Operational Reference

Reference for forecast update schedules, time bundles, regions, unit caveats, accumulated fields, and system status.

Forecast Update Schedule¶

Spire’s global atmospheric forecast model runs 4 times per day. New data becomes available approximately at:

Optimized Point Forecast Updates¶

The Optimized Point Forecast system (/forecast/point/optimized) updates every hour.

Current Weather Conditions Updates¶

The current weather conditions (/current/weather/) update every hour.

Time Bundles¶

Time bundles control the temporal resolution and extent of forecast data returned by the API. Use the time_bundle parameter to select which time grouping you want.

Example¶

Request only hourly data for the first 2 days:

curl -X GET \
  'https://api.wx.spire.com/forecast/point?lat=40.0&lon=-105.0&bundles=basic&time_bundle=hourly' \
  -H 'spire-api-key: YOUR_API_KEY'

import requests

response = requests.get(
    "https://api.wx.spire.com/forecast/point",
    params={
        "lat": 40.0,
        "lon": -105.0,
        "bundles": "basic",
        "time_bundle": "hourly",
    },
    headers={"spire-api-key": "YOUR_API_KEY"},
)
data = response.json()

const response = await fetch(
  "https://api.wx.spire.com/forecast/point?lat=40.0&lon=-105.0&bundles=basic&time_bundle=hourly",
  { headers: { "spire-api-key": "YOUR_API_KEY" } }
);
const data = await response.json();

Regions¶

Forecast file data is organized by geographic region. Available regions depend on your subscription.

Unit Differences Between APIs¶

Some variables have different units depending on whether they are returned by the Point/Route API (JSON) or the File API (GRIB2):

Working with Accumulated Fields¶

Several variables in the forecast data are accumulated from the start of the forecast (issuance time). These include:

• Accumulated precipitation

• Accumulated snowfall

• Accumulated radiation (shortwave/longwave, incoming/outgoing)

Deriving Hourly Values¶

To get the hourly amount for an accumulated field, subtract the previous time step’s value from the current one:

# Example: derive hourly precipitation from accumulated values
hourly_precip = []
for i in range(1, len(data)):
    current = data[i]['values']['precipitation_amount']
    previous = data[i-1]['values']['precipitation_amount']
    hourly_precip.append(current - previous)

Accumulation Bundles¶

For convenience, Spire offers “accumulation” bundles that provide pre-computed 1-hour, 3-hour, and 6-hour accumulation amounts, eliminating the need to compute differences manually:

• basic-accumulation — 1h/3h/6h precipitation amounts

• precipitation-accumulation — 1h/3h/6h snowfall amounts

• solar-energy-accumulation — 1h/3h/6h radiation amounts

These are available at the Point API endpoint and are opt-in. Contact Spire if you are interested.

GRIB2 File Concatenation¶

GRIB2 files from Spire can be concatenated together. This is useful for combining multiple lead times or bundles into a single file for processing:

cat sof-d.20240115.t00z.0p25.basic.global.f000.grib2 \
    sof-d.20240115.t00z.0p25.basic.global.f006.grib2 \
    sof-d.20240115.t00z.0p25.basic.global.f012.grib2 \
    > combined.grib2

System Status¶

Spire Weather provides an online status page to monitor the health of the API and weather data products. The status page can be accessed at: Spire Weather Status

Monitored Components¶

Status Values¶

Impact of Degraded Performance¶

When a forecast component shows degraded performance:

• Short-range forecast (first 24–36 hours) may be based on the previous model run and have slightly reduced accuracy

• The medium-range forecast may be missing the last few hours of its range (e.g., only 9.5 days instead of 10)

• Historical/archived data remains unaffected