--- title: "weatherOz for BOM" author: "Jonathan Carroll, Dean Marchiori, Paul Melloy, Mark Padgham, Hugh Parsonage, Keith Pembleton and Adam H. Sparks" output: rmarkdown::html_vignette: toc: true vignette: > %\VignetteIndexEntry{weatherOz for BOM} %\VignetteEngine{knitr::rmarkdown_notangle} %\VignetteEncoding{UTF-8} --- # Using {weatherOz} With BOM Data Several functions are provided by {weatherOz} to retrieve Australian Bureau of Meteorology (BOM) data. A family of functions retrieve data files from BOM or parse local files from BOM and return data frames; * `get_precis_forecast()` and `parse_precis_forecast()`, which return the précis (short) forecast; * `get_ag_bulletin()` and `parse_ag_bulletin()`, which return the agriculture bulletin; * `get_coastal_forecast()` and `parse_coastal_forecast()`, which return coastal waters forecasts for each state. ## Using get_precis_forecast() This function only takes one argument, `state`. The `state` parameter allows the user to select the forecast for just one state or a national forecast. States or territories are specified using the official postal codes or full name with fuzzy matching performed via `agrep()`. - **ACT** - Australian Capital Territory - **NSW** - New South Wales - **NT** - Northern Territory - **QLD** - Queensland - **SA** - South Australia - **TAS** - Tasmania - **VIC** - Victoria - **WA** - Western Australia - **AUS** - Australia, returns national forecast including all states, NT and ACT. ### Results The function, `get_precis_forecast()`, will return a data frame of the weather forecast for the daily forecast for selected towns. See Appendix 1 for a full description of the fields and values. ### Example 1: Getting a Forecast Following is an example fetching the forecast for Queensland. ``` r library(weatherOz) (QLD_forecast <- get_precis_forecast(state = "QLD")) #> ----------- Australian Bureau of Meteorology (BOM) Precis Forecast. - #> The HTML version of Short Form (Precis) Forecast for #> QLD can be found at: #> #> Please note information at the page #> . #> -------------------------------------------------------------------------------- #> index product_id state town aac lat lon elev start_time_local end_time_local #> #> 1: 0 IDQ11295 QLD Brisbane QLD_PT001 -27.48080 153.0389 8.1 2024-10-21 09:22:36 2024-10-22 #> 2: 1 IDQ11295 QLD Brisbane QLD_PT001 -27.48080 153.0389 8.1 2024-10-22 00:00:00 2024-10-23 #> 3: 2 IDQ11295 QLD Brisbane QLD_PT001 -27.48080 153.0389 8.1 2024-10-23 00:00:00 2024-10-24 #> 4: 3 IDQ11295 QLD Brisbane QLD_PT001 -27.48080 153.0389 8.1 2024-10-24 00:00:00 2024-10-25 #> 5: 4 IDQ11295 QLD Brisbane QLD_PT001 -27.48080 153.0389 8.1 2024-10-25 00:00:00 2024-10-26 #> --- #> 787: 2 IDQ11295 QLD Port Douglas QLD_PT254 -16.48681 145.4635 70.4 2024-10-23 00:00:00 2024-10-24 #> 788: 3 IDQ11295 QLD Port Douglas QLD_PT254 -16.48681 145.4635 70.4 2024-10-24 00:00:00 2024-10-25 #> 789: 4 IDQ11295 QLD Port Douglas QLD_PT254 -16.48681 145.4635 70.4 2024-10-25 00:00:00 2024-10-26 #> 790: 5 IDQ11295 QLD Port Douglas QLD_PT254 -16.48681 145.4635 70.4 2024-10-26 00:00:00 2024-10-27 #> 791: 6 IDQ11295 QLD Port Douglas QLD_PT254 -16.48681 145.4635 70.4 2024-10-27 00:00:00 2024-10-28 #> utc_offset start_time_utc end_time_utc minimum_temperature maximum_temperature #> #> 1: 10:00 2024-10-20 23:22:36 2024-10-21 14:00:00 NA 28 #> 2: 10:00 2024-10-21 14:00:00 2024-10-22 14:00:00 17 28 #> 3: 10:00 2024-10-22 14:00:00 2024-10-23 14:00:00 17 28 #> 4: 10:00 2024-10-23 14:00:00 2024-10-24 14:00:00 19 32 #> 5: 10:00 2024-10-24 14:00:00 2024-10-25 14:00:00 20 29 #> --- #> 787: 10:00 2024-10-22 14:00:00 2024-10-23 14:00:00 23 32 #> 788: 10:00 2024-10-23 14:00:00 2024-10-24 14:00:00 22 33 #> 789: 10:00 2024-10-24 14:00:00 2024-10-25 14:00:00 22 34 #> 790: 10:00 2024-10-25 14:00:00 2024-10-26 14:00:00 23 32 #> 791: 10:00 2024-10-26 14:00:00 2024-10-27 14:00:00 23 31 #> lower_precipitation_limit upper_precipitation_limit precis probability_of_precipitation #> #> 1: NA NA Partly cloudy. 20 #> 2: NA NA Partly cloudy. 20 #> 3: NA NA Partly cloudy. 20 #> 4: NA NA Partly cloudy. 20 #> 5: 0 1 Mostly sunny. 30 #> --- #> 787: 0 1 Partly cloudy. 30 #> 788: NA NA Mostly sunny. 5 #> 789: NA NA Sunny. 10 #> 790: 0 1 Possible shower. 40 #> 791: 0 5 Shower or two. 50 ``` ## Using get_ag_bulletin() `get_ag_bulletin()` only takes one argument, `state`. The `state` parameter allows the user to select the bulletin for just one state or a national forecast. States or territories are specified using the official postal codes or full name with fuzzy matching performed via `agrep()`. - **NSW** - New South Wales - **NT** - Northern Territory - **QLD** - Queensland - **SA** - South Australia - **TAS** - Tasmania - **VIC** - Victoria - **WA** - Western Australia - **AUS** - Australia, returns bulletin for all states and NT. ### Results The function, `get_ag_bulletin()`, will return a data frame of the agriculture bulletin for selected stations. See Appendix 3 for a full list and description of the fields and values. ### Example 2: Getting an Ag Bulletin Following is an example fetching the ag bulletin for Western Australia. ``` r library(weatherOz) (WA_bulletin <- get_ag_bulletin(state = "WA")) #> ----------- Australian Bureau of Meteorology (BOM) Ag Bulletin. ----------- #> Please note information at the foot of #> , #> the HTML version of Agricultural Observations Bulletin for #> WA. Also see #> . #> ---------------------------------------------------------------------------- #> product_id state station site obs_time_local obs_time_utc time_zone r tn tx #> #> 1: IDW65176 WA Beverley 10515 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 5.2 26.8 #> 2: IDW65176 WA Brookton 10524 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 4.0 25.4 #> 3: IDW65176 WA Broome 03003 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 25.8 32.2 #> 4: IDW65176 WA Carnarvon 06011 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 17.7 25.1 #> 5: IDW65176 WA Corrigin 10536 2024-10-21 09:00:00 2024-10-21 01:00:00 WST NA 5.0 29.0 #> --- #> 30: IDW65176 WA Salmon Gums RS 12071 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 10.9 37.9 #> 31: IDW65176 WA Wagin 10647 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 2.2 5.1 24.0 #> 32: IDW65176 WA Wandering 10917 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 2.0 4.4 23.1 #> 33: IDW65176 WA Wongan Hills RS 08137 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.8 10.0 26.5 #> 34: IDW65176 WA York 10311 2024-10-21 09:00:00 2024-10-21 01:00:00 WST 0.0 4.8 26.0 #> twd ev tg sn solr t5 t10 t20 t50 t1m wr #> #> 1: 3.4 NA NA NA 15.7 NA NA NA NA NA NA #> 2: 4.8 NA NA NA 15.7 NA NA NA NA NA NA #> 3: 4.4 NA NA NA 27.8 NA NA NA NA NA NA #> 4: 5.3 NA NA NA 23.4 NA NA NA NA NA NA #> 5: 2.0 NA NA NA 16.9 NA NA NA NA NA NA #> --- #> 30: NA NA NA NA 21.6 NA NA NA NA NA NA #> 31: 4.2 NA 4.6 NA 14.4 NA NA NA NA NA NA #> 32: NA NA NA NA 14.3 NA NA NA NA NA NA #> 33: 2.7 NA 8.6 NA 20.2 NA NA NA NA NA NA #> 34: 4.0 NA NA NA 15.2 NA NA NA NA NA NA ``` ## Using get_coastal_forecast() This function only takes one argument, `state`. The `state` parameter allows the user to select the forecast for just one state or a national forecast. States or territories are specified using the official postal codes or full name with fuzzy matching performed via `agrep()` - **ACT** - Australian Capital Territory - **NSW** - New South Wales - **NT** - Northern Territory - **QLD** - Queensland - **SA** - South Australia - **TAS** - Tasmania - **VIC** - Victoria - **WA** - Western Australia - **AUS** - Australia, returns national forecast including all states, NT and ACT. ### Results The function, `get_coastal_forecast()`, will return a data frame of the coastal waters forecast for marine zones in each state. See Appendix 6 for a full description of the fields and values. ### Example 3: Getting a Coastal Forecast Following is an example fetching the forecast for Queensland. ``` r library(weatherOz) (QLD_coastal_forecast <- get_coastal_forecast(state = "QLD")) #> ------- Australian Bureau of Meteorology (BOM) Coastal Waters Forecast. ------- #> Please note information at the foot of #> , #> the HTML version of Coastal Waters Forecast for #> QLD. #> Also see #> . #> -------------------------------------------------------------------------------- #> index product_id type state_code dist_name pt_1_name #> #> 1: IDQ11290 QLD Queensland #> 2: IDQ11290 QLD Queensland Gulf of Carpentaria #> 3: IDQ11290 QLD North Queensland #> 4: IDQ11290 QLD South Queensland #> 5: 0 IDQ11290 QLD South East Gulf of Carpentaria: QLD-NT Border to Cape Keerweer #> --- #> 45: 1 IDQ11290 QLD Gold Coast Waters: Cape Moreton to Point Danger #> 46: 2 IDQ11290 QLD Gold Coast Waters: Cape Moreton to Point Danger #> 47: 0 IDQ11290 QLD Great Barrier Reef Offshore Waters #> 48: 1 IDQ11290 QLD Great Barrier Reef Offshore Waters #> 49: 2 IDQ11290 QLD Great Barrier Reef Offshore Waters #> pt_2_name aac start_time_local end_time_local utc_offset start_time_utc #> #> 1: QLD_FA001 2024-10-21 10:30:10 2024-10-21 10:30:10 10:00 2024-10-21 10:30:10 #> 2: QLD_FA002 2024-10-21 05:00:00 2024-10-21 05:00:00 10:00 2024-10-21 05:00:00 #> 3: QLD_FA003 2024-10-21 05:00:00 2024-10-21 05:00:00 10:00 2024-10-21 05:00:00 #> 4: QLD_FA004 2024-10-21 05:00:00 2024-10-21 05:00:00 10:00 2024-10-21 05:00:00 #> 5: QLD_MW001 2024-10-21 09:22:24 2024-10-21 09:22:24 10:00 2024-10-21 09:22:24 #> --- #> 45: QLD_MW014 2024-10-22 00:00:00 2024-10-22 00:00:00 10:00 2024-10-22 00:00:00 #> 46: QLD_MW014 2024-10-23 00:00:00 2024-10-23 00:00:00 10:00 2024-10-23 00:00:00 #> 47: QLD_MW015 2024-10-21 05:00:00 2024-10-21 05:00:00 10:00 2024-10-21 05:00:00 #> 48: QLD_MW015 2024-10-22 00:00:00 2024-10-22 00:00:00 10:00 2024-10-22 00:00:00 #> 49: QLD_MW015 2024-10-23 00:00:00 2024-10-23 00:00:00 10:00 2024-10-23 00:00:00 #> end_time_utc forecast_seas #> #> 1: 2024-10-21 10:30:10 #> 2: 2024-10-21 05:00:00 #> 3: 2024-10-21 05:00:00 #> 4: 2024-10-21 05:00:00 #> 5: 2024-10-21 09:22:24 Around 1 metre, increasing to 1 to 1.5 metres south of Kowanyama during the afternoon. #> --- #> 45: 2024-10-22 00:00:00 1 to 2 metres, decreasing to 1 to 1.5 metres around midday. #> 46: 2024-10-23 00:00:00 Below 1 metre. #> 47: 2024-10-21 05:00:00 Below 1 metre. #> 48: 2024-10-22 00:00:00 Below 1 metre. #> 49: 2024-10-23 00:00:00 Below 1 metre. #> forecast_weather #> #> 1: #> 2: #> 3: #> 4: #> 5: Mostly sunny. The chance of a thunderstorm in the morning and afternoon. #> --- #> 45: Mostly sunny. #> 46: Mostly sunny. #> 47: Mostly sunny. #> 48: Mostly sunny. #> 49: Sunny. #> forecast_winds #> #> 1: #> 2: #> 3: #> 4: #> 5: Northwest to northeasterly 15 to 20 knots becoming variable about 10 knots in the late evening. #> --- #> 45: Southerly 15 to 20 knots, reaching up to 25 knots offshore south of Point Lookout during the morning. #> 46: South to southwesterly 10 to 15 knots becoming variable about 10 knots during the morning then becoming north to northeasterly 10 to 15 knots during the afternoon. #> 47: Southeasterly 10 to 15 knots turning easterly in the evening. #> 48: Easterly 10 to 15 knots turning northeasterly in the evening. #> 49: North to northeasterly 10 to 15 knots. #> forecast_swell1 #> #> 1: #> 2: #> 3: #> 4: #> 5: Below 0.5 metres. #> --- #> 45: Southerly 2 to 3 metres, decreasing to 1.5 to 2 metres by early evening. #> 46: Southerly 1 to 2 metres, decreasing to around 1 metre during the afternoon. #> 47: Easterly around 1 metre. #> 48: Southeasterly below 1 metre, increasing to around 1 metre through the Capricorn Channel. #> 49: Southeasterly below 1 metre. #> forecast_swell2 forecast_caution marine_forecast tropical_system_location forecast_waves #> #> 1: NA NA #> 2: NA NA #> 3: NA NA #> 4: NA NA #> 5: NA NA #> --- #> 45: Easterly around 1 metre. NA NA #> 46: Easterly around 1 metre. NA NA #> 47: NA NA #> 48: Easterly around 1 metre. NA NA #> 49: NA NA ``` ## Working with BOM Image Files A second family of functions retrieve information pertaining to satellite and radar imagery. * `get_available_imagery()`, which returns available satellite imagery; * `get_satelllite_imagery()` which returns a [terra::SpatRaster] or [stars] object as requested; * `get_available_radar()`, which returns available radar images; and * `get_radar_imagery()` which returns radar images as a [magick] object. ### Using {weatherOz} to retrieve BOM satellite imagery {weatherOz} provides functionality to retrieve high-definition GeoTIFF satellite imagery provided by BOM through public FTP with the following types of imagery being available: i.) [Infrared images](http://www.bom.gov.au/australia/satellite/about_images.shtml#ir), ii.) [Visible images](http://www.bom.gov.au/australia/satellite/about_images.shtml#vis) and iii.) [Clouds/surface composite](http://www.bom.gov.au/australia/satellite/about_images.shtml#cloud). #### Working with Satellite Imagery Valid BOM satellite Product IDs for GeoTIFF files include:
Product IDDescriptionTypeDelete time
IDE00420AHI cloud cover only 2km FD GEOS Satellite24
IDE00421AHI IR (Ch13) greyscale 2km FD GEOS Satellite24
IDE00422AHI VIS (Ch3) greyscale 2km FD GEOS Satellite24
IDE00423AHI IR (Ch13) Zehr 2km FD GEOS Satellite24
IDE00425AHI VIS (true colour) / IR (Ch13 greyscale) composite 1km FD GEOS Satellite24
IDE00426AHI VIS (true colour) / IR (Ch13 greyscale) composite 2km FD GEOS Satellite24
IDE00427AHI WV (Ch8) 2km FD GEOS Satellite24
IDE00430AHI cloud cover only 2km AUS equirect.Satellite24
IDE00431AHI IR (Ch13) greyscale 2km AUS equirect.Satellite24
IDE00432AHI VIS (Ch3) greyscale 2km AUS equirect.Satellite24
IDE00433AHI IR (Ch13) Zehr 2km AUS equirect.Satellite24
IDE00435AHI VIS (true colour) / IR (Ch13 greyscale) composite 1km AUS equirect. Satellite24
IDE00436AHI VIS (true colour) / IR (Ch13 greyscale) composite 2km AUS equirect. Satellite24
IDE00437AHI WV (Ch8) 2km AUS equirect.Satellite24
IDE00439AHI VIS (Ch3) greyscale 0.5km AUS equirect.Satellite24
Information gathered from Australian Bureau of Meteorology (BOM)
#### Using get_available_imagery() `get_available_imagery()` only takes one argument, `product_id`, a BOM identifier for the imagery that you wish to check for available imagery. Using this function will fetch a listing of BOM GeoTIFF satellite imagery from [ftp://ftp.bom.gov.au/anon/gen/gms/](ftp://ftp.bom.gov.au/anon/gen/gms/) to display which files are currently available for download. These files are available at ten minute update frequency with a 24 hour delete time. This function can be used see the most recent files available and then specify in the `_imagery()` function. If no valid Product ID is supplied, defaults to all GeoTIFF images currently available. #### Example 4: Checking Available Imagery ``` r library(weatherOz) (avail <- get_available_imagery(product_id = "IDE00425")) #> [1] "IDE00425.202410200210.tif" "IDE00425.202410200220.tif" "IDE00425.202410200230.tif" #> [4] "IDE00425.202410200250.tif" "IDE00425.202410200300.tif" "IDE00425.202410200310.tif" #> [7] "IDE00425.202410200320.tif" "IDE00425.202410200330.tif" "IDE00425.202410200340.tif" #> [10] "IDE00425.202410200350.tif" "IDE00425.202410200400.tif" "IDE00425.202410200410.tif" #> [13] "IDE00425.202410200420.tif" "IDE00425.202410200430.tif" "IDE00425.202410200440.tif" #> [16] "IDE00425.202410200450.tif" "IDE00425.202410200500.tif" "IDE00425.202410200510.tif" #> [19] "IDE00425.202410200520.tif" "IDE00425.202410200530.tif" "IDE00425.202410200540.tif" #> [22] "IDE00425.202410200550.tif" "IDE00425.202410200600.tif" "IDE00425.202410200610.tif" #> [25] "IDE00425.202410200620.tif" "IDE00425.202410200630.tif" "IDE00425.202410200640.tif" #> [28] "IDE00425.202410200650.tif" "IDE00425.202410200700.tif" "IDE00425.202410200710.tif" #> [31] "IDE00425.202410200720.tif" "IDE00425.202410200730.tif" "IDE00425.202410200740.tif" #> [34] "IDE00425.202410200750.tif" "IDE00425.202410200800.tif" "IDE00425.202410200810.tif" #> [37] "IDE00425.202410200820.tif" "IDE00425.202410200830.tif" "IDE00425.202410200840.tif" #> [40] "IDE00425.202410200850.tif" "IDE00425.202410200900.tif" "IDE00425.202410200910.tif" #> [43] "IDE00425.202410200920.tif" "IDE00425.202410200930.tif" "IDE00425.202410200940.tif" #> [46] "IDE00425.202410200950.tif" "IDE00425.202410201000.tif" "IDE00425.202410201010.tif" #> [49] "IDE00425.202410201020.tif" "IDE00425.202410201030.tif" "IDE00425.202410201040.tif" #> [52] "IDE00425.202410201050.tif" "IDE00425.202410201100.tif" "IDE00425.202410201110.tif" #> [55] "IDE00425.202410201120.tif" "IDE00425.202410201130.tif" "IDE00425.202410201140.tif" #> [58] "IDE00425.202410201150.tif" "IDE00425.202410201200.tif" "IDE00425.202410201210.tif" #> [61] "IDE00425.202410201220.tif" "IDE00425.202410201230.tif" "IDE00425.202410201240.tif" #> [64] "IDE00425.202410201250.tif" "IDE00425.202410201300.tif" "IDE00425.202410201310.tif" #> [67] "IDE00425.202410201320.tif" "IDE00425.202410201330.tif" "IDE00425.202410201340.tif" #> [70] "IDE00425.202410201350.tif" "IDE00425.202410201400.tif" "IDE00425.202410201410.tif" #> [73] "IDE00425.202410201420.tif" "IDE00425.202410201430.tif" "IDE00425.202410201450.tif" #> [76] "IDE00425.202410201500.tif" "IDE00425.202410201510.tif" "IDE00425.202410201520.tif" #> [79] "IDE00425.202410201530.tif" "IDE00425.202410201540.tif" "IDE00425.202410201550.tif" #> [82] "IDE00425.202410201600.tif" "IDE00425.202410201610.tif" "IDE00425.202410201620.tif" #> [85] "IDE00425.202410201630.tif" "IDE00425.202410201640.tif" "IDE00425.202410201650.tif" #> [88] "IDE00425.202410201700.tif" "IDE00425.202410201710.tif" "IDE00425.202410201720.tif" #> [91] "IDE00425.202410201730.tif" "IDE00425.202410201740.tif" "IDE00425.202410201750.tif" #> [94] "IDE00425.202410201800.tif" "IDE00425.202410201810.tif" "IDE00425.202410201820.tif" #> [97] "IDE00425.202410201830.tif" "IDE00425.202410201840.tif" "IDE00425.202410201850.tif" #> [100] "IDE00425.202410201900.tif" "IDE00425.202410201910.tif" "IDE00425.202410201920.tif" #> [103] "IDE00425.202410201930.tif" "IDE00425.202410201940.tif" "IDE00425.202410201950.tif" #> [106] "IDE00425.202410202000.tif" "IDE00425.202410202010.tif" "IDE00425.202410202020.tif" #> [109] "IDE00425.202410202030.tif" "IDE00425.202410202040.tif" "IDE00425.202410202050.tif" #> [112] "IDE00425.202410202100.tif" "IDE00425.202410202110.tif" "IDE00425.202410202120.tif" #> [115] "IDE00425.202410202130.tif" "IDE00425.202410202140.tif" "IDE00425.202410202150.tif" #> [118] "IDE00425.202410202200.tif" "IDE00425.202410202210.tif" "IDE00425.202410202220.tif" #> [121] "IDE00425.202410202230.tif" "IDE00425.202410202240.tif" "IDE00425.202410202250.tif" #> [124] "IDE00425.202410202300.tif" "IDE00425.202410202310.tif" "IDE00425.202410202320.tif" #> [127] "IDE00425.202410202330.tif" "IDE00425.202410202340.tif" "IDE00425.202410202350.tif" #> [130] "IDE00425.202410210000.tif" "IDE00425.202410210010.tif" "IDE00425.202410210020.tif" #> [133] "IDE00425.202410210030.tif" "IDE00425.202410210040.tif" "IDE00425.202410210050.tif" #> [136] "IDE00425.202410210100.tif" "IDE00425.202410210110.tif" "IDE00425.202410210120.tif" #> [139] "IDE00425.202410210130.tif" "IDE00425.202410210140.tif" "IDE00425.202410210150.tif" #> [142] "IDE00425.202410210200.tif" "IDE00425.202410210210.tif" "IDE00425.202410210220.tif" #> [145] "IDE00425.202410210230.tif" ``` #### Using get_satellite_imagery() `get_satellite_imagery()` fetches BOM satellite GeoTIFF imagery, returning a SpatRaster object and takes two arguments. Files are available at ten minute update frequency with a 24 hour delete time. It is suggested to check file availability first by using `get_available_imagery()`. The arguments are: * `product_id`, a character value of the BOM product ID to download. Alternatively, a vector of values from `get_available_imagery()` may be used here. This argument is mandatory. * `scans` a numeric value for the number of scans to download, starting with the most recent and progressing backwards, *e.g.*, `1` - the most recent single scan available , `6` - the most recent hour available, `12` - the most recent 2 hours available, etc. Negating will return the oldest files first. Defaults to 1. This argument is optional. #### Example 6: Fetching Satellite Imagery and Viewing It ``` r library(weatherOz) # Specify product ID and scans i <- get_satellite_imagery(product_id = "IDE00425", scans = 1) ``` `terra::plot()` has been re-exported to simplify visualising these files while using {weatherOz}. ``` r plot(i) ``` ### Using {weatherOz} With BOM Radar Imagery {weatherOz} provides functionality to retrieve the latest radar imagery provided by BOM through a public FTP server. These are the latest snapshots for each radar locations at various radar ranges _e.g._, 512km, 256km, 128km and 64km for some stations. #### Using get_available_radar() `get_available_radar()` fetches the available radar imagery from the BOM FTP and returns a data frame for reference. This data frame contains the product_id, which is required when using the `get_radar_imagery()` function. The files available are the latest `.png` files of BOM radar imagery which are typically updated each 6-10 minutes. Only the most recent image is retrieved for each radar location. There are usually several radar ranges available for each radar location, such as 512km, 256km, 128km and possibly 64km. The arguments are: * `radar_id` which is the BOM radar ID number; this defaults to 'all' which will return a data frame of all radar IDs in Australia. #### Example 7: Getting Available Radar Imagery ``` r library(weatherOz) x <- get_available_radar() head(x) #> product_id LocationID range Name Longitude Latitude Radar_id Full_Name IDRnn0name #> #> 1: IDR641 64 512km Adelaide 138.4689 -34.6169 64 Adelaide (Buckland Park) BuckPk #> 2: IDR642 64 256km Adelaide 138.4689 -34.6169 64 Adelaide (Buckland Park) BuckPk #> 3: IDR643 64 128km Adelaide 138.4689 -34.6169 64 Adelaide (Buckland Park) BuckPk #> 4: IDR644 64 64km Adelaide 138.4689 -34.6169 64 Adelaide (Buckland Park) BuckPk #> 5: IDR311 31 512km Albany 117.8163 -34.9418 31 Albany Albany #> 6: IDR312 31 256km Albany 117.8163 -34.9418 31 Albany Albany #> IDRnn1name State Type Group_ Status Archive as.is #> #> 1: BucklandPk SA Doppler Yes Public BuckPk TRUE #> 2: BucklandPk SA Doppler Yes Public BuckPk TRUE #> 3: BucklandPk SA Doppler Yes Public BuckPk TRUE #> 4: BucklandPk SA Doppler Yes Public BuckPk TRUE #> 5: Albany WA Doppler Yes Public Albany TRUE #> 6: Albany WA Doppler Yes Public Albany TRUE ``` #### Using get_radar_imagery() `get_radar_imagery()` fetches the latest BOM radar imagery for a given product ID. The files available are the latest `.png` files of BOM radar imagery, which are typically updated each 6-10 minutes. Only the most recent image is retrieved for each radar location. There are usually several radar ranges available for each radar location, such as 512km, 256km, 128km and possibly 64km. The only argument is: * `product_id` the BOM product_id associated with each radar imagery file. These can be obtained from the `get_available_radar()` function. This value must be specified and the function will accept only one at a time. #### Example 8: Fetching Radar Imagery ``` r library(weatherOz) y <- get_radar_imagery(product_id = "IDR032") plot(y) ``` ## References [Australian Bureau of Meteorology (BOM) Weather Data Services](http://www.bom.gov.au/catalogue/data-feeds.shtml) [Australian Bureau of Meteorology (BOM) FTP Public Products](http://www.bom.gov.au/catalogue/anon-ftp.shtml) [Australian Bureau of Meteorology (BOM) Weather Data Services Agriculture Bulletins](http://www.bom.gov.au/catalogue/observations/about-agricultural.shtml) [Australian Bureau of Meteorology (BOM) Weather Data Services Observation of Rainfall](http://www.bom.gov.au/climate/how/observations/rain-measure.shtml) [Australian Bureau of Meteorology (BOM) High-definition satellite images](http://www.bom.gov.au/australia/satellite/index.shtml) ## Appendix 1 - Output From get_precis_forecast() The functions, `get_precis_forecast()` or `parse_precis_forecast(), will return a data frame of the 7 day short forecast with the following fields:
index
Forecast index number, 0 = current day ... 7 day
product_id
BOM Product ID from which the data are derived
state
State name (postal code abbreviation)
town
Town name for forecast location
aac
AMOC Area Code, _e.g._, WA_MW008, a unique identifier for each location
lat
Latitude of named location (decimal degrees)
lon
Longitude of named location (decimal degrees)
elev
Elevation of named location (metres)
start_time_local
Start of forecast date and time in local TZ
end_time_local
End of forecast date and time in local TZ
UTC_offset
Hours offset from difference in hours and minutes from Coordinated Universal Time (UTC) for `start_time_local` and `end_time_local`
start_time_utc
Start of forecast date and time in UTC
end_time_utc
End of forecast date and time in UTC
maximum_temperature
Maximum forecast temperature (degrees Celsius)
minimum_temperature
Minimum forecast temperature (degrees Celsius)
lower_precipitation_limit
Lower forecast precipitation limit (millimetres)
upper_precipitation_limit
Upper forecast precipitation limit (millimetres)
precis
Précis forecast (a short summary, less than 30 characters)
probability_of_precipitation
Probability of precipitation (percent)
## Appendix 2 - Output From get_ag_bulletin() The functions, `get_ag_bulletin()` or `parse_ag_bulletin(), will return a data frame of the agriculture bulletin with the following fields:
product_id
BOM Product ID from which the data are derived
state
State name (postal code abbreviation)
dist
BOM rainfall district
name
Full station name (some stations have been retired so "station" will be same, this is the full designation
wmo
World Meteorological Organization number (unique ID used worldwide)
site
Unique BOM identifier for each station
station
Station name
obs-time-local
Observation time
obs-time-utc
Observation time (time in UTC)
time-zone
Time zone for observation
lat
Latitude (decimal degrees)
lon
Longitude (decimal degrees)
elev_m
Station elevation (metres)
bar_ht
Bar height (metres)
station
BOM station name
start
Year data collection starts
end
Year data collection ends (will always be current)
r
Rain to 9am (millimetres). Trace will be reported as 0.01
tn
Minimum temperature (degrees Celsius)
tx
Maximum temperature (degrees Celsius)
twd
Wet bulb depression (degrees Celsius)
ev
Evaporation (millimetres)
tg
Terrestrial minimum temperature (degrees Celsius)
sn
Sunshine (hours)
solr
Solar Radiation MJ/sq m
t5
5cm soil temperature (degrees Celsius)
t10
10cm soil temperature (degrees Celsius)
t20
20cm soil temperature (degrees Celsius)
t50
50cm soil temperature (degrees Celsius)
t1m
1m soil temperature (degrees Celsius)
wr
Wind run (kilometres)
## Appendix 3 - Output From get_coastal_forecast() The output of `get_coastal_forecast()` or `parse_coastal_forecast()` will return a data frame with coastal waters forecast values of each area within the given state with the following fields:
index
Forecast index number. 0 = current day
product_id
BOM Product ID from which the data are derived
type
Forecast Region type e.g. Coastal
state_code
State name (postal code abbreviation)
dist_name
Name of forecast district
pt_1_name
Start of forecast district
pt_2_name
End of forecast district
aac
AMOC Area Code, _e.g._, WA_MW008, a unique identifier for each location
start_time_local
Start of forecast date and time in local TZ
end_time_local
End of forecast date and time in local TZ
UTC_offset
Hours offset from difference in hours and minutes from Coordinated Universal Time (UTC) for `start_time_local` and `end_time_local`
start_time_utc
Start of forecast date and time in UTC
end_time_utc
End of forecast date and time in UTC
forecast_seas
Forecast sea conditions
forecast_weather
Forecast weather summary
forecast_winds
Forecast winds summary
forecast_swell1
Forecast primary swell summary
forecast_swell2
Forecast seondary swell summary (not always provided)
forecast_caution
Forecast caution issued (not always provided)
marine_forecast
Additional marine forecast warning information (not always provided)