Adding 1 day to time interval for some resources

mikejohnson51 commented 3 years ago

The date interval is off by one for some resources.

mikejohnson51 commented 3 years ago

library(sf)
#> Warning: package 'sf' was built under R version 4.0.2
#> Linking to GEOS 3.8.1, GDAL 3.1.1, PROJ 6.3.1
library(climateR)

AOI = st_sfc(st_point(c(-70.06456, 41.93111)), crs = 4326)

prism   = getPRISM(AOI, "prcp", 
                   startDate = "2018-01-01", 
                   endDate = "2018-01-31")
gridMet = getGridMET(AOI, 
                     param = "prcp",
                     startDate = "2018-01-01",
                     endDate = "2018-01-31")

plot(prism$date, prism$prcp, type = "l")
lines(c(gridMet$date), c(gridMet$prcp), type = "l", col = "red")

^{Created on 2021-01-19 by the reprex package (v0.3.0)}

mikejohnson51 commented 3 years ago

Turns out this was not a bug in climateR but an actual lag between the gridmet and prism dataset! This is being reverted:

Thank you to @sgoslee for identifying this was not a correct fix. The data we expect now is demonstrated below with a comparison to a CSV downloaded from the gridmet producers.

Appears to have a one day lag....

library(sf)
#> Warning: package 'sf' was built under R version 4.0.2
#> Linking to GEOS 3.8.1, GDAL 3.1.4, PROJ 6.3.1
library(climateR)

AOI = st_sfc(st_point(c(-70.06456, 41.93111)), crs = 4326)

prism   = getPRISM(AOI, "prcp", 
                   startDate = "2018-01-01", 
                   endDate = "2018-01-31")
gridMet = getGridMET(AOI, 
                     param = "prcp",
                     startDate = "2018-01-01",
                     endDate = "2018-01-31")

plot(prism$date, prism$prcp, type = "l")
lines(c(gridMet$date), c(gridMet$prcp), type = "l", col = "red")

Checking Gridmet...

# As evidence, we download the following file from: 
# https://climatetoolbox.org/tool/Data-Download
from_gridmet = readr::read_csv('/Users/mikejohnson/Downloads/metdata_41.93111N_70.06456W.csv', skip = 8) %>% 
  dplyr::mutate(date = as.Date(paste(Year, 
                                      sprintf("%02d", Month), 
                                      sprintf("%02d", Day), sep = "-")))
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   Year = col_double(),
#>   Month = col_double(),
#>   Day = col_double(),
#>   `pr(mm)` = col_double()
#> )

head(from_gridmet)
#> # A tibble: 6 x 5
#>    Year Month   Day `pr(mm)` date      
#>   <dbl> <dbl> <dbl>    <dbl> <date>    
#> 1  2018     1     1      0   2018-01-01
#> 2  2018     1     2      0   2018-01-02
#> 3  2018     1     3      0   2018-01-03
#> 4  2018     1     4     25.4 2018-01-04
#> 5  2018     1     5      0   2018-01-05
#> 6  2018     1     6      0   2018-01-06
plot(from_gridmet$`pr(mm)`, gridMet$prcp)

plot(from_gridmet$date, from_gridmet$`pr(mm)`, type = "l")
lines(c(gridMet$date), c(gridMet$prcp), type = "l", col = "red")

^{Created on 2021-03-09 by the reprex package (v0.3.0)}

Checking PRISM...

A reasonable question is "well GridMet is right, PRISM must be off..." however I am confident the PRISM URLs are correct as they only contain a single time point per file and are specified by date. For example:

http://convection.meas.ncsu.edu:8080/thredds/dodsC/prism/daily/combo/2018/PRISM_combo_20180101.nc.html

With a DDS of (note time = 1):

Dataset {
    Float64 t[t = 1];
    Grid {
     ARRAY:
        Float64 ppt[t = 1][latitude = 621][longitude = 1405];
     MAPS:
        Float64 t[t = 1];
        Float64 latitude[latitude = 621];
        Float64 longitude[longitude = 1405];
    } ppt;
    Grid {
     ARRAY:
        Float64 tmean[t = 1][latitude = 621][longitude = 1405];
     MAPS:
        Float64 t[t = 1];
        Float64 latitude[latitude = 621];
        Float64 longitude[longitude = 1405];
    } tmean;
    Grid {
     ARRAY:
        Float64 tmin[t = 1][latitude = 621][longitude = 1405];
     MAPS:
        Float64 t[t = 1];
        Float64 latitude[latitude = 621];
        Float64 longitude[longitude = 1405];
    } tmin;
    Grid {
     ARRAY:
        Float64 tmax[t = 1][latitude = 621][longitude = 1405];
     MAPS:
        Float64 t[t = 1];
        Float64 latitude[latitude = 621];
        Float64 longitude[longitude = 1405];
    } tmax;
    Float64 longitude[longitude = 1405];
    Float64 latitude[latitude = 621];
} prism/daily/combo/2018/PRISM_combo_20180101.nc;

So, if there is an error/lag, it is in the raw data and not in the climateR extraction/formatting...

mikejohnson51 / climateR