FY-3 satellite data tuning and assimilation Qifeng Lu

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The 4th THORPEX-Asia Science Workshop and 9th ARC Meeting

FY-3 satellite data tuning and assimilation

Qifeng Lu

National Satellite Meteorological Center, CMA, BeijingEmail: [email protected]

ECMWF

Thanks to all who contributed to this work

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Outline

Microwave sounding data in NWP and climate research: operational satellites from the US, Europe & China : 1978-2020

China’s FY-3A satellite: The Microwave Temperature Sounder (MWTS)

Identifying and characterising MWTS biases using NWP fields:

Passband shifts

Radiometer non-linearities

Improved Assimilation of MWTS

Initial Assessment of FY-3B

Summary and conclusion

Next Steps: Early results from the evaluation of MSU and AMSUA from 1978-2011

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US

Europe

China

• Microwave sounding data provides information on temperature and humiditywhich has been widely used in :

• Operational NWP data assimilation systems and;• Climate research – to determine long term trends in atmospheric state

• The US has launched a series of polar satellites, dating back to 1978;• Europe began to contribute in 2006 (MetOp-A)• China began to contribute in 2008 (FY-3A)

Operational Sounding Satellites

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The importance of MW sounding data in NWP

Largest positive impact (per system)is obtained from microwavetemperature sounding data

Forecast sensitivity toobservations (FSO)Is an adjoint based technique for assessing the influence of observing systems on forecast accuracy

(from C. Cardinali, ECMWF)

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The 4th THORPEX-Asia Science Workshop and 9th ARC Meeting 5

ok

Microwave TemperatureSounder (MWTS)4 channel (~MSU)

Microwave HumiditySounder (MWHS)5 channel (~MHS)

InfraredAtmospheric Sounder(IRAS) 20 channels (~HIRS/3)

Microwave Radiation Imager10 channels (~AMSR-E)

The FY-3A/B Instrument Suite

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Approach involves a comparison of observations (OBS) with simulated observations based on short range (up to T+9 hour) forecast fields (‘First Guess’, FG) and radiative transfer modelling → ‘FG departures’

FG is ‘proxy’ for truth → ‘FG departures’ (OBS – FG) indicate error in the measurements or RT modelling

High accuracy of the NWP fields results from the large & diverse range of observations assimilated (MW sounders, Advanced IR sounders, GPSRO, radiosondes … etc)

Able to detect biases at ~0.1K level for temperature sounders (MWTS and IRAS), sensitivity slightly lower for MW humidity sounders & imagers (~0.5K)

Similar work ongoing at NOAA/NCEP, UK Met Office and DWD

Initial Data Quality Assessment at ECMWF:General Approach

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Initial FY-3A Evaluation

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Microwave TemperatureSounder

Microwave HumiditySounder

Infrared Sounder

Microwave Imager

STDEV (first guess departures):measures the misfit between model & measurement (in TB

space)

FY-3A data quality is comparable with MetOp/Aqua equivalents

Initial Data Quality Assessment at ECMWF:Comparison of FY-3A with MetOp & Aqua

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Full System OSEs: Full System + FY-3A VASS suite (MWTS, MWHS, IRAS)T511, 3 month experiment

positiveimpact from FY-3A

The impact of the FY-3A data is :

• neutral in SH

• slightly positive in the NH

Initial Data Quality Assessment at ECMWF:Assimilation Experiments

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Characterising MWTS biases using NWP fields

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Comparison of MWTS and AMSU-A Brightness Temperatures

State dependent inter-satellite (MWTS vs AMSU-A) biases:

Region 1 (tropics): MWTS TBs warm relative to AMSU-ARegion 2 (high northern latitudes) : No significant bias

Brightness temperature map from cycle 2008091700

Characterize the MWTS

1

2

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Schematic of error terms

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MWTS-2 MWTS-3 MWTS-4

First Guess Departures (K) ,i.e.,Observation minus Simulation

Pre-launch measured passband

Optimised passband

• from line-by-line modelling• uncertainties of ~32-55 MHz detected and corrected

Non-linearity corrected

AMSU-A equivalent

Characterising the FY-3A MWTS:Detecting and Correcting passband errors and Non-linearities

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Characterising the FY-3A MWTS:Assessing corrections in the CMA-GRAPES model

Pre-launch measured passbandOptimised passbandOptimised + non-linearity corrected

→ the corrections, developed at ECMWF, improve the (OBS-GRAPES_MODEL) fits.

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MWTS OSEs Forecast Verification: Z at 200, 500 and 700 hPa

Improvementdue to MWTS data

Normalised differences in RMSErrors in Z, verified against own analysis90% confidence intervals shown

Small improvementsin SH in going from:

original data

→ recalibrated (low weight)

→ recalibrated (high weight)

NH close to neutralwith some benefit in recalibrated data

PRELAUNCH_MWTS(full system + original MWTS data)

HIOBSERR_MWTS(Full system + optimised MWTSwith low weight)

LOWOBSERR_MWTS(Full system + optimised MWTSwith high weight)

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MWTS: current status

Ground system changes implemented at CMA, March 2011

STD of 0.2 K is normally monitored

MetOp AMSU-A Ch. 9FY-3A MWTS-4

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Initial FY-3B Evaluation

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FY-3B MWTS FG DepartureChannel 3: 54.072 GHz

• Correction of passband measurement bias and radiometer non-linearity has been implemented in pre-processing at NSMC/CMA

• No significant problems with the MWTS-2 and -3 observations

• Cross scan bias is dominant & accounts for non-gaussian FG departures (corrected by variational bias correction scheme):

After VarBCSTDEV(O-FG) = 0.17 K

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FY-3B MWTS FG DepartureChannel 4: 57.3353 GHz

• Strong cross scan biases & regional biases detected

•

• Variational bias correction unable to significantly reduce these biases

• Work is ongoing to improve the correction of these anomalies

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MWTS FG Departure

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Summary FY-3A data has been evaluated at ECMWF through a comparison with simulated

radiances & full assimilation experiments in which FY-3A data is introduced in the

ECMWF system.

The study revealed, and corrected, biases in FY-3A MWTS related to :

Uncertainties in the passband centre frequencies

Radiometer non-linearities

These corrections bring the MWTS data close to the quality of equivalent AMSU-A

data & in assimilation experiments this MWTS data delivers improvements in forecast

accuracy.

The high value of NWP in Cal/Val of new satellite sensors has been clearly

demonstrated – further improvements in FY-3A and FY-3B data are expected, and it is

hoped NWP will again play a crucial role for FY-3C, …. FY-3G !

A powerful new general approach to diagnosing an important group of biases

affecting microwave sounders has been developed.

This work demonstrates the significant benefits of close collaboration between

satellite agencies and NWP centres.

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Next Steps: Initial results from an evaluation of MSU and AMSUA from

1978

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MSU CH3 (54.96 GHz): NOAA-6 to NOAA-14Fr

eque

ncy

Shift

/ M

Hz

STD

(FG

_DEP

)Im

prov

emen

t in

STD

(FG

_DEP

)

• LbL modelling based on ERA-Interim fields• 1 cycle per month: 1979 -2011

•Blue dots represent FG_DEP after shift correction•Colour dots before

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Finally … Thanks !

We would also like to acknowledge the contribution of colleagues from across the world (from CMA, ECMWF, UK Met Office and others besides) who made this work possible

And finally - thanks to the local organizing committee for their hospitality here in the wonderful city of Kunming !

Documents

FY-3 satellite data tuning and assimilation Qifeng Lu