Capabilities of IRS-MTG to sound ozone, CO and methane using ESA pre-phase A specifications

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1 Capabilities of IRS-MTG to sound ozone, CO and methane using ESA pre-phase A specifications Task 2: Ozone from a synergetic use of UV and IR radiances P. Coheur, C. Clerbaux, D. Hurtmans, J. Hadji-Lazaro, S. Turquety and R. van Oss Page 1

2 BACKGROUND Requirement on ozone: tropospheric column [Lelieveld, 2003, Golding et al., 2003] Operational Atmospheric Chemistry Applications Life: respiratory effects Threshold Target : 10 %, 10 km : 5%, 2km IRS Instrument requirements [MRD] IRS results on (tropospheric) ozone: threshold met UVS on MTG?? Page 2

3 OBJECTIVE To study the improvement to be gained on the retrievals of ozone profiles, in terms of accuracy and vertical resolution, from a synergetic use of IRS and UVS radiances. Ozone using UVS Ozone using UVS & IRS Sensitivity assessment (limited) Page 3

4 APPROACH Optimal Estimation Y: measurement vector X: state vector Y = F(x) + ε Bayes Theorem: P(x/y) := P(y/x) P(x) Gaussian statistics P(x OE /y) is maximal >> x OE = {analytic solution} Measurement noise A-priori Page 4

5 APPROACH (2) Combined measurement Y = {y 1, y 2 } measurement vector P(x/y) := P(y/x) P(x) = P(y 1 /x) P(y 2 /x) P(x) Y 1,2 independent = P(y 1 /x) P(x/y 2 ) = P(y 1 /x) P (x) A-priori = retrieval result using y 2 Page 5

6 APPROACH (3) Averaging Kernel x OE -x A = A (x true x A ) + ε Combined: x 1 -x 2 = A 1 (x true -x 2 ) + ε 1 DFS = Trace (A) (linear approach) substitute: x 2 -x A = A 2 (x true x A ) + ε 2 >>>> A 12 = A 1 + A 2 -A 1 A 2 DFS 12 = DFS 1 + DFS 2 Tr(A 1 A 2 ) Page 6

7 UVS / Spectral MTG / UVS OMI Spectral range (& O 2 A) nm nm Spectral resolution 0.4 nm nm Spectral sampling 6 1½ - 3 Signal to Noise Signal to Noise comparable but on more pixels / nm!! UVS: 0.07 nm; OMI: 0.32 nm Page 7

8 1.E+14 1.E MRD Reference spectra and Noise 1.E+12 1.E+11 1.E Page 8

9 NOISE Noise model Requirement Fit S/ N Fit Page 9

10 Algorithm: OPERA UV RETRIEVAL Developed at KNMI (van Oss, Tuinder, Spurr, van der A) Operational usage : GOME: ESA CHEOPS-GOME GOME2: O3MSAF, GOME2 Tools (CVF) OMI: ODPS Method On-line radiative transfer: lidorta Optimal estimation Page 10

11 Level 1 usage RETRIEVAL SETTINGS (1) Channel UVS-1A UVS-1B UVS-1C UVS-2 UVS-3 Wavelength range nm nm nm nm nm (IR: IRS-3 [ cm -1 ] ) Page 11

12 RETRIEVAL SETTINGS (2) STATE 30 layer-averaged ozone volume mixing ratio values. Layers are set at 2 km thickness, ranging from 0 to 60 km (top). The IR algorithm retrieves scaling factors w.r.t. to the initial and a-priori state. The UV algorithm retrieves layer column values APRIORI + INITIAL PROFILE global, yearly-averaged value from a model (MOZART) Covariance: A full 30 x 30 matrix representing the variation of ozone through all seasons and all latitudes and longitudes, derived from a model run (MOZART).. Page 12

13 RETRIEVAL SETTINGS (2) ATMOSPHERE Altitude, pressure and temperate are given at all 31 levels (fixed altitude grid: 0, 2,, 60 km). The (Lambertian) UV surface albedo is 0.05 The scene is cloud free and no aerosols are included. VIEWING Solar zenith angle at surface = 38 or 70 Line-of-sight polar angle at surface = 53 (NW Europe) Relative azimuth angle at surface 152 Page 13

14 O 3 A priori profile x a CO CH 4 O3 Altitude (km) Altitude (km) A priori covariance 18 matrix S a CO Altitude (km) Vmr (ppm) MTG Mission Team expert meeting on The UVS candidate mission, August , EUMETSAT, 28 August 2006 CH4 Altitude (km) Page E-3 0 1E

15 RETRIEVAL SETTINGS (3) RETRIEVAL One iteration -> Averaging kernel and error estimates are given for initial/apriori profile Additional 0.5% random measurement noise, to account for forward model & calibration errors Page 15

16 TESTS Test IR channels UV channels Solar zenith angle 0 IRS-3 None N/A 1 None UV1abc, UV2, UV None UV2, UV IRS-3 UV1abc, UV2, UV IRS-3 UV2, UV IRS-3 UV1 c, UV2, UV IRS-3 UV1 bc, UV2, UV IRS-3 UV1abc, UV2, UV 3 70 Page 16

17 ACCURACY / A-PRIORI ERROR REDUCTION Page 17

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28 TESTS sza TROPO3 error DFS IRS-3 None None IRS-3 IRS-3 None UV1abc, UV2, UV 3 UV2, UV3 UV1abc, UV2, UV 3 UV2, UV3 N/A % 6.1 % 9.9 % 5.0 % 8.2 % IRS-3 UV1 c, UV2, UV % IRS-3 UV1 bc, UV2, UV % IRS-3 UV1abc, UV2, UV % 7.1 Page 28

29 VERTICAL RESOLUTION / AVERAGING KERNEL Page 29

30 IR UV UV & IR Page 30

31 Conclusions Tropospheric ozone with UV only: almost meets Target (!) Error 6% Resolution 2-3 km Tropospheric ozone with UV & IR: meets Target Error 5% Resolution 2-3 km Higher solar angle: tropospheric information decreases rapidly, especially lowest layer Page 31

32 MRD UV noise req. are much better than G.S.O.G2. Spectral shape of MRD UV noise unrealistic A-priori covariance large: Now: global, all-season statistics Climatologies: 10 deg-latitude, monthly: smaller covariance Consequences for regularisation > convergence Page 32

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