Abstract
Abstract. Two independently derived SCIAMACHY total water vapour column (WVC) products are compared with integrated water vapour data calculated from radiosonde measurements, and with each other. The two SCIAMACHY WVC products are retrieved with two different retrieval algorithms applied in the visible and short-wave infrared wavelength regions respectively. The first SCIAMACHY WVC product used in the comparison is ESA's level 2 version 5.01 WVC product derived with the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) retrieval algorithm applied in the visible wavelength range (SCIAMACHY-ESA). The second SCIAMACHY WVC product is derived using the iterative maximum likelihood method (IMLM) in the short-wave infrared wavelength range and developed by Netherlands Institute for Space Research (SCIAMACHY-IMLM). Both SCIAMACHY WVC products are compared with collocated water vapour amounts determined from daily relative humidity radiosonde measurements obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) radiosonde network. The SCIAMACHY-ESA WVC product is compared with radiosonde-derived WVC amounts for an 18-month period from February 2010 to mid-August 2011, and the SCIAMACHY-IMLM WVC amounts are compared with radiosonde WVC amounts for the two individual years of 2004 and 2009. In addition the WVC amounts from SCIAMACHY-ESA and SCIAMACHY-IMLM are also compared with each other for a 1-month period for June 2009. The AMC-DOAS method used to retrieve SCIAMACHY-ESA WVC is able to correct for water vapour present below the clouds and can be used during cloudy conditions over both land and ocean surfaces. Results indicate a good agreement between the WVC amounts of SCIAMACHY-ESA and that of radiosondes, with a mean difference of −0.32 g cm−2 for all collocated cases. Overall the SCIAMACHY-ESA WVC amounts are smaller than the radiosonde WVC amounts, especially over oceans. For cloudy conditions the WVC bias has a clear dependence on the cloud top height and increases with increasing cloud top heights larger than approximately 2 km. A likely cause for this could be the different vertical profile shapes of water vapour and O2 leading to different relative changes in their optical thickness, which makes the air mass factor (AMF) correction method used in the algorithm less suitable for high clouds. The SCIAMACHY-IMLM product's water vapour measurements are best used over land surfaces during cloud-free conditions, and in these cases a good agreement is found when compared to radiosonde WVC amounts, with a mean difference of 0.08 g cm−2. It is shown that over ocean surfaces during cloudy conditions the partial SCIAMACHY-IMLM water vapour column above the cloud can be well estimated by using the simultaneously retrieved methane column to calculate the cloud top height. Comparing the two satellite WVC products with each other indicates that SCIAMACHY-ESA consistently measures higher WVC amounts than those of SCIAMACHY-IMLM. Furthermore, the importance of the choice of cloud product is highlighted, as intercomparisons between the two SCIAMACHY WVC products indicate that using different cloud products to screen water vapour data for cloud-free conditions influences the data selection and may ultimately lead to a variation in results. In the last section of the paper, various options for filtering the two SCIAMACHY WVC data sets are discussed and best selection criteria suggested.
Highlights
Water vapour is one of the most abundant constituents in the earth’s atmosphere
Measurement results obtained from the visible wavelength region are available over both land and ocean surfaces, whereas for the short-wave infrared region the low sensitivity over ocean surfaces caused by low reflectivity means that measurements from this wavelength range are limited to land surfaces only (Gloudemans et al, 2008) or to cloudy observations over the ocean (Gloudemans et al, 2009)
The iterative maximum likelihood method (IMLM) is described in detail in Gloudemans et al (2008). It is based on scaling a priori atmospheric profiles, and a model of the expected detector signal is fitted to the measurements by adjusting the total column amounts of the trace gases (H2O, CO and CH4) that play a role in this particular retrieval window (Schrijver and Gloudemans, 2008; Schrijver et al, 2009)
Summary
Water vapour is one of the most abundant constituents in the earth’s atmosphere. It is the most important greenhouse gas because of its strong absorption of infrared radiation. One of the advantages of SCIAMACHY retrieval results from the visible and short-wave infrared wavelength regions is that measurements are sensitive down to the boundary layer (Schrijver et al, 2009) This is favourable for water vapour, since the majority of water vapour is found in the lower parts of the atmosphere. Measurement results obtained from the visible wavelength region are available over both land and ocean surfaces, whereas for the short-wave infrared region the low sensitivity over ocean surfaces caused by low reflectivity means that measurements from this wavelength range are limited to land surfaces only (Gloudemans et al, 2008) or to cloudy observations over the ocean (Gloudemans et al, 2009) In this wavelength window the sensitivity for the lower parts of the atmosphere is even stronger (Schrijver et al, 2009).
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