ImperialCollegeLondon / ImperialCollegeLondon/virtual_ecosystem

M1.4.3 Add simple snow albedo parameterization

Open
#1,708 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
20
Forks
5
Avg merge
2d 1h
Merged PRs (30d)
34

Description

Summary

Implement a simple snow albedo representation suitable for coupling snow to the existing energy-balance model.

Purpose

Represent the high reflectivity of snow and, if desired and feasible, its decline with aging between snowfall events.

Tasks

  • Implement either fixed snow albedo for v1, or simple fresh-snow to aged-snow decay
  • Define whether new snowfall resets snow albedo fully or partially.
  • Document the selected scheme.

Acceptance criteria

  • Fresh snowfall increases snow albedo if a prognostic scheme is used.
  • Snow albedo decays toward an aged-snow value if aging is used.
  • Snow albedo stays within prescribed bounds.
  • The chosen scheme is documented and wired into effective surface albedo calculations.

Suggested tests

  • Fixed-albedo mode.
  • Aging without snowfall.
  • Albedo refresh after snowfall.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Locate the existing energy-balance model and effective surface albedo calculations first; the issue does not name specific files or entry points. Choose and document either fixed snow albedo or an aging scheme, wire it into effective albedo, and add tests covering the selected mode, bounds, aging, and snowfall refresh behavior.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
backend
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.