Validation of GOME-2/MetOp-A total water vapour column using reference radiosonde data from the GRUAN network

Abstract

Abstract. The main goal of this paper is to validate the total water vapour column (TWVC) measured by the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor and generated using the GOME Data Processor (GDP) retrieval algorithm developed by the German Aerospace Centre (DLR). For this purpose, spatially and temporally collocated TWVC data from highly accurate sounding measurements for the period January 2009-May 2014 at six sites are used. These balloon-borne data are provided by the GCOS Reference Upper-Air Network (GRUAN). The correlation between GOME-2 and sounding TWVC data is reasonably good (determination coefficient, R 2 , of 0.89) when all available radiosondes (1400) are employed in the intercomparison. When cloud-free cases (544) are selected by means of the satellite cloud fraction (CF < 5 %), the correlation exhibits a remarkable improvement (R 2 ∼ 0.95). Nevertheless, the analysis of the relative differences between GOME-2 and GRUAN data shows a mean absolute bias error (weighted with the combined uncertainty derived from the estimated errors of both data sets) of 15 % for all-sky conditions (9 % for cloud-free cases). These results evidence a notable bias in the satellite TWVC data against the reference balloon-borne measurements, partially related to the cloudy conditions during the satellite overpass. The detailed analysis of the influence of cloud properties -CF, cloud top albedo (CTA) and cloud top pressure (CTP) -on the satellitesounding differences reveals, as expected, a large effect of clouds in the GOME-2 TWVC data. For instance, the relative differences exhibit a large negative dependence on CTA, varying from −6 to −23 % when CTA rises from 0.3 to 0.8. Furthermore, the satellite-sounding TWVC differences show a strong dependence on the satellite solar zenith angle (SZA) for values above 50 • . Hence the smallest relative differences found in this satellite-sounding comparison are achieved for those cloud-free cases with satellite SZA below 50 • . Finally, the relative differences also show a negative dependence on the reference TWVC values, e.g. changing from +10 % (TWVC below 10 mm) to −10 % (TWVC above 40 mm) when cloud-free conditions with SZA below 50 • are selected. Overall, relative differences within ±10 % with respect to reference sounding data for a large range of TWVC values can be considered as a good result for satellite retrievals.

Validation of GOME-2/Metop total column water vapour with ground-based and in situ measurements

“…The range of these variations is about 15 %. This is similar to behaviour observed by (Antón et al, 2015). (Grossi et al, 2015) also reported residual cloud effects in comparisons with ECMWF ERA-Interim and combined SSM/I-MERIS data sets.…”

“…This is probably due to a larger fraction of data with smaller water vapour abundances being observed at large solar zenith angles. (Antón et al, 2015) observed similar behaviour while also reporting positive bias for cloud-free cases at solar zenith angles above 50 • . Large positive differences observed at low water vapour amounts (Fig.…”

“…Large water vapour abundances are commonly associated with high cloud top heights and cloud top albedos and are less likely to include cloud-free scenes (not shown here). These factors are shown by (Antón et al, 2015) to be associated with dry biases.…”

“…Wet bias was observed against GPS for GOME/GOME-2/SCIAMACHY in cloud-free observations, with dry bias in cloudy scenes. (Antón et al, 2015) validated GOME-2A against radiosonde data from GRUAN network. They reported reasonably good correlation when all available reference data were used.…”

Intercomparison of XH2O Data from the GOSAT TANSO-FTS (TIR and SWIR) and Ground-Based FTS Measurements: Impact of the Spatial Variability of XH2O on the Intercomparison

“…Although IWV from satellite measurements are validated using data from radiosonde [11,12] and ground-based instruments, such as GPS [13], microwave radiometer [14], and sun-photometer [15], it is difficult to find the strict matching pairs. Therefore, if the satellite-based IWV is compared with the validation data, spatial and temporal discrepancies may contribute heavily to the differences between them.…”