Köhler, Carmen; Steiner, Andrea; Lee, Daniel; Thieler, Jens; Ritter, Bodo (2014): Case studies of the effects of a total solar eclipse on weather with varying degrees of cloud cover using a local numerical weather prediction model [dataset]. Deutscher Wetterdienst/Seewetteramt, Offenbach/Hamburg, PANGAEA, https://doi.org/10.1594/PANGAEA.839163
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Abstract:
The importance of renewable energies for the European electricity market is growing rapidly. This presents transmission grids and the power market in general with new challenges which stem from the higher spatiotemporal variability of power generation. This uncertainty is due to the fact that renewable power production results from weather phenomena, thus making it difficult to plan and control.
We present a sensitivity study of a total solar eclipse in central Europe in March. The weather in Germany and Europe was modeled using the German Weather Service's local area models COSMO-DE and COSMO-EU, respectively (http://www.cosmo-model.org/). The simulations were performed with and without considering a solar eclipse for the following 3 situations:
1. An idealized, clear-sky situation for the entire model area (Europe, COSMO-EU)
2. A real weather situation with mostly cloudy skies (Germany, COSMO-DE)
3. A real weather situation with mostly clear skies (Germany, COSMO-DE)
The data should help to evaluate the effects of a total solar eclipse on the weather in the planetary boundary layer. The results show that a total solar eclipse has significant effects particularly on the main variables for renewable energy production, such as solar irradiation and temperature near the ground.
Comment:
The data is stored in the meteorological format GRIB. We recommend using the ECMWF's GRIB API (http://software.ecmwf.int/wiki/display/GRIB/) to view and process the data. It is divided into 3 parts:
- {Europe_no_clouds} (situation 1)
- {Germany_overcast} (situation 2)
- {Germany_clear_sky} (situation 3)
Each part contains 2 subfolders:
{control} and {eclipse}, which each refer to either the control or the eclipse run of the simulated situation.
Each subfolder contains the following files:
- {analysis.grib} - The model run's initial conditions
- {constants.grib} - The constants used
- {forecast_DDHHMMSS.grib} - The forecast model fields, where {DDHHMMSS} is the timestamp referring to model lead time.
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | File content | Content | Köhler, Carmen | |||
| 2 | Uniform resource locator/link to model result file | URL model | Köhler, Carmen | GRIB, zipped | ||
| 3 | File size | File size | kByte | Köhler, Carmen |
License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Size:
18 data points