The Retrieval of Infrared Cooling Rate Profiles from Thermal Infrared Remote Sounder Radiance Measurements

Transcription

1 The Retrieval of Infrared Cooling Rate Profiles from Thermal Infrared Remote Sounder Radiance Measurements Daniel Feldman Candidacy Presentation May 13, 2005

2 Outline 1. Background 2. Motivation 3. Cooling Rate Retrieval 4. Cross-Comparison Results 5. Future Research 6. Conclusions

3 1. Background: IR Cooling Rate Earth Radiation Budget Cartoon From Liou, 2002

4 Background: Total IR Cooling Rate MODTRAN 5 Calculated cooling rate profiles for 6 model atmospheres, cm ( z) & θ = ρ 1 ( z) C p df( z) dz

5 1. Background: Spectral Contribution to IR Cooling Rate: MLS ( z) θ & 10-3 K/day/cm -1 ν Clough et al, 1995

6 1. Background: Spectral Contribution to IR Cooling Rate: MLS.1 R ν ( z) = 0 ν 0 ν & θ max ν & θ ν ( z) ( z) dν dν 1 Pressure (mb) Wavenumber (cm -1 )

7 2. Motivation: Species Contribution to IR Cooling Rate 10 Pressure (mb) Heating Rate (K/day) From 1994 McMurdo Station Sounding Hicke et al, 1999

8 2. Motivation: CO 2 radiative forcing in stratosphere CO 2 increase impacts cooling rate profile and temperature in midupper stratosphere CO 2 ν 2 band cooling rate is largest component of IR cooling rate in mid- and upper-stratosphere. Need to understand role of radiative relaxation in polar regions during sudden stratospheric warming events and spring vortex breakup. Contribution to observed T (K), mbar Species O N/A N/A CO CO 2, CH 4, N 2 O, CFCs < Ramaswamy et al., 2001

9 3. Cooling Rate Retrieval: Concept

10 Liou & Xue, Cooling Rate Retrieval: Theory Relates cooling rate profile to angular radiance measurements for non-window H 2 O cooling y ν df ( ) ( z) Tν z dz 0 dz = Kν 0 * α I ν spec ν I ( z) & θ ( z) dz ( µ ) + β ( µ ) ν meas y θ ˆ& = α.*i = spec ( µ ) + β.* I ( µ ) T 1 T ( K K + γ H) K ( y y ) a

11 3. Cooling Rate Retrieval: Updates to Retrieval Methods Linear Bayesian update to a priori profile Redefine y, K K to include multiple zenith angle scans θ & Measurement metric defined in terms of maximum information content for cooling rate profile. Balance between spatial resolution and accuracy for cross-track scanning instruments y n y = θ& ˆ = ( ρ ( z) C ( )) pt µ n, z & θ ( z) dz = γ ni( n ) 0 [ y L y ] = µ 0 n ( ( ) ( ) ) T T K S y K S θ& 1 K S( y) y S( θ& ) & & + & + θ θ a ( ) 1 θ& θ a a

12 3. Cooling Rate Retrieval: Weighting Functions: MLS CO 2 ν 2 band 1 ( µ ) K θ = & 0 ρ max ( z) C pt( µ o, z) ρ ( z) C T( µ, z) ( ) p o 10 Pressure (mb) Wavenumber (cm -1 )

13 3. Cooling Rate Retrieval: Weighting Functions: MLS CO 2 ν 2 band 1 = K θ& ( ) K ( ) µ max µ θ& 0 % 10 Pressure (mb) Wavenumber (cm -1 )

14 3. Cooling Rate Retrieval: Signal Comparison y (W/m 2 /m) y y ( µ = 0 ) ( µ = 45 ) y (W/m 2 /m) y y y ( θ& ( mbar ) = + 0.1) ( µ = 45 µ = 0 ) () ε Wavenumber (cm -1 )

15 Grating spectrometer 4. Cross-Comparison: AIRS Instrument 2378 independent channels: cm -1 Polar-orbiting cross-track scanning instrument High level of calibration and validation Courtesy of JPL

16 4. Cross-Comparison: S-HIS Instrument AIRS vs. S-HIS: Different observation altitudes (AIRS is 705km, SHIS is ~20km on ER2, ~14km on Proteus). Different view angles (AIRS is near nadir, SHIS is ~±35deg from nadir & zenith). Different spatial footprints (AIRS is ~15km at nadir, SHIS is ~2km at nadir). Different spectral response (AIRS ν=ν/1200, SHIS ν=~0.5 cm -1 ) and sampling. AIRS SHIS and AIRS SRFs SHIS Revercomb et al., 2004

17 4. Cross-Comparison Scanning HIS/WB57 Aura Validation Experiment (AVE) S-HIS scans cross-track downward &looks upward 26 October 12 November 2004 Left Wing Pod Revercomb et al., 2004

18 4. Cross-Comparison: Scanning HIS/Proteus Mixed-Phase Arctic Cloud Experiment (MPACE) Revercomb et al., September-18 October 2004

19 4. Cross-Comparison: Specifics Starting point for retrieval: state vector & associated errors from AIRS L2 product T, H 2 O, O 3, T surf, ε surf From S-HIS zenith & nadir spectra, perform T & CO 2 retrieval, calculate cooling rate profile & error. Retrieve cooling rate profile from AIRS L1B product.

20 1 AVE cooling rate profiles: a priori, in situ retrieved, remote retrieved AVE: 24.8 N, E, Pressure (mbar) Good agreement to ~20 mbar Surface problems: SST skin BT Spectral emissivity No Jacobian coverage in upper stratosphere Cooling Rate (K/day) Cooling Rate (K/day) AIRS S-HIS Prior estimate

21 1 MPACE cooling rate profiles: a priori, in situ retrieved, remote retrieved MPACE: 62.7 N, E, Pressure (mbar) Good agreement in lower stratosphere only A priori state vector problems, more isothermal atmosphere, ice covered surface Cooling Rate (K/day) Cooling Rate (K/day) AIRS S-HIS Prior estimate

22 5. Future Research: Larger-scale CO 2 cooling rate analysis Theory: Understand mapping from state vector component error to cooling rate error. Validation: Radiosondes: mb T<0.5 K RH<5% More S-HIS validation experiments Operation: Angular weighting coefficient tables Granule radiance subsetting Science Analysis of sudden-stratospheric warming events Polar spring and fall cooling rate variation Relative contribution of strong radiators to total lower stratospheric cooling rate.

23 Advantages: 5. Future Research: CO 2 Cooling Rate from AIRS and IRIS-D Long base-line for comparison: CO 2 ~ 60 ppmv T ~ -2K O 3 column decrease H 2 O increase Expected change in lower- and mid stratospheric CO 2 cooling rate ~ 0.5 K/day Disadvantages: No cross-track scanner on IRIS-D Meaningful cal/val more difficult for IRIS-D

24 5. Future Research: Water Vapor Cooling Current instruments insensitive to H 2 O rotational band (0-600 cm -1 ) FIRST (Kratz et al. 2005) and other instruments may allow for observation of non-window cooling. Continuum model questions Window region affects clear-sky surface cooling Non-window region affects mid-troposphere cooling

25 5. Future Research: Mineral Dust Cooling Dust signature detectable in AIRS data Large signature in forward cooling rate calculations Non-isotropic source function Clouds vs. Dust Knowledge of T surf and ε surf (ν)essential TES instrument may be useful & θ : & θ : cm cm 1

26 Dust signature in angular radiances Dust signature detectable in AIRS data Detectable signature in forward cooling rate calculations I = I clear I dust K Cross-Track Scan Angle (Degrees) Wavenumber (cm -1 )

27 Dust signature in angular radiances Dust signature detectable in AIRS data Detectable signature in forward cooling rate calculations K clear θdust y = & & n ( µ n ) θdust K dust ( µ n ) K dust ( µ n ) θ& dust % Cross-Track Scan Angle (Degrees) Wavenumber (cm -1 )

28 6. Conclusions Thermal IR flux vertical distribution determines local radiative forcing. Cooling rate retrievals are a novel utilization of angular radiance information. Cross-comparison of coincidental data for CO 2 cooling rate retrieval shows promising results. Understanding cooling rate profile error budget is imperative Retrieval of cooling rates due to other atmospheric constituents may be possible (with other instruments) TES: Window H 2 O and mineral dust FIRST: Non-window H 2 O

29 Caltech: Yuk Yung Run-Lie Shia Xun Jiang Jack Margolis UCLA: Kuo-NanLiou JPL: Dave Rider Annemarie Eldering Brian Kahn University of Wisconsin: Dave Tobin Spectral Sciences: LexBerk NCAR: Natalie Mahowald Acknowledgements