Calculate the local time for the monitor, as well as sunrise, sunset and solar noon times, and create several temporal masks.
The returned dataframe will have as many rows as the length of the incoming
time vector and will contain the following columns:
localStdTime_UTC – UTC representation of local standard time
daylightSavings – logical mask = TRUE if daylight savings is in effect
localTime – local clock time
sunrise – time of sunrise on each localTime day
sunset – time of sunset on each localTime day
solarnoon – time of solar noon on each localTime day
day – logical mask = TRUE between sunrise and sunset
morning – logical mask = TRUE between sunrise and solarnoon
afternoon – logical mask = TRUE between solarnoon and sunset
night – logical mask = opposite of day
Monitor ID for a specific monitor in
While the lubridate package makes it easy to work in local timezones, there is no easy way in R to work in "Local Standard Time" (LST) as is often required when working with air qualitiy data. EPA regulations mandate that daily averages be calculated based on LST.
localStdTime_UTC is primarily for use internally and provides
an important tool for creating LST daily averages and LST axis labeling.
A dataframe with times and masks.
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library(PWFSLSmoke) carmel <- monitor_subset(Carmel_Valley, tlim = c(20160801,20160810)) # Create timeInfo object for this monitor ti <- monitor_timeInfo(carmel) # Subset the data based on day/night masks data_day <- carmel$data[ti$day,] data_night <- carmel$data[ti$night,] # Build two monitor objects carmel_day <- list(meta = carmel$meta, data = data_day) carmel_night <- list(meta = carmel$meta, data = data_night) # Plot them monitor_timeseriesPlot(carmel_day, shadedNight = TRUE, pch = 8, col = 'goldenrod') monitor_timeseriesPlot(carmel_night, pch = 16, col = 'darkblue', add = TRUE)
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