dazhiyang/bsrn-nsrdb-aggregated

BSRN NSRDB PSM v4 aggregated

Point-extracted NSRDB (National Solar Radiation Database) PSM v4 (aggregated variant) data for Baseline Surface Radiation Network (BSRN) stations.

Dataset Description

Each file contains 30-minute NSRDB variables at a single BSRN station location. Extraction is performed via the NREL NSRDB API (NLR). The aggregated variant (v4.0.0) provides 4 km spatial resolution and covers the Contiguous United States and other regions using the GOES archive from 1998 to 2024.

File Structure

Station folders use the lowercase BSRN three-letter code (e.g. ber).

{station}/
  {station}{MM}{YY}_nsrdb_aggregated.parquet   # One file per month

Example:

• ber/ber0198_nsrdb_aggregated.parquet — BER, January 1998

Variables

Column	Description	Units
ghi_nsrdb	Global Horizontal Irradiance	W/m²
bni_nsrdb	Beam Normal Irradiance (DNI)	W/m²
dhi_nsrdb	Diffuse Horizontal Irradiance	W/m²

• Index: UTC DatetimeIndex (30-minute resolution).
• Time coverage: NSRDB PSM v4 aggregated variant spans 1998–2024.

Usage

Load from Hugging Face

from huggingface_hub import hf_hub_download
import pandas as pd

# Download a single file; path is {station}/{station}{MM}{YY}_nsrdb_aggregated.parquet
path = hf_hub_download(
    repo_id="dazhiyang/bsrn-nsrdb-aggregated",
    filename="ber/ber0198_nsrdb_aggregated.parquet",
    repo_type="dataset",
)
df = pd.read_parquet(path)
# df has DatetimeIndex (UTC) and columns: ghi_nsrdb, bni_nsrdb, dhi_nsrdb

Use with bsrn package

The bsrn package can fetch NSRDB data from Hugging Face into RAM (no disk cache) automatically.

from bsrn.io.nsrdb import add_nsrdb_columns

# Add NSRDB columns to an existing BSRN DataFrame
df = add_nsrdb_columns(df, station_code="BER", variant="aggregated")

Data Sources

• NSRDB: NREL National Solar Radiation Database
• API: NREL Developer Network (NLR)
• Station inventory: BSRN FTP

References

1. Sengupta, M., Xie, Y., Lopez, A., Habte, A., Maclaurin, G., & Shelby, J. (2018). The national solar radiation data base (NSRDB). Renewable and Sustainable Energy Reviews, 89, 51-60.

2. Xie, Y., Yang, J., Sengupta, M., Liu, Y., & Zhou, X. (2022). Improving the prediction of DNI with physics-based representation of all-sky circumsolar radiation. Solar Energy, 231, 758-766.

3. Xie, Y., Sengupta, M., Yang, J., Buster, G., Benton, B., Habte, A., & Liu, Y. (2023). Integration of a physics-based direct normal irradiance (DNI) model to enhance the National Solar Radiation Database (NSRDB). Solar energy, 266, 112195.

4. Xie, Y., Sengupta, M., & Dudhia, J. (2016). A Fast All-sky Radiation Model for Solar applications (FARMS): Algorithm and performance evaluation. Solar Energy, 135, 435-445.

Citation

If you use this dataset, please cite the references above and the bsrn package: dazhiyang/bsrn.

License

NSRDB data is provided by NREL and is subject to their Data Usage Policy.