Leatherback ROMS model
The most recent map products from the model are shown below, in addition to an interactive map of the latest prediction.
Status of environmental products from ROMS: 
ROMS has been down for 79 days
Latest Map Products
Interactive Map
This example shows both model predictions and environmental covariates used to estimate the models. Change the date and selected variable to explore these relationships in more detail.
Download Map Products and Raster Layers
From website
From GitHub
Clone the repository: https://github.com/joshcullen/CEG_operationalization
From R
library(curl)
library(httr)
library(tidyverse)
library(glue)
download_files_git = function(save_dir, file_type, start_date, end_date){
folder <- switch(file_type,
"raster" = "rasters",
"image" = "img")
# Find files from repo folder
prods <- httr::GET(glue("https://api.github.com/repos/joshcullen/CEG_operationalization/contents/model_prediction/ROMS/{folder}"))
httr::stop_for_status(prods) #check to make sure no errors w/ request (should return nothing to console if working properly)
filelist <- unlist(lapply(content(prods), "[", "name"), use.names = F)
prod_df <- data.frame(files = filelist,
date = gsub("^[A-Za-z]+\\_|\\.tiff$", "", filelist) |>
as.Date()
)
# Filter files by date range
prod_filt <- prod_df |>
filter(date >= as.Date(start_date),
date <= as.Date(end_date)) |>
pull(files)
git_url <- glue("https://raw.githubusercontent.com/joshcullen/CEG_operationalization/main/model_prediction/ROMS/{folder}/{prod_filt}")
file_dest <- glue("{save_dir}/{prod_filt}")
curl::multi_download(urls = git_url, destfiles = file_dest)
}
# Download files
download_files_git(save_dir = "~/Downloads",
file_type = "raster",
start_date = "2024-11-08",
end_date = "2024-11-30")
download_files_git(save_dir = "~/Downloads",
file_type = "image",
start_date = "2024-11-08",
end_date = "2024-11-30")