Comparison of Cloud Properties from Ground-Based Infrared Cloud Measurement and Visual Observations

Abstract

Cloud properties derived from the whole-sky infrared cloud-measuring system (WSIRCMS) are analyzed in relation to measurements of visual observations and a ceilometer during the period July-August 2010 at the Chinese Meteorological Administration Yangjiang Station, Guangdong Province, China. The comparison focuses on the performance and features of the WSIRCMS as a prototype instrument for automatic cloud observations. Cloud cover derived from the WSIRCMS cloud algorithm compares quite well with cloud cover derived from visual observations. Cloud cover differences between WSIRCMS and visual observations are within ±1 octa in 70.83% and within ±2 octa in 82.44% of the cases. For cloud-base height from WSIRCMS data and Vaisala ceilometer CL51, the comparison shows a generally good correspondence in the lower and midtroposphere up to the height of about 6 km, with some systematic difference due to different detection methods. Differences between the resulting cloud-type classifications derived from the WSIRCMS and from visual observations show that cumulus and cirrus are classified with high accuracy, but that stratocumulus and altocumulus are not. Stratocumulus and altocumulus are suggested to be treated as waveform cloud for classification purposes. In addition, it is considered an intractable problem for automatic cloud-measurement instruments to do cloud classification when the cloud amount is less than 2 octa.

Field trial of an automated ground‐based infrared cloud classification system

“…Human observation or visible wavelength cameras cannot provide the required data during the hours of darkness, so an automated, ground-based infrared (IR) cloud classification system offers the advantage of real-time uninterrupted cloud monitoring to compensate for the lack of human vision at night (Rumi et al, 2013). Liu et al (2013) studied the cloud cover and type based on measurement from a whole-sky IR cloud measuring system (WSIRCMS) and ceilometer. The CB cloud classification was excluded from their analysis, due to 780 E. Rumi et al (a) (b) the system's inability to identify CB clouds without atmospheric electric field measurement.…”

Cloud classification of ground-based infrared images combining manifold and texture features

“…The datasets include the zenithal images and whole-sky images, which are gathered by the Whole-Sky Infrared Cloud 5 Measurement System (WSIRCMS) (Liu et al, 2013). The WSIRCMS is a ground-based passive system that an uncooled microbolometer detector array of pixels is used to measure downwelling atmospheric radiance in 8-14μm (Liu et al, 2011).…”

A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

“…Consequently, similar to the previous studies (Brutsaert, 1975;Idso, 1981;Marty and Philipona, 2000;Zhnag et al, 2007;Long and Turner, 2008;Carmona et al, 2014), an empirical formula which relates the downwelling infrared radiation to the surface weather data can be derived. Depending on the spectral range and variable of interest, such as the radiance measured in the narrow window region vs. the irradiance representing the integrated flux in the whole infrared region, a slightly different formula (such as those given by Idso, 1981, Liu et al, 2013) is required. Thus, with the several different types of the scatter plot between the different variables, such as shown in Fig.…”