Open AccessEstimating Geo‐Referenced Cloud‐Base Height With Whole‐Sky Imagers
Author(s) -
Lyu Baolei,
Chen Yang,
Guan Yuqiu,
Gao Tianlei,
Liu Jun
Publication year - 2021
Publication title -
earth and space science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.843
H-Index - 23
ISSN - 2333-5084
DOI - 10.1029/2019ea000944
Subject(s) - ceilometer , cloud computing , cloud base , sky , environmental science , meteorology , remote sensing , base (topology) , satellite , cloud height , computer science , cloud cover , mathematics , geology , geography , physics , astronomy , mathematical analysis , operating system
Accurate and frequent cloud‐base height calculation is beneficial to solar farming and agricultural activities and also indicative for future meteorology conditions. This study used paired whole‐sky imagers to estimate cloud‐base height with high quality. The study obtained quality assured cloud base feature points with a robust Shi‐Tomasi‐Scale Invariant Feature Transform algorithm before employing double‐eye locating approach, which is fast and easy to implement operationally. The estimated cloud‐base heights have high spatial coverages. Evaluated against ceilometer observations, estimated cloud‐base heights have a high accuracy level, with R 2 = 0.92 and RMSE = 424 m. The method is generally unbiased with NME = 9.2%. The high‐quality cloud‐base features in this study are quantitatively geo‐referenced, which would benefit a lot to meteorological studies such as fusion with satellite observations, evaluation for model simulations and upper‐level wind specifications.