SFMS Insights: Decision on Weather Pipeline
- Dominant language
- Python
- Stars
- 65
- Forks
- 11
- Avg merge
- 21h 25m
- Merged PRs (30d)
- 70
Description
**Describe the task**
MVP: Weather Forecasters recommend using:
1) HRDPS for the first 48 hours, then
2) RDPS out to 72 hours,
3) and use global ensembles (GEPS, REPS, EU, GEFS) for anything beyond 72 hours.
**Acceptance Criteria**
- [ ] Determine model source of Numerical Weather modelling Data for each Weather Parameter
- [ ] Determine how Forecasters will spatially enhance Numerical Weather Forecast over the next 24-48 hours.
- [ ] System must run Automatically regardless Weather Forecasters are available or not
**Additional context**
- Initial UX Research indicates forecasters would like to spatially adjust temperature (and potentially RH) for elevation using lapse rates.
Contributor guide
Research direction
No files, tests, or entry points are named. Start by mapping each weather parameter to a numerical model source and reviewing the proposed 24–48-hour elevation adjustment approach. Done means the model sources, spatial-enhancement method, and automatic operation requirements are decided and documented.
Written by the indexing model from the issue text.
Assessment
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100