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Installation

Install the package from r-universe as follows. The source code is available on GitHub.

# Install slrcsap in R:
install.packages('slrcsap', repos = c('https://tbep-tech.r-universe.dev', 'https://cloud.r-project.org'))

Load the package in an R session after installation:

library(slrcsap)

Usage

The package includes two core workflows to download and plot data relevant to assess sea level rise risks in the Tampa Bay region. The first workflow retrieves and plots historical sea level data and the second retrieves and plots sea level rise scenario data. Default arguments for all functions are set for the tidal gauge at St. Petersburg, FL. The content below demonstrates how to use the functions in this package for each workflow.

Sea level Data

Sea level data are downloaded from the NOAA Tides and Currents website. The data are available for all NOAA tide gauges and is setup to download data for the St. Petersburg, FL gauge (NOAA ID 8726520) by default. The data is read directly into R from the URL https://tidesandcurrents.noaa.gov/sltrends/data/8726520_meantrend.txt. The data for St. Petersburg, includes monthly mean sea level (MSL) values from 1947 to the present, including a seasonal correction.

# Download sea level data for St. Petersburg
spsealevel <- get_sealevel()
head(spsealevel)
#>     gauge Year Month       date  msl_m     msl_ft
#> 1 8726520 1947     1 1947-01-01 -0.063 -0.2066929
#> 2 8726520 1947     2 1947-02-01 -0.132 -0.4330709
#> 3 8726520 1947     3 1947-03-01 -0.142 -0.4658793
#> 4 8726520 1947     4 1947-04-01 -0.150 -0.4921260
#> 5 8726520 1947     5 1947-05-01 -0.086 -0.2821522
#> 6 8726520 1947     6 1947-06-01 -0.064 -0.2099738

Data for alternative stations can be obtained using the gauge argument.

# Download sea level data for Cedar Key
cksealevel <- get_sealevel(gauge = 8727520)
head(cksealevel)
#>     gauge Year Month       date  msl_m     msl_ft
#> 1 8727520 1914     4 1914-04-01 -0.170 -0.5577428
#> 2 8727520 1914     5 1914-05-01 -0.161 -0.5282152
#> 3 8727520 1914     6 1914-06-01 -0.142 -0.4658793
#> 4 8727520 1914     7 1914-07-01 -0.129 -0.4232284
#> 5 8727520 1914     8 1914-08-01 -0.098 -0.3215223
#> 6 8727520 1914     9 1914-09-01 -0.186 -0.6102362

The sea level data can be plotted using the plot_sealevel() function.

# Plot sea level data for St. Petersburg
plot_sealevel(spsealevel)


# Plot sea level data for Cedar Key
plot_sealevel(cksealevel)

Various arguments for plot_sealevel() can change the appearance of the plot. Below, the color, units, and x-axis range are modified

# Change arguments for the plot
plot_sealevel(spsealevel, col = 'tomato1', units = 'm', 
              xrng = as.Date(c('2000-01-01', '2023-01-01')))

The plot is also a ggplot() object and can be modified with additional ggplot2 functions. Below, the plot is modified to add a title and change the theme.

# Add a title and change the theme
library(ggplot2)
plot_sealevel(spsealevel) +
  ggtitle('Monthly Mean Sea Level (MSL) at St. Petersburg, FL') +
  theme_grey()

Sea Level Rise Scenarios

Sea level rise scenarios can be downloaded using the get_scenario() function. Data are downloaded from the Interagency Sea Level Rise Scenario Tool website that uses regionally corrected NOAA 2022 curves. Details of the methods used in this tool are found in the technical report [1]. The data are downloaded as an Excel sheet to from the URL https://sealevel.nasa.gov/task-force-scenario-tool?psmsl_id=520, set to St. Petersburg, FL by default. Emissions scenarios of NOAA Intermediate Low, Intermediate, and Intermediate High are downloaded by default, as recommended by the Climate Science Advisory Panel. The data show relative sea level change (RSLC) from 2020 to 2150 for each scenario in meters and feet.

# Download sea level rise scenarios for St. Petersburg
spscenario <- get_scenario()
head(spscenario)
#> # A tibble: 6 × 5
#>      id scenario               year slr_m slr_ft
#>   <dbl> <fct>                 <dbl> <dbl>  <dbl>
#> 1   520 NOAA Intermediate Low  2020 0.113  0.372
#> 2   520 NOAA Intermediate Low  2030 0.180  0.592
#> 3   520 NOAA Intermediate Low  2040 0.250  0.821
#> 4   520 NOAA Intermediate Low  2050 0.322  1.06 
#> 5   520 NOAA Intermediate Low  2060 0.392  1.29 
#> 6   520 NOAA Intermediate Low  2070 0.463  1.52

Data for alternative locations and scenarios can be obtained using the id and scenario arguments, respectively.

# Download sea level rise scenarios for Cedar Key
ckscenario <- get_scenario(id = 428, scenario = c('Low', 'IntLow', 'Int', 'IntHigh', 'High'))
head(ckscenario)
#> # A tibble: 6 × 5
#>      id scenario  year slr_m slr_ft
#>   <dbl> <fct>    <dbl> <dbl>  <dbl>
#> 1   428 NOAA Low  2020 0.101  0.332
#> 2   428 NOAA Low  2030 0.153  0.502
#> 3   428 NOAA Low  2040 0.207  0.679
#> 4   428 NOAA Low  2050 0.258  0.847
#> 5   428 NOAA Low  2060 0.301  0.988
#> 6   428 NOAA Low  2070 0.340  1.12

The sea level rise scenarios can be plotted using the plot_scenario() function. Note the default x-axis range that extends only to 2100.

# Plot sea level rise scenarios for St. Petersburg
plot_scenario(spscenario)


# Plot sea level rise scenarios for Cedar Key
plot_scenario(ckscenario)

Various arguments for plot_scenario() can change the appearance of the plot. Below, the color ramp, units, and x-axis range are modified

# Change arguments for the plot
plot_scenario(spscenario, cols = c('green', 'blue', 'red'), units = 'm', 
              xrng = c(2020, 2150))

The plot is also a ggplot() object and can be modified with additional ggplot2 functions. Below, the plot is modified to add a title, subtitle, and change the theme.

# Add a title, subtitle and change the theme
plot_scenario(spscenario) +
  labs(
    title = 'Relative Sea Level Change Predictions',
    subtitle = 'Gauge 8726520, St. Petersburg, FL'
  ) +
  theme_grey() + 
  theme(legend.position = 'bottom')

References

[1]
W.V. Sweet, B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, C. Zuzak, Global and regional sea level rise scenarios for the United States: Updated mean projections and extreme water level probabilities along U.S. coastlines, National Oceanic; Atmospheric Administration, National Ocean Service, Silver Spring, MD, 2022. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf.