A few interesting examples

library(tidyverse)
library(stationaRy)
library(sf)
library(tmap)
library(spData)

library(AOI)
library(climateR)

library(raster)
library(rasterVis)

library(patchwork)

Precip and temp for specified location (point)

# Get the data 

#loc2use <- 'Death Valley National Park'
loc2use <- 'Union College'

AOI = AOI::geocode(loc2use,
                   pt = TRUE)

ts  = getGridMET(AOI, param = c("tmax","tmin", "prcp"),
                 startDate = "2021-01-01", 
                 endDate = "2021-12-30")
# convert units 
ts <- ts %>% 
  mutate(tmax = ((tmax - 273.15)*(9/5) +32),
         tmin = ((tmin - 273.15)*(9/5) +32),
         prcp = prcp/25.4
         )
# Summary table

ts %>% 
  summarize(pcrp_max = max(prcp),
            temp_max = max(tmax),
            temp_min = min(tmin),
            temp_mean = mean((tmin+tmax)/2),
            temp_max_change = max(tmax - tmin)
            )
##   pcrp_max temp_max temp_min temp_mean temp_max_change
## 1 2.996063    92.57    -4.81  49.84299           40.86
# Make the figures 

fig_01 <- ts %>% 
  ggplot() +
  geom_line(aes(x = date, y = tmax), color = "red") +
  geom_line(aes(x = date, y = tmin), color = "blue") +
  
  labs(x = "", 
       y = "Temperature (F)"
       ) +
  
  geom_hline(yintercept = 32, linetype = "dashed") +
  theme_bw() 
  


fig_02 <- ts %>% 
  ggplot() +
  geom_col(aes(x = date, y = prcp), color = "black") +
    
  labs(y = "Precipitation (inches)") +
    
  theme_bw()
# Make the figures 

(fig_01 / fig_02) +
  plot_annotation(title = paste(loc2use,": Temperature and precipitation", sep = ""),
                  caption = "Data source: GridMET",
                  tag_levels = "a"
                  )

Obtain and analyze precipitation data for Hurricane Henry

henri = getGridMET(aoi_get(state = c("NY", "NJ","CT","MA")), 
                  param = "prcp", 
                  startDate = "2021-08-16", endDate = "2021-08-24")
#> Spherical geometry (s2) switched off
#> Spherical geometry (s2) switched on

#rasterVis::levelplot(henri$gridmet_prcp, par.settings = BTCTheme, main = "Hurricane Henri")
r = raster::stack(henri)
r_inches <- r/25.4

Static map

tmap_mode("plot") 

fig_map <- r_inches %>% 
  tm_shape() +
  tm_raster(style = "cont") +
  tm_shape(spData::us_states) +
  tm_borders()

fig_map


Interactive map

tmap_mode("view")

fig_map 


tmap_mode("plot")


Get the maximum precipitation amount for each day of the storm

round(raster::maxValue(r_inches),2) %>% as.data.frame()
##      .
## 1 4.52
## 2 3.78
## 3 5.03
## 4 4.02
## 5 2.06
## 6 8.13
## 7 7.17
## 8 3.19
## 9 1.10


Get climate data for specified region of the US

temperature_US = getGridMET(aoi_get(state = "conus"), 
                  param = "tmax", 
                  startDate = "2021-12-30", endDate = "2021-12-30")
#> Spherical geometry (s2) switched off
#> Spherical geometry (s2) switched on
temperature_US <- raster::stack(temperature_US)
temperature_US <- temperature_US - 273.15
temperature_US <- (temperature_US*9/5) + 32
temperature_US %>% 
  tm_shape() +
  tm_raster(style = "cont", palette = "-RdBu", midpoint = 32) +
  tm_shape(spData::us_states) +
  tm_borders()