Package 'jmastats'

Japan Meteorological Agency's earthquake observe stations

Description

This data corresponds to the July 18, 2024 update.

Usage

earthquake_station

Format

A simple feature data frame with 671 rows 7 variables

Examples

head(earthquake_station)

---

Scales to use for ggplot2

Description

Usage

scale_color_jma_absolute(type = "precipitation", ...)

scale_color_jma_relative(type = "amedas", ...)

scale_fill_jma_absolute(type = "precipitation", ...)

scale_fill_jma_relative(type = "amedas", ...)

Arguments

type	Display item
...	Arguments to pass on to ggplot2::scale_color_gradientn or ggplot2::scale_fill_gradientn

Value

A ScaleContinuous object that can be added to a ggplot object

Examples

d <-
data.frame(
  date = as.Date(c(17410, 17411, 17412, 17413, 17414, 17415), origin = "1970-01-01"),
  precipitation_sum = units::set_units(c(3.5, 9.5, 0, 0, 0, 5), "mm"))

library(ggplot2)
library(units)
ggplot(d, aes(date, precipitation_sum,
          color = drop_units(precipitation_sum),
          fill = drop_units(precipitation_sum))) +
  geom_bar(stat = "identity") +
  scale_color_jma_absolute(type = "precipitation") +
  scale_fill_jma_absolute(type = "precipitation")

---

Collect JMA Historical Weather Data

Description

Refer to the data available in the JMA Historical Weather Data Search. Executed by specifying the target location and date. Currently, not all types of data acquisition are supported.

Usage

jma_collect(
  item = NULL,
  block_no,
  year,
  month,
  day,
  cache = TRUE,
  pack = TRUE,
  quiet = FALSE
)

Arguments

item	Type of weather data to be acquired. Mainly specifies the interval between records (e.g. daily or hourly). See NOTE for details.
block_no	Block number of the location to be observed. It is assumed that block_no is input as a string consisting of a 4- or 5-digit number. If a numeric value is specified, it is processed as a string.
year	select year
month	select month
day	select date (default NULL)
cache	use cash and save to cache. (TRUE, the default)
pack	Whether to packing common variables or not. (TRUE, the default)
quiet	Whether to output information on variable and row combinations that were treated as missing values for some reason. (TRUE, the default)

Value

a tbl object

Note

The parameter item chooses one from these:

• annually: Annual value. Please specify a location by block_no.

• monthly: Monthly value. Please specify location and year.

• 3monthly: Value every 3 months. Please specify location and year.

• 10daily: Seasonal value. Please specify location and year.

• mb5daily: Semi-seasonal value. Please specify location and year.

• daily: Daily value. Please specify location, year and month.

• hourly: Hourly value. Please specify location, year, month and day.

• rank: Values of the largest in the history of observations.

• nml_ym: Climatological normals for each year and month.

• nml_3m: Climatological normals for each 3 months.

• nml_10d: Climatological normals for each season (almost 10 days).

• nml_mb5d: Climatological normals for each semi-season (almost 5 days).

• nml_daily: Daily climatological normals for specific month. for each location.

Examples

# Annually
jma_collect(item = "annually", "1284", year = 2017, month = 11, cache = FALSE)
# Daily
jma_collect(item = "daily", block_no = "0010", year = 2017, month = 11, cache = FALSE)
jma_collect(item = "daily", "0422", year = 2017, month = 11, cache = FALSE)
# Hourly
jma_collect("hourly", "0010", 2018, 7, 30, cache = FALSE)
# Historical Ranking
jma_collect("rank", block_no = "47646", year = 2020, cache = FALSE)
# Climatological normals
jma_collect("nml_ym", block_no = "47646", cache = FALSE, pack = FALSE)
jma_collect("nml_3m", "47646", cache = FALSE, pack = FALSE, quiet = TRUE)
jma_collect("nml_10d", "0228", cache = FALSE, pack = FALSE, quiet = TRUE)
jma_collect("nml_mb5d", "0228", cache = FALSE, pack = FALSE, quiet = FALSE)

---

Find out neighborhood stations

Description

Return the nearest stations information to the given coordinates.

Usage

nearest_station(longitude, latitude, geometry = NULL)

pick_neighbor_stations(
  longitude,
  latitude,
  distance = 1,
  .unit = "m",
  geometry = NULL
)

pick_neighbor_tide_stations(
  year,
  longitude,
  latitude,
  distance = 100,
  .unit = "km",
  geometry = NULL
)

Arguments

longitude	Longitude.
latitude	Latitude.
geometry	XY sf::sf object.
distance	Distance from station to station to adjustment.
.unit	Unit used for extraction from the point of interest. Default m (meters). This value is passed to units::as_units.
year	For tide level data. Restricted to the observation points in the target year.

Details

• nearest_station(): Return single station data.

• pick_neighbor_stations(): Pick-up neighbourhood stations.

• pick_neighbor_tide_stations(): Pick-up neighbourhood tidal observation stations. Filter by distance from target point.

Value

an object of class sf.

Examples

nearest_station(142.9313, 43.70417)

pick_neighbor_stations(140.10, 36.08, 300000)

d <-
  pick_neighbor_stations(140.10, 36.08, 30, "km")
pick_neighbor_stations(geometry = sf::st_point(c(140.1833, 36.23333)),
                       distance = 100)

pick_neighbor_tide_stations(longitude = 133.4375, latitude = 34.45833,
                            year = 2020,
                            distance = 100, .unit = "km")

---

Parse data variable units

Description

Usage

parse_unit(data, rename = TRUE)

Arguments

data	data
rename	logical

Value

a tbl object

Examples

# For data retrieved with jma_collect(), here is a minimal example.
d <-
tibble::tibble(date = as.Date(c(17742, 17742, 17742, 17742, 17742, 17742), origin = "1970-01-01"),
               time = c(1, 2, 3, 4, 5, 6),
               `precipitation(mm)` = c(0, 0, 0, 0, 0, 0),
               `temperature(℃)` = c(22.4, 22.1, 21, 20.2, 20.4, 23.5))
d |> parse_unit(rename = TRUE)

---

Convert and split tidal level data

Description

Usage

pivot_tide_level(data)

Arguments

data	tidal level data

Value

List to store two datasets containing hourly and tide level data.

See Also

read_tide_level()

Examples

read_tide_level(system.file("dummy/tide.txt", package = "jmastats")) |>
  pivot_tide_level()

---

Read the csv of the earthquake database

Description

Usage

read_eqdb_csv(path, show_metadata = TRUE)

Arguments

path	local file path to earthquake record file.
show_metadata	logical. If FALSE, returns only the values observed at each location.

Value

a tbl object

See Also

https://www.data.jma.go.jp/svd/eqdb/data/shindo/index.html

Examples

read_eqdb_csv(system.file("dummy/eqdb.csv", package = "jmastats"))

---

Read the past weather

Description

Read the past weather data files downloaded from JMA.

Usage

read_jma_weather(path)

Arguments

path	The path to the downloaded file.

Value

a tbl object

See Also

https://www.data.jma.go.jp/gmd/risk/obsdl/index.php, https://www.data.jma.go.jp/gmd/risk/obsdl/top/help3.html

Examples

read_jma_weather(system.file("dummy/dl_data.csv", package = "jmastats"))

---

Read Kishou Disaster Prevention Information Feed

Description

Usage

read_kishou_feed(frequency, type)

Arguments

frequency	Release frequency. Select either high frequency ("high") or long term ("low")
type	Feed type. Specify the item to be retrieved as a string. See details for the items.

Details

The following items can be specified in the type argument.

• regular: It will be announced on time.

• extra: It will be announced at any time.

• eqvol: Earthquakes and Volcanoes.

• other: Other informations.

Value

a tbl object

See Also

https://xml.kishou.go.jp

Examples

read_kishou_feed("high", type = "regular")
read_kishou_feed("low", "other")

---

Read RSMC Tokyo-Typhoon Center's best track data

Description

Tidy formatting best track data and combine each point to line.

Usage

read_rsmc_besttrack(path)

track_combine(
  data,
  group_vars = c("international_number", "storm_name"),
  keep_vars = NULL,
  geometry = geometry
)

Arguments

path	path to best track data (.txt). Give the path as a directory in the user's computer or the URL.
data	Import data using read_rsmc_besttrack
group_vars	To combine track variables.
keep_vars	Keep variables.
geometry	geometry column name (default geometry).

Details

• read_rsmc_besttrack(): Read single best track data into sf contains observation record as point.

• track_combine(): Combine track data to line by id (such as international_number and storm_name).

Value

a tbl object

See Also

https://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/RSMC_HP.htm

Examples

read_rsmc_besttrack(path = system.file("dummy/bst.txt", package = "jmastats"))

read_rsmc_besttrack(path = system.file("dummy/bst.txt", package = "jmastats")) |>
  track_combine()

---

Read and parse tide level text data

Description

Usage

read_tide_level(path = NULL, .year, .month, .stn, raw = FALSE)

Arguments

path	URL or local file path to sea tide level file
.year	A.D. 1997 to present year.
.month	Month number. 1997 only, valid after March.
.stn	Station identification name in uppercase two-digit letters.
raw	If TRUE, return raw format data

Value

a tbl object

See Also

https://www.data.jma.go.jp/gmd/kaiyou/db/tide/suisan/readme.html

Examples

# Read a local storage file (dummy data)
read_tide_level(system.file("dummy/tide.txt", package = "jmastats"))

# Request from URL
read_tide_level("https://www.data.jma.go.jp/gmd/kaiyou/data/db/tide/suisan/txt/2020/TK.txt")
# Request from parameters
read_tide_level(.year = 2020, .month = 2, .stn = "TK")

---

Remove all cache files

Description

Remove all package cache files.

Usage

reset_cache()

Value

None

Examples

if (interactive())
  reset_cache()

---

Japan Meteorological Agency's Stations list

Description

This data corresponds to the April 1, 2024 update.

Usage

stations

Format

A data frame with 1323 rows 14 variables:

• area

• station_no

• station_type

• station_name

• address

• elevation

• observation_begin

• note1

• note1

• note2

• katakana

• prec_no

• block_no

• pref_code

• geometry

Examples

head(stations)
dim(stations)

---

Tidal observation stations of Japan Meteorological Agency

Description

Observation stations from 1997 to 2024. This data corresponds to the January 1, 2024 update.

Usage

tide_station

Format

A data frame with 1949 rows 7 variables

Examples

head(tide_station)

---