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NOAA-ORR-ERD / PyGnome

The General NOAA Operational Modeling Environment
https://gnome.orr.noaa.gov/doc/pygnome/index.html
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Beach type implementation #122

Open ClaudiaFarris opened 2 years ago

ClaudiaFarris commented 2 years ago

Hello! I need some help. I'm using the pyGNOME utilities to simulate the dispersion of marine litter in the sea, i was wondering how can I implement the information about the beach type in the BNA map.

Thank you in advance! Claudia

jay-hennen commented 2 years ago

What sort of information are you referring to? Land in GNOME are simulated very simply. They are little more than a wall for the oil to run into.

The primary configurable parameter on any Map object is the refloat_halflife which is the time period (units = hours) after which half the oil is expected to refloat, or leave the beach.

Raising this makes the beach 'stickier' while lowering it has the opposite effect.

ClaudiaFarris commented 2 years ago

My purpose is to use different refloat_halflife parameters according to the different beach types. I read this sentence 'In theory the half-life could be set to different values along different segments of the shoreline depending on the beach type' on page 15 of the General NOAA Operational Modeling Environment (GNOME) Technical Documentation, and I thought that this parameter could be set maybe in the map.

So, my question was if it is possible to set the refloat_halfile in the BNA map for every different segment that represents a specific beach type. If it is not possible in this way, is there any other method to set different refloat_halflife parameters?

jay-hennen commented 2 years ago

In theory yes it's possible to do that but the code to do so doesn't exist yet, nor has it been designed yet. I can only guess that since it hasn't been prioritized over the last few years it's not a major issue for GNOME users in practice. Perhaps (and I'm only guessing here) such a feature may be considered 'too much control' over an aspect of the simulation that in reality is extremely chaotic and unpredictable.

@ChrisBarker-NOAA or @AmyMacFadyen may be able to shed more light on this issue.