trying to figure out nc issues

Author: atyrell3

data-raw/scripts/2026/7km_trimmed_fixedgeometries/7km_grid_clipped_fixed_geometry.cpg

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+UTF-8

data-raw/scripts/2026/7km_trimmed_fixedgeometries/7km_grid_clipped_fixed_geometry.dbf

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+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data-raw/scripts/2026/7km_trimmed_fixedgeometries/7km_grid_clipped_fixed_geometry.prj

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+## Download FISHBOT data from ERDDAP
+end = Sys.Date()
+start = end - lubridate::days(7)
+url = paste0(
+  "https://erddap.ondeckdata.com/erddap/tabledap/fishbot_realtime.csvp?time%2Ctemperature%2Cgrid_id%2Clatitude%2Clongitude&time%3E=",
+  lubridate::year(start),
+  "-",
+  lubridate::month(start),
+  "-",
+  lubridate::day(start),
+  "T00%3A00%3A00Z&time%3C=",
+  lubridate::year(Sys.Date()),
+  "-",
+  lubridate::month(Sys.Date()),
+  "-",
+  lubridate::day(Sys.Date()),
+  "T00%3A00%3A00Z"
+)
+# url=paste0(
+#   'https://erddap.ondeckdata.com/erddap/tabledap/fishbot_realtime.csvp?time%2Ctemperature%2Ctemperature_count%2Cdata_provider%2Cgrid_id%2Clatitude%2Clongitude&time%3E=2025-08-21T00%3A00%3A00Z&time%3C=2025-08-28T00%3A00%3A00Z'
+# )
+data = read.csv(url)
+## Download bathymetric data
+bath = marmap::getNOAA.bathy(
+  lon1 = min(-80.83),
+  lon2 = max(-56.79),
+  lat1 = min(34),
+  lat2 = max(46.89),
+  resolution = 1
+)
+## Create color ramp
+blues = c(
+  "lightsteelblue4",
+  "lightsteelblue3",
+  "lightsteelblue2",
+  "lightsteelblue1"
+)
+## Set up plot
+filename = paste0(here::here("data-raw/scripts/2026/FISHBOT.png"))
+file.create(filename)
+
+png(
+  filename,
+  height = 1000,
+  width = 800,
+  units = "px"
+)
+plot(
+  bath,
+  step = 100,
+  deepest.isobath = -1000,
+  shallowest.isobath = 0,
+  col = "darkgray",
+  image = TRUE,
+  land = TRUE,
+  lwd = 0.1,
+  bpal = list(
+    c(0, max(bath), "gray"),
+    c(min(bath), 0, blues)
+  ),
+  main = paste0(
+    "Gridded Bottom Temperature Observations ",
+    start,
+    " to ",
+    end
+  ),
+  xlim = c(-76, -66),
+  ylim = c(34, 45)
+)
+## Load the shapefile
+grid = sf::read_sf(here::here(
+  "data-raw/scripts/2026/7km_trimmed_fixedgeometries/7km_grid_clipped_fixed_geometry.shp"
+))
+grid = subset(grid, grid$id %in% data$grid_id)
+grid$temp = NA
+grid$color = NA
+for (i in 1:nrow(grid)) {
+  grid$temp[i] = mean(
+    subset(data, data$grid_id == grid$id[i])$temperature..degree_C.
+  )
+}
+grid$TEMP = grid$temp * 9 / 5 + 32
+mintemp = floor(min(grid$TEMP))
+maxtemp = ceiling(max(grid$TEMP))
+tempcol = viridis::magma(n = length(seq(mintemp, maxtemp, 1)))
+for (i in 1:nrow(grid)) {
+  grid$color[i] = tempcol[which(
+    seq(mintemp, maxtemp, 1) == round(grid$TEMP[i], 0)
+  )]
+}
+plot(
+  sf::st_geometry(grid),
+  max.plot = 1,
+  add = TRUE,
+  border = grid$color,
+  col = grid$color
+)
+datacolors = data.frame(
+  TEMP = seq(mintemp, maxtemp, 1),
+  COL = tempcol
+)
+datacolors = subset(
+  datacolors,
+  datacolors$TEMP %in% round(quantile(datacolors$TEMP), 0)
+)
+legend(
+  'bottomright',
+  fill = datacolors$COL,
+  border = datacolors$COL,
+  legend = datacolors$TEMP,
+  title = "Bottom Temperature (F)"
+)
+dev.off()

data-raw/scripts/2026/7km_trimmed_fixedgeometries/7km_grid_clipped_fixed_geometry.shp

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+file <- here::here("data-raw/2026/fishbot_2000_2026.nc")
+
+terra::rast(file)
+terra::sds(file)
+
+nc_check <- ncdf4::nc_open(file)
+print(nc_check)
+ncdf4::nc_close(nc_check)
+
+# 1. Open the file and see what's inside
+nc_file <- ncdf4::nc_open(here::here("data-raw/2026/fishbot_2000_2026.nc"))
+
+# Print to find the exact variable names for lon, lat, and your data
+# print(nc_file)
+
+# 2. Extract the coordinates and the data variable
+# Replace 'lon', 'lat', and 'variable_name' with the names found in print(nc_file)
+lons <- ncdf4::ncvar_get(nc_file, "longitude")
+lats <- ncdf4::ncvar_get(nc_file, "latitude")
+data_array <- ncdf4::ncvar_get(nc_file, "temperature") # e.g., "temp" or "biomass"
+
+ncdf4::nc_close(nc_file)
+
+# 3. Handle the data structure
+# NetCDF data is often stored [lon, lat]. terra expects [row, col]
+# We might need to transpose the matrix
+data_mat <- t(data_array)
+
+# 4. Manually create the SpatRaster
+# We define the extent based on the min/max of our lon/lat vectors
+r <- terra::rast(
+  data_mat,
+  extent = terra::ext(min(lons), max(lons), min(lats), max(lats)),
+  crs = "EPSG:4326" # Assuming standard WGS84
+)
+
+# 5. Fix orientation
+# NetCDF often stores data "upside down" compared to standard GIS formats
+r <- terra::flip(r, direction = "vertical")
+
+terra::plot(r)