Relative impact of GPSRO on forecast error
Tom Auligné, Hans Huang, Hui-Chuan Lin, Xiaoyan Zhang, Xin Zhang
National Center for Atmospheric Research
NCAR is sponsored by the National Science Foundation
Goal: Community WRF DA system for • regional/global• research/operations• deterministic/probabilistic
Techniques: • 3D-Var• 4D-Var• Ensemble• Hybrid Variational/Ensemble
WRF Data Assimilation system
WRFDA Observations
In-Situ:- Surface (SYNOP, METAR, SHIP, BUOY).- Upper air (TEMP, PIBAL, AIREP, ACARS, TAMDAR).
• Remotely sensed retrievals:- Atmospheric Motion Vectors (geo/polar).- SATEM thickness.- Ground-based GPS Total Precipitable Water/Zenith Total Delay.- SSM/I oceanic surface wind speed and TPW.- Scatterometer oceanic surface winds.- Wind Profiler.- Radar radial velocities and reflectivities.- Satellite temperature/humidity/thickness profiles.- GPS refractivity (e.g. COSMIC).
Radiative Transfer (RTTOV or CRTM):– HIRS from NOAA-16, NOAA-17, NOAA-18, NOAA-19, METOP-2– AMSU-A from NOAA-15, NOAA-16, NOAA-18, NOAA-19, EOS-Aqua, METOP-2– AMSU-B from NOAA-15, NOAA-16, NOAA-17– MHS from NOAA-18, NOAA-19, METOP-2– AIRS from EOS-Aqua– SSMIS from DMSP-16
•Bogus: – TC bogus.– Global bogus.
From Langland and Baker (2004)
ForecastError
xt is the true state, estimated by the analysis at the time of the forecastxf is the forecast from analysis xaxg is the forecast from first-guess at the time of the analysis xa
e is the verification norm (e.g. Total Dry Energy)
Time
Impact of Observations on Forecast Error
Observation(y)
WRFData
Assimilation
WRF-ARWModel
Forecast(xf)
DeriveForecastAccuracy
Background(xb)
Analysis(xa)
Adjoint of WRF-ARW
Linear Model
ObservationSensitivity(δF/ δy)
Observation Impact
<y-H(xb)> (δF/ δy)
Adjoint of WRF Data
Assimilation
DefineForecastAccuracy
ForecastAccuracy
(F)
Figure adapted from Liang Xu (NRL)
UpdateBC
Adjoint ofUpdate
BC
Impact of Observations on Forecast Error
12h Forecast error reduction against ERA
Observation impact for Arctic System Reanalysis
Observation impact for Arctic System Reanalysis
Observation impact for CONUS
June January
Observation impact for Taiwan CWB operations
Observation impact for Taiwan CWB operations
Summary
• GPSRO observations consistently reduce WRF forecast error • various domains, periods, experimental setups• different platforms• 00, 06, 12 and 18UTC
• GPSRO has a large impact per observation.(comparable results at AFWA and Met Office)
• Linear assumption (Adjoint of the forecast model and analysis)
• Approximation of the “truth” for calculation of forecast error
• Results depend on the choice of norm
• Does not include accumulated and indirect impact
Limitations
