Typhoon Predictions with GPS Radio Occultation Data Assimilations Using WRF 3DVAR with Local and Non

1
Typhoon Predictions with GPS Radio Occultation
Data Assimilations Using WRF 3DVAR with Local
and Nonlocal Operators

• Shu-Ya Chen1, Ching-Yuang Huang1, Ying-Hwa
  Kuo2,3,
• Yong-Run Guo3 and Sergey Sokolovskiy2
• 1Department of Atmospheric Sciences, National
  Central University, Jhongli, Taiwan
• 2University Corporation for Atmospheric Research,
  Boulder, Colorado, USA
• 3National Center for Atmospheric Research,
  Boulder, Colorado, USA

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Introduction

• Global Positioning System (GPS) radio occultation
  (RO) measurements have several advantages, e.g.,
  high vertical resolution, no calibration need, no
  influence by cloud or rainfall, and global
  coverage.
• GPS RO refractivity is an intermediate product
  after taking an Abel transform of bending angles
  defined for each incident ray tangent to its
  perigee point.
• Currently, assimilation with the Abel-retrieved
  refractivity obtained from GPS RO data has
  assumed local measurement at the perigee point
  where the GPS ray is closest to the earth (e.g.
  Huang et al. 2005).

Local (refractivity)
where Pw is water vapor pressure, T air
temperature, and P the pressure of the
atmosphere.
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• However, the Abel-retrieved refractivity
  accounts for an integrated amount of refractivity
  along the total path of the ray in a
  spherically-symmetric atmosphere. But, bending
  angle assimilation is not feasible for regional
  models and is not cost effective due to ray
  tracing.
• In order to take the effect of the integration
  into account, Sokolovskiy et al. (2005) suggest
  use of excess phase for assimilation, which is an
  integrated amount of the refractivity along the
  ray.

Nonlocal (excess phase)

• In this study, we extend the previous work to
  assimilate the excess phase to account for the
  nonlocal effect along the ray. In this
  preliminary study, we develop a nonlocal operator
  and implant it into the WRFVAR version 2.1. We
  will compare the results with assimilation by
  both local and nonlocal operators in simulation
  of Typhoon Kaemi (2006).

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Nonlocal operator

• Interpolate both observation and model
  refractivity into the mean heights of the model.
• Integrate the observed refractivity along the ray
  path straightline.
• Consider blocking effect when the ray is
  interrupted by model boundaries and mountains.

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One month statistic obs. error by
Hollingsworth-Lonngberg method (2003/08/152003/09
/15)
horizontal resolution 45 km grids
22212830 data CHAMP 314 points in the domain
height (km)
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Typhoon Kaemi (initial time2006/07/23 00 UTC)

• Domain 1 15115131 with resolution 45 km
• Domain 2 15115131 with resolution 15 km
• Domain 3 15115131 with resolution 5 km
• Initial field AVN analysis
• OBS Data FORMOSAT-3/COSMIC
• Model WRF v2.1.2
• Integration 72 hours

NONE no assimilation REF assimilated
refractivity by local operator EPH assimilated
excess phase by nonlocal operator
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T q N
EPH
484 mb int.0.05 ? int. 0.1 g kg-1
int. 0.5 N-units
T q N
REF
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EPH
(AN-BN) / BN 100
Interval 0.3
2259
0029
0030
0050
0203
0211
0235
9
REF
2259
0029
0030
0050
0203
0211
0235
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Cold Start Experiments Tracks and Intensity
Best track (dots) NONE (EXP0) REF (EXP1) EPH
(EXP2)
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Observational rainfall
Int. 10 mm
Int. 30 mm
Int. 30 mm
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NONE
757
Max. 126.1 mm
294.9 mm 1024 mm
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REF
900
Max. 114.8 mm 271.8 mm
908.6 mm
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EPH
350
Max. 157.4 mm 241.7 mm
912 mm
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differences of wet refractivity (EPH-NONE)
The differences of wet refractivity (N-unit)
between EPH and NONE at 0.5 km height at (a) 48 h
and (b) 72 h. The horizontal wind vectors (m s-1)
for EPH are also overlapped.
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Cycling with BogusEPH assimilation

• TC Bogus pressure and wind field
• EPH GPS excess phase

All assimilations for 3 domains
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Observation distribution
2006/07/22 00 UTC
2006/07/22 06 UTC
2006/07/22 18 UTC
2006/07/23 00 UTC
2006/07/22 12 UTC
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Obs. number
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Cycling experiments Tracks and Intensity
Best track (dots) BogusEPH (EXP3) Bogus
(EXP4) EPH (EXP5)
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Precipitation (second day)
OBS Bogus
BogusEPH
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Conclusion

• The analysis increments in WRF 3DVAR produced by
  both nonlocal operator and local operator are
  quite similar in magnitudes and spatial
  distributions. However, the increments of the
  nonlocal operator are of broader vertical scale
  and show elongation along the rays direction,
  when compared with those of local observation
  operator.
• For cold start experiments, the use of nonlocal
  observation operator produces better
  precipitation forecast than local observation
  operator.
• The best forecast of typhoon track and intensity
  is obtained with (i) cycling, (ii) typhoon bogus
  and (iii) excess phase assimilation.
• The assimilation of COSMIC GPS RO data with
  nonlocal observation improves precipitation
  forecast when compared with cycling experiments
  with typhoon bogus.

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The end

• Thank you