working on Sargassum indicator

Gulf-IEA · Jun 28, 2024 · 623084e · 623084e
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diff --git a/.Rhistory b/.Rhistory
diff --git a/2011 ACL Amendment FEIS 10_25_2011_FEIS Submitted to EPA Oct_25_2011.pdf b/2011 ACL Amendment FEIS 10_25_2011_FEIS Submitted to EPA Oct_25_2011.pdf
diff --git a/indicator_data/TCRMP/fish_density_USVI.RData b/indicator_data/TCRMP/fish_density_USVI.RData
diff --git a/indicator_data/TCRMP/slopeSizeSpec_USVI.RData b/indicator_data/TCRMP/slopeSizeSpec_USVI.RData
diff --git a/indicator_objects/disturbance.RData b/indicator_objects/disturbance.RData
diff --git a/indicator_processing/fishery_dependent/compile_indicators.R b/indicator_processing/fishery_dependent/compile_indicators.R
@@ -46,7 +46,7 @@ ind <- list(labels = indnames, indicators = inddata, datelist = datdata) #, ulim
 class(ind) <- "indicatordata"
 plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 3, sublabel = T, sameYscale = F)
 
-save(ind, file = "indicator_objects/mean_Lmax.RData")
+# save(ind, file = "indicator_objects/mean_Lmax.RData")
 
 Lmax <- mat
 

diff --git a/indicator_processing/non_automated/CRMP_processing/TCRMP_fish.R b/indicator_processing/non_automated/CRMP_processing/TCRMP_fish.R
@@ -147,6 +147,7 @@ for (j in sitelis) {
     mat[i, 3:12] <- c(su2, su[3:length(su)])
     mat[i, 13] <- sum(f1$Total, na.rm = T)  }
 } 
+
 dim(mat)
 mat <- mat[-which(rowSums(mat[3:ncol(mat)]) == 0), ]
 dim(mat)

diff --git a/indicator_processing/non_automated/Sargassum_inundation.R b/indicator_processing/non_automated/Sargassum_inundation.R
@@ -1,16 +1,63 @@
+#
+# Sargassum inundation indicator
+#
+# direct download from ERDDAP
+# https://cwcgom.aoml.noaa.gov/erddap/griddap/noaa_aoml_atlantic_oceanwatch_AFAI_7D.graph
+
+# specification file and libraries -----------------------------
 
 rm(list = ls())
 dev.off()
 
+library(lubridate)
 library(maps)
 library(plotTimeSeries)
+library(rerddap)
 
 load("indicator_processing/spec_file.RData")
 
 # define years  --------------------------------
-styear <- 1961
+styear <- 2012
 enyear <- terminal_year
 
+# get ERDDAP info  --------------------------------
+afai <- info('noaa_aoml_atlantic_oceanwatch_AFAI_7D',
+              url = 'https://cwcgom.aoml.noaa.gov/erddap')
+afai
+
+# download data --------------------
+
+yr1 <- as.numeric(substr(afai$alldata$NC_GLOBAL$value[35], 1, 4)) + 1
+yr2 <- as.numeric(substr(afai$alldata$NC_GLOBAL$value[34], 1, 4)) - 1
+yr1
+yr2
+
+res <- griddap(afai, fields = 'AFAI', 
+                    time = c(paste0(yr1, '-01-01'), paste0(yr2, '-12-31')), 
+                    longitude = c(min_lon, max_lon), 
+                    latitude = c(min_lat, max_lat))
+
+res$data$lim <- 0
+res$data$lim [which(res$data$AFAI > 0.002)] <- 1
+
+res$data$year <- substr(res$data$time, 1, 4)
+res$data$tim <- substr(res$data$time, 1, 7)
+
+head(res$data)
+
+mon_afai <- tapply(res$data$lim, res$data$tim, sum, na.rm = T)
+yr_afai <- tapply(res$data$lim, res$data$year, sum, na.rm = T)
+
+plot(mon_afai, type = "l")
+plot(2017:2023, 
+     yr_afai, type = "l")
+
+# create indicator object --------------
+
+#################    INCOMPLETE  ########################
+# need to look up algorithm to convert AFAI units to Area of inundation 
+# check Chuanmin write-up and find methods
+
 # load data -------------------------------------
 
 d <- read.csv("indicator_data/sargassum_innundation_monthly_mean_hu.csv", skip = 2)