&lt;title&gt;Development of ADEOS-II/GLI operational algorithm for Earth observation&lt;/title&gt;

Nakajima, Teruyuki; Nakajima, Takashi Y.; Nakajima, M.

doi:10.1117/12.373198

Cited by 4 publications

(2 citation statements)

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“…The GLI has 36 channels that can observe the land, ocean, and atmosphere [ Nakajima et al , 1999]. It can retrieve detailed particle optical properties in the atmosphere.…”

Section: Datamentioning

confidence: 99%

“…We used the Comprehensive Analysis Program for Cloud Optical Measurement (CAPCOM) [ Nakajima and Nakajima , 1995; Kawamoto et al , 2001] to retrieve cloud optical thickness from MTSAT‐1R/JAMI. This algorithm was also adopted as one of the standard algorithms for the Advanced Earth Observing Satellite II/Global Imager (ADEOS‐II/GLI) products [ Nakajima et al , 1999]. The original CAPCOM estimated the cloud optical thickness, effective particle radius, and cloud‐top temperature from visible, near‐infrared, and thermal infrared channels using a LUT calculated from radiative transfer [ Nakajima and Tanaka , 1986, 1988] under a plane‐parallel and single‐layer cloud model.…”

Section: Retrieval Of Cloud Optical Propertiesmentioning

confidence: 99%

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Estimation of solar radiation using a neural network based on radiative transfer

et al. 2011

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[1] This study developed an algorithm for estimating solar radiation from space using a neural network (NN) with an improved learning algorithm to approximate radiative transfer code. The NN solver for the solar radiation budget is based on radiative transfer calculations. All data sets for testing and training the NN were generated from radiative transfer code. Thus the NN traces the radiative transfer calculation that is approximated by a learning algorithm. To demonstrate the effectiveness of the NN approach for high-speed estimation and multiparameter problems, the NN was applied to data from a geostationary satellite and a Sun-synchronous subrecurrent orbit satellite. The developed algorithm was applied to data from the Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) geostationary satellite, and estimations were validated against in situ observations for March 2006 at four SKYNET sites. Byproducts of the algorithm include UVA, UVB, and photosynthetically active radiation (PAR) fluxes as well as direct and diffuse components. The NN approach enables semi-real-time analysis of these products by high-speed calculation. In addition, the NN allows for consideration of detailed particle optical parameters in the solar radiation budget without the need for a massive database. The method was also applied to observations from the Advanced Earth Observing Satellite-II/Global Imager (ADEOS-II/GLI) for May 2003. The results showed trends in the direct and diffuse components of downward solar radiation over the North Pacific Ocean. This report outlines the construction of the NN for radiation budget estimation and demonstrates the effectiveness of the NN approach.

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“…The GLI has 36 channels that can observe the land, ocean, and atmosphere [ Nakajima et al , 1999]. It can retrieve detailed particle optical properties in the atmosphere.…”

Section: Datamentioning

confidence: 99%