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Status report: Level 2 project Bruno Carli IFAC - CNR (Italy). Contributing Institutes IFAC-CNR - Italy University of Bologna - Italy ISAC-CNR - Italy IMK - Germany University of Oxford - U.K. University of Leicester - U.K. LPPM - France Instituto de Astrofisica de Andalucia - Spain.
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Status report: Level 2 project Bruno Carli IFAC - CNR (Italy)
Contributing Institutes • IFAC-CNR - Italy • University of Bologna - Italy • ISAC-CNR - Italy • IMK - Germany • University of Oxford - U.K. • University of Leicester - U.K. • LPPM - France • Instituto de Astrofisica de Andalucia - Spain
Contents • Introduction • - Operations of Level 2 • - Level 2 approach • - Level 2 Commissioning Phase objectives • Preliminary L2 Commissioning Phase activities • - Baseline verifications • - Tuning • - Preliminary L2 performances • Evolution of algorithm baseline • Conclusions
Introduction Operations of Level 2 Level 2 Calibrated and geolocated spectra Retrieved profiles • Retrieved vertical profiles of : • altitude correction and temperature (p,T retrieval) • VMR of minor constituent (H2O, O3, HNO3, CH4, N2O and NO2)
Introduction Level 2 approach • Use of micro-windows
Introduction Level 2 approach • Use of micro-windows • Use of non-linear least-square fit
Introduction Level 2 approach • Use of micro-windows • Use of non-linear least-square fit • Global fit of • limb scanning sequence
Introduction Level 2 approach • Use of micro-windows • Use of non-linear least-square fit • Global fit of • limb scanning sequence • Sequential fit of species
Introduction Level 2 approach • Use of micro-windows • Use of non-linear least-square fit • Global fit of • limb scanning sequence • Sequential fit of species • Near real time operation
Introduction Objectives of Level 2 Commissioning Phase • To verify assumptions of algorithm baseline • To Tune processor set-up parameters for robustness, accuracy and time efficiency • To assess performances • To consider and test options for evolution of the algorithm baseline
Level 2 Activities Diagnostics and baseline verifications • Intensity calibration
Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration
Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration • ILS calibration
Height correction vs horizontal gradient Correlation coefficient = - 0.0196 Probability for Delta(z) e gradT to be uncorrelated = 58 % Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration • ILS calibration • Assumption of vertical profile
Retrieval with engineering LOS information Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration • ILS calibration • Assumption of vertical profile • Use of LOS info
Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration • ILS calibration • Assumption of vertical profile • Use of LOS info • Altitude independent instrument offset
Level 2 Activities Diagnostics and baseline verifications • Intensity calibration • Frequency calibration • ILS calibration • Assumption of vertical profile • Use of LOS info • Altitude independent instrument offset • Local Thermal Equilibrium
Level 2 Activities Difference between temperature retrieved with and without LTE assumption
Level 2 Activities Tuning • Performed the tuning of • convergence criteria • Marquardt parameters • Altitude range of fitted continuum • FOV modelling
The time for the full analysis (62 available scans of the 75 made in one orbit) is less than one hour on a COMPAQ ES45 Server with 2 CPU at 1000 MHz. Preliminary L2 Performances Performances of orbit #504 retrievals
Preliminary L2 Performances Results of orbit #504 retrievals Temperature [K] Altitude [km] Orbital coordinate [deg]
VMR (ppmv) Water vapour Ozone N2O Altitude [km] CH4 HNO3 NO2 Orbital coordinate [deg] Preliminary L2 Performances Results of orbit #504 retrievals
Temperature profile error budget Preliminary L2 Performances Error budget
Preliminary L2 Performances Averaging Kernels The Averaging Kernels are tabulated in the case of the nominal measurement scenarios for a set of latitude ranges and seasons.
Evolution of algorithm baseline Implemented in prototype • The delay of Envisat launch was used to implement in prototype some options that were identified as possible critical points: • handle sweeps at low altitudes & low latitudes by constraining correction of profile in pT • handling of single microwindow OM in the case of regularisation • recursive pT & H2O retrievals • cloud detection and filtering of L1B input during L2 pre-processing
Evolution of algorithm baseline Cloud top height
Evolution of algorithm baseline Implemented in scientific code • Some changes are implemented in the scientific code in order to assess their relevance : • use of a tunable scaling factor for the definition of the unknown of the continuum • correction of negative VMR profile points • modification in the numerical correction of the singularity at tangent point • extension of minimum retrieval altitude from 12 to 6 km
Evolution of algorithm baseline Extension of retrieval to 6 km altitude
Evolution of algorithm baseline Possible future changes for scientific code • As a result of ACVT activities other changes may be considered for the scientific code, e.g. : • check that a consistent definition of continuum parameters is used in the case of retrieval range defined by cloud detection • linear vs polynomial interpolation for FOV convolution • improved modelling of troposphere for extension of retrieval to 6 km • additional outputs ( continuum profiles, cloud indices, initial guess profile, product confidence data)
Conclusions (1/2) • Results are based on preliminary analysis • Some improvement of intensity calibration. Level 2 is affected by intensity calibration errors and cannot easily detect them. • A frequency calibration much better than requirements is possible. Level 2 is little affected by frequency calibration errors and can accurately detect them. • A very small bias is observed in ILS determination • Good agreement between calibration diagnostics of Level 1 and Level 2.
Conclusions (2/2) • Assumptions made in code development are verified with real data (small and altitude independent instrument offset, use of LOS information and hydrostatic equilibrium, LTE) • A small number of iterations is sufficient to reach convergence • Our error budget is slightly overestimated • Retrieval is robust • Details are being considered for baseline changes.