Research Papers

Neural network cloud screening algorithm Part II: global synthetic cases using high resolution spectra in O2 and CO2 near infrared absorption bands in nadir and sun glint

[+] Author Affiliations
Thomas E. Taylor

Colorado State University, Department of Atmospheric Sciences, 1371 Campus Delivery, Fort Collins, Colorado 80523

D. M. O'Brien

Cooperative Institute for Research in the Atmosphere, Fort Collins, CO 80523

J. Appl. Remote Sens. 4(1), 043518 (March 19, 2010). doi:10.1117/1.3386045
History: Received August 4, 2009; Revised February 18, 2010; Accepted March 17, 2010; March 19, 2010; Online March 19, 2010
Text Size: A A A

Open Access Open Access

Abstract

In Part I a set of two layer feed-forward neural networks, trained via back propagation of sensitivities, was applied to a synthetic set of radiances in micro-windows of the near-infrared to make predictions of cloud water (cw), cloud ice (ci), effective scattering heights of cloud water and ice, (pcw and pci, respectively) and the column water vapor (w). A threshold test, using 2 g/m-2> for cloud water and 10 g/m-2> for cloud ice, was applied to the retrieved values to distinguish clear from cloudy scenes. In that work the discussion was limited to the nadir viewing geometry, and was applied only to land surfaces, excluding desert and snow and ice fields. Part II describes the extension to a set of high resolution radiances, as might be measured by a grating spectrometer from space, in both nadir and sun glint viewing geometries. Furthermore, results are given for all land surface types as well as scenes over ocean. Prior to neural network training, a Principal Component Analysis (PCA) is applied to the high resolution spectra, which consist of three bands centered at 0.76μm (O2 A-band), 1.61μm (weak CO2 band) and 2.06μm (strong CO2 band), each with 1016 channels. Analysis shows that the five leading EOFs together capture 99.9% of the variance in each band, reducing the data size by more than two orders of magnitude. Application of the trained neural networks to an independent data set, generated using CloudSat and Calipso cloud and aerosol profiles, as well as carbon dioxide profiles from a chemical transport model, were used to quantify the skill in the retrieval. The results vary significantly with surface type, viewing mode and cloud properties. Accuracies range from 7% to 100% (typically close to 75%), with confidence levels almost always greater than 90%.

References

T. E. Taylor and D. O'Brien, "A neural network cloud screening algorithm. Part I: a synthetic case over land surfaces using micro-windows in O2> and CO2> near infrared absorption bands with nadir viewing," J. Appl. Rem. Sens. 3, 033548 (2009)
D. Crisp, C. E. Miller, and P. L. DeCola, "NASA orbiting carbon observatory: measuring the column averaged carbon dioxide mole fraction from space," J. Appl. Rem. Sens. 2, 023508 (2008)
C. Miller, D. Crisp, P. DeCola, S. Olsen, J. Randerson, A. Michalak, A. Alkhaled, P. Rayner, D. Jacob, P. Suntharalingam, D. Jones, A. Denning, M. Nicholls, S. Doney, S. Pawson, H. Boesch, B. Connor, I. Fung, D. O'Brien, R. Salawitch, S. Sander, B. Sen, P. Tans, G. Toon, P. Wennberg, S. Wofsy, Y. Yung, and R. Law, "Precision requirements for space-based XCO2> data," J. Geophys. Res. 112, D10314 (2007)
D. Crisp, R. Atlas, F.-M. Breon, L. R. Brown, J. Burrows, P. Ciais, B. J. Connor, S. C. Doney, I. Y. Fung, D. J. Jacob, C. E. Miller, D. O'Brien, S. Pawson, J. T. Randerson, P. Rayner, R. J. Salawitch, S. P. Sander, B. Sen, G. L. Stephens, P. P. Tans, G. C. Toon, P. O.Wennberg, S. C.Wofsy, Y. L. Yung, Z. Kuang, B. Chudasama, G. Sprague, B.Weiss, R. Pollock, D. Kenyon, and S. Schroll, "The orbiting carbon observatory (OCO) mission," Adv. Space Res. 34, 700-709 (2004)
B. J. Connor, H. Boesch, G. Toon, B. Sen, C. Miller, and D. Crisp, "Orbiting carbon observatory: inverse method and prospective error analysis," J. Geophys. Res. 113, D05305 (2008)
F. Breon, D. O'Brien, and J. Spinhirne, "Scattering layer statistics from space borne GLAS observations," Geophys. Res. Lett. 32, L22802 (2005)
F. Chevallier, "Sampled databases of 60-level atmospheric profiles from the ECMWF analyses," SAF Programme Research Report 4, EUMETSAT/ECMWF, Darmstadt, Germany (2001).
C. Cox and W. H. Munk, "The measurement of the roughness of the sea surface from photographs of the sun's glitter," J. Opt. Soc. Amer. 44, 838-850 (1954)
E. C. Monahan and I. OMuircheartaigh, "Optimal power-law description of oceanic whitecap coverage dependence on wind speed," J. Phys. Oceanogr. 10, 2094-2099 (1980)
D. O'Brien, I. Polonsky, P. Stephens, and T. E. Taylor, "Feasibility of cloud screening using proxy photon pathlength distributions derived from high-resolution spectra in the near infrared," J. Atmos. Oceanic Technol. 27, 135-146 (2010)
E. P. Shettle and R. W. Fenn, "Models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties," Tech. Rep. Environment. Res., No. 676, AFGL-TR-79-0214, Air Force Geophys. Lab., Hanscom Air Force Base, MA (1979).
A. K. Heidinger, C. O'Dell, R. Bennartz, and T. Greenwald, "The successive-order-ofinteraction radiative transfer model: Part I: model development," J. Appl. Meteorol. Clim. 45, 1388-1402 (2006)
C. O'Dell, A. K. Heidinger, T. Greenwald, P. Bauer, and R. Bennartz, "The successive order- of-interaction radiative transfer model: Part II: model performance and applications," J. Appl. Meteorol. Clim. 45, 1403-1413 (2006)
C. W. O'Dell, "Acceleration of multiple-scattering, hyperspectral radiative transfer calculations via low-streams interpolation," J. Geophys. Res. (2010) in press.
G. Golub and C. Reinsch, "Singular value decomposition and least squares solutions," Numer. Math. 14, 403-420 (1970)
S. R. Kawa, D. J. Erickson, S. Pawson, and Z. Zhu, "Global CO2 transport simulations using meteorological data from the NASA data assimilation system," J. Geophys. Res.109, 18312 (2004)
H. Bosch, G. C. Toon, B. Sen, R. A. Washenfelder, P. O. Wennberg, M. Buchwitz, R. de Beek, J. P. Burrows, D. Crisp, M. Christi, B. J. Connor, V. Natraj, and Y. L. Yung, "Space-based near-infrared CO2> measurements: Testing the Orbiting Carbon Observatory retrieval algorithm and validation concept using SCIAMACHY observations over Park Falls, Wisconsin," J. Geophys. Res. 111, D23302 (2006)
© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Thomas E. Taylor and D. M. O'Brien
"Neural network cloud screening algorithm Part II: global synthetic cases using high resolution spectra in O2 and CO2 near infrared absorption bands in nadir and sun glint", J. Appl. Remote Sens. 4(1), 043518 (March 19, 2010). ; http://dx.doi.org/10.1117/1.3386045


Figures

Tables

References

T. E. Taylor and D. O'Brien, "A neural network cloud screening algorithm. Part I: a synthetic case over land surfaces using micro-windows in O2> and CO2> near infrared absorption bands with nadir viewing," J. Appl. Rem. Sens. 3, 033548 (2009)
D. Crisp, C. E. Miller, and P. L. DeCola, "NASA orbiting carbon observatory: measuring the column averaged carbon dioxide mole fraction from space," J. Appl. Rem. Sens. 2, 023508 (2008)
C. Miller, D. Crisp, P. DeCola, S. Olsen, J. Randerson, A. Michalak, A. Alkhaled, P. Rayner, D. Jacob, P. Suntharalingam, D. Jones, A. Denning, M. Nicholls, S. Doney, S. Pawson, H. Boesch, B. Connor, I. Fung, D. O'Brien, R. Salawitch, S. Sander, B. Sen, P. Tans, G. Toon, P. Wennberg, S. Wofsy, Y. Yung, and R. Law, "Precision requirements for space-based XCO2> data," J. Geophys. Res. 112, D10314 (2007)
D. Crisp, R. Atlas, F.-M. Breon, L. R. Brown, J. Burrows, P. Ciais, B. J. Connor, S. C. Doney, I. Y. Fung, D. J. Jacob, C. E. Miller, D. O'Brien, S. Pawson, J. T. Randerson, P. Rayner, R. J. Salawitch, S. P. Sander, B. Sen, G. L. Stephens, P. P. Tans, G. C. Toon, P. O.Wennberg, S. C.Wofsy, Y. L. Yung, Z. Kuang, B. Chudasama, G. Sprague, B.Weiss, R. Pollock, D. Kenyon, and S. Schroll, "The orbiting carbon observatory (OCO) mission," Adv. Space Res. 34, 700-709 (2004)
B. J. Connor, H. Boesch, G. Toon, B. Sen, C. Miller, and D. Crisp, "Orbiting carbon observatory: inverse method and prospective error analysis," J. Geophys. Res. 113, D05305 (2008)
F. Breon, D. O'Brien, and J. Spinhirne, "Scattering layer statistics from space borne GLAS observations," Geophys. Res. Lett. 32, L22802 (2005)
F. Chevallier, "Sampled databases of 60-level atmospheric profiles from the ECMWF analyses," SAF Programme Research Report 4, EUMETSAT/ECMWF, Darmstadt, Germany (2001).
C. Cox and W. H. Munk, "The measurement of the roughness of the sea surface from photographs of the sun's glitter," J. Opt. Soc. Amer. 44, 838-850 (1954)
E. C. Monahan and I. OMuircheartaigh, "Optimal power-law description of oceanic whitecap coverage dependence on wind speed," J. Phys. Oceanogr. 10, 2094-2099 (1980)
D. O'Brien, I. Polonsky, P. Stephens, and T. E. Taylor, "Feasibility of cloud screening using proxy photon pathlength distributions derived from high-resolution spectra in the near infrared," J. Atmos. Oceanic Technol. 27, 135-146 (2010)
E. P. Shettle and R. W. Fenn, "Models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties," Tech. Rep. Environment. Res., No. 676, AFGL-TR-79-0214, Air Force Geophys. Lab., Hanscom Air Force Base, MA (1979).
A. K. Heidinger, C. O'Dell, R. Bennartz, and T. Greenwald, "The successive-order-ofinteraction radiative transfer model: Part I: model development," J. Appl. Meteorol. Clim. 45, 1388-1402 (2006)
C. O'Dell, A. K. Heidinger, T. Greenwald, P. Bauer, and R. Bennartz, "The successive order- of-interaction radiative transfer model: Part II: model performance and applications," J. Appl. Meteorol. Clim. 45, 1403-1413 (2006)
C. W. O'Dell, "Acceleration of multiple-scattering, hyperspectral radiative transfer calculations via low-streams interpolation," J. Geophys. Res. (2010) in press.
G. Golub and C. Reinsch, "Singular value decomposition and least squares solutions," Numer. Math. 14, 403-420 (1970)
S. R. Kawa, D. J. Erickson, S. Pawson, and Z. Zhu, "Global CO2 transport simulations using meteorological data from the NASA data assimilation system," J. Geophys. Res.109, 18312 (2004)
H. Bosch, G. C. Toon, B. Sen, R. A. Washenfelder, P. O. Wennberg, M. Buchwitz, R. de Beek, J. P. Burrows, D. Crisp, M. Christi, B. J. Connor, V. Natraj, and Y. L. Yung, "Space-based near-infrared CO2> measurements: Testing the Orbiting Carbon Observatory retrieval algorithm and validation concept using SCIAMACHY observations over Park Falls, Wisconsin," J. Geophys. Res. 111, D23302 (2006)

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement


 

  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.