Sentinel-5 precursor: TROPOMI Cloud slicing retrieval: Program development and testing with SCIAMACHY/GOME-2 WFDOAS data Kai-Uwe Eichmann, Mark Weber,

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Sentinel-5 precursor: TROPOMI Cloud slicing retrieval: Program development and testing with SCIAMACHY/GOME-2 WFDOAS data Kai-Uwe Eichmann, Mark Weber, IUP Bremen

Background TOZ: Total ozone / GVC: Ghost vertical column / CF: Cloud fraction

Input/output data Level 2 data –Total ozone TOZ [DU] (WFDOAS) –Ghost vertical column GVC [DU] (WFDOAS) –Cloud top height CTH [km] (SACURA or FRESCO) –Cloud fraction CF [-] (SACURA or FRESCO) Auxiliary data –Latitude/Longitude [deg] (Instrument) Derived data –Cloud top pressure CTP [hPa] Output data –Cloud slicing Ozone VMR (CSV) [ppmv] between CTH(min) and CTH(max)

CSL program development IDL program (M. Weber) using an iterative approach to deal with outliers in the data Speed increase with packing all WFDOAS data into one file per month, restricted to the tropics (25 deg): SCIAMACHY factor 12 (6 Min ->30 sec, GOME-2 factor 20: 20 to 1 min). FORTRAN 90 draft version is ready (linear least square only), unpacked data version takes about 3 Min. IDL version used for testing different parameters: –Cloud fraction = [0.8,0.9] –CTH(min) = [6, 7] km (5.5 km GOME-2) –Grid boxes: 5° Lat / [30°, 10°] Lon –Number of data per grid box: [15, 50] –Number of days: [6, 15, 30]

SCIAMACHY cloud top heights Gridcell

Results from SCIAMACHY WFDOAS CTH(min)=7km 2006/10: 30d of data CF(min)=90% Outliers vmr=slope*1.27E3

Two regimes of ozone Negative VMR due to change of ACCO during the month Thus monthly means are not the best choice Problem: ACCO time-dependent

Dividing into 6 days periods

GOME-2 results GOME-2 has about 4 times more measurements than SCIAMACHY. CTH is generally lower (FRESCO) than for SCIAMACHY (SACURA). Differences are about 3 km on average. This will have an effect on the calculated VMR (cloud slicing volume mixing ratio).

Comparison SCIA / GOME-2

Results Reducing the cloud fraction to 0.8: –increases the number of cloudy pixels by up to 40% depending on altitude. –The effect needs to be further analyzed. The height to pressure conversion is error prone, as the temperature profile is not taken into account. –The differences between pressures calculated with a scale height of 8 km or using the international barometric height formula are, depending on the altitude, quite different (up to 40 hPa at 15km = 40%). Using data from a whole month for the CSL calculation is in a lot of cases not the best choice, as the above cloud ozone may change considerably during the month.

Outlook Extent the parameter study, – e.g. SACURA vs. FRESCO Use sonde data to decide which parameters are best for the retrieval (see E. Leventidou) Precalculated data input to FORTRAN program Test the code with OMI data –different input parameter, definition of ACCO