Ecomon + NRHA

NEFSC · Aug 15, 2024 · 98f0d53 · 98f0d53
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diff --git a/get_thresholds_NRHA_Ecomon.R b/get_thresholds_NRHA_Ecomon.R
@@ -0,0 +1,157 @@
+# Use pulled survdat.rds file to get environmental thresholds for Atlantis groups
+library(dplyr)
+library(here)
+library(geosphere)
+
+# Temporal and spatial bounds
+
+isWithinBounds <- function(CTD_loc,p1_loc,SPATIAL_BOUND) {
+
+  distance <- distm(CTD_loc,p1_loc,fun=distGeo) * 0.000621371
+  if (distance <= SPATIAL_BOUND) {
+    return(TRUE)
+  } else {
+    return(FALSE)
+  }
+}
+
+convertCTDdate <- function(date) {
+  split.points <- c(4,6,8)
+  converted_date <- substring(date,c(1,split.points + 1), c(split.points, nchar(date)))
+  converted_date <- as.Date(paste(converted_date[1],"-",converted_date[2],"-",converted_date[3],sep=""))
+  return(converted_date)
+}
+
+TEMPORAL_BOUND <- 14      # days
+SPATIAL_BOUND <- 5       # miles
+# Get output data
+NRHA_dt <-read.csv(here("data","NRHA_data.csv"))
+CTD_dt <-read.csv(here("data","CTD_data.csv"))
+
+# create empty dts to be filled for later analysts
+rows_CTD_dt <- nrow(CTD_dt)
+surfbot_dt <- CTD_dt[-c(1:rows_CTD_dt),]
+nearest_dt <- surfbot_dt
+
+# create list of uniqueIDs for CTD casts
+uniqueID_list <- unique(CTD_dt$UniqueID)[]
+
+
+# Make temporary data structure with just first (surface) and last (bottom) records, 
+# and add the first row to nearest_dt and the first and last to to surfbot_dt
+
+numCasts <- length(uniqueID_list)
+
+for(i in 1:numCasts) {
+  print(i)
+  temp_dt <- filter(CTD_dt, UniqueID == uniqueID_list[i])
+  nearest_dt <- rbind(nearest_dt,temp_dt[1,])
+  surfbot_dt <- rbind(surfbot_dt,temp_dt[1,])
+  surfbot_dt <- rbind(surfbot_dt,temp_dt[nrow(temp_dt),])
+}
+
+surfbot_dt_old <- surfbot_dt
+nearest_dt_old <- nearest_dt
+
+
+nearest_dt <- mutate(nearest_dt, DATE = convertCTDdate(Date))
+surfbot_dt$Date <- convertCTDdate(surfbot_dt$Date)
+
+surfbot_numRows <- nrow(surfbot_dt)
+
+newDates <- c(convertCTDdate(surfbot_dt$Date[1]))
+for (i in 2:surfbot_numRows) {
+  print(i)
+  newDate <- convertCTDdate(surfbot_dt$Date[i])
+  newDates <- append(newDates,newDate)
+}
+
+surfbot_dt$Date <- newDates
+atlantis_groups_dt <- read.csv(here("inputs","atlantis_codes_svspp_survey_thresholds.csv"))
+
+# Modify data tables for ease of use
+colnames(atlantis_groups_dt)[2] <- "COMNAME"
+atlantis_groups_dt <- group_by(atlantis_groups_dt,Code)
+
+atlantis_NRHA_dt <- inner_join(NRHA_dt,atlantis_groups_dt,by="COMNAME")
+
+atlantis_NRHA_tows_dt <- unique(select(atlantis_NRHA_dt,DATE,Start_Lat,Start_Lon))
+
+atlantis_NRHA_dt$SurfTEMP <- NA
+atlantis_NRHA_dt$BottTEMP <- NA
+atlantis_NRHA_dt$SurfSALIN <- NA
+atlantis_NRHA_dt$BottSALIN <- NA
+
+# Convert date columns to date object
+atlantis_NRHA_dt$DATE <- as.Date(atlantis_NRHA_dt$DATE)
+
+numRecords <- nrow(atlantis_NRHA_dt)
+
+for (n in 1:numRecords) {
+  loc_tow <- c(atlantis_NRHA_dt$Start_Lat[n], atlantis_NRHA_dt$Start_Lon[n])
+  date_tow <- as.Date(atlantis_NRHA_dt$DATE[n])
+
+  min_date <- date_tow - TEMPORAL_BOUND
+  max_date <- date_tow + TEMPORAL_BOUND
+
+  min_lat <- atlantis_NRHA_dt$Start_Lat[n] - 0.2
+  max_lat <- atlantis_NRHA_dt$Start_Lat[n] + 0.2
+  min_lon <- atlantis_NRHA_dt$Start_Lon[n] - 0.2
+  max_lon <- atlantis_NRHA_dt$Start_Lon[n] + 0.2
+
+  surfbot_dt_filtered <- filter(surfbot_dt, Date >= min_date & Date <= max_date)
+  surfbot_dt_filtered <- filter(surfbot_dt_filtered, Latitude >= min_lat & Latitude <= max_lat & Longitude >= min_lon & Longitude <= max_lon)
+  print(n)
+  numCasts <- nrow(surfbot_dt_filtered)
+
+  if (numCasts > 0) {
+    for (i in 1:numCasts) {
+      loc_ctd <- c(surfbot_dt_filtered$Latitude[i], surfbot_dt_filtered$Longitude[i])
+      if (isWithinBounds(loc_tow,loc_ctd,SPATIAL_BOUND)) {
+        print("Within Bounds")
+        atlantis_NRHA_dt$SurfTEMP[n] <- surfbot_dt_filtered$Temperature[i]
+        atlantis_NRHA_dt$SurfSALIN[n] <- surfbot_dt_filtered$Salinity[i]
+        i <- i + 1
+        atlantis_NRHA_dt$BottTEMP[n] <- surfbot_dt_filtered$Temperature[i]
+        atlantis_NRHA_dt$BottSALIN[n] <- surfbot_dt_filtered$Salinity[i]
+      } else {
+        i <- i + 1
+      }
+    }
+  }
+
+}
+
+# The data includes a lot of 0's in the surface temperature data and some above 40 (104 F)
+# for the surface temperature data.  This constricts the ranges to exclude 0's and temperatures above 40.
+
+atlantis_NRHA_dt$BottTEMP[(atlantis_NRHA_dt$BottTEMP == 0) | (atlantis_NRHA_dt$BottTEMP > 40)] <- NA
+atlantis_NRHA_dt$SurfTEMP[(atlantis_NRHA_dt$SurfTEMP == 0) | (atlantis_NRHA_dt$SurfTEMP > 40)] <- NA
+
+atlantis_NRHA_summary_table <- group_by(atlantis_NRHA_dt,Code,SEASON)
+atlantis_NRHA_summary_table_SEASON <- summarise(atlantis_NRHA_summary_table, min_bottom_temp = min(BottTEMP, na.rm=T), max_bottom_temp = max(BottTEMP, na.rm=T),
+                                  min_surface_temp = min(SurfTEMP,na.rm=T), max_surface_temp = max(SurfTEMP,na.rm=T),
+                                  min_bottom_sal = min(BottSALIN,na.rm=T), max_bottom_sal = max(BottSALIN,na.rm=T),
+                                  min_surface_sal = min(SurfSALIN,na.rm=T), max_surface_sal = max(SurfSALIN,na.rm=T))
+
+
+atlantis_NRHA_summary_table_SPECIES <- group_by(atlantis_NRHA_dt,Code)
+atlantis_NRHA_summary_table_SPECIES <- summarise(atlantis_NRHA_summary_table_SPECIES, min_bottom_temp = min(BottTEMP, na.rm=T), max_bottom_temp = max(BottTEMP, na.rm=T),
+                                   min_surface_temp = min(SurfTEMP,na.rm=T), max_surface_temp = max(SurfTEMP,na.rm=T),
+                                   min_bottom_sal = min(BottSALIN,na.rm=T), max_bottom_sal = max(BottSALIN,na.rm=T),
+                                   min_surface_sal = min(SurfSALIN,na.rm=T), max_surface_sal = max(SurfSALIN,na.rm=T))
+
+# Removes infinity values from the outputs and sets to NA
+atlantis_NRHA_summary_table_SEASON$min_bottom_sal[(atlantis_NRHA_summary_table_SEASON$min_bottom_sal == 'Inf') | (atlantis_NRHA_summary_table_SEASON$min_bottom_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SEASON$max_bottom_sal[(atlantis_NRHA_summary_table_SEASON$max_bottom_sal == 'Inf') | (atlantis_NRHA_summary_table_SEASON$max_bottom_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SEASON$min_surface_sal[(atlantis_NRHA_summary_table_SEASON$min_surface_sal == 'Inf') | (atlantis_NRHA_summary_table_SEASON$min_surface_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SEASON$max_surface_sal[(atlantis_NRHA_summary_table_SEASON$max_surface_sal == 'Inf') | (atlantis_NRHA_summary_table_SEASON$max_surface_sal == '-Inf')] <- 'NA'
+
+atlantis_NRHA_summary_table_SPECIES$min_bottom_sal[(atlantis_NRHA_summary_table_SPECIES$min_bottom_sal == 'Inf') | (atlantis_NRHA_summary_table_SPECIES$min_bottom_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SPECIES$max_bottom_sal[(atlantis_NRHA_summary_table_SPECIES$max_bottom_sal == 'Inf') | (atlantis_NRHA_summary_table_SPECIES$max_bottom_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SPECIES$min_surface_sal[(atlantis_NRHA_summary_table_SPECIES$min_surface_sal == 'Inf') | (atlantis_NRHA_summary_table_SPECIES$min_surface_sal == '-Inf')] <- 'NA'
+atlantis_NRHA_summary_table_SPECIES$max_surface_sal[(atlantis_NRHA_summary_table_SPECIES$max_surface_sal == 'Inf') | (atlantis_NRHA_summary_table_SPECIES$max_surface_sal == '-Inf')] <- 'NA'
+
+
+write.csv(atlantis_NRHA_summary_table_SEASON,here("thresholds","seasonal_thresholds_NRHA_ecomon.csv"),row.names=FALSE)
+write.csv(atlantis_NRHA_summary_table_SPECIES,here("thresholds","group_thresholds_NRHA_ecomon.csv"),row.names=FALSE)
diff --git a/thresholds/group_thresholds_NRHA_ecomon.csv b/thresholds/group_thresholds_NRHA_ecomon.csv
@@ -0,0 +1,34 @@
+"Code","min_bottom_temp","max_bottom_temp","min_surface_temp","max_surface_temp","min_bottom_sal","max_bottom_sal","min_surface_sal","max_surface_sal"
+"BLF",5.66,28.08,4.44,27.08,"-1e+10","36.38","-1e+10","36.428"
+"BSB",3.44,28.91,2.99,27.36,"-1e+10","36.43","-1e+10","36.404"
+"BUT",1.087,29.4,-1e+10,28.51,"-1e+10","36.574","-1e+10","36.846"
+"COD",1.087,23.08,1.35,21.95,"-1e+10","35.921","-1e+10","36.517"
+"DOG",1.087,27.76,2.09,23.11,"-1e+10","36.466","-1e+10","36.517"
+"DRM",2.9,29.57,-1e+10,28.51,"-1e+10","36.606","-1e+10","37.3033"
+"FDE",1.087,26.15,1.27,27.3,"-1e+10","36.031","-1e+10","37.3033"
+"HAD",1.087,27.59,2.32,20.08,"-1e+10","36.3064","-1e+10","35.742"
+"HAL",1.17,18.71,2.74,16.57,"-1e+10","33.619","26.547","35.075"
+"HER",1.3,25.16,1.23,22.12113,"-1e+10","35.921","-1e+10","36.418"
+"LSK",1.087,28.36,-1e+10,24.26,"-1e+10","36.406","-1e+10","35.932"
+"MAK",1.21,25.73,2.93,22.53,"-1e+10","36.43","-1e+10","35.932"
+"OHK",3.48,29.44,4.2548,24.54,"-1e+10","36.579","32.234","36.463"
+"OPT",1.3,27.59,1.27,19.85,"-1e+10","35.968","-1e+10","35.772"
+"PLA",1.17,20.97,1.35,17.723,"-1e+10","34.797","-1e+10","35.637"
+"POL",1.087,22.03,2.18,21.233,"-1e+10","35.26","-1e+10","36.517"
+"QHG",3.94,20.14,2.93,20.51,"29.161","33.481","30.747","34.461"
+"RED",1.68,20.68,2.32,18.53,"-1e+10","34.99","31.252","35.754"
+"RHK",1.17,27.59,-1e+10,24.2445,"-1e+10","36.466","-1e+10","36.361"
+"SAL",Inf,-Inf,Inf,-Inf,"NA","NA","NA","NA"
+"SCU",3.18,29.57,-1e+10,28.51,"-1e+10","36.606","-1e+10","36.741"
+"SDF",6.24,25.97,5.33,25.59,"-1e+10","33.786","24.8037","35.726"
+"SHK",1.087,29.4,-1e+10,28.51,"-1e+10","36.561","-1e+10","36.517"
+"SK",1.087,29.76,-1e+10,28.28,"-1e+10","36.579","-1e+10","36.554"
+"SUF",1.55,29.27,-1e+10,28.22,"-1e+10","36.606","-1e+10","36.741"
+"TAU",2.51,27.37,1.61,26.55,"-1e+10","34.55","-1e+10","36.21"
+"TYL",6.42,27.16,7.68,22.66,"32.245","36.43","32.829","36.459"
+"WHK",1.17,29.4,2.54,22.61,"-1e+10","36.409","-1e+10","36.348"
+"WIF",1.3,25.9152,-1e+10,24.26,"-1e+10","35.209","-1e+10","37.3033"
+"WPF",1.17,28.58,-1e+10,26.7,"-1e+10","35.921","-1e+10","36.3209"
+"WSK",1.087,23.77,1.27,21.88,"-1e+10","36.3064","-1e+10","36.431"
+"WTF",1.55,26.41,2.09,18.53,"-1e+10","36.409","-1e+10","35.894"
+"YTF",1.087,25.23,-1e+10,20.02,"-1e+10","35.772","-1e+10","35.76"
diff --git a/thresholds/seasonal_thresholds_NRHA_ecomon.csv b/thresholds/seasonal_thresholds_NRHA_ecomon.csv
@@ -0,0 +1,130 @@
+"Code","SEASON","min_bottom_temp","max_bottom_temp","min_surface_temp","max_surface_temp","min_bottom_sal","max_bottom_sal","min_surface_sal","max_surface_sal"
+"BLF","Fall",9.88,28.08,6.34,27.08,"-1e+10","36.261","-1e+10","36.422"
+"BLF","Spring",5.66,21.7,4.44,22.55,"26.5","36.38","-1e+10","36.428"
+"BLF","Summer",11.49,25.6666,5.916,26.4927,"25.38","32.332","0.0697","33.708"
+"BLF","Winter",6.41,19.75,8.82,17.64,"-1e+10","36.362","32.803","36.312"
+"BSB","Fall",9.68,28.91,6.28,27.36,"-1e+10","36.129","-1e+10","36.401"
+"BSB","Spring",3.44,23.01,3.25,21.05,"-1e+10","36.43","-1e+10","36.404"
+"BSB","Summer",8.511,27.37,3.64,26.63,"0.0669","34.55","26.8188","36.21"
+"BSB","Winter",3.46,19.75,2.99,19.64,"-1e+10","36.401","-1e+10","36.361"
+"BUT","Fall",7.93,29.4,3.99,28.51,"-1e+10","36.352","-1e+10","36.539"
+"BUT","Spring",1.087,24.41,2.653,22.67,"-1e+10","36.574","-1e+10","36.846"
+"BUT","Summer",7.11,27.54,-1e+10,26.63,"0.0669","34.55","0.0697","36.21"
+"BUT","Winter",3.45,19.43,3.37,19.64,"-1e+10","36.466","-1e+10","36.361"
+"COD","Fall",5.67,23.08,3.83,21.95,"-1e+10","35.168","-1e+10","35.366"
+"COD","Spring",1.087,16.06,1.35,17.723,"-1e+10","35.921","-1e+10","36.517"
+"COD","Summer",7.11,21.244,3.63,18.3924,"9.8712","32.65","26.733","35.085"
+"COD","Winter",1.21,9.59,1.36,12.56,"-1e+10","33.398","30.729","35.402"
+"DOG","Fall",5.67,27.76,3.83,23.11,"-1e+10","35.874","-1e+10","35.892"
+"DOG","Spring",1.087,20.12,2.39,22.07,"-1e+10","36.43","-1e+10","36.517"
+"DOG","Summer",8.842,23.72,3.61,21.233,"29.335","33.34","29.095","34.818"
+"DOG","Winter",2.22,19.4,2.09,16.62,"-1e+10","36.466","-1e+10","36.255"
+"DRM","Fall",10.13,29.57,7.35,28.51,"-1e+10","36.261","-1e+10","36.454"
+"DRM","Spring",2.9,22.77,2.681,22.55,"22.29","36.606","24.655","36.62"
+"DRM","Summer",11.49,25.6666,-1e+10,26.4927,"0.0669","32.5","0.0657","37.3033"
+"DRM","Winter",5.06,11.4,4.53,19.64,"30.71","35.231","30.18","36.361"
+"FDE","Fall",8.212,26.15,3.83,27.3,"-1e+10","35.361","23.114","36.168"
+"FDE","Spring",1.087,16.7,1.27,18.47,"-1e+10","36.031","-1e+10","36.063"
+"FDE","Summer",7.11,25.59,3.63,26.63,"8.5465","32.532","12.449","37.3033"
+"FDE","Winter",1.21,12.6,1.36,14.44,"-1e+10","35.274","-1e+10","35.781"
+"HAD","Fall",8.015,27.59,4.47,20.08,"-1e+10","35.874","-1e+10","35.742"
+"HAD","Spring",1.087,20.0199,2.32,17.723,"-1e+10","36.3064","-1e+10","35.648"
+"HAD","Summer",7.11,21.244,4.22,14.08,"28.796","32.65","26.8188","35.085"
+"HAD","Winter",1.55,11.815,3.03,12.66,"-1e+10","34.788","31.48","35.402"
+"HAL","Fall",8.389,18.71,5.19,16.57,"-1e+10","33.619","31.654","35.075"
+"HAL","Spring",1.17,14.11,2.74,9.7546,"-1e+10","32.992","26.547","34.947"
+"HAL","Summer",7.11,13.05,3.973,7.964,"30.958","32.494","31.663","35.031"
+"HAL","Winter",5.98,8.56,5.57,8.64,"32.044","32.282","32.183","33.603"
+"HER","Fall",5.67,25.16,3.83,21.6275,"-1e+10","34.279","-1e+10","35.5099"
+"HER","Spring",1.58,16.06,1.23,20.63,"-1e+10","35.921","-1e+10","36.418"
+"HER","Summer",7.11,23.545,3.35,22.12113,"9.8712","32.537","23.9704","35.062"
+"HER","Winter",1.3,11.815,1.36,13.73,"-1e+10","34.816","-1e+10","35.387"
+"LSK","Fall",8.84,28.36,4.67,23.86,"-1e+10","35.885","-1e+10","35.932"
+"LSK","Spring",1.087,19.11,1.71,17.723,"-1e+10","36.406","-1e+10","35.772"
+"LSK","Summer",7.11,25.8,-1e+10,24.26,"26.2394","32.94","26.8188","35.576"
+"LSK","Winter",1.21,14.92,1.36,15.72,"-1e+10","35.816","-1e+10","35.845"
+"MAK","Fall",8.361,25.73,4.95,22.53,"-1e+10","35.361","28.4369","35.932"
+"MAK","Spring",1.21,20.12,2.93,14.66,"-1e+10","36.43","28.215","35.728"
+"MAK","Summer",11.08,23.61,4.22,22.47,"29.137","32.65","24.8037","33.819"
+"MAK","Winter",3.06,12.8,3.1,15.77,"-1e+10","35.231","-1e+10","35.753"
+"OHK","Fall",11.32,29.44,4.314,24.54,"-1e+10","36.133","32.234","36.426"
+"OHK","Spring",3.69,22.7,4.2548,20.14,"-1e+10","36.579","32.338","36.463"
+"OHK","Summer",Inf,-Inf,Inf,-Inf,"NA","NA","NA","NA"
+"OHK","Winter",3.48,18.84,6.34,14.3,"-1e+10","36.409","32.741","35.781"
+"OPT","Fall",8.32,27.59,3.83,19.85,"-1e+10","35.391","31.119","35.688"
+"OPT","Spring",1.58,16.69,1.27,13.98,"-1e+10","35.968","26.123","35.772"
+"OPT","Summer",7.11,23.95,3.61,18.75,"29.597","32.94","31.125","34.741"
+"OPT","Winter",1.3,9.24,1.4,14.01,"-1e+10","34.199","-1e+10","35.753"
+"PLA","Fall",5.67,19.94,3.83,17.174,"-1e+10","34.797","31.041","35.588"
+"PLA","Spring",1.17,14.11,1.35,17.723,"-1e+10","33.864","-1e+10","35.573"
+"PLA","Summer",7.11,20.97,3.35,13.578,"30.545","32.537","31.119","35.031"
+"PLA","Winter",2.22,9.76,3.32,13.03,"-1e+10","33.673","32.033","35.637"
+"POL","Fall",6.26,22.03,4.59,18.56,"-1e+10","35.168","-1e+10","35.345"
+"POL","Spring",1.087,12.25,2.18,17.723,"-1e+10","33.924","-1e+10","36.517"
+"POL","Summer",7.11,20.97,3.35,21.233,"30.455","32.367","26.733","34.717"
+"POL","Winter",3.59,10.96,2.78,12.14,"32.101","35.26","32.272","35.512"
+"QHG","Fall",11.64,20.14,7.48,20.51,"30.695","32.382","30.904","33.592"
+"QHG","Spring",5.28,9.75,2.93,10.101,"29.161","33.481","30.747","34.185"
+"QHG","Summer",8.67,10.38,5.05,7.63,"31.207","32.494","31.62","32.286"
+"QHG","Winter",3.94,3.94,5.72,10.53,"32.421","32.421","31.772","34.461"
+"RED","Fall",5.67,20.68,3.83,18.53,"-1e+10","34.99","31.487","35.754"
+"RED","Spring",1.68,14.11,2.32,13.98,"-1e+10","33.923","31.252","35.583"
+"RED","Summer",7.11,20.24,3.35,10.83,"30.57","32.537","31.513","35.085"
+"RED","Winter",4.37,10.24,7.04,14,"32.282","33.906","32.183","35.638"
+"RHK","Fall",5.67,27.59,3.83,22.5603,"-1e+10","35.961","-1e+10","36.107"
+"RHK","Spring",1.17,20.12,1.71,18.79,"-1e+10","36.43","9.631","36.148"
+"RHK","Summer",7.11,24.41,-1e+10,24.2445,"23.3206","33.34","26.8188","35.29"
+"RHK","Winter",1.21,19.75,1.36,19.64,"-1e+10","36.466","-1e+10","36.361"
+"SAL","Spring",Inf,-Inf,Inf,-Inf,"NA","NA","NA","NA"
+"SAL","Winter",Inf,-Inf,Inf,-Inf,"NA","NA","NA","NA"
+"SCU","Fall",9.53,29.57,6.2,28.51,"-1e+10","36.261","-1e+10","36.459"
+"SCU","Spring",3.18,22.45,3.35,22.67,"-1e+10","36.606","26.123","36.741"
+"SCU","Summer",8.511,25.9152,-1e+10,26.63,"0.0669","32.5","0.0697","36.18"
+"SCU","Winter",3.45,19.75,4.3,19.64,"-1e+10","36.466","-1e+10","36.361"
+"SDF","Fall",17.45,25.97,12.26,25.59,"-1e+10","31.319","25.2287","35.505"
+"SDF","Spring",6.39,9.47,5.33,20.74,"22.29","32.171","29.801","35.501"
+"SDF","Summer",10.38,20.44,7.39,16.1,"29.15","31.455","24.8037","32.683"
+"SDF","Winter",6.24,8.37,5.92,13.75,"32.683","33.786","31.772","35.726"
+"SHK","Fall",5.67,29.4,3.83,28.51,"-1e+10","36.133","-1e+10","36.36"
+"SHK","Spring",1.087,22.37,2,20.14,"-1e+10","36.561","-1e+10","36.517"
+"SHK","Summer",7.11,26.88,-1e+10,22.46,"26.238","33.34","26.8188","35.49"
+"SHK","Winter",1.55,18.78,1.45,15.9,"-1e+10","36.325","-1e+10","36.043"
+"SK","Fall",5.67,29.76,3.83,28.28,"-1e+10","36.359","-1e+10","36.524"
+"SK","Spring",1.087,24.41,2.16,22.55,"-1e+10","36.579","-1e+10","36.554"
+"SK","Summer",7.11,27.46,-1e+10,23.45,"0.0669","33.59","0.0697","35.2"
+"SK","Winter",2.37,19.75,1.76,17.76,"-1e+10","36.466","31.436","36.342"
+"SUF","Fall",10.13,29.27,6.2,28.22,"-1e+10","36.34","-1e+10","36.459"
+"SUF","Spring",2.75,23.21,2.1,22.16,"-1e+10","36.606","9.631","36.741"
+"SUF","Summer",10.101,27.37,-1e+10,26.63,"0.0669","34.55","0.0697","36.21"
+"SUF","Winter",1.55,19.4,1.74,19.64,"-1e+10","36.466","-1e+10","36.361"
+"TAU","Fall",10.61,23.67,6.98,23.37,"-1e+10","32.726","-1e+10","33.346"
+"TAU","Spring",2.51,14.8081,2.03,14.133,"11.7212","32.508","25.5215","34.355"
+"TAU","Summer",8.842,27.37,3.973,26.55,"26.238","34.55","26.733","36.21"
+"TAU","Winter",3.01,7.96,1.61,8.91,"30.83","33.582","30.44","33.818"
+"TYL","Fall",22.08,27.16,7.68,22.66,"32.245","36.113","32.829","36.459"
+"TYL","Spring",6.42,20.12,8.91,13.83,"32.903","36.43","33.941","35.719"
+"TYL","Winter",9.91,18.25,11.14,14.01,"34.276","36.362","34.651","35.62"
+"WHK","Fall",8.15,29.4,4.3,22.61,"-1e+10","35.862","30.904","36.348"
+"WHK","Spring",1.17,19.19,2.54,18.79,"-1e+10","36.361","-1e+10","36.148"
+"WHK","Summer",7.11,23.95,3.35,15.67,"30.5453","32.537","31.125","35.085"
+"WHK","Winter",2.99,18.84,3.59,14.01,"-1e+10","36.409","-1e+10","35.743"
+"WIF","Fall",8.015,24.01,3.83,23.12,"-1e+10","35.209","-1e+10","35.44"
+"WIF","Spring",1.64,15.811,1.23,14.133,"-1e+10","33.923","23.8486","35.489"
+"WIF","Summer",7.11,25.9152,-1e+10,24.26,"9.8712","32.94","23.8486","37.3033"
+"WIF","Winter",1.3,9.59,1.36,11.25,"-1e+10","34.019","29.941","34.836"
+"WPF","Fall",9.18,28.58,5.34,26.7,"-1e+10","35.772","-1e+10","35.331"
+"WPF","Spring",1.17,17.804,1.71,22.55,"-1e+10","35.921","9.631","36.3209"
+"WPF","Summer",7.11,25.8,-1e+10,26.4927,"0.0669","32.94","0.0697","36.11"
+"WPF","Winter",1.21,10.36,1.36,12.27,"-1e+10","35.281","-1e+10","35.282"
+"WSK","Fall",8.7,23.77,4.74,21.88,"-1e+10","35.874","-1e+10","35.847"
+"WSK","Spring",1.087,20.0199,1.27,18.91,"-1e+10","36.3064","-1e+10","36.431"
+"WSK","Summer",7.11,21.244,3.973,19.42,"28.796","32.532","29.095","35.031"
+"WSK","Winter",1.21,12.6,1.36,13.73,"-1e+10","35.273","-1e+10","35.637"
+"WTF","Fall",5.67,26.41,3.83,18.53,"-1e+10","35.961","31.536","35.894"
+"WTF","Spring",2.31,20.0199,2.32,14.26,"-1e+10","36.406","30.691","35.772"
+"WTF","Summer",7.11,20.24,3.35,13.578,"30.57","32.537","31.639","35.031"
+"WTF","Winter",1.55,18.84,2.09,14.8,"-1e+10","36.409","-1e+10","35.845"
+"YTF","Fall",8.83,25.23,4.3,20.02,"-1e+10","35.772","31.041","35.76"
+"YTF","Spring",1.087,14.16,1.98,13.35,"-1e+10","35.328","-1e+10","35.645"
+"YTF","Summer",8.842,22.99,-1e+10,18.75,"30.455","32.94","31.125","35.031"
+"YTF","Winter",1.21,9.24,1.44,13.03,"-1e+10","34.067","-1e+10","35.637"