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Open AccessArticle

Uncertainty Assessment of the Vertically-Resolved Cloud Amount for Joint CloudSat–CALIPSO Radar–Lidar Observations

1
Centrum Badań Kosmicznych Polaskiej Akademii Nauk (CBK PAN), 00-716 Warsaw, Poland
2
Department of Climatology, University of Warsaw, 00-927 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Wei Gong
Remote Sens. 2021, 13(4), 807; https://doi.org/10.3390/rs13040807
Received: 25 January 2021 / Revised: 17 February 2021 / Accepted: 19 February 2021 / Published: 23 February 2021
(This article belongs to the Special Issue Active and Passive Remote Sensing of Aerosols and Clouds)
The joint CloudSat–Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) climatology remains the only dataset that provides a global, vertically-resolved cloud amount statistic. However, data are affected by uncertainty that is the result of a combination of infrequent sampling, and a very narrow, pencil-like swath. This study provides the first global assessment of these uncertainties, which are quantified using bootstrapped confidence intervals. Rather than focusing on a purely theoretical discussion, we investigate empirical data that span a five-year period between 2006 and 2011. We examine the 2B-Geometric Profiling (GEOPROF)-LIDAR cloud product, at typical spatial resolutions found in global grids (1.0°, 2.5°, 5.0°, and 10.0°), four confidence levels (0.85, 0.90, 0.95, and 0.99), and three time scales (annual, seasonal, and monthly). Our results demonstrate that it is impossible to estimate, for every location, a five-year mean cloud amount based on CloudSat–CALIPSO data, assuming an accuracy of 1% or 5%, a high confidence level (>0.95), and a fine spatial resolution (1°–2.5°). In fact, the 1% requirement was only met by ~6.5% of atmospheric volumes at 1° and 2.5°, while the more tolerant criterion (5%) was met by 22.5% volumes at 1°, or 48.9% at 2.5° resolution. In order for at least 99% of volumes to meet an accuracy criterion, the criterion itself would have to be lowered to ~20% for 1° data, or to ~8% for 2.5° data. Our study also showed that the average confidence interval: decreased four times when the spatial resolution increased from 1° to 10°; doubled when the confidence level increased from 0.85 to 0.99; and tripled when the number of data-months increased from one (monthly mean) to twelve (annual mean). The cloud regime arguably had the most impact on the width of the confidence interval (mean cloud amount and its standard deviation). Our findings suggest that existing uncertainties in the CloudSat–CALIPSO five-year climatology are primarily the result of climate-specific factors, rather than the sampling scheme. Results that are presented in the form of statistics or maps, as in this study, can help the scientific community to improve accuracy assessments (which are frequently omitted), when analyzing existing and future CloudSat–CALIPSO cloud climatologies. View Full-Text
Keywords: CloudSat; CALIPSO; cloud amount; uncertainty; 2B-GEOPROF-LIDAR; confidence interval CloudSat; CALIPSO; cloud amount; uncertainty; 2B-GEOPROF-LIDAR; confidence interval
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MDPI and ACS Style

Kotarba, A.Z.; Solecki, M. Uncertainty Assessment of the Vertically-Resolved Cloud Amount for Joint CloudSat–CALIPSO Radar–Lidar Observations. Remote Sens. 2021, 13, 807. https://doi.org/10.3390/rs13040807

AMA Style

Kotarba AZ, Solecki M. Uncertainty Assessment of the Vertically-Resolved Cloud Amount for Joint CloudSat–CALIPSO Radar–Lidar Observations. Remote Sensing. 2021; 13(4):807. https://doi.org/10.3390/rs13040807

Chicago/Turabian Style

Kotarba, Andrzej Z.; Solecki, Mateusz. 2021. "Uncertainty Assessment of the Vertically-Resolved Cloud Amount for Joint CloudSat–CALIPSO Radar–Lidar Observations" Remote Sens. 13, no. 4: 807. https://doi.org/10.3390/rs13040807

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