Water Vapour Column Density Time Series from the GOME, SCIAMACHY and GOME-2 Instruments
Grossi, Margheria¹; Valks, Pieter¹; Slijkhuis, Sander¹; Loyola, Diego¹; Aberle, Bernd¹; Beirle, Steffen²; Mies, Kornelia²; Wagner, Thomas²; Gleisner, Hans³; Nielsen, Johannes³; Lauritsen, Kent^3
1DLR, GERMANY; ²MPI-C, GERMANY; ³DMI, DENMARK

The knowledge of the effective total column water vapour (TCWV) is fundamental for climate analysis and weather monitoring as well as for the improvement of the water vapour product derived by postprocessing of satellite data. In the framework of the ESA DUE GlobVapour project and EUMETSAT's Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF), we perform a series of validation activities aimed to estimate the absolute accuracy and the long-term stability of H2O columns retrieved from GOME-type instruments.
We use the recently reprocessed TCWV datasets from the GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/MetOp-A and GOME-2/MetOp-B instruments generated by DLR using the GOME Data Processor (GDP) version 4.6 integrated into the UPAS system. Measurements are carried out in the visible part of the solar spectrum and present a partly cloud corrected global dataset that is available over both land and ocean. The retrieval algorithm is based on a classical DOAS method (developed by MPI-Mainz) to obtain the trace gas slant column. Subsequently, the vertical column is derived, making use of the simultaneously measured O2 absorption and radiative transfer calculations. The atmospheric modeling is deliberately kept to a minimum. Although this may compromise the accuracy of each individual measurement, it makes the product more suited for long-term climatological studies.
We perform the validation using comparisons against global positioning system radio occultation (GPS RO) measurements from CHAllenging Minisatellite Payload (CHAMP) as well as from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission. Total column water vapour estimates from the GOME/SCIAMACHY/GOME-2 instruments are then collocated and compared with SSM/I measurements processed by the latest HOAPS 3.2 algorithm (over ocean only) and with a combined SSM/I + MERIS dataset (as developed in the framework of the ESA DUE GlobVapour project) independent satellite. Finally, we present exemplary results from about 6 months measurements of the new GOME-2 instrument (FM2) on MetOp-B, launched on 17 October 2012.
From our analysis, we find mean biases as small as +/- 1 kg/m2 between GOME/SCIAMACHY/ GOME-2 and all other datasets, but we observe a clear seasonal cycle over sea areas with dry bias during the northern hemispheric winter and wet bias during the northern hemispheric summer. We also discuss possible improvements in the H2O retrieval algorithm for GOME-type instruments, in particular regarding the strong sunglint effect observed over ocean.