scholarly journals Constraining aerosol phase function using dual‐view geostationary satellites

Author(s):  
Qijing Bian ◽  
Sonia Kreidenweis ◽  
J. Christine Chiu ◽  
Steven D. Miller ◽  
Xiaoguang Xu ◽  
...  
2021 ◽  
Author(s):  
Qijing Bian ◽  
Sonia M. Kreidenweis ◽  
J. Christine Chiu ◽  
Steven D. Miller ◽  
Xiaoguang Xu ◽  
...  

2004 ◽  
Vol 36 (9) ◽  
pp. 29-34
Author(s):  
Evgeniy S. Kozyrev ◽  
Evgeniya S. Sibiryakova ◽  
Alexander V. Shulga

2006 ◽  
Vol 51 (22) ◽  
pp. L39-L41 ◽  
Author(s):  
T Binzoni ◽  
T S Leung ◽  
A H Gandjbakhche ◽  
D Rüfenacht ◽  
D T Delpy

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hirofumi Hashimoto ◽  
Weile Wang ◽  
Jennifer L. Dungan ◽  
Shuang Li ◽  
Andrew R. Michaelis ◽  
...  

AbstractAssessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.


2021 ◽  
Vol 13 (5) ◽  
pp. 1042
Author(s):  
Jung-Hyun Yang ◽  
Jung-Moon Yoo ◽  
Yong-Sang Choi

The detection of low stratus and fog (LSF) at dawn remains limited because of their optical features and weak solar radiation. LSF could be better identified by simultaneous observations of two geostationary satellites from different viewing angles. The present study developed an advanced dual-satellite method (DSM) using FY-4A and Himawari-8 for LSF detection at dawn in terms of probability indices. Optimal thresholds for identifying the LSF from the spectral tests in DSM were determined by the comparison with ground observations of fog and clear sky in/around Japan between April to November of 2018. Then the validation of these thresholds was carried out for the same months of 2019. The DSM essentially used two traditional single-satellite tests for daytime such as the 0.65-μm reflectance (R0.65), and the brightness temperature difference between 3.7 μm and 11 μm (BTD3.7-11); in addition to four more tests such as Himawari-8 R0.65 and BTD13.5-8.5, the dual-satellite stereoscopic difference in BTD3.7-11 (ΔBTD3.7-11), and that in the Normalized Difference Snow Index (ΔNDSI). The four were found to show very high skill scores (POD: 0.82 ± 0.04; FAR, 0.10 ± 0.04). The radiative transfer simulation supported optical characteristics of LSF in observations. The LSF probability indices (average POD: 0.83, FAR: 0.10) were constructed by a statistical combination of the four to derive the five-class probability values of LSF occurrence in a grid. The indices provided more details and useful results in LSF spatial distribution, compared to the single satellite observations (i.e., R0.65 and/or BTD3.7-11) of either LSF or no LSF. The present DSM could apply for remote sensing of environmental phenomena if the stereoscopic viewing angle between two satellites is appropriate.


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