Boston_sea_level

Boston Harbor Sea Level Trends, 1920-2016

Data taken from NOAA site for Boston Harbor: https://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?stnid=8443970

Monthly mean sea level, by month, 1920-2017

setwd("\\\\psf/Home/Dropbox (Personal)")

get# Assemble data into one dataframe

## function (x, pos = -1L, envir = as.environment(pos), mode = "any", 
##     inherits = TRUE) 
## .Internal(get(x, envir, mode, inherits))
## <bytecode: 0x0336075c>
## <environment: namespace:base>

options(stringsAsFactors=FALSE)

tides <- read.csv("\\\\psf/Home/Dropbox (Personal)/MysticDB/Rcode/Sandbox/Andy/Climate/Boston_meantrend.csv", strip.white=TRUE)

tides$Date <- mdy(tides$Date)

tides$Month_f <- factor(tides$Month, levels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"))

#Monthly averages by year, with line of best fit
g <- ggplot(tides, aes(Date, Monthly_MSL , ymin=0)) +
  geom_smooth(method = 'lm', col = "red")

#g + geom_line() + geom_area() + facet_grid(parameter~Station, scales = "free_y") 
g + geom_line() 

setwd("\\\\psf/Home/Dropbox (Personal)")

# Assemble data into one dataframe
options(stringsAsFactors=FALSE)

tides <- read.csv("\\\\psf/Home/Dropbox (Personal)/MysticDB/Rcode/Sandbox/Andy/Climate/Boston_meantrend.csv", strip.white=TRUE)

tides$Month_f <- factor(tides$Month, levels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"))

#Monthly averages by year, with line of best fit
g <- ggplot(tides, aes(Year, Monthly_MSL , ymin=0)) +
  geom_smooth(method = 'lm', col = "red", formula = y~x)

#g + geom_line() + geom_area() + facet_grid(parameter~Station, scales = "free_y") 
g + geom_line() + geom_point() + facet_wrap( ~ Month_f) + theme_bw()

Mean sea level, by month, 1970-2017

setwd("\\\\psf/Home/Dropbox (Personal)/")

# Assemble data into one dataframe
options(stringsAsFactors=FALSE)

tides_recent <- read.csv("\\\\psf/Home/Dropbox (Personal)/MysticDB/Rcode/Sandbox/Andy/Climate/Boston_meantrend.csv", strip.white=TRUE)%>%
  filter(Year > 1969)

tides_recent$Month_f <- factor(tides_recent$Month, levels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"))

# Monthly averages by month, with line of best fit
g <- ggplot(tides_recent, aes(Year, Monthly_MSL , ymin=0)) +
  geom_smooth(method = 'lm', col = "red", formula = y~x)

g + geom_line() + geom_point() + facet_wrap( ~ Month_f) 

## Variability by month

# load monthly data with linear trend removed
intannvar <- read.csv("\\\\psf/Home/Dropbox (Personal)/MysticDB/Rcode/Sandbox/Andy/Climate/Boston_intannvar.csv", strip.white=TRUE)

g <- ggplot(data = intannvar, aes(factor(Month), Interannual_Variation), group_by = Month)
g + geom_boxplot()  + theme_bw()

Monthly Max Tides

# load monthly data with linear trend removed
minmax<- read.csv("\\\\psf/Home/Dropbox (Personal)/MysticDB/Rcode/Sandbox/Andy/Climate/BosHarMinMax.csv", strip.white=TRUE)

minmax$Max.Date <- ymd(minmax$Max.Date)
minmax$Min.Date <- ymd(minmax$Min.Date)

tides <- read.csv("/MysticDB/Rcode/Sandbox/Andy/Climate/Boston_meantrend.csv", strip.white=TRUE)

tides$Date <- mdy(tides$Date)
tides$Monthly_MSLft <- (tides$Monthly_MSL*3.28 + 8.73)


g <- ggplot(minmax, aes(Max.Date, Max.WL, ymin=0)) +
  geom_smooth(method = 'lm', col = "red", formula = y~x)

#g + geom_line() + geom_area() + facet_grid(parameter~Station, scales = "free_y") 
g + geom_line()  + geom_line(data = tides, aes(x= Date, y= Monthly_MSLft)) +
  geom_line(data=minmax, aes(Min.Date, Min.WL))

setwd("\\\\psf/Home/Dropbox (Personal)/")

minmax$high <- (ifelse(minmax$Max.WL >16, 1, 0))

# Monthly averages by month, with line of best fit
g <- ggplot(minmax, aes(Max.Date, Max.WL, color=high))
  #geom_smooth(method = 'lm', col = "red", formula = y~x)

g  + geom_point() + facet_wrap( ~ factor(Month))