Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- A longitude and latitude for the location being tested
Global gridded daily meteorology and solar estimates for building renewable energy, agriculture, climate, and infrastructure planning tools.
From source to product signal
POWER serves analysis-ready solar and meteorological estimates for selected coordinates. Start with one point, two parameters, and one month. Values represent model or satellite grid cells rather than a site sensor, latency differs by parameter, and recent meteorology is later quality-replaced.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
import pandas as pd
import requests
response = requests.get(
"https://power.larc.nasa.gov/api/temporal/daily/point",
params={
"parameters": "T2M,ALLSKY_SFC_SW_DWN",
"community": "RE",
"longitude": -112.074,
"latitude": 33.4484,
"start": "20250701",
"end": "20250731",
"format": "JSON",
"time-standard": "UTC",
},
timeout=30,
)
response.raise_for_status()
daily = pd.DataFrame(response.json()["properties"]["parameter"])
daily.index = pd.to_datetime(daily.index)
print(daily.head())Test a useful signal
Compare daily solar radiation and temperature for Phoenix during July 2025.
NASA Langley Research Center is a government source. Last verified 2026-08-13. Temporal coverage: 1981-present for daily meteorology with parameter-specific coverage.