gsee-climate-data

Data companion package for GSEE: monthly probability density functions (PDFs) of daily mean global horizontal irradiance. These are used by GSEE's climate data interface (gsee.climate.run_climate with pdfs="builtin") to synthesize day-to-day variability when running the PV model on annual, seasonal or monthly climate data.

Install together with GSEE via the climate extra:

pip install gsee[climate]

Data provenance

Derived from NASA MERRA-2 reanalysis surface radiation for 2011-2015, aggregated to a 3x3 degree grid over land and near-land cells (latitudes -57 to 72), with per-month histograms of daily irradiance in 128 bins per cell. This is the same dataset that GSEE v0.3 downloaded at runtime (MERRA2_rad3x3_2011-2015-PDFs_land_prox.nc), converted from NetCDF4 to NumPy .npz format so that reading it requires nothing beyond numpy.

Arrays in the .npz file (see gsee_climate_data.load()):

  • xk — bin values (daily mean irradiance), float32, dims (lat, lon, month, bins)
  • pk — bin probabilities (not normalized), float32, same dims
  • lat, lon, month — coordinate vectors (month is 1..12)

Cells without data (oceans) hold zeros/NaN probabilities and are treated as "no PDF available" by GSEE.

Citation

When using this data, please cite MERRA-2:

Gelaro, R., McCarty, W., Suarez, M. J., et al. (2017). The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Journal of Climate, 30(14), 5419-5454. https://doi.org/10.1175/JCLI-D-16-0758.1

and, for the derived PDFs and the GSEE model that consumes them:

Pfenninger, S., & Staffell, I. (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy, 114, 1251-1265. https://doi.org/10.1016/j.energy.2016.08.060

License

Code and data in this package are covered by different terms:

  • Code — the gsee_climate_data Python package is licensed under the BSD 3-Clause License (see LICENSE).
  • Data — the bundled .npz is derived from NASA MERRA-2, produced by the NASA Global Modeling and Assimilation Office and distributed by GES DISC.

See NOTICE for the full statement.

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Credits

Author: Stefan Pfenninger

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BSD-3-Clause
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Requires

Python >=3.11

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