Abstract
Abstract. This study develops the use of spectral total and diffuse irradiance measurements, made from a prototype hyperspectral total-diffuse sunshine pyranometer (SPN-S), to retrieve layer fine-mode aerosol (τaer) and total optical depths from airborne platforms. Additionally, we use spectral analysis in an attempt to partition the total optical depth into its τaer and cirrus cloud optical depth (τcld) components in the absence of coarse-mode aerosols. Two retrieval methods are developed: one leveraging information in the diffuse irradiance and the other using spectral characteristics of the transmitted direct beam, with each approach best suited for specific cloud and aerosol conditions. The SPN-S has advantages over traditional sun photometer systems, including no moving parts and a low cost. However, a significant drawback of the instrument is that it is unable to measure the direct-beam irradiance as accurately as sun photometers. To compensate for the greater measurement uncertainty in the radiometric irradiances, these retrieval techniques employ ratioed inputs or spectral information to reduce output uncertainty. This analysis uses irradiance measurements from the SPN-S and the solar spectral flux radiometer (SSFR) aboard the National Aeronautics and Space Administration's (NASA) P-3 aircraft during the 2018 deployment of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission to quantify above-aircraft cirrus τcld and derive vertical profiles of layer τaer. Validation of the τaer retrieval is accomplished by comparison with co-located measurements of direct solar irradiance made by the Sky-Scanning Sun-Tracking Atmospheric Research (4STAR) and in situ measurements of aerosol optical depth. For the aggregated 2018 ORACLES results, regression between the SPN-S-based method and sun photometer τaer values yields a slope of 0.96 with an R2 of 0.96, while the root mean square error (RMSE) is 3.0×10-2. When comparing the retrieved τaer to profiles of integrated in situ measurements of optical extinction, the slope, R2, and RMSE values for ORACLES are 0.90, 0.96, and 3.4×10-2, and for CAMP2Ex they are 0.94, 0.97, and 3.4×10-2, respectively. This paper is a demonstration of methods for deriving cloud and aerosol optical properties in environments where both atmospheric constituents may be present. With improvements to the low-cost SPN-S radiometer instrument, it may be possible to extend these methods to a broader set of sampling applications, such as ground-based settings.
Highlights
IntroductionClouds and aerosol particles both play important roles in controlling the flux of solar radiation through the Earth’s atmosphere
In this paper we address some of the issues associated with remote sensing of thin-cloud and aerosol systems by leveraging the capabilities of a new hyperspectral total-diffuse radiometer, SPN-S
To compensate for lower accuracy, we propose a method for deriving τcld of thin clouds using narrowband measurements of the diffuse-to-total ratio (DR)
Summary
Clouds and aerosol particles both play important roles in controlling the flux of solar radiation through the Earth’s atmosphere. Traditional passive remote sensing methods retrieve aerosol properties in the absence of clouds (Holben et al, 1998; Levey et al, 2013). For automated aerosol optical depth (τaer) retrievals, the challenge of cloud detection and removal is a significant hurdle to overcome (Smirnov et al, 2000; Remer et al, 2012; Spencer et al, 2019; Yang et al, 2019). Advanced methods, such as the spectral deconvolution algorithm (SDA), have been developed to differentiate between fine- and coarse-mode τaer using spectral sun photometry data (O’Neill et al, 2003), though these techniques are limited when cirrus is present (Smirnov et al, 2018). For the case of thin Arctic clouds, Garrett and Zhao (2013) demonstrated the utility of thermal spectral remote sensing to derive the optical properties when the clouds have an emissivity less than unity
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