Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds
Abstract:Abstract. Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System -Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Pr… Show more
“…The GOES dataset used here, if fact, uses the cloud optical thickness to parameterize the clouds. Some examples of studying the impact of clouds on solar irradiance using optical thickness include References [44][45][46].…”
Since the main attenuation of solar irradiance reaching the earth’s surface is due to clouds, it has been hypothesized that global horizontal irradiance attenuation and its temporal variability at a given location could be characterized simply by cloud properties at that location. This hypothesis is tested using global horizontal irradiance measurements at two stations in San Antonio, Texas, and satellite estimates of cloud types and cloud layers from the Geostationary Operational Environmental Satellite (GOES) Surface and Insolation Product. A modified version of an existing solar attenuation variability index, albeit having a better physical foundation, is used. The analysis is conducted for different cloud conditions and solar elevations. It is found that under cloudy-sky conditions, there is less attenuation under water clouds than those under opaque ice clouds (optically thick ice clouds) and multilayered clouds. For cloud layers, less attenuation was found for the low/mid layers than for the high layer. Cloud enhancement occurs more frequently for water clouds and less frequently for mixed phase and cirrus clouds and it occurs with similar frequency at all three levels. The temporal variability of solar attenuation is found to decrease with an increasing temporal sampling interval and to be largest for water clouds and smallest for multilayered and partly cloudy conditions. This work presents a first step towards estimating solar energy potential in the San Antonio area indirectly using available estimates of cloudiness from GOES satellites.
“…The GOES dataset used here, if fact, uses the cloud optical thickness to parameterize the clouds. Some examples of studying the impact of clouds on solar irradiance using optical thickness include References [44][45][46].…”
Since the main attenuation of solar irradiance reaching the earth’s surface is due to clouds, it has been hypothesized that global horizontal irradiance attenuation and its temporal variability at a given location could be characterized simply by cloud properties at that location. This hypothesis is tested using global horizontal irradiance measurements at two stations in San Antonio, Texas, and satellite estimates of cloud types and cloud layers from the Geostationary Operational Environmental Satellite (GOES) Surface and Insolation Product. A modified version of an existing solar attenuation variability index, albeit having a better physical foundation, is used. The analysis is conducted for different cloud conditions and solar elevations. It is found that under cloudy-sky conditions, there is less attenuation under water clouds than those under opaque ice clouds (optically thick ice clouds) and multilayered clouds. For cloud layers, less attenuation was found for the low/mid layers than for the high layer. Cloud enhancement occurs more frequently for water clouds and less frequently for mixed phase and cirrus clouds and it occurs with similar frequency at all three levels. The temporal variability of solar attenuation is found to decrease with an increasing temporal sampling interval and to be largest for water clouds and smallest for multilayered and partly cloudy conditions. This work presents a first step towards estimating solar energy potential in the San Antonio area indirectly using available estimates of cloudiness from GOES satellites.
“…However, assuming a homogeneous and plane-parallel water cloud layer, the SSAc and the phase function of the cloud droplets play a minor role in the determination of the transmission of the cloud layer, in contrast to COT (Rawlins and Foot, 1990). Under this consideration, the shortwave radiative effect of a water cloud can be either characterised by the COT alone or by a combination of the r eff and the LWC (Leontyeva and Stamnes, 1994). For the shortwave radiation range, the extinction coefficient in clouds, and thus also COT, has a weak dependence on the wavelength (Slingo and Schrecker, 1982).…”
Section: Methodsmentioning
confidence: 99%
“…Cloud optical properties can also be estimated from airborne measurements (e.g. Finger et al, 2016;Krisna et al, 2018). Flying directly below or above clouds allows both accurate measurements and direct comparisons and validations of the COT values retrieved from satellite sensors.…”
Section: Introductionmentioning
confidence: 99%
“…A number of studies have presented methods for the retrieval of COT using data from ground-based instruments, for example, from lidars (Gouveia et al, 2017), broadband pyranometers (Leontyeva and Stamnes, 1994; Barnard and Long, 2004;Qiu, 2006), sunphotometers (Min and Harrison, 1996;Chiu et al, 2010) or UV radiometers (Serrano et al, 2014). With ground-based microwave instruments the liquid water path (LWP) is determined (Dupont et al, 2018), which can be used to calculate the cloud optical thickness, knowing or assuming r eff (Stephens, 1994).…”
Abstract. We have used a method based on ground-based solar radiation measurements and radiative transfer models (RTMs) in order to estimate the following cloud optical properties: cloud optical thickness (COT), cloud single scattering albedo (SSAc) and effective droplet radius (reff). The method is based on the minimisation of the difference between modelled and measured downward shortwave radiation (DSR). The optical properties are estimated for more than 3000 stratus–altostratus (St–As) and 206 cirrus–cirrostratus (Ci–Cs) measurements during 2013–2017, at the Baseline Surface Radiation Network (BSRN) station in Payerne, Switzerland. The RTM libRadtran is used to simulate the total DSR as well as its direct and diffuse components. The model inputs of additional atmospheric parameters are either ground- or satellite-based measurements. The cloud cases are identified by the use of an all-sky cloud camera. For the low- to mid-level cloud class St–As, 95 % of the estimated cloud optical thickness values using total DSR measurements in combination with a RTM, herein abbreviated as COTDSR, are between 12 and 92 with a geometric mean and standard deviation of 33.8 and 1.7, respectively. The comparison of these COTDSR values with COTBarnard values retrieved from an independent empirical equation results in a mean difference of -1.2±2.7 and is thus within the method uncertainty. However, there is a larger mean difference of around 18 between COTDSR and COT values derived from MODIS level-2 (L2), Collection 6.1 (C6.1) data (COTMODIS). The estimated reff (from liquid water path and COTDSR) for St–As are between 2 and 20 µm. For the high-level cloud class Ci–Cs, COTDSR is derived considering the direct radiation, and 95 % of the COTDSR values are between 0.32 and 1.40. For Ci–Cs, 95 % of the SSAc values are estimated to be between 0.84 and 0.99 using the diffuse radiation. The COT for Ci–Cs is also estimated from data from precision filter radiometers (PFRs) at various wavelengths (COTPFR). The herein presented method could be applied and validated at other stations with direct and diffuse radiation measurements.
“…The SMART-Albedometer has been utilized to measure the spectral upward and downward irradiances; thereby it is called as an albedometer, as well as to measure the spectral upward radiance. The SMART-Albedometer is designed initially to cover measurements in the solar spectral range between 300 and 2,200 nm (Krisna et al, 2018;Wendisch et al, 2001;Wendisch et al, 2016). However, due to decreasing sensitivity of the spectrometers at large wavelengths, the use of the wavelengths was restricted to 300 -1,800 nm.…”
Abstract. The indirect effect of atmospheric aerosol particles on the Earth’s radiation balance remains one of the most uncertain components affecting climate change throughout the industrial period. This issue is partially a result of the incomplete understanding of aerosol-cloud interactions. One objective of the GoAmazon2014/5 and ACRIDICON-CHUVA projects was to improve the understanding of the influence of the emissions of the tropical megacity of Manaus (Brazil) on the surrounding atmospheric environment of the rainforest and to investigate its role in the life cycle of convective clouds. During one of the intensive observation periods (IOPs) in the dry season from September 1 to October 10, 2014, comprehensive instrument suites collected data from several ground sites. In a coordinated way, the advanced suites of sophisticated instruments were deployed in situ both from the U.S. Department of Energy Gulfstream-1 (G1) aircraft and the German High Altitude and Long-Range Research Aircraft (HALO) during three coordinated flights on September 9, 21, and October 1. Here we report on the comparison of measurements collected by the two aircraft during these three flights. Such comparisons are difficult to obtain, but they are essential for assessing the data quality from the individual platforms and quantifying their uncertainty sources. Similar instruments mounted on the G1 and HALO collected vertical profile measurements of aerosol particles number concentration and size distribution, cloud condensation nuclei concentration, ozone, and carbon monoxide concentration, cloud droplet size distribution, and downward solar irradiance. We find that the above measurements from the two aircraft agreed within the range given by the measurement uncertainties. Aerosol chemical composition measured by instruments on HALO agreed with the corresponding G1 data collected at high altitudes only. Furthermore, possible causes of discrepancies between the data sets collected by the G1 and HALO instrumentation are addressed in this paper. Based on these results, criteria for meaningful aircraft measurement comparisons are discussed.
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