An algorithm to screen cloud-affected data for sky radiometer data analyses Export

@article{khatriJMSJ2008, abstract = {Aerosol optical parameters obtained from sky radiometer instrument are important not only for studying aerosol effects on climate change, but also for validating several results obtained from satellite retrievals and numerical simulations. However, the greatest challenge is to separate cloud-affected and cloud free data from data measured by sky radiometer. In this study, we present an algorithm to separate such cloud-affected and cloud free data. The proposed algorithm is comprehensively tested with observational data. The algorithm consists three tests: (i) test with global irradiance data, (ii) spectral variability test, and (iii) statistical analyses test. Though the test with the global irradiance data is the most powerful test, our study shows that it has some limitations, which can}, author = {Khatri, Pradeep and Takamura, Tamio}, citeulike-article-id = {3926451}, journal = {Journal of the Meteorological Society of Japan}, keywords = {cloud-screening, sun-photometer}, pages = {835+}, posted-at = {2009-01-23 05:42:35}, priority = {0}, title = {An algorithm to screen cloud-affected data for sky radiometer data analyses} }

TY - JOUR ID - khatriJMSJ2008 L3 - citeulike-article-id:3926451 N2 - Aerosol optical parameters obtained from sky radiometer instrument are important not only for studying aerosol effects on climate change, but also for validating several results obtained from satellite retrievals and numerical simulations. However, the greatest challenge is to separate cloud-affected and cloud free data from data measured by sky radiometer. In this study, we present an algorithm to separate such cloud-affected and cloud free data. The proposed algorithm is comprehensively tested with observational data. The algorithm consists three tests: (i) test with global irradiance data, (ii) spectral variability test, and (iii) statistical analyses test. Though the test with the global irradiance data is the most powerful test, our study shows that it has some limitations, which can JF - Journal of the Meteorological Society of Japan TI - An algorithm to screen cloud-affected data for sky radiometer data analyses SP - 835 KW - cloud-screening KW - sun-photometer AU - Khatri, Pradeep AU - Takamura, Tamio ER -