calc_light_merged: Merge modeled and observed PAR into a single timeseries

In USGS-R/streamMetabolizer: Models for Estimating Aquatic Photosynthesis and Respiration

Merge modeled and observed PAR into a single timeseries

Description

Merge two time series (one observed, one modeled) of photosynthetically active radiation (PAR) for a series of date-times. You can also think about this as a way to smoothly interpolate a time series of observations.

Usage

calc_light_merged(
  PAR.obs = mm_data(solar.time, light),
  solar.time,
  latitude,
  longitude,
  max.PAR = NA,
  max.gap = as.difftime(3, units = "hours"),
  attach.units = deprecated()
)

Arguments

PAR.obs	a 2-column data.frame with columns solar.time and light, as in argument default, containing the full time series of observed light (should be at a lower temporal resolution than PAR.mod)
solar.time	a vector of mean solar times for which the light should be modeled and merged with the values in PAR.obs
latitude	numeric value or vector indicating the site latitude in decimal degrees (never radians or deg-min-sec, no matter what format is) between -90 (South Pole) and 90 (North Pole).
longitude	numeric, in degrees, either positive and unitted ("degE" or "degW") or with sign indicating direction (positive = East), describing location of the site
max.PAR	the maximum PAR, as in calc_light. if NA, this function does its best to guess a max.PAR that will make modeled light pretty similar to cloud-free days of observed light
max.gap	difftime or NA. If difftime, the maximum gap between a light observation and a time point in solar.time, beyond which no value will be given for light at that solar.time. If NA, all values will be modeled, even if they are many days away from a light observation.
attach.units	(deprecated, effectively FALSE in future) logical. Should the returned vector be a unitted object?

Examples

## Not run: 
library(dplyr)
library(ggplot2)
library(unitted)
timebounds <- as.POSIXct(c('2008-03-12 00:00', '2008-03-12 23:59'), tz='UTC')
coords <- list(lat=32.4, lon=-96.5)
PAR.obs <- tibble::tibble(
  solar.time=seq(timebounds[1], timebounds[2], by=as.difftime(3, units='hours')),
  light=c(0, 0, 85.9, 1160.5, 1539.0, 933.9, 0, 0)
) %>% as.data.frame()
PAR.mod <- tibble::tibble(
  solar.time=seq(timebounds[1], timebounds[2], by=as.difftime(0.25, units='hours')),
  light=calc_light(solar.time, latitude=coords$lat, longitude=coords$lon)
) %>% as.data.frame()
PAR.merged <- calc_light_merged(PAR.obs, PAR.mod$solar.time,
  latitude=coords$lat, longitude=coords$lon, max.gap=as.difftime(20, units='hours'))
ggplot(bind_rows(mutate(v(PAR.obs), type='obs'), mutate(v(PAR.mod), type='mod'),
                 mutate(v(PAR.merged), type='merged')) %>%
       mutate(type=ordered(type, levels=c('obs','mod','merged'))),
  aes(x=solar.time, y=light, color=type)) + geom_line() + geom_point() + theme_bw()

## End(Not run)

USGS-R/streamMetabolizer documentation built on Aug. 15, 2023, 7:50 a.m.