Note: this code has not necessarily been tested; if you find any problems or bugs, please feel free to adjust the page accordingly!

Python

clrs = {'merra2'  :'#e21f26',
        'merra'   :'#f69999',
        'erai'    :'#295f8a',
        'era5'    :'#5f98c6',
        'era40'   :'#afcbe3',
        'jra55'   :'#723b7a',
        'jra55c'  :'#ad71b5',
        'jra25'   :'#d6b8da',
        'ncep1'   :'#f57e20',
        'ncep2'   :'#fdbf6e',
        '20crv2c' :'#ec008c',
        '20crv2'  :'#f799D1',
        'cera20c' :'#00aeef',
        'era20c'  :'#60c8e8',
        'cfsr'    :'#34a048',
        'rem'     :'#b35b28', # reanalysis ensemble mean
        'other'   :'#ffd700',
        'obs'     :'#000000', # observations black
        'obs2'    :'#777777'} # observations grey

Example:

import matplotlib.pyplot as plt
plt.plot(x, y, ls='-', lw=2, color=clrs['merra2'])

IDL

clrs = ['merra2','merra','erai','era5', 'era40','jra55','jra55c','jra25','ncep1','ncep2','20crv2c','20crv2','cera20c','era20c','cfsr','rem','other','obs','obs2']
rvct = [ 226, 246, 41, 95, 175, 114, 173, 214, 245, 253, 236, 247, 0, 96, 52, 179, 255, 0, 119]
gvct = [  31, 153, 95, 152, 203, 59, 113, 184, 126, 191, 0, 153, 174, 200, 160, 91, 215, 0, 119]
bvct = [  38, 153, 138, 198, 227, 122, 181, 218, 32, 110, 140, 209, 239, 232, 72, 40, 0, 0, 119]
tvlct,rvct,gvct,bvct

Examples:

plot, x, y, linestyle=0, thick=2, color=where(clrs eq 'merra2')[0]

; Code to make plots using IDL function graphics
sripcolor=hash()
for i=0,clrs.length-1 do sripcolor[clrs[i]] = [rvct[i],gvct[i],bvct[i]]
a = plot(/test, color=sripcolor['merra2'])

NCL

• Courtesy Cathy.Smith (NOAA) 13 July 2017
• See also reanalysis.org pages, (1) and (2).

NCL code is below. Save as something like reanalysis.rgb

-----------------------------------------------------------------------------------------

ncolors=19
#r g b
226  31  38
246 153 153
 41  95 138
 95 152 198
175 203 227
114  59 122
173 113 181
214 184 218
245 126  32
253 191 110
236   0 140
247 153 209
  0 174 239
 96 200 232
 52 160  72
179  91  40
255 215   0
  0   0   0
119 119 119

;      reanalysis color table
;https://s-rip.ees.hokudai.ac.jp/mediawiki/index.php/ColourTables

;       'merra2'  :'#e21f26', red
;       'merra'   :'#f69999', salmon
;       'erai'    :'#295f8a', blue grey
;       'era5'    :'#5f98c6'  lighter blue grey
;       'era40'   :'#afcbe3', even lighter blue grey
;       'jra55'   :'#723b7a', purple
;       'jra55c'  :'#ad71b5', lavendar
;       'jra25'   :'#d6b8da', lighter lavendar
;       'ncep1'   :'#f57e20', orange
;       'ncep2'   :'#fdbf6e', lighter orange
;       '20crv2c' :'#ec008c', magenta
;       '20crv2'  :'#f799D1', pink
;       'cera20c' :'#00aeef', sky blue
;       'era20c'  :'#60c8e8', light sky blue
;       'cfsr'    :'#34a048', green
;       'rem'     :'#b35b28', brown                   |reanalysis ensemble mean
;       'other'   :'#ffd700', yellow
;       'obs'     :'#000000', black                   |observations black
;       'obs2'    :'#777777'} grey                    |observations grey

DCL

Put colormap_01.x11 at the current directory. Specify the following colour number (and index) in the program. (Run dclclr to see the colour-table figure. create_colormap_s-rip_ver2-0.f and srip-color-scale_mf3.csv were used to create this colormap file.)

11: MERRA-2 
12: MERRA 
13: ERA-Interim 
14: ERA5
15: ERA-40 
16: JRA-55 
17: JRA-55C, JRA-55AMIP 
18: JRA-25 
19: NCEP-NCAR R1 
20: NCEP-DOE R2 
21: 20CR v2c 
22: 20CR v2 
23: CERA-20C 
24: ERA-20C 
25: CFSR 
26: REM (reanalysis ensemble mean) 
27: Other 
28: Observations - black
29: Other observations  - grey

00 to 09: from the original colormap_01.x11 
50 to 60: for grey tones (50: black;  60: white)