Rutherford Appleton Laboratory Remote Sensing Group Tropospheric ozone retrieval from uv/vis spectrometery RAL Space - Remote Sensing Group Richard Siddans,

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Rutherford Appleton Laboratory Remote Sensing Group Tropospheric ozone retrieval from uv/vis spectrometery RAL Space - Remote Sensing Group Richard Siddans, Georgina Miles Brian Kerridge, Barry Latter 21 st May 2014 TEMPO 2 nd Science Meeting, Hampton, VA

Remote Sensing Group RAL Remote Sensing Group Development and application of retrieval schemes to retrieve trace gases, aerosol and cloud from satellite observations Ozone: –Munro et al., 1998 (Nature), demonstrating first tropospheric ozone profiles –Role in GOME series (& MAG) since ~1990 –Involved ESA’s Climate Change Initiative Essential Climate Variable programme –Developing NRT initiative for MACC/Copernicus Atmosphere Service –Involvements in Operational ESA Sentinals 4, 5 and 5 Precursor (S4 & 5 MAG) © 2010 RalSpace

Remote Sensing Group RAL UV Ozone Profile Processor 3-step retrieval (Hartley bands, surface albedo, Huggins bands) Designed to fit to high precision in Huggins bands required for tropospheric ozone information Currently optimised for GOME, SCIAMACHY and GOME-2A/B Selected as ESA Ozone CCI prototype nadir profile processor for sensitivity to tropospheric ozone Algorithm validation paper about to be submitted to AMTD (Miles et al, 2014) A joint IASI+GOME-2 (IR+UV) version is available, currently developing Chappuis add-on. January 2008 Surface - 450hPa ozone 2008 J F M A M J J A S O N D

Remote Sensing Group Ozone retrieval from the Chappuis bands Why? –Sensitivity to near-surface ozone in visible region –Typically less Rayleigh scattering/brighter over land than in UV Why not? –Broadband ozone feature (1 piece of information, not profiles on its own) –Works in theory, but it’s hard to do in practice. Many other spectral patterns to interfere with ozone fit: –Surface/scattering/other gases/water vapour… –Instrumental ‘features’/spectroscopic errors…

Remote Sensing Group Ozone retrieval using the Chappuis Bands for near-surface information UV+Vis retrieval simulations indicate a signal to noise ratio of ≥300 is needed to add information to the UV-only profile retrieval This implies a Chappuis-only total column fit precision of 2-4DU is required for Chappuis bands to add useful information on near-surface ozone to UV profile retrieval Dark surface in Chappuis region Over ‘grass’ surface type (Miles et al., 2012) Simulated AKs AK 0-2km 0-6km 6-12km

Remote Sensing Group Chappuis-only DOAS slant column fit Spectrally averaged GOME-2A B3/4 measurements ( nm) WL range after Richter et al, 2012 Fit 7 leading principle components from land spectral databases (ASTER/USGS) Further spectral patterns to fit: –O 2, O 3, O 4, H 2 O(2), NO 2, Ring(2), liquid water, registration/shifts parameters(2),, air molecule Ring effect(2) and polynomials to represent Rayleigh, cloud and aerosol scattering All parameters are fit in a straightforward least squares manner. A third order polynomial is subtracted from all patterns (other than the fitted polynomial. patterns). © 2010 RalSpace

Remote Sensing Group Visible-only DOAS retrievals of total column ozone with GOME-2 Spectral fitting for ozone is challenging in the Chappuis bands, mostly due to surface effects – so lots of things need to be fitted! → See O3MSAF VS Report for details (Miles et al., 2012) reports.html reports.html

Remote Sensing Group Column fit results

Remote Sensing Group Principle of combining UV+Vis information Information from Chappuis only yields 1 piece of information Use RT simulations using RAL UV-retrieved ozone profile to predict relative light-path sensitivity in UV and Chappuis (AMFs) Combine with total column Chappuis fit to inform UV profile in further (linear) retrieval step RT simulation AMFs at different wavelengths 550nm 325nm 340nm 450nm 760nm With cloud

Remote Sensing Group Combining UV+Vis information x UV+Vis = x + (S x -1 + K t S y -1 K) -1 K t S y -1 (y-Kx) x, S x : UV retrieved profile and covariance y, S y : Chappuis column and fit error K: weighting functions that map x onto y Use linear retrieval step to combine information including AMF as weighting function: GOME-2 profile

Remote Sensing Group Impact on surface ozone number density UV+VisUV-only Cloud screened All land pixels Difference 20% CF 2km CTZ

Remote Sensing Group Next Steps UV+Vis ozone profile retrievals: –Process more data –Plenty of scope for improving quality of Chappuis slant column fit –Improvements expected to forward model for linear step We note the gap in spectral coverage in Chappuis bands for TEMPO –This technique probably won’t work with TEMPO spectral gap. GOME-2B/C will continue to provide data –0-2km ozone subcolumn target will be very challenging This work will be actively progressed in the coming months within UK National Centre for Earth Observation at RAL We intend to support TEMPO in parallel to S4 and other European missions © 2010 RalSpace