monitor_forecastPlot: Compare forecasts

In MazamaScience/AirFireModeling: Utilities for Working with Monitoring Data and Smoke Model Output

Description

Plots monitor data and overlays models of the bluesky forecasts.

For each model, a timeseries is created by gathering count grid cells within radius meters of the ws_monitor. The resulting set of timeseries are then collapsed into a single timeseries by applying the quantile() using the user specified probability prob.

Usage

monitor_forecastPlot(
  ws_monitor,
  modelName = NULL,
  modelMode = "forecast",
  baseUrl = "https://haze.airfire.org/bluesky-daily/output/standard",
  radius = 20,
  count = 9,
  prob = 0.5,
  verbose = TRUE,
  ...
)

Arguments

ws_monitor	ws_monitor object.
modelName	Model identifier(s).
modelMode	Subdirectory path containing BlueSky output, i.e. 'forcast'.
baseUrl	Base URL for BlueSky output.
radius	Distance (km) of radius from target location.
count	Number of grid cells within radius to return.
prob	Quantile probability used when plotting model data.
verbose	Logical to display messages.
...	Additional arguments passed to PWFSLSmoke::monitor_timeseriesPlot().

Examples

library(PWFSLSmoke)
initializeMazamaSpatialUtils()

library(AirFireModeling)
setModelDataDir('~/Data/Bluesky')

San_Pablo <-
  monitor_load(20191025, 20191029) %>%
  monitor_subset(monitorIDs = '060131004_01')

models <- bluesky_findModels(
  San_Pablo$meta$longitude,
  San_Pablo$meta$latitude
)

monitor_forecastPlot(
  San_Pablo,
  modelName = models
)

MazamaScience/AirFireModeling documentation built on March 13, 2021, 12:02 a.m.