Atmospheric water vapor amounts retrieved from GOME satellite data

Noël, Stefan; Buchwitz, Michael; Bovensmann, H.; Hoogen, R.; Burrows, John P.

doi:10.1029/1999gl900437

Cited by 86 publications

(71 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular it can observe the total atmospheric H 2 O column including the layers near the surface. GOME is now continuously operating for more than 7 years, thus these observations might be well suited for the investigation of trends of atmospheric trace gases like H 2 O. Atmospheric H 2 O has already been analysed from GOME observations and compared to independent data sets by different groups Maurellis et al, 2000;Casadio et al, 2000;Noël et al, 2000;2002, Lang et al, 2003 and reasonable agreement was found. However, these GOME H 2 O algorithms suffer from different shortcomings: a.…”

Section: Introductionmentioning

confidence: 84%

“…The earlier H 2 O algorithms did not take this cloud influence into account at all. First very promising attempts for a cloud correction using O 2 absorptions were undertaken by Noël et al (2000Noël et al ( , 2002 and Casadio et al (2000). However, usually the atmospheric profiles of O 2 with a scale height of ≈8 km and H 2 O are quite different (see Sect.…”

Section: Introductionmentioning

confidence: 99%

“…different reference atmospheres (see e.g. Noël et al 1999) or vertically resolved atmospheric modelling (see e.g. Lang et al 2003).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements

et al. 2003

View full text Add to dashboard Cite

Abstract. Atmospheric water vapour is the most important greenhouse gas which is responsible for about 2/3 of the natural greenhouse effect, therefore changes in atmospheric water vapour in a changing climate (the water vapour feedback) is subject to intense debate. H 2 O is also involved in many important reaction cycles of atmospheric chemistry, e.g. in the production of the OH radical. Thus, long time series of global H 2 O data are highly required. Since 1995 the Global Ozone Monitoring Experiment (GOME) continuously observes atmospheric trace gases. In particular it has been demonstrated that GOME as a nadir looking UV/visinstrument is sensitive to many tropospheric trace gases. Here we present a new, fast H 2 O algorithm for the retrieval of vertical column densities from GOME measurements. In contrast to existing H 2 O retrieval algorithms it does not depend on additional information like e.g. the climatic zone, aerosol content or ground albedo. It includes an internal cloud-, aerosol-, and albedo correction which is based on simultaneous observations of the oxygen dimer O 4 . From sensitivity studies using atmospheric radiative modelling we conclude that our H 2 O retrieval overestimates the true atmospheric H 2 O vertical column density (VCD) by about 4% for clear sky observations in the tropics and sub-tropics, while it can lead to an underestimation of up to −18% in polar regions. For measurements over (partly) cloud covered ground pixels, however, the true atmospheric H 2 O VCD might be in general systematically underestimated. We compared the GOME H 2 O VCDs to ECMWF model data over one whole GOME orbit (extending from the Arctic to the Antarctic) including also totally cloud covered measurements. The correlation of the GOME observations and the model data yield the following results: a slope of 0.96 (r 2 = 0.86) and an average bias of 5%. Even for measurements with large cloud fractions between 50% and 100% an average underestimaCorrespondence to: T. Wagner (Thomas.Wagner@iup.uni-heidelberg.de) tion of only −18% was found. This high accuracy of our GOME H 2 O data is also confirmed by the excellent agreement with in-situ aircraft measurements during the MINOS campaign in Greece in summer 2001 (slope of 0.97 (r 2 = 0.86), and an average bias of only 0.2%). Our H 2 O algorithm can be directly adapted to the nadir observations of SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) which was launched on ENVISAT in March 2002. Near real time H 2 O column data from GOME and SCIAMACHY might be of great value for meteorological weather forecast.

show abstract

Section: Introductionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements

et al. 2003

View full text Add to dashboard Cite

show abstract

“…Kaufman and Gao, 1992;Bauer and Schlüssel, 1993;Noël et al, 1999Noël et al, , 2004Maurellis et al, 2000;Wagner et al, 2006;Li et al, 2006;Deeter, 2007;Lang et al, 2007;Mieruch et al, 2008;Pougatchev et al, 2009). Within this framework, the European satelliteborne atmospheric sensor Global Ozone Monitoring Experiment 2 (GOME-2) aboard the Meteorological Operational satellite program (MetOp-A and MetOp-B) provides the potential for a detailed analysis of the global distribution of the atmospheric water vapour .…”

mentioning

confidence: 99%

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

et al. 2015

View full text Add to dashboard Cite

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.

show abstract

“…In this context a new near real time retrieval algorithm was developed to demonstrate the capability of GO• to measure other trace gasses than ozone and nitrogen dioxide. Recently an attempt to retrieve water vapour concentration from GO• spectra has been presented, based on a modified DOAS (Differential Optical Absorption Spectroscopy) approach (Noel, 1999). In what follows an extremely simplified spectroscopic technique is proposed, which uses only raw uncalibrated spectra and geolocation information and requires only a few seconds computation time per orbit (including about 2000 single measurements).…”

Section: Introductionmentioning

confidence: 99%

Empirical retrieval of the atmospheric air mass factor (ERA) for the measurement of water vapour vertical content using GOME data

Casadio

Zehner

Pisacane

et al. 2000

Geophysical Research Letters

View full text Add to dashboard Cite

Abstract. A new empirical technique for the fast retrieval of vertical concentrations of water vapour from the GOME uncalibrated spectra is described in detail. The ERA technique (Empirical Retrieval of Atmospheric air mass factor) makes maximum use of GOME's capability to measure atmospheric spectra over a broad wavelength range with high spectral resolution, by retrieving a normalisation factor for the water vapour concentrations directly from the data (oxygen slam column measurements). ERA results are cornpared to the ECMWF TCWV analysis (Total Column Water Vapour), showing good agreement.

show abstract

Atmospheric water vapor amounts retrieved from GOME satellite data

Cited by 86 publications

References 5 publications

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements

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

Empirical retrieval of the atmospheric air mass factor (ERA) for the measurement of water vapour vertical content using GOME data

Contact Info

Product

Resources

About

Atmospheric water vapor amounts retrieved from GOME satellite data

Cited by 86 publications

References 5 publications

A fast H&lt;sub&gt;2&lt;/sub&gt;O total column density product from GOME – Validation with in-situ aircraft measurements

A fast H&lt;sub&gt;2&lt;/sub&gt;O total column density product from GOME – Validation with in-situ aircraft measurements

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

Empirical retrieval of the atmospheric air mass factor (ERA) for the measurement of water vapour vertical content using GOME data

Contact Info

Product

Resources

About

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements

A fast H<sub>2</sub>O total column density product from GOME – Validation with in-situ aircraft measurements