Abstract:Abstract. Cloud droplet chemical composition is a key observable property that can aid
understanding of how aerosols and clouds interact. As part of the Clouds,
Aerosols and Monsoon Processes – Philippines Experiment (CAMP2Ex),
three case studies were analyzed involving collocated airborne sampling of
relevant clear and cloudy air masses associated with maritime warm convection. Two of the cases represented a polluted marine background, with
signatures of transported East Asian regional pollution, aged over wa… Show more
“…3b) from 2009 to 2018 over the Manila Observatory was observed from July (~1.4) to September (~1.3), during the southwest monsoon. This period is associated with the biomass burning southwest of the Philippines (Oanh et al, 2018;Stahl et al, 2021;Crosbie et al, 2022). The median (per month) EAE ranged from ~0.9 in November to ~1.4 in August, a range which is within the values from previous studies collected from mixed sites and urban/industrial areas with both fine and coarse particles (Eck et al, 2005;Giles et al, 2012).…”
Section: Aerosol Optical Depthsupporting
confidence: 70%
“…1b). The highest median level of relative humidity for a month was in August (86.5 %) during the summer southwest monsoon, which is also the time of the year (June to August) when rainfall peaks in the region where the sampling station (Manila Observatory) is located (Coronas, 1920;Cruz et al, 2013). The highest mean hourly precipitation (Fig.…”
Section: Meteorology and Atmospheric Circulationmentioning
confidence: 97%
“…Studying this area is informative owing to the wide dynamic range in aerosol particle and weather conditions, which are interconnected. Aerosol particle lifecycle in the region is impacted by Philippine weather that is marked by two distinct monsoons, typhoons, and impacts from El Niño-Southern Oscillation and Madden-Julian Oscillation (Cruz et al, 2013;Xian et al, 2013;Reid et al, 2012;Reid et al, 2015;Hilario et al, 2021b).…”
Abstract. Aerosol particles in Southeast Asia have a complex life cycle and consequently are challenging to characterize. The diverse topography and weather in the region complicate the situation. An aerosol climatology was established based on AERONET data (December 2009 to October 2018) for clear sky days in Metro Manila, Philippines. Aerosol optical depth (AOD) values were highest in August, coinciding with the summer southwest monsoon, due partly to fine particles from urban aerosol particles, including soot. Also, August corresponds to the burning season in insular Southeast Asia when smoke is often transported to Metro Manila. Clustering of AERONET volume size distributions (VSD) resulted in five aerosol particle sources based on the position and magnitude of their peaks in the VSD and the contributions of specific particle species to AOD per cluster based on MERRA-2. The clustering showed that the majority of aerosol particles above Metro Manila were from a clean marine source (58 %), which could be related to AOD values there being relatively smaller than in other cities in the region. The following are the other particle sources over Metro Manila: fine polluted (20 %), mixed polluted (12 %), urban/industrial (5 %), and cloud processing (5 %). Furthermore, MERRA-2 AOD data over Southeast Asia were analyzed using empirical orthogonal functions. Along with AOD fractional compositional contributions and wind regimes, four dominant aerosol particle air masses emerged: two sulfate air masses from East Asia, an organic carbon source from Indonesia, and a sulfate source from the Philippines. Knowing the local and regional aerosol particle air masses that impact Metro Manila is useful in identifying the sources while gaining insight on how aerosol particles are affected by long-range transport and their impact on regional weather.
“…3b) from 2009 to 2018 over the Manila Observatory was observed from July (~1.4) to September (~1.3), during the southwest monsoon. This period is associated with the biomass burning southwest of the Philippines (Oanh et al, 2018;Stahl et al, 2021;Crosbie et al, 2022). The median (per month) EAE ranged from ~0.9 in November to ~1.4 in August, a range which is within the values from previous studies collected from mixed sites and urban/industrial areas with both fine and coarse particles (Eck et al, 2005;Giles et al, 2012).…”
Section: Aerosol Optical Depthsupporting
confidence: 70%
“…1b). The highest median level of relative humidity for a month was in August (86.5 %) during the summer southwest monsoon, which is also the time of the year (June to August) when rainfall peaks in the region where the sampling station (Manila Observatory) is located (Coronas, 1920;Cruz et al, 2013). The highest mean hourly precipitation (Fig.…”
Section: Meteorology and Atmospheric Circulationmentioning
confidence: 97%
“…Studying this area is informative owing to the wide dynamic range in aerosol particle and weather conditions, which are interconnected. Aerosol particle lifecycle in the region is impacted by Philippine weather that is marked by two distinct monsoons, typhoons, and impacts from El Niño-Southern Oscillation and Madden-Julian Oscillation (Cruz et al, 2013;Xian et al, 2013;Reid et al, 2012;Reid et al, 2015;Hilario et al, 2021b).…”
Abstract. Aerosol particles in Southeast Asia have a complex life cycle and consequently are challenging to characterize. The diverse topography and weather in the region complicate the situation. An aerosol climatology was established based on AERONET data (December 2009 to October 2018) for clear sky days in Metro Manila, Philippines. Aerosol optical depth (AOD) values were highest in August, coinciding with the summer southwest monsoon, due partly to fine particles from urban aerosol particles, including soot. Also, August corresponds to the burning season in insular Southeast Asia when smoke is often transported to Metro Manila. Clustering of AERONET volume size distributions (VSD) resulted in five aerosol particle sources based on the position and magnitude of their peaks in the VSD and the contributions of specific particle species to AOD per cluster based on MERRA-2. The clustering showed that the majority of aerosol particles above Metro Manila were from a clean marine source (58 %), which could be related to AOD values there being relatively smaller than in other cities in the region. The following are the other particle sources over Metro Manila: fine polluted (20 %), mixed polluted (12 %), urban/industrial (5 %), and cloud processing (5 %). Furthermore, MERRA-2 AOD data over Southeast Asia were analyzed using empirical orthogonal functions. Along with AOD fractional compositional contributions and wind regimes, four dominant aerosol particle air masses emerged: two sulfate air masses from East Asia, an organic carbon source from Indonesia, and a sulfate source from the Philippines. Knowing the local and regional aerosol particle air masses that impact Metro Manila is useful in identifying the sources while gaining insight on how aerosol particles are affected by long-range transport and their impact on regional weather.
“…A suborbital ACI measurement program could be considerably more complex. Reviews of past modeling and measurement work (e.g., Rosenfeld et al, 2014;Mülmenstädt & Feingold, 2018;Bellouin et al, 2020) and experience from recent aircraft campaigns aimed at characterizing aerosol particles, clouds, and their interactions in specific regions (Behrenfeld et al, 2019;Crosbie et al, 2022;Sorooshian et al, 2019Sorooshian et al, , 2021 provide some indication of what would be involved. Both aerosol and cloud properties would need to be measured for this application, on spatial scales ranging from 10 −7 to 10 6 m and temporal scales of minutes to hours or more.…”
Section: Discussion-addressing Suborbital Data Limitationsmentioning
Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent work has produced modest increases only in the confidence of the uncertainty estimate itself. This review summarizes the contributions toward reducing the uncertainty in the aerosol forcing of climate made by satellite observations, measurements taken within the atmosphere, as well as modeling and data assimilation. We adopt a more measurement‐oriented perspective than most reviews of the subject in assessing the strengths and limitations of each; gaps and possible ways to fill them are considered. Currently planned programs supporting advanced, global‐scale satellite and surface‐based aerosol, cloud, and precursor gas observations, climate modeling, and intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved, are all essential. But in addition, new efforts are needed: (a) to obtain systematic aircraft in situ measurements capturing the multi‐variate probability distribution functions of particle optical, microphysical, and chemical properties (and associated uncertainty estimates), as well as co‐variability with meteorology, for the major aerosol airmass types; (b) to conceive, develop, and implement a suborbital (aircraft plus surface‐based) program aimed at systematically quantifying the cloud‐scale microphysics, cloud optical properties, and cloud‐related vertical velocities associated with aerosol‐cloud interactions; and (c) to focus much more research on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the persistent uncertainty in aerosol climate forcing.
“…When rain falls through unsaturated air, some or all of the droplets may evaporate before reaching the ground, so the tracer in the rain may be released back into the atmosphere closer to the ground (Crosbie et al, 2022) under-cloud evaporation leads to an increase in the global aerosol burden, and the increase in the burden of different types of aerosols is about 7.8-15%. When considering raindrop diameter and evaporation rate (Gong et al, 2006), the release of aerosols is greatly reduced, and in combination with the results observed in 1992 in the Mainz vertical wind tunnel and in a 4-meter-high shaft (Mitra et al, 1992), the aerosol particles do not break up during raindrop evaporation and are converted into coarse particles that enhance removal by settling, resulting in a lower aerosol load.…”
Section: Effect Of Secondary Evaporation Under Clouds On Aerosolsmentioning
The study of below‐cloud evaporation effects under clouds in the Yellow River source region is of great significance for regional water resource generation as well as for water resource security in the arid and semi‐arid regions of northern China. In this study, we quantitatively assessed the evapotranspiration effect in the Yellow River source region from March to November based on the improved Stewart model. The study concluded that: (1) below‐cloud evaporation was slightly higher in summer than in other seasons (residual fractions of raindrop evaporation were 80.57% in summer, 81.12% in spring, and 84.2% in autumn, respectively); and (2) sub‐cloud evaporation diminishes with increasing altitude (residual fractions of raindrop evaporation were 83.09% in the western part of the area, 81.82% in the central part of the area, and 81.36% in the eastern part of the area, respectively). (3) The total linear index between study areas f and ∆d is 2.24, where f > 95%, it is 1.19; that is, the evaporation of raindrops increases by 1% and the reduction in the excess of mercury by about 2‰. (4) Local meteorological factors (temperature, precipitation, and relative humidity) and raindrop diameter have a cross‐influence on below‐cloud evaporation, with relative humidity having the most significant effect, with the highest correlation coefficient of 3.03 when relative humidity is less than 70%. The results of the study can provide a parameter basis for hydrological and climatic models in the Yellow River Basin.
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