Constrained Bias Correction (CBC) For Satellite Radiance Assimilation. Wei Han NWPC/CMA

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1 Constrained Bias Correction (CBC) For Satellite Radiance Assimilation Wei Han NWPC/CMA ITSC19, March 27, 2014

2 Outline Background The ias correction is an ill posed prolem Two Remain Issues of ias correction Efforts has een done Methodology Use of priori information as constraint: Constrained BC (CBC) Implementation in VarBC Implementation in offline BC Experiments of CBC in GRAPES Consideration of imperfect QC: AMSUA Ch4 Consideration of imperfect model: AMSUA Ch9 Impact on forecasts Discussions and Further Plan J J, yhx y FSO: Forecast sensitivity to oservation Over or under ias correction could lead to negative impact

3 Background The ias correction is an ill-posed prolem: O-B? There is no asolute caliration of satellite instruments on orit There is no truth of the atmosphere How to separate oservation ias from model ias using O B? Two main issues Imperfect QC affacted BC: QC and BC interaction Window channel: cloud contamination Model ias Temperature sounding channel in stratosphere Trace gas sounding channel, e.g. IASI Ozone channels Developing models : GRAPES

4 Background Efforts een done for QC feedack Imperfect QC Warm tail for microwave window channel departures O B Cold tail for IR window channel departures O B Over correction on oservations y Least Square ased estimation Using mode Han and McNally 2008 Li,McNally and Geer, Jm d m pd n 2 ( ) ( i ) [ ( i)] 2n 1 Han and McNally,2008

5 Mean Based 2007D08JF,ECMWF,IFS Impact of over ias correction Mean: If ias is estimated y <O-B>, It will strongly depend on the QC, 0.7 =0.4; 0.1 =0.28 Mode Based METOP AMSUA CH4 f0xx_ Low cloud cover

6 Background Efforts een done for model error Using UNBIASED oservations Radiosonde mask (Eyre 1992) Radiosonde profile (Joiner and Rokke 2000;Kozo et al.,2005) GPS RO temperature sounding (Zou et al.,2014) VarBC using all other un-corrected oservations Derer and Wu 1998; Dee 2004; Auligne et al.2007 Anchor channel AMSUA Ch14 (McNally,2007) IASI ozone channel (Han and McNally,2010) Bias model selection: Constrain the freedom of ias predictor Freedom of the predictor Asorption correction (Watts and McNally 2004) Frequency correction (Lu et al.,2011)

7 How to separate oservation ias from O-B? Courtesy of Fiona Hilton,ITSC16

8 Radiance priori information: ias and uncertainty Han and McNally,2010

9 Connection etween BC and Caliration Account for the caliration uncertainty in BC Courtesy of Yong Han,2014,ITSC19

10 Methodology T 1 2 J( x, β) ( xx) Bx ( xx) T 1 ( β β ) B ( ββ ) [ y H x x β R y x x β T 1 () h(,)] [ H() h(,)] [ h(,) x β ] R [(,) h x β ] : Regularization parameter R β B 0 T : Priori estimate of oservation ias : Priori estimate uncertainty 0 : Background predictor coefficients : Background predictor coefficients uncertainty Adaptive Use of PRIORI information Radiometric Uncertainty RT model Uncertainty

11 Constrained Bias Correction (CBC) scheme T 1 2 J ( x, β) ( x x) Bx ( x x) T 1 ( ββ) B ( β β) [ y H x h x β R y H x h x β T 1 ( ) (, )] [ ( ) (, )] [ h( x, β) ] R [ h( x, β) ] T d y H ( x) Pβ h( x, β) β J ( x, β) B ββ PR dpβ P Pβ 1 T 1 T 1 ( ) [ ] R [ 1 T 1 T 1 1 T 1 T 1 ( B P R P P R P) β ( B β P R d P R 0) 0 ] βj ( x, β ) 0 Aβ z A B P R PP R P z B β PR d P R 0 1 T 1 T 1 1 T 1 T 1

12 VarBC, Regression BC and Constrained BC(CBC) Aβ z A B P R P P P 1 T 1 T 1 R z B β PR P 1 T 1 d T 1 R 0 0, 0, RI Pβ d Linear Regression BC 1, 0 1 T 1 J(,) ( ) [ ] VarBC β x β B ββ PR dpβ For the simplest example, with a gloal constant as predictor: P 1, β 0, R R N i 1 ( d ) i

13 Experiments of CBC in GRAPES Model ias Ch9 Warm tail Ch4

14 AMSUA CH4(Metop_A) 0, , 0.3(mod e) Model Bias Warm tail <O-B>ori BC <O-B>CBC <1-0>

15 AMSUA CH9(Metop_A) 1-10 June 2013 Model Bias 0, , 0 <O-B>ori BC <O-B>CBC <1-0>

16 Two months cycle experiments in GRAPES gloal May June 2013

17 Impact on Analysis: <T_grapes T_ncep>,20S 20N INT INTCBC

18 N.H. S.H. Zonal Wind N.H. S.H. Geo. Height

19 Impact of CBC on forecasts 60 cases, May 1 June 30,2013

20 Impact of CBC on forecasts Positive Impact Wind RMS Gloal Mean

21 Discussions and Further Plan Implementation of Constrained Bias Correction (CBC) scheme VarBC offline regression BC Capailities of CBC Considering imperfect QC Considering model ias important for developing models Important for trace gases Estimation and Tuning of the Priori Parameters Using mode as priori ias estimate Using other uniased os. to get Radiometric caliration uncertainty RT model uncertainty