# Presentation: 547712

## Assimilation of SSM/I radiances in NCEP global data assimilation system 

- Kozo Okamoto (EMC, UCAR,JMA
-            EMC seminar   March 1st, 2005

## Outline

- Background
- Methodology
- Thinning
- Observation error
- Quality Control (QC)
- Bias Correction (BC)
- Impact on analysis and forecast
- Conclusion and Future plans

## Background

- SSM/I measurement contains accurate moisture and land/ocean surface information
- In the NCEP global data assimilation system,
- SSM/I retrieved ocean surface wind speed and precipitation are assimilated
- No atmospheric information in rain-free areas is used.
- TCWV had adversely affected Hadley Circulation
- SSM/I radiance assimilation has the advantage of
- Consistency with the processing other satellite radiances
- Better vertical distribution of obs information using weighting function in RT model (and B)
- Processing the moisture and surface wind signal together
- Ref : Other Moisture-related measurements used are (as of Feb 2005)
- AMSU-A/-B, HIRS, MSU, GOES sounder radiances
- Radiosondes
- Similar data sources
- AMSR-E, SSMIS, WindSAT
- CMIS, GPM,,,,

## Target data

- SSM/I onboard DMSP-13, -14, and -15
- “clear” radiances
- not contaminated by cloud/rain
- RT code with OPTRAN does not account for cloud/rain at the moment.
-  over ice-free ocean
- Difficulty in estimating cloud liquid water (CLW) over land and sea-ice

## Methodology

## Thinning

- Thinning distance: 160km
- Foot print size = 69X43km at 19GHz, 15X13km at 85GHz
- Operational model resolution : T254(50km)
- Ref:
- AMSU-A:145km, -B:240km, HIRS:180km, AIRS:150km

## Observation error

- Estimate from O-G statistics
- O-G: Tb observed – Tb simulated from guess profile
- bias corrected O-G std * Sqrt(2/3)
- Deblonde (2001): assume O^2=G^2=F^2
- Period: Jul. 1 to Aug. 20, 2003
- Ref: (as of Aug2004)
- AMSU-A1(23.8GHz),-A2(31.4),-A3(50.3),-A15(89): 9.0K
- AMSU-B1(89):9.0K, -B2(150):4.0K
- Adjust obs. error accounting for sensitivity to skin temperature and emissivity
- Same as other radiance data

## Quality Control (1)

- Reject mislocated points
- Reject points over land/coast/ice-sea
- A priori check
- Reject points with TB<70K or TB>320K for any channel
- Reject points with Tb_v<TB_h+2.0K for either 19, 37 or 85 GHz
- Rain check
- Reject points when Scattering Index (SI) > 10
- Ferraro (1997)
- SI=a+b*T19V+c*T22V+d*T22V^2-T85V
- Points with large SI are thrown away at thinning step

## QC (2)

- Cloud check
- Reject channels when CLW>CLW0(ch)
- CLW is retrieved based on Weng et.al.(1997)
- CLW0(ch) is predefined so that liquid water absorption at each frequency is equal to that for CLW=0.1 kg/m^2 at 37GHz
- Cloud.absorption=k(ch)*CLW0(ch) = k(37GHz)*0.1, Rayleigh approximation
- k(ch): abs coefficients at observation frequency
- CLW criteria of 0.1kg/m^2 is based on English et al. (2000)
- CLW0=0.35(19GHz), 0.27(22GHz), 0.10(37GHz), 0.024(85GHz)
- => The higher frequency, the more rejected
- Gross check
- Basically same as other radiance obs
- Reject channels with |O-G|>3*obs.error or 6.0K
- Num of data which passed all QC is about
- 4700 (95%), 4300(87%), 4500(92%), 4100(84%), 3800(78%), 2800(57%), 2500(51%) for ch1-7

## QC (3): example of data use/rejection

- DMSP15 00UTC 01 Jul 2004

## QC (4): example of data use/rejection

- DMSP15 00UTC 01 Jul 2004

## Bias Correction (1)

- Same formula as AMSU-A
- Slowly varying component
- Calculated at each scan position from latest 30 days O-G datasets, and updated at every post-analysis step
- Air-mass dependent component
- Linear regression with 5 predictors :
- Constant
- Scan angle path => set 0 for SSM/I
- CLW
- dT*dtau : weighted lapse rate
- (dT*dtau)^2
- dT:temperature lapse rate, dtau:tau difference (=weight)
- Regression coefficients are optimised as analysis variables
- Dominant predictors for SSM/I
- CLW & lapse rate

## G-O vs. CLW

- Retrieved CLW vs. G-O for data of 6h time window

## BC (2) : G-O histogram

- DMSP15   July2004
-        before bias correction
-        after bias correction

## BC(3): G-O monthly mean:  left w/o BC, right w BC 

## Impact of SSM/I radiance assimilation

## Cycle experiment configuration

- System
- Analysis: GSI (released in Dec. 2004)
- Forecast: operational
- Resolution: T254L64 (FT0-FT84), T170L42(FT84-FT180)
- Data
- Cntl: same as operational
- Test: Cntl + SSM/I radiance (DMSP13,14,15)                – SSM/I ocean-surface-wind-speed retrieval
- Developed emissivity jacobian model with respect to wind for MW ocean emissivity model
- Period: 00UTC UTC 1 Jul – 18UTC 31 Aug 2004

## 1st Anal difference Test-Cntl

- 1st Anal difference Test-Cntl

- Lev=0.85

## 1st Anal difference Test-Cntl

## Anal Test-Cntl : 1 month later

## Anal Test-Cntl : 2 months later

## Time series of initial TCWV

- Moistening
- NH(+0.5mm)
- Tropics(+0.8mm)
- Drying
- SH(-0.3mm)

## Time series of precipitation at 00-06h

- Increases rain in
- NH(+0.1mm)
- Tropics(+0.2mm)
- Decreases in
- SH(-0.1mm)

## RMSE/BIAS of Anal/Guess: T[K] against RAOB  

## Time series : T RMSE at 700hPa in the tropics

**Number used **

## RMSE/BIAS of Anal/Guess: W[m/s] against RAOB

## RMSE/BIAS of Anal/Guess: Q [g/kg] against RAOB

## RMSE/BIAS of F24/F48 : T [K] against RAOB

## RMSE/BIAS of F24/F48 : W [m/s] against RAOB

## RMSE/BIAS of F24/F48 : Q[g/kg] against RAOB

## Fcst scores against anal up to 7 days (500Z) in NH/SH

## Daily Fcst scores of 5 day forecast for 500Z in NH/SH 

- Test outperforms cntl for many cases
- However, several cases show worse scores.

**better **

**worse **

**better **

**worse **

## Fcst scores against anal up to 7 days in the tropics

## Daily Fcst scores of 3 day forecast for 200/850 wind vector in the tropics

- RMSE is reduced for almost all days

**better **

**worse **

**better **

**worse **

## Evolution of forecast rain up to 7 days

- Monthly mean of 6h average rain in July
- In tropics, spin-up is reduced.
- Impact retained up to 1-2 days

## Mean 6h-average rain at 6 hour forecast

- Monthly mean of 00/06/12/18UTC in July
- Intensifies rain in ITCZ and SPCZ

## Evolution of forecast TCWV up to 7 days

- Monthly mean of TCWV in July
- Impacts remains in the forecast
- Up to 7 days in NH
- Up to 3 days in SH
- More than 7 days in the tropics
- Ref: Gerard and Saunders (1999)
- Up to 3 days in SH
- Less in NH and tropics.

## Mean TCWV at initial of forecasts

- Monthly mean of 00UTC in July
- Moistens mid-NH and tropics
- Drys mid- and high- latitude SH

## Is drying in mid- to high- latitude of SH correct?

- Compare test and cntl for AMSU-A1 onboard NOAA15 (sensitive to TCWV)
- Monthly mean of G-O from QC-ed & w/o BC datasets
- G-O is reduced globally
- Positive G-O suggests that negative obs bias or wet model bias
- Decreased moisture decrease G
- If obs bias is smaller than model bias, moisture field get closer to truth

## Disrupt Hadley Circulation? : vertical wind 

- Disrupt Hadley Circulation? : vertical wind

- Monthly zonal mean average of dP/dt [hPa/s] in the 2nd month
- F06/Anal[-12, 12hPa/s]
- Diff[-1.2,1.2hPa/s]
- Not significant changed
- shifted toward equator?
- Slightly smaller in |anal-F06|
- Structure is better kept for 6h forecast

**EQ 10N**

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## Conclusion

- A scheme to assimilate SSM/I clear radiance over ocean has been developed.
- QC and BC procedures are crucial for the performance.
- Accurate CLW retrieval algorithm is needed because CLW is used for both procedures.
- Impacts
- In the NH summer, adds moisture in NH and tropics and reduces in mid- to high- latitudes of SH.
- Moisture added in the tropics may be excessive. However, it reduces model spin-up in the tropics and substantially improves dynamic fields.
- Reducing moisture in the SH makes better fit for AMSU-A water vapour channels.
- Average forecast scores are improved in NH/tropics/SH up to 7 days in spite of some bad cases.
- No Hadley circulation disruption after 2 months run.

## Future plans

- Case study
- Investigate what caused poor forecasts
- Experiments of the NH winter (Jan2005)
- Extend to other MW instruments
- AMSR-E : low frequency ch can relax rain QC
- SSMIS  : how to handle 4 type instruments?
- Independent QC and BC?

## Supplemental slides

## SSMIS G-O : selected ch from all data over ocean

## QC (5): example of data passed/rejected by each QC

**rain**

**cloud**

**gross**

- 4000

- 4000

- 4000

- 4000

- 3000

- 2500

- 2500

## Bias correction (2)

- Alternate or additional predictors are needed?
- For example, moisture or emissivity dependence
- Attempts to include (weighted) TCWV have not made difference.
- (weighted) TCWV has high correlation weighted lapse rate. => colinearity problem
- Weighted lapse rate is correlated to moisture field for MW window channels.
- Emissivity itself, Ts or Ts*emissivity does not have clear relation with O-G.
- Relatively unstable to convergence
- How to get initial value of the coefficients?
- (1). determine tentative values based on least square method
- (2). run 1month BC-cycle starting from (1)

## O-G-CLW vs. lapse rate or (weighted)TCWV

- Similar dependence on lapse rate, TCWV, and weighted TCWV
- High correlation between lapse rate and (weighted)TCWV (around 0.8)
- May cause a colinearity problem

## Time sequences of CLW coefficients

## Corrected amount 

- w/oBC-wBC for O-B

## Disrupt Hadley Circulation? : Northward wind 

- Disrupt Hadley Circulation? : Northward wind

- Monthly zonal mean average of V [m/s]
- F06/Anal[-4K, 4K]
- Diff[-0.4K,0.4K]
- Also, not significant changed
- Weaken in the north side at 200hPa?

**40S**

**40N**

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**40N**