Determine why Cass Lake is so much warmer than nearby similar lakes

[jordansread]

For Gretchen's request on GDD, I did this quick processing (DOWs were her's)

From hyperscales-data-release directory:

library(tidyverse)
dow_xwalk <- readRDS('../lake-temperature-model-prep/2_crosswalk_munge/out/mndow_nhdhr_xwalk.rds')
dows <- paste0('mndow_', c('04003000', '04003800', '04007900', '04000700', '11041500', '04004900'))
dow_xwalk %>% filter(MNDOW_ID %in% dows)
# A tibble: 6 x 2
  MNDOW_ID       site_id       
  <chr>          <chr>         
1 mndow_04000700 nhdhr_166868512
2 mndow_04003000 nhdhr_166868528
3 mndow_04003800 nhdhr_120019527
4 mndow_04004900 nhdhr_166868535
5 mndow_04007900 nhdhr_120019522
6 mndow_11041500 nhdhr_166868528 !!! OH NO same as mndow_04003000

 
predictions_df <- scipiper::scmake('predictions_df')

Gretchens_DOW_GDD_lakes <- predictions_df %>% filter(site_id %in% c('nhdhr_166868512','nhdhr_166868528','nhdhr_120019527','nhdhr_166868535','nhdhr_120019522','nhdhr_166868528')) %>%
    pull(source_filepath) %>% purrr::map(function(file) {
        feather::read_feather(file) %>% mutate(year = lubridate::year(DateTime), temp = temp_0-5, gdd_raw_temp = ifelse(temp < 0, 0, temp)) %>% group_by(year) %>%
            summarize(GDD = sum(gdd_raw_temp), site_id = basename(file))
    }) %>% purrr::reduce(bind_rows)

ggplot(data = Gretchens_DOW_GDD_lakes, aes(x = year, y = GDD, color = site_id)) +
    geom_line() +
    theme_bw() 

[jordansread]

This is because the PB0 driver data were mixed up :(

[aappling-usgs]

Ah ha! 💡

[jordansread]

What it looks like now (and proof to @aappling-usgs that I am continuing to ggplot 😆 )