GribStream.com

GribStream users and weather data fans: big news.

GribStream just added full support for NOAA's GEFS ensemble model. This means you can now access all individual GEFS ensemble members, not just the ensemble mean.

What’s new:

- You get every perturbed forecast member (30 members +1 control)

- Available globally at 0.25° grid, 4 runs per day (00, 06, 12, 18 UTC), out to 10 days

- Access via the same simple API, just set model=gefsatmos and specify the members array if you want specific members

Why this matters:

- Allows you to do true probabilistic and uncertainty analysis

- Calculate spread, percentiles, standard deviation, member agreement, etc

- Build weather risk tools, insurance models, energy applications, or advanced meteorological research on a budget

How to use:

- See the [GribStream GEFS info page](https://gribstream.com/models/gefsatmos) for details, variable list, and example queries

- All endpoints now support model=gefsatmos and an optional members parameter (example: "members": [2,3,4])

- Full documentation and OpenAPI spec have been updated

Tips:

- Data volumes increase if you pull all members — filter by variables, region, or members as needed

- Works worldwide, not just CONUS

- Ensemble members are indexed starting from 0 (control)

This is a big step for anyone who needs more than just the mean forecast. If you use ensembles for weather analytics, power grids, insurance, ag-tech, or just want to play with real ensemble weather data: check it out.

GribStream.com offers full access to historical weather data and forecasts through an efficient API. It's built for meteorologists, researchers, and anyone needing reliable weather data.

Features include:

• A free tier to help you get started

• Full history of weather forecasts

• Leverage state of the art weather models like the National Blend of Models (NBM), the Global Forecast System (GFS) and the Rapid Refresh (RAP) models.

• Blazing fast! Extract timeseries for thousands of coordinates, for months at a time, at hourly resolution in a single HTTP request taking seconds.

• Supports as-of/time-travel, indispensable for proper backtesting of derivative models

• Automatic gap filling of any missing data with the next best (most recent) forecast.

• A long pipeline of incoming features!

Hundreds of weather parameters include:

• Temperature

• Dew point

• Wind speed and direction

• Accumulated rain & snow

• Probability of rain and snow

• Visibility

• Relative humidity

• Cloud cover

• Many, many more!

Check out the documentation: https://gribstream.com/docs

Browse the data: https://gribstream.com/demo/nbm

See examples: https://github.com/GribStream/python-client

Reach out for support at: info@gribstream.com and https://discord.com/invite/33eWFBpdUK