energy Fund (Klima- und Energiefonds) under project number KR19AC0K17532.

Files

Future_RCP45.zip

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Additional details

Related works

Is described by
Journal article: 10.1038/s41597-023-02494-4 (DOI)
Is supplemented by
Software: 10.5281/zenodo.8108927 (DOI)