spike_wave.R

library(heatwaveR)

library(tsibble)
library(lubridate)
library(dplyr)

# Detect the events in a time series
ts <- ts2clm(sst_WA, climatologyPeriod = c("1982-01-01", "2011-12-31"))
mhw <- detect_event(ts, minDuration = 1, maxGap = 0)

# View just a few metrics
events <- mhw$event %>% 
  dplyr::ungroup() %>%
  dplyr::select(event_no, duration, date_start, date_peak, intensity_max, intensity_cumulative) %>% 
  dplyr::arrange(-intensity_max) %>% 
  mutate(spike_wave = ifelse(duration<5, "spike", "wave")) %>%
  as_tsibble(index = date_peak)


annual <- events %>%
  index_by(event_year = year(date_start)) %>%
  group_by(spike_wave) %>%
  tally() %>%
  fill_gaps(n = 0)

ggplot(annual,
       aes(x = event_year, y = n, color = spike_wave)) +
  geom_line()


ggplot(events,
       aes(x = duration, fill = spike_wave)) +
  geom_histogram(position = position_dodge())


ggplot(events,
       aes(x = intensity_max, fill = spike_wave)) +
  geom_histogram(position = position_dodge(),
                 bins = 15)