Negative Aerosol‐Cloud r_e Relationship From Aircraft Observations Over Hebei, China

Abstract

Using six flights observations in September 2015 over Hebei, China, this study shows a robust negative aerosol‐cloud droplet effective radius (re) relationship for liquid clouds, which is different from previous studies that found positive aerosol‐cloud re relationship over East China using satellite observations. A total of 27 cloud samples was analyzed with the classification of clean and polluted conditions using lower and upper 1/3 aerosol concentration at 200 m below the cloud bases. By normalizing the profiles of cloud droplet re, we found significant smaller values under polluted than under clean condition at most heights. Moreover, the averaged profiles of cloud liquid water content (LWC) show larger values under polluted than clean conditions, indicating even stronger negative aerosol‐cloud re relationship if LWC is kept constant. The droplet size distributions further demonstrate that more droplets concentrate within smaller size ranges under polluted conditions. Quantitatively, the aerosol‐cloud interaction is found around 0.10–0.19 for the study region.

Distinct Impacts of Increased Aerosols on Cloud Droplet Number Concentration of Stratus/Stratocumulus and Cumulus

“…According to Twomey (1977), for constant cloud liquid water content (LWC), increasing cloud condensation nuclei (CCN) number would generate a more reflective cloud that consists of more but smaller cloud droplets, which scatters more solar radiation back to space. This was termed aerosol first indirect effect (AIE) or Twomey effect, which has been supported by ample evidences from both remote sensing (Bréon et al, 2002;Christensen et al, 2016;Garrett et al, 2004;Nakajima et al, 2001;Quaas et al, 2008) and in situ aircraft measurements (Pawlowska & Brenguier, 2000;Kleinman et al, 2012;Werner et al, 2014;Zhao, Qiu, et al, 2018).…”

“…The first is referred to as flight-based method, by which flights are classified as clean and polluted according to the sub-cloud N CCNS% (N sub CCNS% , if specified, S% in the subscript denotes the supersaturation). This method was widely used in previous studies (Jia, Ma, & Liu, 2019;Zhao, Qiu, et al, 2018;Zheng et al, 2010Zheng et al, , 2011. Here, N sub CCN is the averaged N CCN during the legs within 200 m below the cloud base, in which cloud base height is the lowest height that cloud can be continuously detected during the flight.…”

Distinct Impacts of Light and Heavy Precipitation on PM2.5 Mass Concentration in Beijing

“…For light pollution cases, precipitation is less likely to scavenge aerosol particles by collision due to few aerosol particles under clean conditions (Chate, 2005;Dong et al, 2016). In contrast, the hygroscopic growth of aerosol particles and the gas-particle conversion or secondary formation of aerosols promote PM 2.5 mass concentration (Su et al, 2016;Wu et al, 2018;Zhao, Qiu, et al, 2018). For PM 2.5 mass concentration in the range of 35-75 μg/m 3 , the light precipitation with amount 0-10 mm can enhance PM 2.5 mass concentration with an average increase of PM 2.5 mass concentration by 2.28-3.68 μg/m 3 ; however, the heavy precipitation with amount 10-50 mm can scavenge aerosol particles and make PM 2.5 mass concentration decrease while the scavenging efficiency was relatively low.…”

A Supercooled Water Cloud Detection Algorithm Using Himawari‐8 Satellite Measurements

“…The second flight was over Shijiazhuang, Baoding, and Datong on 27 August 2017, between 09:36 and 13:03 UTC at a stable flight altitude of approximately 5.9 km. The Particle Measuring System probes onboard the aircraft are used to collect the LWC, cloud temperature, size distribution of particles, and other cloud microphysical information, which are described in detail by Houze et al (1979) and Zhao et al (2018). Based on experience when using airborne measurements, we recognize cloud droplets with temperatures below 0°C, while LWCs higher than 10 −3 g/m 3 indicate SWCs (Reisner et al, 1998).…”