Radiative transfer modeling of atmospheric methane for satellite measurements in the 1.66 micron spectral window

Abstract

Atmospheric methane is the second most important greenhouse gas after carbon dioxide and has significant impact on the atmosphere and climate. Continuous estimation and prediction of atmospheric CH₄ concentrations is important for understanding the associated global climate change. To constrain suitable spectral window and detector resolutions for satellite instruments, spectral simulations have been performed considering tropical atmospheric conditions. The study is focused on the 1.66 micron spectral region having CH₄ bands that are suitable for its detection and estimation. Both CH₄ concentration and spectral resolution are varied to identify optimum spectral resolution limit. The R branch peak at 1.6456 µm is found to be the most sensitive and suitable for CH₄ estimation. A concentration retrieval scheme is proposed and it is interpreted that the spectral resolution should not be worse than 0.2 nm.

Keywords

Remote sensing near infrared optimum spectral resolution

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References

Migeotte

. Methane in the earth’s atmosphere. Astrophys J 1948; 107: 400–403.

IPCC2007, Solomon S, Qin D, et al. Climate change 2007: the physical science basis: Working Group I contribution to the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press, 2007.

IPCC2013, Stocker TF, Qin D, et al. Technical summary. Cambridge, UK: Cambridge University Press, 2013, p.33115, www.climatechange2013.org.

Bousquet

Ciais

Miller

et al.

Contribution of anthropogenic and natural sources to atmospheric methane variability. Nature 2006; 443: 439–443. http://www.nature.com/nature/journal/v443/n7110/suppinfo/nature05132_S1.html .

Rigby

Prinn

Fraser

et al.

Renewed growth of atmospheric methane. Geophys Res Lett 2008; 35: L22805. https://dx-doi-org.web.bisu.edu.cn/10.1029/2008GL036037 .

Dlugokencky

Bruhwiler

White

JWC

et al.

Observational constraints on recent increases in the atmospheric CH₄ burden. Geophys Res Lett 2009; 36: L18103. https://dx-doi-org.web.bisu.edu.cn/10.1029/2009GL039780 .

Prasad

Rastogi

Singh

. Study of satellite retrieved CO₂ and CH₄ concentration over India. Adv Space Res 2014; 54: 1933–1940. https://www-sciencedirect-com.web.bisu.edu.cn/science/article/pii/S0273117714004773 .

Rayner

O’Brien

. The utility of remotely sensed CO₂ concentration data in surface source inversions. Geophys Res Lett 2001; 28: 175–178. https://dx-doi-org.web.bisu.edu.cn/10.1029/2000GL011912 .

Houweling

Breon

Aben

et al.

Inverse modeling of CO₂ sources and sinks using satellite data: a synthetic inter-comparison of measurement techniques and their performance as a function of space and time. Atmos Chem Phys 2004; 4: 523–538. http://www.atmos-chem-phys.net/4/523/2004/ .

10.

Chédin

Hollingsworth

Scott

et al.

Annual and seasonal variations of atmospheric CO₂, N₂O and CO concentrations retrieved from NOAA/TOVS satellite observations. Geophys Res Lett 2002; 29. 110–1–4, https://dx-doi-org.web.bisu.edu.cn/10.1029/2001GL014082.

11.

Chédin

Serrar

Scott

et al.

First global measurement of midtropospheric CO₂ from NOAA polar satellites: tropical zone. J Geophys Res: Atmos 2003; 108: 4581. https://dx-doi-org.web.bisu.edu.cn/10.1029/2003JD003439 .

12.

Smith

Woolf

Hayden

et al.

TIROS-N operational vertical sounder. Bull Am Meteorol Soc 1979; 10: 1177–1187.

13.

Engelen

Andersson

Chevallier

et al.

Estimating atmospheric CO₂ from advanced infrared satellite radiances within an operational 4D-Var data assimilation system: methodology and first results. J Geophys Res: Atmos 2004; 109: D19309.

14.

Aumann

Gregorich

Gaiser

. AIRS hyper-spectral measurements for climate research: Carbon dioxide and nitrous oxide effects. Geophys Res Lett 2005; 32: L05806. https://dx-doi-org.web.bisu.edu.cn/10.1029/2004GL021784 .

15.

Engelen

McNally

. Estimating atmospheric CO₂ from advanced infrared satellite radiances within an operational four-dimensional variational (4D-Var) data assimilation system: results and validation. J Geophys Res: Atmos 2005; 110: D18305.

16.

Strow

Hannon

De-Souza Machado

et al.

Validation of the atmospheric infrared sounder radiative transfer algorithm. J Geophys Res: Atmos 2006; 111: D09S06.

17.

Maddy

Barnet

Goldberg

et al.

CO₂ retrievals from the atmospheric infrared sounder: methodology and validation. J Geophys Res: Atmos 2008; 113: D11301.

18.

Crevoisier

Chédin

Matsueda

et al.

First year of upper tropospheric integrated content of CO₂ from IASI hyperspectral infrared observations. Atmos Chem Phys 2009; 9: 4797–4810.

19.

Kulawik

Jones

DBA

Nassar

et al.

Characterization of tropospheric emission spectrometer (TES) CO₂ for carbon cycle science. Atmos Chem Phys 2010; 10: 5601–5623. http://www.atmos-chem-phys.net/10/5601/2010/ .

20.

Bovensmann

Burrows

Buchwitz

et al.

SCIAMACHY: mission objectives and measurement modes. J Atmos Sci 1999; 56: 127–150.

21.

Kuze

Suto

Nakajima

et al.

Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring. Appl Optics 2009; 48: 6716.

22.

Frankenberg

Meirink

Bergamaschi

et al.

Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: analysis of the years 2003 and 2004. J Geophys Res: Atmos 2006; 111: D07303. https://dx-doi-org.web.bisu.edu.cn/10.1029/2005JD006235 .

23.

Buchwitz

de Beek

Noël

et al.

Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: version 0.5 CO and CH₄ and impact of calibration improvements on CO₂ retrieval. Atmos Chem Phys 2006; 6: 2727–2751. http://www.atmos-chem-phys.net/6/2727/2006/ .

24.

Schneising

Buchwitz

Burrows

et al.

Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite – Part 2: Methane. Atmos Chem Phys 2009; 9: 443–465. http://www.atmos-chem-phys.net/9/443/2009/ .

25.

Yoshida

Ota

Eguchi

et al.

Retrieval algorithm for CO₂ and CH₄ column abundances from short-wavelength infrared spectral observations by the greenhouse gases observing satellite. Atmos Measure Techniques 2011; 4: 717–734. http://www.atmos-meas-tech.net/4/717/2011/ .

26.

Butz

Guerlet

Hasekamp

et al.

Toward accurate CO₂ and CH4 observations from GOSAT. Geophys Res Lett 2011; 38: L14812. https://dx-doi-org.web.bisu.edu.cn/10.1029/2011GL047888 .

27.

Parker

Boesch

Cogan

et al.

Methane observations from the greenhouse gases observing SATellite: comparison to ground-based TCCON data and model calculations. Geophys Res Lett 2011; 38: L15807. https://dx-doi-org.web.bisu.edu.cn/10.1029/2011GL047871 .

28.

Kiemle

Quatrevalet

Ehret

et al.

Sensitivity studies for a space-based methane lidar mission. Atmos Measure Technique 2011; 4: 2195–2211.

29.

Mathew

Sarkar

Srinivas

et al.

Methane sensor for mars. Curr Sci 2015; 109: 1087–1096.

30.

Boudon

Rey

Lote

. The vibrational levels of methane obtained from analyses of high-resolution spectra. J Quant Spec Rad Transfer 2006; 98: 394–404. https://www-sciencedirect-com.web.bisu.edu.cn/science/article/pii/S0022407305002608 .

31.

de Bergh

Courtin

Bézard

et al.

Applications of a new set of methane line parameters to the modeling of titan’s spectrum in the 1.58 µm window. Planetary Space Sci 2012; 61: 85–98. https://www-sciencedirect-com.web.bisu.edu.cn/science/article/pii/S0032063311001577 .

32.

Nikitin

Boudon

Wenger

et al.

High resolution spectroscopy and the first global analysis of the Tetradecad region of methane ¹²CH₄. Phys Chem Chem Phys 2013; 15: 10071–10093. https://dx-doi-org.web.bisu.edu.cn/10.1039/C3CP50799H .

33.

Clough SA, Kneizys FX, Shettle EP, et al. Atmospheric radiance and transmittance – FASCOD2. In: 6th Conference on atmospheric radiation, Williamsburg, VA, May 13-16, 1986. pp.141–144.

34.

Rothman

Gordon

Barbe

et al.

The HITRAN 2008 molecular spectroscopic database. J Quant Spec Rad Transfer 2009; 110: 533–572.

35.

Miller

Brown

. Near infrared spectroscopy of carbon dioxide I. ¹⁶O¹²C¹⁶O line positions. J Mol Spectrosc 2004; 228: 329–354.

36.

Bruegge CJ, Conel JE, Margolis JS, et al. In-situ atmospheric water-vapor retrieval in support of AVIRIS validation. Proc. SPIE 1298, Imaging Spectroscopy of the Terrestrial Environment, September 1, 1990. pp.150–163.

37.

Carrere

Conel

. Recovery of atmospheric water vapor total column abundance from imaging spectrometer data around 940 nm – sensitivity analysis and application to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. Remote Sensing Environ 1993; 44: 179–204. https://www-sciencedirect-com.web.bisu.edu.cn/science/article/pii/003442579390015P .

38.

Tahl

Schönermark

. Determination of the column water vapour of the atmosphere using backscattered solar radiation measured by the modular optoelectronic scanner (MOS). Int J Remote Sensing 1998; 19: 3223–3236.

39.

Prasad

Rastogi

Singh

et al.

Spectral modelling near the 1.6 µm window for satellite based estimation of CO₂. Spectrochimica Acta Part A: Mol Biomol Spectrosc 2014; 117: 330–339. https://www-sciencedirect-com.web.bisu.edu.cn/science/article/pii/S1386142513009098 (accessed 19 August 2013).

40.

Gaunter

Segl

Kaufmann

. Simulation of optical remote sensing scenes with application to the enmap hyperspectral mission. IEEE Transact Geosci Remote Sensing 2009; 47: 2340–2351.

41.

Piters A, Buchmann B, Brunner D, et al. Data quality and validation of satellite measurements of tropospheric composition. In: Physics of earth and space environments, Berlin Heidelberg: Springer, 2011, pp.315–364, https://dx-doi-org.web.bisu.edu.cn/10.1007/978-3-642-14791-3_7.

42.

Mumma

Villanueva

Novak

et al.

Strong release of methane on mars in northern summer 2003. Science 2009; 323: 1041–1045. http://www.sciencemag.org/content/323/5917/1041.full.pdf .