how to find depature from normal in temperature - R 4.0.0

Question

I have been working on a dataset that will be universal on multiple climate stations for analyzing temperature and precipitation. I have run into a brick wall designing the 'climatic norms', I have successfully calculated daily temperature average TAVG, monthly temp avg AVG_TAVG, and summed up PRCP and SNOW for monthly totals.

Where I am at a standstill is calculating departure from normal, currently, data from 1981 - 2010 is considered climate norms.

Here is what my dataset looks like currently:

mso_light
    
    year month day  date       PRCP SNOW  SNWD TMAX TMIN  TAVG
1   1948    1   1   1948-01-01    0    0   102   44 -122 -39.0
2   1948    1   2   1948-01-02    3    0    51   44    6  25.0
3   1948    1   3   1948-01-03    0    0    25   44  -39   2.5
4   1948    1   4   1948-01-04   38   64    76   33  -56 -11.5
5   1948    1   5   1948-01-05    0    0    76   -6  -83 -44.5
6   1948    1   6   1948-01-06  107    0    51   22  -61 -19.5
7   1948    1   7   1948-01-07  147    0    25   28  -17   5.5
8   1948    1   8   1948-01-08    8   13    25   39  -83 -22.0
9   1948    1   9   1948-01-09    0    0    25   -6 -117 -61.5
10  1948    1   10  1948-01-10    8   10    25  -11 -156 -83.5

So I originally felt I needed date for sorting purposes, I will remove it if not needed in the future.

Next, I would like to add a column for DepNormT, which is calculated by taking every Jan 1 - Dec 31 from 1981 - 2010 and averaging TAVG to find the normal average temp. Then DepNormT will be the difference between itself and TAVG for the entire dataset.

I have tried multiple ways to accomplish this here are two versions:

mso_DeptT <- mso_light %>%
  group_by(month, day) %>%
  mean(mso_light$TAVG[1981:2010], na.rm = T) %>%
  ungroup()

This gives me the following error:

  no applicable method for 'ungroup' applied to an object of class "c('double', 'numeric')"
In addition: Warning message:
In mean.default(., mso_light$TAVG[1981:2010], na.rm = T) :
  argument is not numeric or logical: returning NA

This is another version:

##mso_DeptT <- filter(mso_light, year >= "1981", year <= "2010") %>%
##  group_by(day, month) %>%
##  mutate(daily_DeptT = mean(TAVG, na.rm = T)) %>%
##  ungroup()

mso_sum <- mso_light %>%
  group_by(month, year) %>% 
  summarize(AVG_TAVG=mean(TAVG, na.rm = TRUE),
          T_PRCP=sum(PRCP, na.rm=TRUE),
          T_SNOW=sum(SNOW, na.rm=TRUE)) %>% 
  ungroup()

## To find monthly normal precipitation and snowfall - using dataset mso_sum

cli_Avg <- filter(mso_sum, year >= "1981", year <= "2010") %>%
  group_by(month) %>%
  summarize(Mon_Precip = mean(T_PRCP, na.rm = T),
            Mon_Snow = mean(T_SNOW, na.rm = T))

This gave me a 30 year average that was equal to each individual day average TAVG. For example:

    year month day  date       PRCP SNOW  SNWD TMAX TMIN  TAVG  DepNormT
1   1948    1   1   1948-01-01    0    0   102   44 -122 -39.0      -39.0
2   1948    1   2   1948-01-02    3    0    51   44    6  25.0       25.0
3   1948    1   3   1948-01-03    0    0    25   44  -39   2.5        2.5
4   1948    1   4   1948-01-04   38   64    76   33  -56 -11.5        ect
5   1948    1   5   1948-01-05    0    0    76   -6  -83 -44.5          .
6   1948    1   6   1948-01-06  107    0    51   22  -61 -19.5          .
7   1948    1   7   1948-01-07  147    0    25   28  -17   5.5          .
8   1948    1   8   1948-01-08    8   13    25   39  -83 -22.0
9   1948    1   9   1948-01-09    0    0    25   -6 -117 -61.5
10  1948    1   10  1948-01-10    8   10    25  -11 -156 -83.5

Thanks for suggestions.