@article{68b76d5e2e4542d7a7d87dc4a0a50850,
title = "Instantaneous top-of-atmosphere albedo comparison between CERES and MISR over the Arctic",
abstract = " The top-of-atmosphere (TOA) albedo is one of the key parameters in determining the Arctic radiation budget, with continued validation of its retrieval accuracy still required. Based on three years (2007, 2015, 2016) of summertime (May-September) observations from the Clouds and the Earth's Radiant Energy System (CERES) and the Multi-angle Imaging SpectroRadiometer (MISR), collocated instantaneous albedos for overcast ocean and snow/ice scenes were compared within the Arctic. For samples where both instruments classified the scene as overcast, the relative root-mean-square (RMS) difference between the sample albedos grew as the solar zenith angle (SZA) increased. The RMS differences that were purely due to differential Bidirectional Reflectance Factor (BRF) anisotropic corrections (σ ADM ) were estimated to be less than 4% for overcast ocean and overcast snow/ice when the SZA ≤ 70°. The significant agreement between the CERES and MISR strongly increased our confidence in using the instruments overcast cloud albedos in Arctic studies. Nevertheless, there was less agreement in the cloud albedos for larger solar zenith angles, where the RMS differences of σ ADM reached 13.5% for overcast ocean scenes when the SZA > 80°. Additionally, inconsistencies between the CERES and MISR scene identifications were examined, resulting in an overall recommendation for improvements to the MISR snow/ice mask and a rework of the MISR Albedo Cloud Designation (ACD) field by incorporating known strengths of the standard MISR cloud masks.",
keywords = "Arctic, CERES, MISR, Top-of-atmosphere albedo",
author = "Yizhe Zhan and {Di Girolamo}, Larry and Roger Davies and Catherine Moroney",
note = "MISR over the Arctic. We found that most of the large errors in the albedos resulted from the distinct Whilst using a higher resolution (daily instead of monthly) snow/ice mask with the heritage threshold scene classifications adopted by the CERES and MISR albedo retrieval algorithms. MISR tends to could largely improve the sea ice misclassification, adopting a Albedo Cloud Designation field from a overestimate snow/ice cover and the current Albedo Cloud Designation field (based on old SDCM) combination of SDCM, RCCM, and ASCM does improve MISR scene classification by drawing upon overlooks low clouds. Focusing on the collocated CERES-MISR SW albedos with consistent scene the known strengths of the MISR cloud for each underlying surface type. Instead of using the strategy identifications, we showed a remarkable agreement between the CERES and MISR overcast albedo embedded in the current consensus cloud mask (i.e., SDCM + ASCM + RCCM), and certainly in the retrieval algorithms ( ~ 5%) for a solar zenith angle less than 70°. This suggested that both current Albedo Cloud Designation field (old SDCM only), we separated cloud mask combinations instruments derived consistent radiance anisotropy corrections of cloud scenes and this enhanced based on the underlying surface types following a much more reasonable logic similar to what was our confidence in using the instruments datasets within the Arctic. Nevertheless, the strong SZA- done within the MISR CFbA product (SDCM+ASCM for snow/ice, RCCM for open water). On average, dependent also addressed the importance of considering the solar zenith angle while we showed that results from our approach were much more consistent with CERES cloud classifications estimating the corresponding regional and monthly mean albedo uncertainties. than all the other MISR standard cloud mask products (Figure 6). The remaining inconsistencies were mostly over snow/ice surfaces where the CERES also suffers from cloud classification issues. Moreover, Author Contributions: Y.Z. conceived the research and designed the experiments. Y.Z. performed the data analysis and data visualization with critical discussions with L.D.G., R.D., and C.M. The manuscript was drafted product such as TOA albedo, as it uses SAW for these samples. Lastly, the misclassified clouds impact the TOA albedo retrievals to different degrees, depending on the difference of anisotropic corrections Funding: This research was funded by subcontract 1460339 and 147871 from the California Institute of Technology/Jet Propulsion Laboratory to the University of Auckland and the University of Illinois, respectively, and by sponsorship from the Chinese Scholarship Council. This work was also supported in part by the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (NSF) Funding: This research was funded by subcontract 1460339 and 147871 from the California Institute of Technology/Jet Propulsion Laboratory to the University of Auckland and the University of Illinois, respectively, and by sponsorship from the Chinese Scholarship Council. This work was also supported in part by the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (NSF) under Award OCI-0725070 and Award ACI-1238993, and in part by the State of Illinois, USA. This work was also partially supported from the NASA ACCESS program under contract NNX16AMO7A and from the NSF Division of Polar Program under contract 16-03544. The original CERES and MISR datasets were obtained from the NASA Langley Research Center Atmospheric Science Data Center, https://eosweb.larc.nasa.gov/. This research was funded by subcontract 1460339 and 147871 from the California Institute of Technology/Jet Propulsion Laboratory to the University of Auckland and the University of Illinois, respectively, and by sponsorship from the Chinese Scholarship Council. This work was also supported in part by the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (NSF) under Award OCI-0725070 and Award ACI-1238993, and in part by the State of Illinois, USA. This work was also partially supported from the NASA ACCESS program under contract NNX16AMO7A and from the NSF Division of Polar Program under contract 16-03544.",
year = "2018",
month = dec,
day = "1",
doi = "10.3390/rs10121882",
language = "English (US)",
volume = "10",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "12",
}