Detection of Mixed‐Phase Convective Clouds by a Binary Phase Information From the Passive Geostationary Instrument SEVIRI

Abstract

Between −37 and 0 °C, clouds are liquid, ice, or mixed phase. Nearly all retrieval algorithms for passive instruments provide binary phase information—ice or liquid—making it difficult to retrieve mixed‐phase cloud properties. Based on measurements from the geostationary space‐based instrument Spinning Enhanced Visible and InfraRed Imager (SEVIRI), we show that the retrieved ice crystal effective radius is smaller than the liquid droplet effective radius for 48% of 230 analyzed cloud thermodynamic phase transitions—phase transition from liquid to ice of rising convective clouds—while ice crystals are expected to be larger than cloud droplets. We simulate mixed‐phase cloud radiances with the numerical model Santa Barbara DISORT Atmospheric Radiative Transfer for which we compare simulated effective radius retrievals with observations. The phase retrieval algorithm from SEVIRI does not represent well mixed‐phase clouds, and categorizing clouds by only ice and liquid is not enough to accurately represent mixed‐phase cloud optical properties. We conclude that the mixed‐phase nature of clouds explains that retrieved cloud droplet radii are larger than ice crystal radii directly before and after the phase transition. However, from a cloud tracking algorithm perspective, the variation of the effective radius enables the detection of mixed‐phase convective clouds from binary phase information.

Analysis of the Thermodynamic Phase Transition of Tracked Convective Clouds Based on Geostationary Satellite Observations

“…In Figures 3e and 3f, we observe a decrease of r e at the phase transition as already described by Coopman et al (2019): The reason for this apparently unphysical feature is that the values of r e depend on the thermodynamic phase retrieved by the algorithm beforehand. Unfortunately, CLAAS‐2 does not consider mixed‐phase clouds that lead to a bias in cloud microphysical property retrievals.…”

“…Figures 5d, 5e, and 5f show the T g distribution for the two regimes of CAPE(t 0 ), t), and ). We can notice that the lower and upper quartiles of t) and ) are similar, which can be surprising: We expect t) to be larger than t), but the similar values are an artifact around the phase transition already described by Coopman et al (2019) and explained earlier. Clouds with CAPE(t 0 ) less than 11 J/kg are associated with a median T g of −23.9°C and clouds with CAPE(t 0 ) greater than 476.5 J/kg are associated with a median T g of −17.2°C.…”

“…In the final step, we collect the cloud properties of the coldest pixel of a cloud object for each time step, in line with Coopman et al (2019). The transition of the cloud phase of the coldest pixel from liquid to ice represents the initiation of the thermodynamic phase transition of the tracked cloud.…”

Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors

“…Several studies have shown that mixed-phase clouds occur irrespective of the season, can be found in diverse locations, and can be associated with various cloud types (Korolev et al, 2017). Observations of mixed-phase clouds include active (e.g., Zhang et al, 2010;Tan et al, 2014;Cesana & Storelvmo, 2017) and passive satellite (e.g., Coopman et al, 2019;Noh et al, 2019;Tan et al, 2019), airborne in situ (e.g., Korolev, 2008;Costa et al, 2017;Barrett et al, 2020), ground-based (e.g., Henneberger et al, 2013;Yu et al, 2014;Gierens et al, 2020) and aircraft-based remote sensing measurements (e.g., Wang et al, 2012;Plummer et al, 2014). In Tan et al (2014), in particular, mixed-phase clouds have been studied statistically in terms of supercooled cloud fraction, defined as the ratio of the in-cloud frequency of supercooled liquid pixels to the total frequency of supercooled liquid and ice pixels within 2 • latitude by 5 • longitude grid boxes, at several isotherms between -10 • C and -30 • C, distinguishing cases in the Northern Hemisphere (NH) and in the Southern Hemisphere (SH), as well as cases over ocean and over land.…”

“…Several studies have shown that mixed‐phase clouds occur irrespective of the season, can be found in diverse locations, and can be associated with various cloud types (Korolev et al., 2017). Observations of mixed‐phase clouds include active (e.g., Cesana & Storelvmo, 2017; Tan et al., 2014; Zhang et al., 2010) and passive satellite (e.g., Coopman et al., 2019; Noh et al., 2019; Tan et al., 2019), airborne in situ (e.g., Barrett et al., 2020; Costa et al., 2017; Korolev, 2008), ground‐based (e.g., Gierens et al., 2020; Henneberger et al., 2013; Yu et al., 2014) and aircraft‐based remote sensing measurements (e.g., Plummer et al., 2014; Wang et al., 2012). In Tan et al.…”