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WRFVAR_VERIFY_SUMMER

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Exp2(green) : CV5 (len_scaling=1) EXP3(blue) : CV5 (len_scaling=0.5) Chin Hsiao , Chiang ... SYNOP (?????) SYNOP (?????) GEOAMV ( SATOB ) (????) AIREP (???) ... – PowerPoint PPT presentation

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Title: WRFVAR_VERIFY_SUMMER


1
WRFVAR_VERIFY_SUMMER
  • BES data 200507
  • wrfvar WRF Update_cycle

  • 20050701002005071012
  • Obs Data 20050701002005071312
  • Exp1(red) CV3
  • Exp2(green) CV5 (len_scaling1)
  • EXP3(blue) CV5 (len_scaling0.5)

Chin Hsiao , Chiang
2
SYNOP (?????)
3
SYNOP (?????)
4
GEOAMV ( SATOB ) (????)
5
AIREP (???)
6
BUOY (??????)
7
BUOY (??????)
8
GPSREF
9
METAR (?????)
10
PILOT (????)
11
SHIPS (???)
12
SHIPS (???)
13
SONDE_SFC
14
SONDE_SFC
15
SOUND
16
SOUND
17
  • Summary
  • In namelist.3dvar, using length_scaling0.5, the
    RMS and BIAS of observation data will be better
    than using length_scaling1 .
  • I have no idea what is the best choice of
    cv3, so I just change the cv5s
    length_scaling0.5 1 to compare their
    result .
  • After using len_scale0.5, we can see at initial
    time, most of observation datas RMS decrease.
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