Deep Convective Clouds Research Articles

Sensitivity of mixed-phase moderately deep convective clouds to parameterizations of ice formation – an ensemble perspective

Abstract. The formation of ice in clouds is an important processes in mixed-phase and ice-phase clouds. Yet, the representation of ice formation in numerical models is highly uncertain. In the last decade, several new parameterizations for heterogeneous freezing have been proposed. However, it is currently unclear what the effect of choosing one parameterization over another is in the context of numerical weather prediction. We conducted high-resolution simulations (Δx=250 m) of moderately deep convective clouds (cloud top ∼-18 ∘C) over the southwestern United Kingdom using several formulations of ice formation and compared the resulting changes in cloud field properties to the spread of an initial condition ensemble for the same case. The strongest impact of altering the ice formation representation is found in the hydrometeor number concentration and mass mixing ratio profiles. While changes in accumulated precipitation are around 10 %, high precipitation rates (95th percentile) vary by 20 %. Using different ice formation representations changes the outgoing short-wave radiation by about 2.9 W m−2 averaged over daylight hours. The choice of a particular representation for ice formation always has a smaller impact then omitting heterogeneous ice formation completely. Excluding the representation of the Hallett–Mossop process or altering the heterogeneous freezing parameterization has an impact of similar magnitude on most cloud macro- and microphysical variables with the exception of the frozen hydrometeor mass mixing ratios and number concentrations. A comparison to the spread of cloud properties in a 10-member high-resolution initial condition ensemble shows that the sensitivity of hydrometeor profiles to the formulation of ice formation processes is larger than sensitivity to initial conditions. In particular, excluding the Hallett–Mossop representation results in profiles clearly different from any in the ensemble. In contrast, the ensemble spread clearly exceeds the changes introduced by using different ice formation representations in accumulated precipitation, precipitation rates, condensed water path, cloud fraction, and outgoing radiation fluxes.

Convective System Dynamics Viewed in 3D Over the Oceans

AbstractPrevious studies indicated a relationship between deep convection and sea surface wind patterns; however, it remains difficult to remotely observe a deep Convective System (CS) and its dynamics above the ocean due to the lack of data at the mid atmospheric levels. To collect the details of the CS dynamics, some nearly simultaneous data of three CS features, that is, cloud brightness temperature, vertical wind at the midlevels, and horizontal wind at the sea surface, can be now obtained by a combination of sensors from a geostationary (Meteosat) and two polar‐orbiting satellites (Sentinel‐1 and Aeolus), having corresponding acquisition time and orbit track matching. This work thus illustrates a nearly three‐dimensional view of the CS atmospheric dynamics over the sea, including deep convective clouds observed by Meteosat, intense downdrafts measured by Aeolus, and strong surface winds estimated by Sentinel‐1.

Radiometric Performance Evaluation of FY-4A/AGRI Based on Aqua/MODIS.

Fengyun-4A (FY-4A) is the first satellite of the Chinese second-generation geostationary orbit meteorological satellites (FY-4). The Advanced Geostationary Radiation Imager (AGRI), onboard FY-4A does not load with high-precision calibration facility in visible and near infrared (VNIR) channel. As a consequence, it is necessary to comprehensively evaluate its radiometric performance and quantitatively describe the attenuation while using its VNIR data. In this paper, the radiometric performance at VNIR channels of FY-4A/AGRI is evaluated based on Aqua/MODIS data using the deep convective cloud (DCC) target. In order to reduce the influence of view angle and spectral response difference, the bi-directional reflectance distribution function (BRDF) correction and spectral matching have been performed. The evaluation result shows the radiometric performance of FY-4A/AGRI: (1) is less stable and with obvious fluctuations; (2) has a lower radiation level because of 24.99% lower compared with Aqua/MODIS; 3) has a high attenuation with 9.11% total attenuation over 2 years and 4.0% average annual attenuation rate. After the evaluation, relative radiometric normalization between AGRI and MODIS in VNIR channel is performed and the procedure is proved effective. This paper proposed a more reliable reference for the quantitative applications of FY-4A data.

Convective uplift of pollution from the Sichuan Basin into the Asian monsoon anticyclone during the StratoClim aircraft campaign

Abstract. The StratoClim airborne campaign took place in Nepal from 27 July to 10 August 2017 to document the physical and chemical properties of the South Asian upper troposphere–lower stratosphere (UTLS) during the Asian summer monsoon (ASM). In the present paper, simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of Asian monsoon anticyclone (AMA) and on the formation of the Asian tropopause aerosol layer (ATAL) during the StratoClim campaign. StratoClim took place during a break phase of the monsoon with intense convective activity over South China and Sichuan. Comparisons between brightness temperatures (BTs) at 10.8 µm observed by satellite sensors and simulated by Meso-NH highlight the ability of the model to correctly reproduce the life cycle of deep convective clouds. A comparison between CO and O3 concentrations from Meso-NH and airborne observations (StratoClim and IAGOS (In-service Aircraft for a Global Observing System)) demonstrates that the model captures most of the observed variabilities. Nevertheless, for both gases, the model tends to overestimate the concentrations and misses some thin CO plumes related to local convective events probably because the resolution is too coarse, but the convective uplift of pollution is very well captured by the model. We have therefore focused on the impact of Sichuan convection on the AMA composition. A dedicated sensitivity simulation showed that the 7 August convective event brought large amounts of CO deep into the AMA and even across the 380 K isentropic level located at 17.8 km. This Sichuan contribution enhanced the CO concentration by ∼15 % to reach more than 180 ppbv over a large area around 15 km height. It is noteworthy that Meso-NH captures the impact of the diluted Sichuan plume on the CO concentration during a StratoClim flight south of Kathmandu, highlighting its ability to reproduce the transport pathway of Sichuan pollution. According to the model, primary organic aerosol and black carbon particles originating from Sichuan are transported following the same pathway as CO. The large particles are heavily scavenged within the precipitating part of the convective clouds but remain the most important contributor to the particle mass in the AMA. Over the whole AMA region, the 7 August convective event resulted in a 0.5 % increase in CO concentration over the 10–20 km range that lasted about 2 d. The impact of pollution uplift from three regions (India, China, and Sichuan) averaged over the first 10 d of August has also been evaluated with sensitivity simulations. Even during this monsoon break phase, the results confirm the predominant role of India relative to China with respective contributions of 11 % and 7 % to CO concentration in the 10–15 km layer. Moreover, during this period a large part (35 %) of the Chinese contribution comes from the Sichuan Basin alone.

Diurnal variation of deep convective clouds over Indian monsoon region and its association with rainfall

Diurnal cycle of deep convective clouds (DCC) over the Indian Summer Monsoon Region is studied. A harmonic analysis has been applied on the 3 hourly deep convective cloud fraction estimated from satellite observations to derive diurnal and semi-diurnal amplitudes of deep convective clouds. The diurnal cycle of deep convective clouds shows seasonal variations and amplitudes which are stronger during the northern hemispheric summer than winter and exhibits prominence over land as compared to ocean. Irrespective of seasons, deep convection peaks in the late evening hours over land whereas the peak is in the afternoon hours over majority of the oceanic regions considered in our study. The reason for the difference is attributed to the semi-diurnal oscillation which determines the oceanic diurnal cycle of deep convection. Various parameters which represent the tropospheric instability are equally affected by the semi-diurnal oscillation as in deep convective clouds over ocean. These results suggest that diurnal tides could play a key role in governing the daily cycle of deep convective clouds over oceanic regions. The relation between diurnal amplitudes of DCC and rainfall is also explored and it is shown that the strength of the daily cycle of DCC has a strong bearing on the amount of rainfall observed over the Indian summer monsoon region.

Impacts of cloud microphysics parameterizations on simulated aerosol–cloud interactions for deep convective clouds over Houston

Abstract. Aerosol–cloud interactions remain largely uncertain with respect to predicting their impacts on weather and climate. Cloud microphysics parameterization is one of the factors leading to large uncertainty. Here, we investigate the impacts of anthropogenic aerosols on the convective intensity and precipitation of a thunderstorm occurring on 19 June 2013 over Houston with the Chemistry version of Weather Research and Forecast model (WRF-Chem) using the Morrison two-moment bulk scheme and spectral bin microphysics (SBM) scheme. We find that the SBM predicts a deep convective cloud that shows better agreement with observations in terms of reflectivity and precipitation compared with the Morrison bulk scheme that has been used in many weather and climate models. With the SBM scheme, we see a significant invigoration effect on convective intensity and precipitation by anthropogenic aerosols, mainly through enhanced condensation latent heating. Such an effect is absent with the Morrison two-moment bulk microphysics, mainly because the saturation adjustment approach for droplet condensation and evaporation calculation limits the enhancement by aerosols in (1) condensation latent heat by removing the dependence of condensation on droplets and aerosols and (2) ice-related processes because the approach leads to stronger warm rain and weaker ice processes than the explicit supersaturation approach.

A cloud classification method based on random forest for FY-4A

ABSTRACT Cloud is complicated due to its various types and distribution on different layers. Various classification principles and overlapping of clouds on multiple layers make it difficult to classify clouds correctly. A cloud classification method based on random forest (RF) for FengYun-4A (FY-4A) is presented in this paper, aiming at obtaining cloud classification products with high temporal resolution and extensive coverage. The method classifies clouds into multi-layer clouds and 8 categories of single-layer clouds (Deep convective cloud, Nimbostratus, Cumulus, Stratocumulus, Stratus, Altocumulus, Altostratus and Cirrus). Additionally, multi-layer clouds are further classified into 12 categories of two-layer clouds (combinations of 8 single-layer clouds). CloudSat cloud classification products are used as the target class and to evaluate the method. In order to classify clouds correctly, it is necessary to capture cloud properties comprehensively. Thus we perform comparative pre-experiments to analyse the effects of FY-4A cloud products on cloud classification. It is demonstrated that clouds products can improve cloud classification. Therefore, cloud optical thickness (COT), cloud effective radius (CER) and cloud top height (CTH) are used as dataset together with multispectral data in cloud classification. Cloud classification models based on different algorithms and different channels combinations are compared. The results show that RF models perform better than K-Nearest Neighbour (KNN) models and Back Propagation Neural Network (BPNN) models in cloud classification, and models using all channels’ data perform better than models using data of selected channels combination. The method can provide cloud types and distribution for a FY-4A scan full disk in low time cost. Especially, it gives more specific types for multi-layer clouds, which can provide reference for subsequent research on cloud classification and FY-4A satellite.

Rapid Contraction of the Radius of Maximum Tangential Wind and Rapid Intensification of a Tropical Cyclone

AbstractDuring the intensification of a tropical cyclone (TC), the radius of maximum tangential wind (RMW) often contracts due to the spin‐up of tangential wind being much faster inside the RMW than at the RMW itself. However, rapid RMW contractions prior to rapid intensification (RI) of TCs are observed. Statistical analysis of best‐track data for the North Atlantic between 2000 and 2017 indicates that rapid RMW contraction (≥20 nmi within 24 h) does not necessarily cause RI (≥30 kt within 24 h) of a TC. An efficient TC RI is generally seen if the RMW contracts to ≤30 nmi. The change (contraction or expansion) of the RMW is prevalent for weak storms, and RMW contraction is found to be at its most rapid for TC initial intensities ≤60 kt. Rapid RMW contraction and simultaneous RI generally occurs when the initial RMW is >30 nmi. Convective heating associated with very deep convective clouds with infrared brightness temperatures <208 K appearing toward the storm center is important for RMW contraction and sufficient amounts of the convective heating are important for intensification. Less convective heating is required to have the same intensification rate for a storm with an initially smaller RMW. A storm is more likely to experience RI with relatively less convective heating after the RMW contracts to a smaller size. This study demonstrates the role of convective heating on RMW contraction and storm spin‐up through different processes in the early stages of a TC.

Lightning and Secondary Convection in the Anvil of the May 29, 2012 Oklahoma Supercell Storm Observed by DC3

AbstractA supercell thunderstorm formed as part of a cluster of severe storms near Kingfisher, Oklahoma on May 29, 2012 during the Deep Convective Clouds and Chemistry field experiment. This storm produced 5 hail, an EF‐1 tornado, and copious lightning over the course of a few hours within range of the Oklahoma Lightning Mapping Array and the KTLX WSR‐88D radar. This study focuses on a ∼1‐h interval during which a line of secondary convection formed and intensified within the anvil of the Kingfisher supercell. An analysis of radar reflectivity, radial velocity, and low‐level divergence shows that the formation of the secondary convection was consistent with a previously proposed mechanism; the instability leading to the convection was initiated by diabatic cooling in dry air below the anvil from sublimation, melting and evaporation of virga falling from the anvil, coincident with weak rising motion above a surface outflow boundary adjacent to the sub‐anvil downdraft. Prior to the formation of the secondary convection, flashes extended up to 60 km from the deep convection into the anvil. After the line of secondary convection formed, it initiated long lightning flashes that propagated along the line, and it continued to produce lightning as it moved eastward out from under the anvil. The charge structure inferred from flashes in the parent storm and in the downstream anvil suggests that charge was separated locally in the anvil following the development of an outflow boundary by the Kingfisher storm, which also contributed to the initiation of the secondary convection.

3D radiative heating of tropical upper tropospheric cloud systems derived from synergistic A-Train observations and machine learning

Abstract. Upper tropospheric (UT) cloud systems constructed from Atmospheric Infrared Sounder (AIRS) cloud data provide a horizontal emissivity structure, allowing the convective core to be linked to anvil properties. By using machine learning techniques, we composed a horizontally complete picture of the radiative heating rates deduced from CALIPSO lidar and CloudSat radar measurements, which are only available along narrow nadir tracks. To train the artificial neural networks, we combined the simultaneous AIRS, CALIPSO and CloudSat data with ERA-Interim meteorological reanalysis data in the tropics over a period of 4 years. The resulting non-linear regression models estimate the radiative heating rates as a function of about 40 cloud, atmospheric and surface properties, with a column-integrated mean absolute error (MAE) of 0.8 K d−1 (0.5 K d−1) for cloudy scenes and 0.4 K d−1 (0.3 K d−1) for clear sky in the longwave (shortwave) spectral domain. Developing separate models for (i) high opaque clouds, (ii) cirrus, (iii) mid- and low-level clouds and (iv) clear sky, independently over ocean and over land, leads to a small improvement, when considering the profiles. These models were applied to the whole AIRS cloud dataset, combined with ERA-Interim, to build 3D radiative heating rate fields. Over the deep tropics, UT clouds have a net radiative heating effect of about 0.3 K d−1 throughout the troposphere from 250 hPa downward. This radiative heating enhances the column-integrated latent heating by about 22±3 %. While in warmer regions the net radiative heating profile is nearly completely driven by deep convective cloud systems, it is also influenced by low-level clouds in the cooler regions. The heating rates of the convective systems in both regions also differ: in the warm regions the net radiative heating by the thicker cirrus anvils is vertically more extended, and their surrounding thin cirrus heat the entire troposphere by about 0.5 K d−1. The 15-year time series reveal a slight increase of the vertical heating in the upper and middle troposphere by convective systems with tropical surface temperature warming, which can be linked to deeper systems. In addition, the layer near the tropopause is slightly more heated by increased thin cirrus during periods of surface warming. While the relative coverage of convective systems is relatively stable with surface warming, their depth increases, measured by a decrease of their near-top temperature of -3.4±0.2 K K−1. Finally, the data reveal a connection of the mesoscale convective system (MCS) heating in the upper and middle troposphere and the (low-level) cloud cooling in the lower atmosphere in the cool regions, with a correlation coefficient equal to 0.72, which consolidates the hypothesis of an energetic connection between the convective regions and the subsidence regions.

Positional Dependence of SNPP VIIRS Solar Diffuser BRDF Change Factor: An Empirical Approach

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs), primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, quantified by a numerical factor called the H-factor, is determined by the onboard SD stability monitor. Our previous study showed that the H-factor is solar angle- and view direction-dependent. In this study, we determine the dependence of the H-factor on the detector SD view footprint location. We fit an empirical model to the NASA Collection 1 SNPP VIIRS Level 1B (L1B) spectral reflectance difference across the detectors in an RSB over uniform Earth scenes of the Libya 4 desert and deep convective clouds (DCCs). We apply the model predicted SD-positional-dependent H-factor to calibrate the RSBs. Under this new calibration scheme, the original unreal striping is removed from the homogeneous Libya 4 desert and the DCC images, as well as the original unreal striping from the Dunhuang desert image. The SD-positional-dependent H-factor has been used to calculate the SNPP VIIRS RSB radiometric correction factor for the NASA Collection 2.0 SNPP VIIRS L1B products.

The effects of ice nucleation on the microphysical processes and precipitation for a heavy rainfall event in Beijing

In order to better understand the effects of ice nucleation on deep convective clouds, two parameterizations that represent the high active fraction (H-AF case) and low active fraction (L-AF case) of ice nuclei (IN) are implemented into the Weather Research and Forecasting (WRF) model to investigate an extreme real precipitation case. The results indicate that the maximum value of 24-h surface precipitation for the H-AF case is closer to the observation measurement than that for the L-AF case. In early stage of precipitation, increasing IN leads to stronger competition for water vapor in homogeneous regime (above the −40 °C level) and a delay in the growth of ice particles for the H-AF case. With the development of convective system, a large number of ice particles are generated and there are more supercooled droplets occurring above the −20 °C level in H-AF case, resulting in significantly increased mass of snow and graupel and heavier precipitation than that in L-AF case mainly through the processes of R_RCW and R_SML

The development of rainfall retrievals from radar at Darwin

Abstract. The U.S. Department of Energy Atmospheric Radiation Measurement program Tropical Western Pacific site hosted a C-band polarization (CPOL) radar in Darwin, Australia. It provides 2 decades of tropical rainfall characteristics useful for validating global circulation models. Rainfall retrievals from radar assume characteristics about the droplet size distribution (DSD) that vary significantly. To minimize the uncertainty associated with DSD variability, new radar rainfall techniques use dual polarization and specific attenuation estimates. This study challenges the applicability of several specific attenuation and dual-polarization-based rainfall estimators in tropical settings using a 4-year archive of Darwin disdrometer datasets in conjunction with CPOL observations. This assessment is based on three metrics: statistical uncertainty estimates, principal component analysis (PCA), and comparisons of various retrievals from CPOL data. The PCA shows that the variability in R can be consistently attributed to reflectivity, but dependence on dual-polarization quantities was wavelength dependent for 1<R<10mmh-1. These rates primarily originate from stratiform clouds and weak convection (median drop diameters less than 1.5 mm). The dual-polarization specific differential phase and differential reflectivity increase in usefulness for rainfall estimators in times with R>10mmh-1. Rainfall estimates during these conditions primarily originate from deep convective clouds with median drop diameters greater than 1.5 mm. An uncertainty analysis and intercomparison with CPOL show that a Colorado State University blended technique for tropical oceans, with modified estimators developed from video disdrometer observations, is most appropriate for use in all cases, such as when 1<R<10mmh-1 (stratiform rain) and when R>10mmh-1 (deeper convective rain).

Competing aerosol effects in triggering deep convection over the Indian Region

Contrasting direct and feedback effects of aerosols on deep convection in the Gangetic Plain of Indian subcontinent have been analyzed by employing observation and modeling framework during the Ganges Valley Aerosol Experiment conducted in 2011. The key question addressed in the current investigation is: while the aerosol direct radiative effect leads to reduced surface shortwave flux and possible stabilization of the lower atmosphere, how is the deep convection favored in a heavily polluted atmosphere? The composites of aerosol, cloud and meteorological parameters during the formation of deep convective clouds (DCCs) under both light- and heavy- pollution conditions are contrasted to elucidate the aerosol effects. An enhanced low-level warming is discernible due to the presence of heavily polluting absorbing aerosols. A seminal role of aerosols in increasing the moist static energy (MSE) through enhancement of internal energy is identified as a primary feature that increases the convection potential of the lower atmosphere. Concomitantly, the greater moisture convergence facilitated by dynamical feedback of enhanced low-level heating destabilizes the atmospheric stratification. Additionally, the microphysical invigoration is examined for any possible role, nevertheless, only a weakened invigoration could be observed possibly due to dominance of meteorology. The observed results are well supported by model simulation of a deep convective event under high- and low-aerosol backgrounds. Besides highlighting the dominance of radiative processes over microphysical processes under heavily polluted environment, the significant correlation between aerosol and high clouds observed during DCC formation under such conditions suggests that the aerosol direct effect in weakening convection could be overcome primarily through enhancement in MSE and concomitant moisture convergence.

Transport and chemistry of isoprene and its oxidation products in deep convective clouds

Deep convective clouds can transport trace gases from the planetary boundary layer into the upper troposphere where subsequent chemistry may impact aerosol particle formation and growth. In this modelling study, we investigate processes that affect isoprene and its oxidation products injected into the upper troposphere by an isolated deep convective cloud in the Amazon. We run a photochemical box model with coupled cloud microphysics along hundreds of individual air parcel trajectories sampled from a cloud-resolving model simulation of a convective event. The box model simulates gas-phase chemical reactions, gas scavenging by liquid and ice hydrometeors, and turbulent dilution inside a deep convective cloud. The results illustrate the potential importance of gas uptake to anvil ice in regulating the intensity of the isoprene oxidation and associated low volatility organic vapour concentrations in the outflow. Isoprene transport and fate also depends on the abundance of lightning-generated nitrogen oxide radicals (NOx = NO + NO2). If gas uptake on ice is efficient and lightning activity is low, around 30% of the boundary layer isoprene will survive to the cloud outflow after approximately one hour of transport, while all the low volatile oxidation products will be scavenged by the cloud hydrometeors. If lightning NOx is abundant and gas uptake by ice is inefficient, then all isoprene will be oxidised during transport or in the immediate outflow region, while several low volatility isoprene oxidation products will have elevated concentrations in the cloud outflow. Reducing uncertainties associated with the uptake of vapours on ice hydrometeors, especially HO2 and oxygenated organics, is essential to improve predictions of isoprene and its oxidation products in deep convective outflows and their potential contribution to new particle formation and growth.

Convective System Observations by LEO and GEO Satellites in Combination

The combination of Low Earth Orbit (LEO and GEO stationary (GEO satellites brings significant advantages to observe, monitor, and understand convective systems (CSs and the associated vertical and horizontal dynamics. Two LEO, C-band Sentinel-1 Synthetic Aperture Radar (SAR and L-band SMAP radiometer, are used to observe surface wind patterns, while the other LEO (Aeolus lidar instrument offers the measurements of intense convective downdrafts. Meteosat GEO is used to detect deep convective clouds. Four case study examples of LEO and GEO combination illustrate here the matching in location and observation time between deep convective clouds, intense downdrafts, and strong surface wind gusts. In particular, the 2D deep convective cloud patterns and surface wind patterns have the same direction displacement. The observations of surface wind patterns by two different LEO (Sentinel-1 and SMAP indicate that the high-intensity radar backscattering on Sentinel-1 images should be induced by convective wind gusts rather than hydrometeors or convective precipitation at the sea surface as suggested in previous references. Finally, the convective wind gusts estimated from Sentinel-1 and SMAP data correspond to those obtained by the high-frequency radars, small-scale numerical models, and in-situ measurements.

Large‐scale dynamic, heat and moisture structures of monsoon‐influenced precipitation in the East Asian monsoon rainy area

AbstractThis study investigated large‐scale dynamic structures along with heat and moisture budgets associated with monsoon‐influenced precipitation over a typical rainy domain in the East Asian monsoon region. Large‐scale dynamically and thermodynamically consistent forcing data based on multiple measurements were produced by a one‐dimensional constrained variational analysis method. Using the forcing data, distinct characteristics of large‐scale states were documented for cases of notable pre‐monsoon rainfall before the South China Sea monsoon onset (SCSMO), extreme rainfall during SCSMO, and persistent strong rainfall after SCSMO. The pre‐monsoon period mainly resulted from weak and discrete cloud regimes. The extreme‐rain period was associated with a severe deep convective system moving from the west, and the persistent‐rain period was related to moderate convective cells separated from the strong convective system over the northern South China Sea. Large‐scale features including vertical velocity, wind convergence, and diabatic heating and drying were the strongest (weakest) during the extreme‐rain (pre‐monsoon) period. For the pre‐monsoon and persistent‐rain periods, the period‐averaged profiles of vertical velocity and diabatic heating and drying showed a one‐peak structure. However, during the extreme‐rain period, a leap‐forward mutation was seen in the vertical structure and magnitude of these large‐scale states. The multiple peaks shown in the vertical profiles of vertical velocity and diabatic heating during the extreme‐rain period may indicate various convective cloud systems co‐existed. The diabatic heating profiles of extreme rainfall indicated that the first rainfall peak was related to the successive occurrence of stratiform anvils and convective clouds, while the second rainfall peak, which was most intense, was associated with shallow convective clouds, severe deep convective clouds, and detraining stratiform anvils.

Comments on “Do Ultrafine Cloud Condensation Nuclei Invigorate Deep Convection?”

AbstractHere we elaborate on the deficiencies associated with the theoretical arguments and model simulations in a paper by Grabowski and Morrison (2020, hereafter GM20) that argued convective invigoration by aerosols does not exist. We show that the invigoration can be supported by both accurate theoretical analysis and explicit physics modeling with prognostic supersaturation and aerosols. Negligible invigoration by aerosols via drop freezing in GM20 was explained by a complete compensation between the heating effect from the freezing of extra liquid water and the extra loading effect during droplet ascending. But the reality is that droplet ascending then freezing occur at different locations and time scales, producing complex nonlinear responses that depend on the duration and location of the forcing. Also, this argument neglects the effect of off-loading of precipitating ice particles, increases in condensation during ascending, and riming and deposition accompanying droplet freezing. Regarding the warm-phase invigoration, the quasi-steady assumption for supersaturation as adopted in GM20 makes condensation independent of droplet number and size, therefore an incorrect interpretation of warm-phase invigoration. We illustrate that the quasi-steady assumption is invalid for updrafts of deep convective clouds in clean conditions because of the high acceleration of vertical velocity and the fast depletion of droplets by raindrop formation and accretion. Any assumption imposed on supersaturation, such as quasi-steady approximation and saturation adjustment, leads to errors in the evaluation of aerosol effects on diffusional growth and related buoyancy. Furthermore, we demonstrate that the piggybacking approach they used cannot prove or disprove the convective invigoration.

Aerosol invigoration of atmospheric convection through increases in humidity.

Cloud-aerosol interactions remain a major obstacle to understanding climate and severe weather. Observations suggest that aerosols enhance tropical thunderstorm activity; past research, motivated by the importance of understanding aerosol impacts on clouds, has proposed several mechanisms that could explain that observed link. We find that high-resolution atmospheric simulations can reproduce the observed link between aerosols and convection. However, we also show that previously proposed mechanisms are unable to explain the invigoration. Examining underlying processes reveals that, in our simulations, high aerosol concentrations increase environmental humidity by producing clouds that mix more condensed water into the surrounding air. In turn, higher humidity favors large-scale ascent and stronger convection. Our results provide a physical reason to expect invigorated thunderstorms in high-aerosol regions of the tropics.

Aerosols give clouds a lift

Cloud Physics It has been observed that atmospheric aerosols can strengthen updrafts in deep convective clouds such as those that form in thunderstorms. Past work has linked such invigoration with the latent heat released by water condensation or freezing in chains of processes that depend on aerosol concentrations. Abbott and Cronin suggest a third possibility in which updrafts intensify because high aerosol concentrations increase environmental humidity by mixing more condensed water into the surrounding air, which in turn favors stronger updrafts. Science , this issue p. [83][1] [1]: /lookup/doi/10.1126/science.abc5181