References

Primary references on the MCARaTS

• Iwabuchi, H.: Efficient Monte Carlo methods for radiative transfer modeling. J. Atmos. Sci., 63, 2324-2339, 2006.

• Iwabuchi, H., and R. Okamura: Multispectral Monte Carlo radiative transfer simulation by using the maximum cross-section method. Journal of Quantitative Spectroscopy and Radiative Transfer, 193, 40–46, March 10, 2017. doi: 10.1016/j.jqsrt.2017.01.025

On elements of MCARaTS

• 岩渕 弘信, 小林 秀樹：モンテカルロ法を用いた曇天大気および植生キャノピーの放射伝達のモデル化. FRCGC Technical Report No. 7, 2006.

• Iwabuchi, H., and H. Kobayashi, 2008: Modeling of radiative transfer in cloudy atmospheres and plant canopies using Monte Carlo methods. FRCGC Technical Report No. 8, 199 pp, 2008.

• Iwabuchi, H., T. Suzuki: Fast and accurate radiance calculations for cloudy atmospheres using truncation approximation. In Press, Journal of Quantitative Spectroscopy & Radiative Transfer, doi:10.1016/j.jqsrt.2009.04.006, 2009.

• Lucht, W., C.B. Schaaf, A.H. Strahler: An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Trans. Geosci. Remote Sens., vol. 38, 977-998 (2000).

• Marchuk, G., G. Mikhailov, M. Nazaraliev, R. Darbinjan, B. Kargin, and B. Elepov, The Monte Carlo Methods in Atmospheric Optics. Springer-Verlag, 208 pp., 1980.

• Nakajima, T., & M. Tanaka, 1983: Effect of wind-generated waves on the transfer of solar radiation in the atmosphere-ocean system. J. Quant. Spectrosc. Radiat. Transfer, 29, 521-537.

• Nakajima, T., and M. Tanaka 1988: Algorithms for radiative intensity calculations in moderately thick atmospheres using a truncation approximation. J. Quant. Spectrosc. Radiat. Transfer, 40, 51–69.

• Press, W. H., S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, 2007: Numerical Recipes: The Art of Scientific Computing. Third Edition. Cambridge University Press, 1235 pp.

• Rahman, H., B. Pinty, & M. M. Verstraete, 1993: Coupled surface-atmosphere reflectance (CSAR) model. 2.0_R_ Semiempirical surface model usable with NOAA Advanced High Resolution Radiometer data. J. Geophys. Res., 98, D11, 20791-20801

• Okamura, R., H. Iwabuchi, K. S. Schmidt, Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning, Atmos. Meas. Tech., 10, 4747–4759, 2017 https://doi.org/10.5194/amt-10-4747-2017

• Masuda, R., H. Iwabuchi, K. S. Schmidt, A. Damiani, and R. Kudo: Retrieval of Cloud Optical Thickness from Sky-View Camera Images using a Deep Convolutional Neural Network based on Three-Dimensional Radiative Transfer. Remote Sens., 2019, 11, 1962; doi:10.3390/rs11171962

The above technical report (Iwabuchi and Kobayashi, 2008) can be delivered to you by request. Please feel free to ask. English and Japanese versions are available.