---
title: "NDBC"
output: html_document
---


# [National Data Buoy Center](https://www.ndbc.noaa.gov/)

To read [NDBC](https://www.ndbc.noaa.gov/) data we suggest that you use the [rnoaa](https://docs.ropensci.org/rnoaa/) package from [rOpenSci](https://ropensci.org/).

### Requirements

You only need the [rnoaa](https://docs.ropensci.org/rnoaa/) package to get data, but we include helper packages, `dplyr` and `ggplot2`, for the purpose of this tutorial. 

```{r}
suppressPackageStartupMessages({
  required <- c("dplyr", "ggplot2", "rnoaa")
  installed <- installed.packages() |>
    dplyr::as_tibble() 
  needed <- !(required %in% installed$Package)
  if (any(needed)){
    install.packages(required[needed])
  }
  ok <- sapply(required, library, character.only = TRUE)
})
```

## Generate a list of buoys, and, as an example, narrow the list to Gulf of Maine.

```{r}
bb <- c(xmin = -72, xmax = -63, ymin = 39, ymax = 46)
buoys <- buoy_stations() |>
  filter(between(lat, bb['ymin'], bb['ymax']),
         between(lon, bb['xmin'], bb['xmax']))

glimpse(buoys)
```

## We select one buoy, Cutler Farris Wharf, in Maine and filter the listing down to just that one record (row).
 
```{r}
CFW_id <- buoys |>
filter(grepl("Cutler Farris Wharf", description, fixed = TRUE))

glimpse(CFW_id)
```

## Now we can pull buoy data, but only one dataset, such as standard meteorology, for a single year at a time may be requested. The function yields a list of two elements... 

 + `meta` a list variable descriptions
 
 + `data` a data frame (tibble) with reported data 

```{r, message = FALSE}
stdmet <- buoy("stdmet", CFW_id$station[1], year = 2021)
names(stdmet)
```


```{r}
glimpse(stdmet$data)
```


With just a little manipulation, we can start viewing the data graphically. First we must convert the timestamp data from character to numeric, specifically a POSIX timestamp (seconds of time since that start of an arbitrary origin, in this case 1970-01-01 00:00:00).

```{r}
stdmet$data <- mutate(stdmet$data, time = as.POSIXct(time, format = "%Y-%m-%dT%H:%M:%SZ"))
```


```{r, warning = FALSE, message = FALSE}
sst_meta <- stdmet$meta$sea_surface_temperature

ggplot(data = stdmet$data, 
       aes(x = time, 
           y = sea_surface_temperature)) +
  geom_point(size = 0.2, alpha = 0.4) + 
  labs(title = sub("National Data Buoy Center - Recent observations from station ", 
                   "",
                   CFW_id$description),
       y = sprintf("%s\n(%s)", sst_meta$longname, sst_meta$units),
       x = "Date") 
```