Choosing dataset

Dataset name is:

“ERA5 hourly data on single levels from 1979 to present”

Metadata are here:

https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview

Downloading data

Python script to download sample data, for two days in 2018, at highest temporal resolution (hourly):

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'reanalysis-era5-single-levels',
    {
        'format':'netcdf',
        'product_type':'reanalysis',
        'format':'netcdf',
        'variable':'boundary_layer_height',
        'year':'2018',
        'month':'01',
        'day':[
            '01','02'
        ],
        'time':[
            '00:00','01:00','02:00',
            '03:00','04:00','05:00',
            '06:00','07:00','08:00',
            '09:00','10:00','11:00',
            '12:00','13:00','14:00',
            '15:00','16:00','17:00',
            '18:00','19:00','20:00',
            '21:00','22:00','23:00'
        ],
        'area':[49.393, -124.863, 24.391, -66.873],
        'grid':[0.125,0.125]
    },
    'download2.nc')

According to metadata, the resolution for athmospheric variables is 0.25*0.25 degrees so this is what was chosen in the request.

Examining sample data in R

library(stars, quietly = TRUE)
## Linking to GEOS 3.7.1, GDAL 2.4.0, PROJ 5.2.0
setwd("/home/michael/Dropbox/BGU/Allan_Just/p_16_sample_code_for_PBL_data_over_US/")

# Reading NetCDF file
r = read_stars("download2.nc")

# Checking contents
r
## stars object with 3 dimensions and 1 attribute
## attribute(s), summary of first 1e+05 cells:
##  download2.nc [m]  
##  Min.   :   9.256  
##  1st Qu.: 161.453  
##  Median : 431.646  
##  Mean   : 498.954  
##  3rd Qu.: 765.617  
##  Max.   :1977.288  
## dimension(s):
##      from  to         offset   delta  refsys point values    
## x       1 464       -124.925   0.125      NA    NA   NULL [x]
## y       1 201        49.4535  -0.125      NA    NA   NULL [y]
## time    1  48 2018-01-01 UTC 1 hours POSIXct    NA   NULL
# Plot: Entire file
plot(r)

# Plot: First time step only
plot(r[, , , 1])