AIRS Sounding and Cloud Property Study
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AIRS Sounding and Cloud Property Study. Xuebao Wu, Jun Li, Paul Menzel,Allen Huang In collaboration with CIMSS colleagues National Satellite Meteorology Center, Beijing, China CIMSS, University of Wisconsin-Madison, Madison, U.S.A. Mar.6, 2006. Outline. ( Clear Sounding Study)

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AIRS Sounding and Cloud Property Study

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Airs sounding and cloud property study

AIRS Sounding and Cloud Property Study

Xuebao Wu, Jun Li, Paul Menzel,Allen Huang

In collaboration with CIMSS colleagues

National Satellite Meteorology Center, Beijing, China

CIMSS, University of Wisconsin-Madison, Madison, U.S.A.

Mar.6, 2006


Airs sounding and cloud property study

Outline

( Clear Sounding Study)

1. Algorithm---Regression&Physical

2. Two Experiments

3. Validation

(Cloud Property Study)

4. MR Retrieval Method

5. Case Study: MPACE

6. Validation


Airs sounding and cloud property study

(Courtesy of Lee et al., 2005)


Part 1 clear ir sounding retrieval

Part 1. Clear IR Sounding Retrieval

Regression

Physical retrieval (regularization) which needs

--Radiance measurements and observation errors

--First guess from regression or other sources

--Fast Radiative Transfer Model

-- Others


Airs sounding and cloud property study

Regularization Inversion

Equations

Unknowns

Solutions

Newton Iteration

Discrepancy Principle (Li and Huang 1999)


Airs sounding and cloud property study

Discrepancy Principle

γ

Residual = Observation error


Airs sounding and cloud property study

394 AIRS Channels

1688 AIRS Channels


Airs sounding and cloud property study

Sept.6, 2002, G193

1km MODIS Cloud Mask


Airs sounding and cloud property study

Against

ECMWF


Airs sounding and cloud property study

500 hPa T difference

500 hPa q (g/kg) difference


Validation with match up dataset

Validation with match up dataset

  • Match up dataset at ARM SGP Site AIRS/Best Estimate (Sept. of July 2002 – Aug. of 2004) )

  • Use AIRS retrieval algorithm developed at CIMSS (regression + physical)


Airs sounding and cloud property study

Part 2 Cloud Property Study

Some features:

  • Minimum Residual Retrieval Method

  • Ping Yang’s fast cloud RT model

  • MODIS cloud mask and cloud phase to characterize the AIRS SFOV


Airs sounding and cloud property study

1DVAR algorithm for cloud retrieval

Observed AIRS Radiance Measurements

Background Information from MODIS

Fast Cloudy Radiative Transfer Model: coupled

CTP: Cloud-Top Pressure; ECA: Effective Cloud Amount

CPS: Cloud Particle Size; COT: Cloud Optical Thickness at 0.55µm

CTP and ECA: 720 – 790 cm**-1

COT and CPS: 790 – 1130 cm**-1

Minimum Residual (MR) algorithm for cloud retrieval


Airs sounding and cloud property study

MODIS Cloud Phase

( Courtesy of Chianyi LIU)


Airs sounding and cloud property study

AIRS CTH (m)

Barrow


Conclusion

Conclusion?

  • Clear sky sounding retrieval algorithm has been tested using AIRS data. Physical retrieval work reliably. One day MPACE study.

  • Ongoing works and Remaining issues(Esfc,BiasCorr)

  • Acknowledge: HalW, KevinB, JinglongL,SeeBor, DaveT


Airs sounding and cloud property study

Reference:

Wu Xuebao, Li Jun, Zhang Wenjian, and Wang Fang, Atmospheric Profile Retrieval with AIRS Data and Validation at the ARM CART Site, Advances in Atmospheric Sciences, 2005, Vol. 22, No. 5, 647–654.

Wu, X., J. Li, W. P. Menzel, A. Huang, K. Baggett, and H. Revercomb, Evaluation of AIRS cloud properties using MPACE data, Geophys. Res. Lett., 2005, 32, L24819.


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