TeamOverbyeWeather

Python client for the Team Overbye Weather Data API at Texas A&M University — ERA5 reanalysis, HRRR history and forecasts, and NOAA/GFS forecasts, as PowerWorld .pww files.

Download, crop to a region, and crop in time, in one call.

Installation

pip install TeamOverbyeWeather

Python 3.10 or newer. No credentials needed.

Quick start

from TeamOverbyeWeather import WeatherClient

client = WeatherClient()

# What is available?
client.sources()                        # ['era5', 'hrrr', 'noaa']
client.types("hrrr")                    # ['archive', 'current', 'forecast', ...]
client.list("hrrr", "hourly_current")   # ['2026-07-21', '2026-07-20', ...]

# Download, cropped to Texas and to a six-hour window
client.download(
    "hrrr",
    type="hourly_current",
    dates="2026-07-21",
    region="TX",
    time_start="2026-07-21T06:00",
    time_end="2026-07-21T18:00",
    dest="./data",
)

Cropping happens server-side, so only what you asked for crosses the network — a Texas six-hour NOAA slice is 240 KB instead of the 120 MB full file.

One file is written per date key, already cropped, ready to open in PowerWorld.

Selecting a region

Use exactly one of:

client.download(..., region="TX")                       # one state
client.download(..., region=["TX", "OK", "NM"])         # union bounding box
client.download(..., iso="ERCOT")                       # ISO zone
client.download(..., bbox=(33.0, -100.0, 30.0, -96.0))  # lat_max, lon_min, lat_min, lon_max

List valid ids with client.region_ids("states") and client.region_ids("iso"). Multiple states crop to the union rectangle, not to the state outlines.

Selecting a time window

client.download(..., time_start="2026-07-21T06:00", time_end="2026-07-21T18:00")
client.download(..., time_start="2026-07-21T06:00")   # to the end of the file
client.download(..., time_end="2026-07-21T18:00")     # from the start

Times are UTC and both bounds are inclusive. datetime objects work too.

Data sources

Extreme temperature events

62 curated historical events (1899–2023) — the three hottest and three coldest per ISO zone, plus notable scenarios like ERCOT's 2011 rolling outages. Each comes with an animation.

client.extreme.zones()                       # ISO zones with events
client.extreme.events("Texas")               # events in a zone, newest first
client.extreme.find("uri")                   # search by title

event = client.extreme.find("uri")[0]
client.extreme.download(event["key"], region_ids=["TX"], region_layer="states",
                        time_start="2021-02-15T00:00", dest="./data")
client.extreme.video(event["key"], dest="./data")     # the .mp4 animation
client.extreme.coverage("Texas", dest="./data")       # zone coverage map

Always take date keys from client.list(source, type) — formats differ per source, and NOAA recent / archive are separate folders rather than a date split.

Reading the data

from TeamOverbyeWeather import pww_io

header, stations, arr = pww_io.read_pww(open(path, "rb").read())
arr.shape        # (time, variable, latitude, longitude)

255 marks missing data. Latitude ascends, longitude descends.

Documentation

Full guides and API reference: https://chunsikpark.github.io/Weather_data_GUI/

Point-and-click alternative: https://weather-data-gui.pages.dev

License

MIT