Aerosol-DCC Invigoration

1. Motivations for the Study of Deep Convective Clouds (DCC)

Through the severe weather produced, deep convective clouds (DCCs) pose a significant hazard to those in their vicinity, as well as producing significant impacts on local, state, and national economies. In 2011, outbreaks of severe thunderstorms across the southeastern US were responsible for over 350 fatalities. A 2017 insurance report (Gunturi and Tippett 2017) found that severe convective storms in the US between 2003 and 2015 caused average annual losses of $11.23 billion (in 2016 dollars). Due to both increased societal vulnerability (Cutter et al. 2003) and increased severe thunderstorm environment frequency (Gensini et al., 2014), there is also an increasing trend of losses from severe thunderstorms (Changnon et al. 2001) and tornadoes (Changnon 2009).

By modifying atmospheric radiation, momentum, heat, and moisture, DCCs strongly impact the Earth’s climate. The energy balance and water cycle depend on cloud properties such as coverage, vertical extent, and precipitation. For example, the anvils of DCCs are climatically important because of their latent heating and radiative effects (Houze and Hobbs 1982; Ackerman et al. 1988; Randall et al. 1989). Further, a high percentage of rainfall occurs in conjunction with DCCs, especially in the tropics (Schumacher and Houze 2003; Janiga and Thorncroft 2014).

In addition to climatic impacts, DCCs play a significant role in various other atmospheric phenomena. The coupling between DCCs and the synoptic scale is important in modulating tropical (Mapes 2000) and mid-latitude synoptic-scale systems (Bullock and Johnson 1971). Further, DCCs are central to the overall dynamics of the tropical troposphere (Raymond et al. 2015). Overshooting convection is a key mechanism for troposphere–stratosphere exchange (Fischer et al. 2003; Liu and Zipser 2005; Corti et al. 2008). Thus a complete understanding of DCCs is important to the understanding of weather and climate systems.

Both global circulation models and regional weather and climate models exhibit significant biases in DCC top temperature (Varble et al. 2011), reflectivity profiles (Eitzen and Xu 2005; Xu et al. 2005; Lang et al. 2007; Blossey et al. 2007), and precipitation (Stephens et al. 2010; Varble et al. 2011). Cumulus parameterizations in general circulation models (GCMs) poorly represent the evolution of DCCs (Del Genio et al. 2012) while the choice of microphysics parameterizations in cloud resolving models (CRMs) can strongly vary the representation of a range of DCC properties (Morrison et al. 2015; Feng et al. 2018). Such issues can produce large biases and spread in climate models (Zhang et al. 2010; Kalognomou et al. 2013) with a strong impact on confidence in future climate projections. Since DCCs impact atmospheric radiation, momentum, heat, and moisture, such errors can produce outsized impacts on downstream weather in real-time forecasts (Lillo and Parsons 2017). Improving model representation of DCCs therefore requires detailed characterization of their structural life cycle given environmental thermodynamic, kinematic, and aerosol conditions.


2. Prior Understanding on the Interaction between Aerosols and DCC Invigoration

For warm convective clouds a number of aerosol effects have been proposed. Twomey et al. (1984) suggested that the effect of higher concentrations of cloud condensation nuclei (CCN) is to promote more numerous but smaller cloud droplets. This is supported by many studies (e.g., Gunn and Phillips 1957; Rosenfeld 1999). Albrecht (1989) proposed that cloud coverage and cloud lifetime increase in the presence of higher concentrations of aerosols. This is supported by Lindsey and Fromm (2008) and Koren et al. (2010). However, Jiang et al. (2006) used large eddy simulations (LES) to show little change in warm cloud lifetime with increased aerosol concentrations.

For deep convective clouds (DCCs) with mixed-phase regions, many studies have observed an increase in cloud-top height (CTH) or a decrease in cloud-top temperature (CTT) coincident with an increase of aerosol-loading (e.g., Andreae et al. 2004; Li et al. 2011; Koren et al. 2012; Storer and van den Heever 2013; Storer et al. 2013). This implies an invigoration of DCCs by increased aerosol concentrations; a fact corroborated by both observational (Andreae et al. 2004) and modelling studies (van den Heever et al. 2006) which show enhanced updrafts in polluted conditions. In addition, in a survey of TRMM convective features between 2004 and 2011, Stolz et al. (2015) showed that reflectivity in the mixed phase region of DCCs is up to 5 dBz greater in polluted environments than in pristine environments.

However, Varble (2018) argued that the aerosol-CTT relationship for DCCs over the DOE Southern Great Plains ARM site (SGP) is questionable upon careful consideration of ambient thermodynamic conditions such as convective available potential energy (CAPE) and the level of neutral buoyancy (LNB). Further, while van den Heever et al. (2011) showed that with increased CCN there is increased anvil cloud coverage associated with tropical oceanic DCCs, Khairoutdinov and Yang (2013) showed the opposite. In addition, by examining four different regions using NASA Tropical Rainfall Measurement Mission (TRMM) data, Wall et al. (2014) showed that the aerosol-DCC relationship can vary by location.

A number of studies have argued that rainfall is suppressed in individual DCCs when aerosol concentrations are high (Rosenfeld 1999; Rosenfeld et al. 2001; Storer and van den Heever 2013) especially in the early stages (Tao et al. 2007). On the other hand, Koren et al. (2012) argued that increased aerosol-loading increases DCC rain rates, Tao et al. (2007) showed that rainfall in more mature DCCs can increase or decrease, dependent on the environment, while Khain et al. (2005) and Tao et al. (2007) showed that there is only an increase in precipitation for DCCs in maritime air-masses. Further, Fan et al. (2013) found little relationship between aerosols and DCC rainfall, although the stratiform proportion was increased coincident with broader and deeper anvils. Despite many studies on the effect of aerosols on DCC rainfall, there is still little consensus on the overall effect, although the environment is a clear modulator of the aerosol-precipitation relationship.

There are a number of proposed mechanisms to explain the observed DCC invigoration found in many studies as noted above. Khain et al. (2005) and Rosenfeld et al. (2008) built off the “Twomey effect” (more numerous but smaller cloud droplets in warm clouds) by hypothesizing that the delay in the collision-coalescence process allows for more cloud water to be advected to higher altitudes, leading to more cloud water freezing and larger releases of latent heat. This in turn invigorates DCC updrafts. This is often referred to as a thermodynamic aerosol indirect effect (Fan et al 2013) due to the increased release of latent heat in the updraft.

Fan et al. (2013) show that this is most common in the early-stages of DCCs. However, this mechanism has been shown insignificant in various conditions by many modelling studies, as will be highlighted in the next section. Further, negative buoyancy from increased condensate loading is often neglected. Lebo and Seinfeld (2011) demonstrate that the balance between latent heating and the increase in condensed water aloft, each having opposing effects on buoyancy, varies the invigoration of DCCs. Lee et al. (2008) argued that through increased evaporation of cloud water (in high-aerosol cases), stronger more numerous cold pools with convergence lines developed. This in turn led to stronger updrafts with greater precipitation rates.

In contrast to ideas invoking an increased updraft speed, Morrison and Grabowski (2011) and Fan et al. (2013) argue for a microphysical reason for the aerosol-CTH relationship. They propose that the increased number of smaller cloud droplets reaching the anvils of DCCs in more polluted cases, leads to a reduced ice particle size and therefore fall velocity. Since DCC anvils dissipate through the fallout of hydrometeors, lower fall velocities reduce the dissipation of anvils. In the updraft region of the anvil, fall velocities can be zero, or even negative, and this effect will then lead to increased CTH. More succinctly, an increase in aerosols induces larger amounts of smaller but longer-lasting ice particles in the anvils of deep convection that lead to the observed increase in CTH.

This section highlights the complexity of results pertaining to DCC invigoration by aerosols. While the consensus seems to be that DCCs are enhanced in environments with high aerosol concentrations, there are many contrasting results, especially with respect to under what conditions this occurs and which mechanisms cause the invigoration.


3. Challenges in Aerosol-Convection Interactions

Quantifying aerosol impacts on DCC properties by disentangling them from other environmental factors has been particularly challenging (Fan et al. 2016). For example, Varble (2018) demonstrated that the aerosol-CTT relationship as presented by Li et al. (2011) (a heavily cited paper on the aerosol-CTT relationship) is rendered insignificant by a careful statistical evaluation that considered only two thermodynamic variables. Similarly, Mauger and Norris (2007) also found significant meteorological bias in the proposed relationship between aerosol optical depth (AOD) and cloud fraction. Further, Gryspeerdt et al. (2014) showed that by considering cloud properties such as cloud fraction, the relationship between AOD and cloud top height is mediated. Many other studies have highlighted issues in various approaches to diagnosing aerosol-indirect effects (e.g., Yuter et al. 2013; Wall et al. 2014; Grabowski 2016). Other studies further argue that errors in models (White et al. 2017, Grabowski 2015) and observations (Grabowski and Morrison 2016) are larger than the aerosol indirect effects.

A further issue is the varying results for different environments, alluded to in the previous section. Specifically, the aerosol indirect effect on DCC invigoration has been found to be insignificant or non-existent in dry conditions (Khain et al. 2005; Tao et al. 2007; Lebo and Seinfeld 2011; Lebo et al. 2012), for cold cloud base convection (Fan et al. 2012), and in environments with strong wind shear (Fan et al. 2009, 2012). Further, the effects of aerosols on a single, isolated convective cell may differ from cumulative effects over mesoscale or synoptic scales because of meteorological buffers that minimize the overall impact of aerosols on the DCCs analyzed (e.g., Stevens and Feingold 2009; van den Heever et al. 2011).

Disentangling aerosol impacts on DCCs from meteorological impacts has been further complicated by the limited availability of measurements, including thermodynamic and aerosol profiles, in close proximity to DCC. The aerosol measurement of primary importance to aerosol indirect effects on DCCs is cloud condensation nuclei (CCN) concentration but this is complicated to measure. Thus, many studies have used AOD or condensation nuclei (CN) concentration as proxies for CCN concentration (e.g. Li et al. 2011). Altaratz et al. (2013) showed that AOD can vary by 20% depending on relative humidity. Such issues with AOD are supported by many studies (e.g., Zhang et al. 2005; Chand et al. 2012; Boucher and Quass 2013; Omar et al. 2013). Finally, surface aerosol concentrations and those in the free troposphere are not always comparable (e.g., Fridlind et al. 2004; Corrigan et al. 2008). Correlations also therefore need to be controlled for surface-based vs. elevated convection.

Only through careful statistical approaches, with appropriate aerosol measurements, and by employing both observational and modelling methodologies, is it possible to accurately diagnose aerosol indirect effects on DCCs.


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