Create groups based on contiguous rows for displaying in a ggplot line chart

I have an extended time series, and wish to highlight some trends of interest within the chart. Something along these lines:

The problem is, the highlights could be high (red) or low (green), so I need to map a colour aesthetic to the chart as well. When I do so, ggplot assumes I want all the highlighted points to be a contiguous group (which makes sense!) and puts a line across the gap as well:

The obvious solution is to map the 'group' aesthetic to keep each mini-trend on its own group, but I don't know ahead of time where each trend will start and end, so I am struggling to find a way to do that on the fly.

Is there either a way to identify these groups on the fly (maybe with using a lag() function or something?) and create a column to map for groups, or else a way to tell ggplot "Hey, if I have an NA between these two points, break the line and we'll talk again later"?

Here's the code I used to produce the second chart above (the first is the same code but with colour set manually rather than mapped):

library(dplyr)
library(broom)
library(ggplot2)

df <- sunspot.year %>%
  tidy() %>%
  rename(year = index, sunspots = value) 

hl_df <- df %>%
  filter(year >= 1750 & year <= 1800 |
         year >= 1875 & year <= 1900) %>%
  mutate(highlight = sunspots) %>%
  mutate(highlight_colour = 'high')

df %>%
  left_join(hl_df) %>%
  mutate(year = paste0(year,'-01-01')) %>%
  mutate(year = as.Date(year)) %>%
  ggplot(aes(x = year, y = sunspots)) +
  geom_line() +
  geom_line(aes(y = highlight, col = highlight_colour)) +
  scale_colour_manual(values = c('high' = 'darkred', 'low' = 'darkolivegreen')) +
  theme_bw() +
  theme(legend.position = 'none')

Add group = 1 to the top level aesthetic (or just in geom_line() I think should work too):

df %>%
  left_join(hl_df) %>%
  mutate(year = paste0(year,'-01-01')) %>%
  mutate(year = as.Date(year)) %>%
  ggplot(aes(x = year, y = sunspots,group = 1)) +
  geom_line() +
  geom_line(aes(y = highlight, col = highlight_colour)) +
  scale_colour_manual(values = c('high' = 'darkred', 'low' = 'darkolivegreen')) +
  theme_bw() +
  theme(legend.position = 'none')

The idea here is that group is a separate (easy to overlook) aesthetic that you can set. When you map something to color, group is inferred from that, so if you want a different "grouping" for the continuous line drawn you have to reset the group aesthetic. Setting group = 1 is the way to tell ggplot() to treat everything as a single group.

Separate from the group = 1 issue, you're plotting things multiple times with the duplicated geom_line() call. When you add in group = 1 to your bag of tricks, that over-plotting isn't necessary and removes some of the anti-aliasing artifacts that are introduced when you plot things on top of themselves:

df %>%
  left_join(hl_df) %>%
  mutate(year = paste0(year,'-01-01')) %>%
  mutate(year = as.Date(year)) %>%
  ggplot(aes(x = year, y = sunspots,group = 1,color = highlight_colour)) +
  geom_line() +
  scale_colour_manual(values = c('high' = 'red', 'low' = 'green')) +
  theme_bw() +
  theme(legend.position = 'none')