Assessment of Nighttime Cloud Cover Products from MODIS and Himawari-8 Data with Ground-Based Camera Observations

Lagrosas, Nofel; Xiafukaiti, Alifu; Kuze, Hiroaki; Shiina, Tatsuo

doi:10.3390/rs14040960

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…Due to this reason, Himawari-8 cannot identify the variability of the hourly clear sky fractions. As discussed by Lagrosas et al (2022), Himawari-8 has a limitation in detecting low altitude (<2 km) clouds, especially the small fragments. On some occasions, the occurrences of low-altitude clouds, mainly in the first half of the night, were confirmed during several site visits.…”

Section: Temporal Variabilitymentioning

confidence: 99%

“…The divergence between the SQM-based and satellite-based results hinders us from firmly confirming the ground truth. In-situ observation usually is regarded as a better way to characterise an astronomical site compared to the remote sensing approach (Lagrosas et al 2022). However, zenithal sky brightness measurement is not an ultimate way of monitoring the sky, considering how narrow the field of view of the instrument is compared to the whole observable sky.…”

Section: Monthmentioning

confidence: 99%

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Characterisation of Timau National Observatory using limited in-situ measurements

Priyatikanto,

Mumpuni,

Hidayat

et al. 2022

Preprint

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A new astronomical observatory in southeastern Indonesia is currently under construction. This Timau National Observatory will host a 3.8-metre telescope for optical and near-infrared observations. To support the operation and planning, the characterisation of the site needs to be appropriately performed. However, limited resources and access to the site hindered the deployment of instruments for comprehensive site testing. Fortunately, in-situ sky brightness data from the Sky Quality Meter (SQM) have been available for almost two years. Based on the data acquired in 470 nights, we obtain a background sky brightness of 𝜇 0 = 21.86 ± 0.38 magnitude/arcsec 2 . Additionally, we evaluate the moonlit sky brightness to estimate the atmospheric extinction coefficient (𝑘) and level of scattering on site. We find an alleviated value of 𝑘 = 0.48 ± 0.04, associated with a high atmospheric aerosol content. It is considered regular for an equatorial area situated at a low altitude (∼1300 masl). By analysing the fluctuation of the sky brightness and infrared images from Himawari-8 satellite, we estimate the available observing time (AOT) of at least 5.3 hours/night and the yearly average percentage of usable nights of 66%. The monthly average AOT from SQM and satellite data analysis correlate with 𝑅 = 0.82. In terms of the monthly percentage of usable nights, the correlation coefficient is 𝑅 = 0.78. During the wet season (November-April), the results from SQM and satellite data analysis deviate more significantly, mainly due to the limited capability of Himawari-8 in detecting fragmented low-altitude clouds. According to these results, we expect Timau to complement other observatories greatly.

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Section: Temporal Variabilitymentioning

confidence: 99%

Section: Monthmentioning

confidence: 99%

Characterisation of Timau National Observatory using limited in-situ measurements

Priyatikanto,

Mumpuni,

Hidayat

et al. 2022

Preprint

View full text Add to dashboard Cite

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Characterization of Timau National Observatory using limited in situ measurements

Priyatikanto

Mumpuni

Hidayat

et al. 2022

Monthly Notices of the Royal Astronomical Society

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A new astronomical observatory in south-eastern Indonesia is currently under construction. This Timau National Observatory will host a 3.8-m telescope for optical and near-infrared observations. To support the operation and planning, the characterization of the site needs to be appropriately performed. However, limited resources and access to the site hindered the deployment of instruments for comprehensive site testing. Fortunately, in situ sky brightness data from the Sky Quality Meter (SQM) have been available for almost 2 yr. Based on the data acquired in 470 nights, we obtain a background sky brightness of μ0 = 21.86 ± 0.38 mag arcsec−2. Additionally, we evaluate the moonlit sky brightness to estimate the atmospheric extinction coefficient (k) and level of scattering on site. We find an elevated value of k = 0.48 ± 0.04, associated with a high atmospheric aerosol content. It is considered regular for an equatorial area situated at a low altitude (∼1300 masl). By analysing the fluctuation of the sky brightness and infrared images from Himawari-8 satellite, we estimate the available observing time (AOT) of at least 5.3 h/night and the yearly average percentage of usable nights of $66{{\ \rm per\ cent}}$. The monthly average AOT from SQM and satellite data analysis correlate with R = 0.82. In terms of the monthly percentage of usable nights, the correlation coefficient is R = 0.78. During the wet season (November–April), the results from SQM and satellite data analysis deviate more significantly, mainly due to the limited capability of Himawari-8 in detecting fragmented low-altitude clouds. According to these results, we expect Timau to complement other observatories greatly.

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QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation

Liu

Zhang

Zhao

et al. 2022

Sensors

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The difficulty of atmospheric correction based on a radiative transfer model lies in the acquisition of synchronized atmospheric parameters, especially the aerosol optical depth (AOD). At the moment, there is no fully automatic and high-efficiency atmospheric correction method to make full use of the advantages of geostationary meteorological satellites in large-scale and efficient atmospheric monitoring. Therefore, a QUantitative and Automatic Atmospheric Correction (QUAAC) method is proposed which can efficiently correct high-spatial-resolution (HSR) satellite images. QUAAC uses the atmospheric aerosol products of geostationary satellites to match the synchronized AOD according to the temporal and spatial information of HSR satellite images. This method solves the problem that the AOD is difficult to obtain or the accuracy is not high enough to meet the demand of atmospheric correction. By using the obtained atmospheric parameters, atmospheric correction is performed to obtain the surface reflectance (SR). The whole process can achieve fully automatic operation without manual intervention. After QUAAC applied to Gaofen-2 (GF-2) HSR satellite and Himawari-8 (H-8) geostationary satellite, the results show that the effect of QUAAC correction is slightly better than that of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) correction, and the QUAAC−corrected surface spectral curves have good coherence to that of the synchronously measured by field experiments.

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Assessment of Nighttime Cloud Cover Products from MODIS and Himawari-8 Data with Ground-Based Camera Observations

Cited by 3 publications

References 45 publications

Characterisation of Timau National Observatory using limited in-situ measurements

Characterisation of Timau National Observatory using limited in-situ measurements

Characterization of Timau National Observatory using limited in situ measurements

QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation

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