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Water Vapour Retrieval using AMC-DOAS


Introduction       Retrieval Method       Data Products       Data Access       References       Contact


This is the AMC-DOAS main page.

Top Introduction

Water vapour is one of the most important atmosphere constituents. Most of it is located in the troposphere close to the surface of the Earth. Especially, water vapour is the major greenhouse gas; without the natural greenhouse effect due to water vapour life on Earth as we know it would not be possible. The knowledge about the global distribution of water vapour is a relevant input quantity for atmospheric models aiming to predict weather or climate.
The probably most accurate tropospheric water vapour measurements are performed by radio sondes. However, radio sondes can only provide very localized snapshots of the atmospheric conditions, and the distribution of radio sonde measurement sites over the Earth is rather inhomogeneous and considerably sparse especially over the oceans and in the southern hemisphere.
Only satellite measurements using remote sensing techniques can provide water vapour data on the global scale, but they are usually limited in spatial and/or temporal coverage and resolution. Different sensors using different spectral regions and viewing geometries and various retrieval methods have been developed to derive water vapour concentrations from satellite data.
The Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) is a method to retrieve total water vapour column amounts from spectral measurements in the visible wavelength region around 700 nm. Because data in the visible spectral range are analysed, the AMC-DOAS method is only applicable to measurements on the dayside and to (almost) cloud-free ground scenes. A significant advantage of the AMC-DOAS method is that the derived water vapour columns do not depend on additional external information, like a calibration using radio sonde data which is often used in the microwave spectral region. The AMC-DOAS water vapour columns therefore provide a completely independent data set.

GOME spectrum channel 4

Example for an Earthshine spectrum measured by the GOME instrument (channel 4).
The AMC-DOAS fitting window is marked.
(Click to enlarge)

Top Retrieval Method

The AMC-DOAS algorithm is based on a modified DOAS approach as it uses the information contained in the differential absorption structures. The main differences to "standard" DOAS are:
  • Saturation effects arising from highly structured differential spectral features which are not resolved by the measuring instrument are accounted for.
  • O2 absorption features are fitted in combination with H2O to determine an air mass correction factor which compensates to some degree for insufficient knowledge of the background atmospheric characteristics, especially cloudiness, and for geometrical aspects like scan angle dependencies.
Although no clouds are considered explicitly in the retrieval, the method of air mass correction provides the possibility to retrieve meaningful H2O total columns also for partly cloudy scenes.
The size of the air mass correction factor can be used a criterion for the quality of the H2O data product. In the ideal case, i.e. if the atmospheric conditions used in the model calculations match the real conditions, the air mass correction factor should be 1. In the presence of clouds, only the atmosphere above the clouds can be probed by the instrument, so the effective amount of both O2 and H2O seen by the instrument is smaller than the amount used in the model calculations. The air mass factor correction would then try to compensate for this. In this case the correction factor would be smaller than 1.
If the air mass correction factor deviates too much from 1, this is an indication that the conditions of the reference atmosphere differ to much from reality. In this case the retrieved H2O columns are considered to be unrealistic.
In practice, it could be shown that data retrieved with air mass correction factors smaller than 0.8 are unreliable. Therefore, these data have been omitted from the distributed data products. In addition, measurements performed at high solar zenith angles (larger than 88 deg) have been excluded.

Details about the AMC-DOAS method can be found e.g. in Noël et al. (2004).

There is also an Algorithm Description Document available.

Top Data Products

The AMC-DOAS retrieval method has been successfully applied to measurements of GOME (Noël et al., 1999) and SCIAMACHY (Noël et al., 2004) . Because the ground pixel size of SCIAMACHY is typically much smaller than for GOME (30 km x 60 km compared to 40 km x 320 km), the probability for cloud-free scenes is much higher for SCIAMACHY. Global coverage is achieved for SCIAMACHY nadir measurements in 6 days, for GOME in 3 days.

Click to enlarge

SCIAMACHY and GOME H2O total columns over Europe for 27 Jan 2003.
The smaller SCIAMACHY ground pixels are marked by boxes.
(Click to enlarge)


AMC-DOAS water vapour results have been compared with various independent data, including measurements of the Special Sensor Microwave Imager (SSM/I) over ocean, assimilated global water vapour data provided by the European Centre for Medium-Range Weather Forecast (ECMWF) and in-situ radio sonde data. These intercomparisons revealed in general a good agreement between the different data sets, but AMC-DOAS water vapour columns are typically slightly (~0.2 g/cm2) lower than e.g. SSM/I and ECMWF data. This is most likely caused by the exclusion of too cloudy (and thus moist) scenes in the AMC-DOAS data. In all cases a large scatter in the data (~0.5 g/cm2) was observed which can be mainly attributed to the large spatial and temporal variability of water vapour (see e.g. Noël et al., 2005, for details).

Intercomparisons between AMC-DOAS results based on GOME and SCIAMACHY measurements showed a good agreement (Noël et al., 2006, 2007). It is therefore possible to generate a combined GOME/SCIAMACHY water vapour climatology which is useful for climatological trend analysis applications.

Click to enlarge

The combined GOME (1996-2002) and SCIAMACHY (2003-2006) water vapour data set (monthly means).
(Click to enlarge)


The AMC-DOAS method has also been applied to GOME-2 data. Click here for first results or have a look at the Noël et al. (2008) paper.

Top Data Access

AMC-DOAS water vapour total column data have been derived for all GOME data from July 1995 until December 2004 (with reduced coverage after June 2003).
All available SCIAMACHY data since August have been processed. The analysis is ongoing, have a look at the SCIAMACHY DOAS nadir browser for most recent results.

Current data product version is 1.0. Click here for a list of changes. You may also download the Product Specification Document.

Access to all data is possible under certain conditions; click here for details.

Top References

Top Contact

If you are interested in more information on AMC-DOAS water vapour, please contact Stefan Noël.



Author of this page: Stefan Noël
       
©2008