Cloud Microphysics Research Articles

Probing the Physics of Molecular Clouds in Spiral Galaxies NGC 5055 and NGC 3627

Although galaxies can be grouped in a few categories in terms of morphology, they have remarkably different intrinsic properties. Spiral galaxies host substantial amounts of molecular gas and have ongoing star formation activity with respect to elliptical galaxies lacking star formation. Molecular emission lines are used to probe the internal properties of molecular gas clouds where stars are born and die. Carbon monoxide (CO) is easily detectable in the interstellar medium (ISM) of galaxies. In this research, we probe the physics of the gas clouds at multiple positions in disc galaxies NGC 5055 (M63) and NGC 3627 (M66) using four CO transitions and their line ratios. 12CO(J=1-0) is the brightest across the disc of both galaxies compared to the other lines, i.e., 12CO(J=2-1, J=3-2) and 13CO(J=1-0). The CO intensities show a decrease from the center of the galaxies to the outskirts. However, NGC 3627 shows a rather irregular decrease pattern compared to NGC 5055. The CO line ratios show an increase up to a distance from the center and start to decrease. Although NGC 5055 shows a similar variation in the line ratios on each side of the disc, NGC 3627 has an opposite trend on either side. Therefore, the ISM could have different temperatures, opacity, densities, and levels of star formation in different regions of the galaxy’s disc. Our results indicate that the line ratios found at the center of both galaxies are different. The difference could be the result of the bar-driven gas accumulation in the center of NGC 3627. The line ratios in the center of NGC 5055 are within the range found for the centers of other spiral and active galaxies in the literature, but the ratios in the center of NGC 3627 are relatively lower.

Does a Scale‐Aware Convective Parameterization Scheme Improve the Simulation of Heavy Rainfall Events?

AbstractPrecipitation predictability using the non‐scale‐aware and scale‐aware convective parameterization schemes (CPSs) was investigated to assess the necessity of the CPSs within the gray‐zone. This study evaluates the performance of the Weather Research and Forecasting (WRF) model's CPS for 135 heavy rainfall events (HREs) over the Korean Peninsula for 10 years (i.e., 2011–2020). We tested the Kain–Fritsch (KF) scheme (non‐scale‐aware) and Multi‐scale Kain–Fritsch (MSKF) scheme (scale‐aware) in the WRF model. The MSKF scheme shows an overall improved performance of precipitation simulation compared to the KF scheme, but the precipitation forecast performance of CPS depends on the characteristics of HREs. When the HREs are characterized by synoptic‐scale atmospheric conditions with strong winds and large‐scale water vapor transport, the forecast performance of both CPSs is similar because a cloud microphysics scheme can explicitly resolve most of the precipitation. However, in the case of HREs with weak synoptic forcing conditions (e.g., moisture transport and winds) related to the localized and meso‐scale HREs, the MSKF scheme can improve overall simulated precipitation by increasing grid‐scale precipitation and reducing the overestimation of subgrid‐scale precipitation simulated in the KF scheme. Therefore, using the scale‐aware CPS in the gray‐zone can provide more accurate precipitation forecasts regardless of the environmental condition of the HREs.

Heat-flux-limited Cloud Activity and Vertical Mixing in Giant Planet Atmospheres with an Application to Uranus and Neptune

Storms operated by moist convection and the condensation of CH4 or H2S have been observed on Uranus and Neptune. However, the mechanism of cloud formation, thermal structure, and mixing efficiency of ice giant weather layers remains unclear. In this paper, we show that moist convection is limited by heat transport on giant planets, especially on ice giants where planetary heat flux is weak. Latent heat associated with condensation and evaporation can efficiently bring heat across the weather layer through precipitations. This effect was usually neglected in previous studies without a complete hydrological cycle. We first derive analytical theories and show that the upper limit of cloud density is determined by the planetary heat flux and microphysics of clouds but is independent of the atmospheric composition. The eddy diffusivity of moisture depends on the planetary heat fluxes, atmospheric composition, and surface gravity but is not directly related to cloud microphysics. We then conduct convection- and cloud-resolving simulations with SNAP to validate our analytical theory. The simulated cloud density and eddy diffusivity are smaller than the results acquired from the equilibrium cloud condensation model and mixing length theory by several orders of magnitude but consistent with our analytical solutions. Meanwhile, the mass-loading effect of CH4 and H2S leads to superadiabatic and stable weather layers. Our simulations produced three cloud layers that are qualitatively similar to recent observations. This study has important implications for cloud formation and eddy mixing in giant planet atmospheres in general and observations for future space missions and ground-based telescopes.

Exploring the excess of cloud condensation nuclei and rain suppression using a minimal three-dimensional Boussinesq model with bulk cloud microphysics

Over the years, there have been discussions about the possibility of air pollution affecting the process of rain formation. In this study, we have developed a simplified model that represents the atmospheric dynamics and cloud microphysics to explore the impact of pollution on rain formation. We used an existing three-dimensional minimal model consisting of five equations, for which we added a simple bulk parametrization that represents the role of cloud condensation nuclei (CCN) in cloud formation processes. We conducted numerical tests using two CCN profiles, with either one or two accumulation layers and modified their abundance to explore the effects of different CCN concentrations and distributions. We conducted four numerical tests corresponding to the two aforementioned profiles with polluted and low-polluted scenarios. The numerical simulations suggested that a layer with high CCN concentration close to the surface tends to suppress precipitation, while the same concentration distributed over two layers tends to enhance the efficiency of rain formation. The simulations also showed that CCN particles far from the surface produced higher cloud tops and longer events, consistent with previous research. Although the model includes a stable representation of precipitating turbulent convection with bulk cloud microphysics, we expect its simplicity and conservation properties to allow for deeper theoretical analyses that can help us better understand the physical processes involved in the studied phenomenon. We hope this model will serve as a tool to explore different aerosol-related scenarios within the context of minimal models.

Emulation of Cloud Microphysics in a Climate Model

AbstractWe present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao‐Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global‐average bias (≤4%) for 1 year of continuous simulation when replacing the Fortran scheme. The stability and success of this emulator stems from key design decisions. By separating the emulation of condensation and precipitation processes, we can better enforce physical priors such as mass conservation and locality of condensation, and the vertical dependence of precipitation falling downward, using specific network architectures. An activity classifier for condensation imitates the discrete‐continuous nature of the Fortran microphysics outputs (i.e., tendencies are identically zero where the scheme is inactive, and condensate is zero where clouds are fully evaporated). A temperature‐scaled conditional loss function ensures accurate condensate adjustments for a high dynamic range of cloud types (e.g., cold, low‐condensate cirrus clouds or warm, condensate‐rich clouds). Despite excellent overall performance, the emulator exhibits some deficiencies in the uppermost model levels, leading to biases in the stratosphere. The emulator also has short episodic skill dropouts in isolated grid columns and is computationally slower than the original Fortran scheme. Nonetheless, our challenges and strategies should be applicable to the emulation of other microphysical schemes. More broadly, our work demonstrates that with suitable physically motivated architectural choices, ML techniques can accurately emulate complex human‐designed parameterizations of fast physical processes central to weather and climate models.

Modulation of Tropical Convection‐Circulation Interaction by Aerosol Indirect Effects in Convective Self‐Aggregation Simulations of a Gray Zone Global Model

AbstractDisentangling the response of tropical convective updrafts to enhanced aerosol concentrations has been challenging. Leading theories for explaining the influence of aerosol concentrations on tropical convection are based on the dynamical response of convection to changes in cloud microphysics, neglecting possible changes in the environment. In recent years, global convection‐permitting models (GCPM) have been developed to circumvent problems arising from imposing artificial scale separation on physical processes associated with deep convection. Here, we use a global model in the convective gray zone that partially simulates deep convection to investigate how enhanced concentrations of aerosols that act as cloud condensate nuclei (CCN) impact tropical convection features by modulating the convection‐circulation interaction. Results from a pair of idealized non‐rotating radiative‐convective equilibrium simulations show that the enhanced CCN concentration leads to weaker large‐scale circulation, the closeness of deep convective systems to the moist cluster edges, and more mid‐level cloud water at an equilibrium state in which convective self‐aggregation occurred. Correspondingly, the enhanced CCN concentration modulates how the physical processes that support or oppose convective aggregation maintain the aggregated state at equilibrium. Overall, the enhanced CCN concentration facilitates the development of deep convection in a drier environment but reduces mean precipitation. Our results emphasize the importance of allowing atmospheric phenomena to evolve continuously across spatial and temporal scales in simulations when investigating the response of tropical convection to changes in cloud microphysics.

Coupling haze and cloud microphysics in WASP-39b’s atmosphere based on JWST observations

ABSTRACT We present a study on the coupling of haze and clouds in the atmosphere of WASP-39b. We developed a cloud microphysics model simulating the formation of Na2S and MgSiO3 condensates over photochemical hazes in gas giant atmospheres. We apply this model to WASP-39b, recently observed with the JWST to study how these heterogeneous components may affect the transit spectrum. We simulate both morning and evening terminators independently and average their transit spectra. While MgSiO3 formation has negligible impact on the spectrum, Na2S condensates produce grey opacities in the water band, in agreement with Hubble Space Telescope (HST) and JWST observations. Moreover, the formation of Na2S on the morning side depletes the atmosphere of its sodium content, decreasing the strength of the Na line. Combining morning and evening profiles results in a good fit of the Na observations. These nominal results assume a small Na2S/haze contact angle (5.7°). Using a larger value (61°) reduces the cloud density and opacity, but the effect on the Na profile and spectral line remains identical. In addition, the presence of haze in the upper atmosphere reproduces the ultraviolet (UV)-visible slope observed in the HST and Very Large Telescope data and contributes to the opacity between the water bands at wavelengths below 2 μm. The averaged spectra are rather insensitive to the variation of eddy diffusion and haze mass flux tested in this study, though the UV-visible slope, probing the haze layer above the clouds, is affected. Finally, our disequilibrium chemistry model, including photochemistry, reproduces the SO2 and CO2 absorption features observed.

Raindrop Size Distributions Simulated Using a Bin Microphysics Scheme: Different Biases in Stratiform and Convective Rain From an Extratropical Cyclone

AbstractBin microphysics schemes prognose the raindrop size distribution (RSD), which can be directly evaluated through comparison with disdrometer observations. This evaluation will provide implications on the reliability of simulated cloud microphysics by bin microphysics schemes. In this study, the RSDs of a precipitation event associated with an extratropical cyclone passing South Korea are simulated using a bin microphysics scheme and compared with those observed by a ground‐based disdrometer. The simulated mean RSD overall agrees with the observation. However, notable overestimations appear in the large‐ (3.3–4.3 mm) and small‐ (0.56–1.88 mm) diameter ranges, which respectively stem from the biases in two different time periods, one dominated by stratiform rain and the other largely involved with convective rain. In the stratiform‐rain‐dominated period, the melting of snow is the largest contributor to RSDs. The overestimation in the large‐diameter range in this period can be associated with overly active ice–ice collection at upper levels, which generates a local maximum in RSD at the diameter of 3.3 mm that is not seen in the observed RSDs. In the convective‐rain‐involved period, the warm‐rain collision–coalescence is the largest contributor to RSDs. The overestimation in the small‐diameter range and underestimation in the large‐diameter range imply that the collisional growth of raindrops is represented to be weaker than that in reality. The findings in this study suggest that the RSDs simulated using a bin microphysics scheme can have some systematic biases associated with misrepresentation of some microphysical processes.

One-dimensional Microphysics Model of Venusian Clouds from 40 to 100 km: Impact of the Middle-atmosphere Eddy Transport and SOIR Temperature Profile on the Cloud Structure

We conducted a simulation of H2SO4 vapor, H2O vapor, and H2SO4–H2O liquid aerosols from 40 to 100 km, using a 1D Venus cloud microphysics model based on the one detailed in Imamura & Hashimoto. The cloud distribution obtained is in good agreement with in situ observations by Pioneer Venus and remote-sensing observations from Venus Express (VEx). Case studies were conducted to investigate sensitivities to atmospheric parameters, including eddy diffusion and temperature profiles. We find that efficient eddy transport is important for determining upper haze population and its microphysical properties. Using the recently updated eddy diffusion coefficient profile by Mahieux et al., our model replicates the observed upper haze distribution. The H2O vapor distribution is highly sensitive to the eddy diffusion coefficient in the 60–70 km region. This indicates that updating the eddy diffusion coefficient is crucial for understanding the H2O vapor transport through the cloud layer. The H2SO4 vapor abundance varies by several orders of magnitude above 85 km, depending on the temperature profile. However, its maximum value aligns well with observational upper limits found by Sandor et al., pointing to potential sources other than H2SO4 aerosols in the upper haze layer that contribute to the SO2 inversion layer. The best-fit eddy diffusion profile is determined to be ∼2 m2 s−1 between 60 and 70 km and ∼360 m2 s−1 above 85 km. Furthermore, the observed increase of H2O vapor concentration above 85 km is reproduced by using the temperature profile from the VEx/SOIR instrument.

Divergent Impacts of Biomass Burning and Fossil Fuel Combustion Aerosols on Fog‐Cloud Microphysics and Chemistry: Novel Insights From Advanced Aerosol‐Fog Sampling

AbstractActivation of biomass burning aerosols (BBA) and fossil fuel combustion aerosols (FFA) in fogs and clouds significantly impact regional air quality through aqueous chemistry and climate by affecting cloud microphysics. However, we lack direct observations of how these aerosols behave in fogs and clouds. Using a newly developed aerosol‐cloud sampling system, we conducted observations during fog events and found that BBA, despite their high organic content, effectively contributed to super‐micron interstitial aerosols and fog droplets in low supersaturation fogs. In contrast, FFA, predominantly externally mixed organic, did not grow beyond the super‐micron size in fogs due to their near‐hydrophobic nature. Measurements conducted under supersaturations relevant for cloud formation revealed that portions of FFA could serve as cloud condensation nuclei, but only when supersaturation exceeded ∼0.14%. These findings have broad implications for future investigations into the influence of BBA and FFA on fog and cloud chemistry and their interactions with clouds.

Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach

Abstract. Atmospheric aerosols have important impacts on air quality and the Earth–atmospheric energy balance. However, as computing power is limited, Earth system models generally use coarse spatial grids and parameterize finer-scale atmospheric processes. These parameterizations and the simulation of atmospheric aerosols are often sensitive to model horizontal resolutions. Understanding the sensitivities is necessary for the development of Earth system models at higher resolutions with the deployment of more powerful supercomputers. Using the Energy Exascale Earth System Model (E3SM) version 1, this study investigates the impact of horizontal grid spacing on the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols (ERFaer) over the contiguous United States. We examine the resolution sensitivity by comparing the nudged simulation results for 2016 from the low-resolution model (LR) and the regional refinement model (RRM). As expected, the simulated emissions of natural dust, sea salt, and marine organic matter are substantially higher in the RRM than in the LR. In addition, RRM simulates stronger aqueous-phase production of sulfate through the enhanced oxidation of sulfur dioxide by hydrogen peroxide due to increased cloud liquid water content. In contrast, the gas-phase chemical production of sulfate is slightly suppressed. The RRM resolves more large-scale precipitation and produces less convective precipitation than the LR, leading to increased (decreased) aerosol wet scavenging by large-scale (convective) precipitation. Regarding aerosol effects on clouds, RRM produces larger temporal variabilities in the large-scale liquid cloud fractions than LR, resulting in increased microphysical cloud processing of aerosols (more interstitial aerosols are converted to cloud-borne aerosols via aerosol activation) in RRM. Water vapor condensation is also enhanced in RRM compared to LR. Consequently, the RRM simulation produces more cloud droplets, a larger cloud droplet radius, a higher liquid water path, and a larger cloud optical depth than the LR simulation. A comparison of the present-day and pre-industrial simulations indicates that, for this contiguous United States domain, the higher-resolution increases ERFaer at the top of the model by about 12 %, which is mainly attributed to the strengthened indirect effect associated with aerosol–cloud interactions.

Fully time-dependent cloud formation from a non-equilibrium gas-phase in exoplanetary atmospheres

Context. Recent observations suggest the presence of clouds in exoplanet atmospheres, but they have also shown that certain chemical species in the upper atmosphere might not be in chemical equilibrium. Present and future interpretation of data from, for example, CHEOPS, JWST, PLATO, and Ariel require a combined understanding of the gas-phase and the cloud chemistry. Aims. The goal of this work is to calculate the two main cloud formation processes, nucleation, and bulk growth consistently from a non-equilibrium gas phase. The aim is also to explore the interaction between a kinetic gas-phase and cloud microphysics. Methods. The cloud formation is modelled using the moment method and kinetic nucleation, which are coupled to a gas-phase kinetic rate network. Specifically, the formation of cloud condensation nuclei is derived from cluster rates that include the thermochemical data of (TiO2)N from N = 1 to 15. The surface growth of nine bulk Al, Fe, Mg, O, Si, S, and Ti binding materials considers the respective gas-phase species through condensation and surface reactions as derived from kinetic disequilibrium. The effect of the completeness of rate networks and the time evolution of the cloud particle formation is studied for an example exoplanet, HD 209458 b. Results. A consistent, fully time-dependent cloud formation model in chemical disequilibrium with respect to nucleation, bulk growth, and the gas-phase is presented and first test cases are studied. This model shows that cloud formation in exoplanet atmospheres is a fast process. This confirms previous findings that the formation of cloud particles is a local process. Tests on selected locations within the atmosphere of the gas-giant HD 209458 b show that the cloud particle number density and volume reach constant values within 1 s. The complex kinetic polymer nucleation of TiO2 confirms results from classical nucleation models. The surface reactions of SiO[s] and SiO2[s] can create a catalytic cycle that dissociates H2 to 2 H, resulting in a reduction of the CH4 number densities.

Combining effects of cloud microphysical and planetary boundary layer parameterization schemes on the prediction of tropical cyclone intensity

The numerical simulation of tropical cyclone (TC) can be affected by the choices in physics parameterization schemes. These effects can be from the single scheme or the combination of multiple ones due to closely linked physical processes. Previous studies have discussed the roles of different schemes in TC simulation, but the roles of scheme combinations still remain to be explored. To investigate the combining effects of cloud microphysical (MP) and planetary boundary layer (PBL) parameterization schemes on the prediction of TC intensity, two Single-Moment MP schemes, WRF 6-class (WSM6) and Goddard 4ice, and two PBL schemes, non-local closure Yonsei University (YSU) and local closure Quasi-normal Scale Elimination (QNSE), were selected for the cloud-resolving simulations of both real and idealized cases using the Weather Research and Forecasting (WRF) model.Results showed that the experiments combining the PBL scheme with different MP schemes had different performances in reproducing TC intensity. The local QNSE PBL scheme, compared with non-local YSU, simulated larger surface sensible, latent, and moisture fluxes, while not necessarily leading to a stronger TC. When used in conjunction with the Goddard MP scheme, the QNSE scheme can simulate a stronger TC than the YSU scheme, but when used with the WSM6 MP scheme, there was little difference in their intensity. Goddard 4ice scheme adding hail class, compared with WSM6, simulated a better-organized eyewall, more latent heat release and convective bursts, leading to the formation of a clear warm core in the upper troposphere and thus contributing to the intensification of TC. Only with the coupling of MP and PBL schemes, did the simulation generate a compact and erect eyewall, which further enhanced TC intensity via stronger convergence airflow and more water vapor supply at the lower layer. Idealized experiments were consistent with those in real cases, demonstrating the TC sensitivity responding to different combinations while the uncertainties remained in the selection of these schemes.

Radar, Lightning, and Synoptic Observations for a Thunderstorm on 7 January 2012 during the CHUVA-Vale Campaign

Thunderstorms can generate intense electrical activity, hail, and result in substantial economic and human losses. The development of very short-term forecasting tools (nowcasting) is essential to provide information to alert systems in order to mobilize most efficiently the population. However, the development of nowcasting tools depends on a better understanding of the physics and microphysics of clouds and lightning formation and evolution. In this context, the objectives of this study are: (a) to describe the environmental conditions that led to a genesis of a thunderstorm that produce hail on 7 January 2012, in the Metropolitan Area of São Paulo (MASP) during the CHUVA-Vale campaign, and (b) to evaluate the thunderstorm microphysical properties and vertical structure of electrical charge. Data from different sources were used: field campaign data, such as S-band radar, and 2- and 3-dimensional lightning networks, satellite data from the Geostationary Operational Environmental Satellite-13 (GOES-13), the Meteosat Second Generation (MSG), and reanalysis of the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). The thunderstorm developed in a region of low-pressure due to the presence of a near-surface inverted trough and moisture convergence, which favored convection. Convective Available Potential Energy (CAPE) of 1053.6 J kg−1 at the start of the thunderstorm indicated that strong convective energy was present. Microphysical variables such as Vertically Integrated Liquid water content (VIL) and Vertically Integrated Ice (VII) showed peaks of 140 and 130 kg m−2, respectively, before the hail reached the surface, followed by a decrease, indicating content removal from within the clouds to the ground surface. The thunderstorm charge structure evolved from a dipolar structure (with a negative center between 4 and 6 km and a positive center between 8 and 10 km) to a tripolar structure (negative center between 6 and 7.5 km) in the most intense phase. The first lightning peak (100 flashes in 5 min−1) before the hail showed that there had been a lightning jump. The maximum lightning occurred around 18:17 UTC, with approximately 350 flashes 5 min−1 with values higher than 4000 sources 500 m−1 in 5 min−1. Likewise, the vertical cross-sections indicated that the lightning occurred ahead of the thunderstorm’s displacement (maximum reflectivity), which could be useful in predicting these events.

Impact of acidity and surface-modulated acid dissociation on cloud response to organic aerosol

Abstract. Acid dissociation of the organic aerosol fraction has the potential to impact cloud-activating properties by altering aqueous-phase H+ concentrations and water activity but is currently overlooked in most atmospheric aerosol models. We implemented a simple representation of organic acid dissociation in the aerosol–chemistry–climate box model ECHAM6.3–HAM2.3 and investigated the impact on aerosol-forming aqueous sulfur chemistry, cloud droplet number concentrations, and the shortwave radiative effect. Many atmospheric organic acids are also surface-active and may be strongly adsorbed at the surface of small aqueous droplets. The degree of dissociation has recently been observed for several atmospheric surface-active organics with Brönsted acid character to be significantly shifted in the surface, compared to the bulk aqueous solution. In addition to the well-known bulk acidity, we therefore introduced an empirical account of this surface-modulated dissociation to further explore the potential impact on aerosol climate effects. Malonic acid and decanoic acid were used as proxies for atmospheric organic aerosols of different surface-active and acid strengths. Both acids were found to yield sufficient hydrogen ion concentrations from dissociation in an aqueous droplet population to strongly influence aqueous aerosol sulfur chemistry, leading to enhanced cloud droplet number concentrations and a cooling shortwave radiative effect. Further considering the surface modulation of organic acid dissociation, the impact on cloud microphysics was smaller than according to the well-known bulk solution acidity but still significant. Our results show that organic aerosol acid dissociation can significantly influence predictions of aerosol and cloud droplet formation and aerosol–cloud–climate effects and that, even for a well-known bulk solution phenomenon such as acidity, it may be important to also consider the specific influence of surface effects when surface-active acids comprise a significant fraction of the total organic aerosol mass.

Radiative and Microphysical Impacts of the Saharan Dust on Two Concurrent Tropical Cyclones: Danielle and Earl (2010)

AbstractSaharan dust exerts profound impacts on the genesis and intensification of tropical cyclones (TCs). Such impacts on various stages of the TCs have yet to be explored. In this study, we utilize the Cloud‐Resolving weather research and forecasting model (WRF) to investigate the relative importance of the microphysical and radiative effects of dust on two hurricanes (Earl and Danielle) at different life stages under similar dynamical conditions in 2010. Both TCs were embedded in a dusty environment throughout their lifetime. A new dust ice nucleation scheme was implemented into the aerosol‐aware Texas A&M University two‐moment microphysical scheme in WRF. Moreover, the dust radiative effect was included in the Goddard Shortwave Scheme of WRF. Our sensitivity experiments show that the radiative effect of dust (DRAD) amplified the mid‐level ridge in the Central Atlantic Ocean through temperature perturbation, changing the tracks of Danielle and Earl. Further analyses reveal an early shift of Danielle's maximum intensity for 12 hours but a significantly suppressed Earl in DRAD. In addition, the microphysical effect of dust had little impact on the large‐scale dynamical fields and storm tracks. The inclusion of dust as ice nucleation particles results in more variations in the intensity of Danielle and Earl than in other scenarios. This is owing to the higher maximum diabatic heating rate in the rainband region that perturbs the size of the TC. This study shows the dominant dust radiative effects on both intensity and track of the storm. In addition, there is evidence that dust suppresses the early stage TC but provides favorable conditions for matured TC. Both findings have profound implications for hurricane forecast and address the importance of accounting for detailed cloud microphysics and aerosol‐TC interactions in the operational forecasting models.

Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution

Abstract. In accordance with progression in current capabilities towards high-resolution approaches, applying a convective-permitting resolution to global aerosol models helps comprehend how complex cloud–precipitation systems interact with aerosols. This study investigates the impacts of a double-moment bulk cloud microphysics scheme, i.e., NICAM Double-moment bulk Water 6 developed in this study (NDW6-G23), on the spatiotemporal distribution of aerosols in the Nonhydrostatic ICosahedral Atmospheric Model as part of the version-19 series (NICAM.19) with 14 km grid spacing. The mass concentrations and optical thickness of the NICAM-simulated aerosols are generally comparable to those obtained from in situ measurements. However, for some aerosol species, especially dust and sulfate, the differences between experiments of NDW6 and of the NICAM single-moment bulk module with six water categories (NSW6) were larger than those between experiments with different horizontal resolutions (14 and 56 km grid spacing), as shown in a previous study. The simulated aerosol burdens using NDW6 are generally lower than those using NSW6; the net instantaneous radiative forcing due to aerosol–radiation interaction (IRFari) is estimated to be −1.36 W m−2 (NDW6) and −1.62 W m−2 (NSW6) in the global annual mean values at the top of the atmosphere (TOA). The net effective radiative forcing due to anthropogenic aerosol–radiation interaction (ERFari) is estimated to be −0.19 W m−2 (NDW6) and −0.23 W m−2 (NSW6) in the global annual mean values at the TOA. This difference among the experiments using different cloud microphysics modules, i.e., 0.26 W m−2 or 16 % difference in IRFari values and 0.04 W m−2 or 16 % difference in ERFari values, is attributed to a different ratio of column precipitation to the sum of the column precipitation and column liquid cloud water, which strongly determines the magnitude of wet deposition in the simulated aerosols. Since the simulated ratios in the NDW6 experiment are larger than those of the NSW6 result, the scavenging effect of the simulated aerosols in the NDW6 experiment is larger than that in the NSW6 experiment. A large difference between the experiments is also found in the aerosol indirect effect (AIE), i.e., the net effective radiative forcing due to aerosol–cloud interaction (ERFaci) from the present to preindustrial days, which is estimated to be −1.28 W m−2 (NDW6) and −0.73 W m−2 (NSW6) in global annual mean values. The magnitude of the ERFaci value in the NDW6 experiment is larger than that in the NSW6 result due to the differences in both the Twomey effect and the susceptibility of the simulated cloud water to the simulated aerosols between NDW6 and NSW6. Therefore, this study shows the importance of the impacts of the cloud microphysics module on aerosol distributions through both aerosol wet deposition and the AIE.

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at the Daily and Sub-Daily Scales in the Western Mediterranean

In the last decade, substantial improvements have been achieved in quantitative satellite precipitation estimates, which are essential for a wide range of applications. In this study, we evaluated the performance of Integrated Multi-satellitE Retrievals for GPM (IMERG V06B) at the sub-daily and daily scales. Ten years of half-hourly precipitation records aggregated at different sub-daily periods were evaluated over a region in the Western Mediterranean. The analysis at the half-hourly scale examined the contribution of passive microwave (PMW) and infrared (IR) sources in IMERG estimates, as well as the relationship between various microphysical cloud properties using Cloud Microphysics (CMIC–NWC SAF) data. The results show the following: (1) a marked tendency to underestimate precipitation compared to rain gauges which increases with rainfall intensity and temporal resolution, (2) a weaker negative bias for retrievals with PMW data, (3) an increased bias when filling PMW gaps by including IR information, and (4) an improved performance in the presence of precipitating ice clouds compared to warm and mixed-phase clouds. This work contributes to the understanding of the factors affecting satellite estimates of extreme precipitation. Their relationship with the microphysical characteristics of clouds generates added value for further downstream applications and users’ decision making.

Low cloud response to aerosol‐radiation‐cloud interactions: Idealized WRF numerical experiments for EUREC4A project

AbstractAerosols significantly affect cloud microphysics and energy budget in different ways. The contribution of the direct, semi‐direct, and indirect effects of aerosols on radiation are here investigated over the North Atlantic tropical ocean under different aerosol loadings. The Weather Research and Forecasting Model is used to perform a set of numerical idealized experiments, which are forced with prescribed aerosol profiles. We evaluate the effects of aerosols on modeled shallow clouds and surface radiative budget. The results indicate that large aerosol loadings are associated with enhanced cloudiness and reduced precipitation. While the change in rainfall is mainly due to the larger number of smaller droplets, the change in cloudiness is attributed to the effects of absorbing aerosols, mainly dust particles, which are responsible for a rise of temperature that feeds back onto specific humidity. As in the boundary layer the increase of moisture dominates, the net effect is a higher relative humidity, which favors the formation of thin low non‐precipitating clouds. The feedback accounts for a dynamical change in the lower troposphere: shortwave radiation absorption increases temperature at the top of the marine atmospheric boundary‐layer and reduces entrainment of warm and dry air, increasing low level moisture content. Despite the overall increase in cloudiness, daytime cloud cover is reduced. The semi‐direct effect of aerosols on clouds results in a warming of the surface, opposite to the indirect effect.

Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.