Cloud Microphysical Processes Research Articles

Effects of Pollen on Hydrometeors and Precipitation in a Convective System

AbstractAnemophilous (wind‐driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub‐pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) simulations and update the Morrison microphysics scheme within WRF‐Chem using aerosol‐aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes.

Global well-posedness of a model for precipitating convection with hydrostatic pressure under fast autoconversion and rain evaporation conditions

Moist convection in the tropical atmosphere involves the interaction of deep precipitating clouds that can be organized into different patterns and propagate long distances. Their modeling to predict their evolution can be done with PDE-based models but it requires the parametrization of different cloud micro-physical processes. Simplified models can maintain a balance between complexity and precision, and can still capture qualitative observations made in nature. In this work, we prove global existence and uniqueness of a model for precipitating turbulent convection. The model considers a moisture dynamics with phase changes. It assumes fast auto-conversion and rain evaporation together with a hydrostatic pressure approximation. We also show positivity of the variables associated to moisture and equivalent potential temperature. The existing literature is discussed and the new challenges in this model are highlighted.

Impact of Western Ghats orography on the simulation of extreme precipitation over Kerala, India during 14–17 August 2018

The state of Kerala, located in southwest peninsular India, has experienced a series of extremely heavy rainfall events in the past few years, resulting in severe flooding and landslides. Among these events, an extremely heavy rainfall episode (50 to 480 mm/day) occurred during 14–17 August 2018 had led to devastating floods along the southwest coast of India. In this study, we have chosen this event as a case study to analyze the role of orography, using a high-resolution (1-km) cloud-resolving WRF model configuration. We conducted four numerical sensitivity experiments to examine the impact of different topographic configurations, ranging from no-mountain to plateau, moderate, and steep mountain terrains, on the simulation of the extreme rainfall event. The results of the mountain sensitivity experiments indicate that as mountain height increases, simulated low-level wind decelerates quickly. This flow blocking is also manifested in parameters such as reduced upper-air wind intensity, increased dynamical convergence, and increase of vertical velocities at the Western Ghat (WG) mountain barriers, which lead to the variations in moist instability and cloud microphysical processes influencing the horizontal and vertical distribution of solid-phase hydrometeors. Furthermore, the results also show that a reduction in the orography of the WGs decreases the vertical extension of low-level jet winds to upper levels, weakens the tropical easterly flow, and decreases the wind shears between the lower and upper troposphere. In addition, the results suggest that large-scale variations in mountain orography in numerical simulations can affect the simulated magnitude and direction of moisture transport, which may have played a role in determining the magnitude and distribution of simulated rainfall over Kerala.

Solar influences on the Earth’s atmosphere: solved and unsolved questions

Solar influences on the Earth’s atmosphere: solved and unsolved questions

Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method

Abstract. A particle-based cloud model was developed for meter- to submeter-scale-resolution simulations of warm clouds. Simplified cloud microphysics schemes have already made meter-scale-resolution simulations feasible; however, such schemes are based on empirical assumptions, and hence they contain huge uncertainties. The super-droplet method (SDM) is a promising candidate for cloud microphysical process modeling and is a particle-based approach, making fewer assumptions for the droplet size distributions. However, meter-scale-resolution simulations using the SDM are not feasible even on existing high-end supercomputers because of high computational cost. In the present study, we overcame challenges to realize such simulations. The contributions of our work are as follows: (1) the uniform sampling method is not suitable when dealing with a large number of super-droplets (SDs). Hence, we developed a new initialization method for sampling SDs from a real droplet population. These SDs can be used for simulating spatial resolutions between meter and submeter scales. (2) We optimized the SDM algorithm to achieve high performance by reducing data movement and simplifying loop bodies using the concept of effective resolution. The optimized algorithms can be applied to a Fujitsu A64FX processor, and most of them are also effective on other many-core CPUs and possibly graphics processing units (GPUs). Warm-bubble experiments revealed that the throughput of particle calculations per second for the improved algorithms is 61.3 times faster than those for the original SDM. In the case of shallow cumulous, the simulation time when using the new SDM with 32–64 SDs per cell is shorter than that of a bin method with 32 bins and comparable to that of a two-moment bulk method. (3) Using the supercomputer Fugaku, we demonstrated that a numerical experiment with 2 m resolution and 128 SDs per cell covering 13 8242×3072 m3 domain is possible. The number of grid points and SDs are 104 and 442 times, respectively, those of the highest-resolution simulation performed so far. Our numerical model exhibited 98 % weak scaling for 36 864 nodes, accounting for 23 % of the total system. The simulation achieves 7.97 PFLOPS, 7.04 % of the peak ratio for overall performance, and a simulation time for SDM of 2.86×1013 particle ⋅ steps per second. Several challenges, such as incorporating mixed-phase processes, inclusion of terrain, and long-time integrations, remain, and our study will also contribute to solving them. The developed model enables us to study turbulence and microphysics processes over a wide range of scales using combinations of direct numerical simulation (DNS), laboratory experiments, and field studies. We believe that our approach advances the scientific understanding of clouds and contributes to reducing the uncertainties of weather simulation and climate projection.

CAIPEEX: Indian Cloud Seeding Scientific Experiment

Abstract The demand for effective methods to augment precipitation over arid regions of India has been increasing over the past several decades as the changing climate brings warmer average temperatures. In the fourth phase of the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX IV), a scientific investigation was conducted over a rain-shadow region of the Western Ghats mountains in India. The primary objective was to investigate the efficacy of hygroscopic seeding in convective clouds and to develop a cloud seeding protocol. CAIPEEX IV followed the World Meteorological Organization (WMO) recommendations in a peer-reviewed report with physical, statistical, and numerical investigations. The initial results of the campaign in the monsoon period of 2018 and 2019 with two instrumented aircraft, a ground-based dual-polarization C-band radar, a network of rain gauges, radiosondes, and surface aerosol measurements are reported here. The hygroscopic seeding material was detected in cloud droplets and key cloud microphysical processes in the seeding hypothesis were tracked. The formidable challenges of assessing seeding impacts in convective clouds and the results from 150 seed and 122 no-seed samples of randomized experiments are illustrated. Over 5,000 cloud passes from the airborne campaign provided details about the convective cloud properties as the key indicators for a seeding strategy and the evaluation protocol. The experimental results suggest that cloud seeding can be approached scientifically to reduce uncertainty. The results from this study should interest the scientific community and policymakers concerned with climate change’s impact on precipitation and how to mitigate rainfall deficiencies.

Influence of Atmospheric Non-Uniform Saturation on Extreme Hourly Precipitation Cloud Microphysical Processes in a Heavy Rainfall Case in Zhengzhou

Heavy rainfall not only affects urban infrastructure, it also impacts environmental changes, and which then influence the sustainability of development and ecology. Therefore, researching and forecasting heavy rainfall to prevent disaster-related damages is essential. A high-resolution numerical simulation was carried out for a heavy rainfall case in Zhengzhou, Henan Province, China, from 19–20 July 2021. The analysis of weather conditions revealed that the main cause of heavy rainfall in Zhengzhou was the supersaturation and condensation of water vapor, resulting from the invasion of dry and cold air from the upper and middle atmospheric layers. This weather condition is ideally suited for applying generalized potential temperature that is informed by the non-uniform saturation theory. Based on this, the new scheme revised the cloud microphysical scheme of the cloud water condensation parameterization process by substituting generalized potential temperature. The characteristics of the mesoscale environment and water condensates were comparatively analyzed between the original and the new scheme. Then, the quantitative mass budget and latent heat budget related to microphysical conversions were comparatively calculated over Zhengzhou. Furthermore, the possible two-scheme mechanisms through which the cloud microphysics processes affected the rainfall were investigated and discussed. It was found that: (1) The new scheme, which takes into account generalized potential temperature, produced precipitation fields more in line with observations and simulated stronger hourly precipitation compared to the original scheme. (2) The conversions of snow were the main source of microphysical processes that produced precipitation and released latent heat due to the dry and cold air invasion. (3) Given that the condensation of water vapor was hypothesized to occur at 70% relative humidity (RH) or above, rather than the original 100% RH, the new scheme simulated more supercooled water and ice-phase particles than the original scheme. This enhancement, in turn, intensified convective development owing to positive feedback within the cloud microphysics processes and cloud environment, ultimately leading to the simulation of more intense hourly precipitation.

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Probing Dust and Water in Martian Atmosphere with Far-Infrared Frequency Spacecraft Occultation

Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet’s climate evolution over time through radiative–convective and cloud microphysics processes. Thus, accurate measurements of the distribution and variability of dust are required. Observations from the Mars Global Surveyor/Thermal Emission Spectrometer Mars Mars Reconnaissance Orbiter/Mars Climate Sounder and Mars Express/Fourier Transform Spectrometer and the Curiosity Rover have limited capability to measure dust. We show that spacecraft occultation of the Martian atmosphere at far-infrared frequencies between 1 and 10 THz can provide the needed global and temporal data on atmospheric dust by providing co-located measurements of temperature and dust opacity from the top of the atmosphere all the way down to the surface. In addition, spacecraft occultation by a small-satellite constellation could provide global measurements of the development of dust storms.

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

A Comparative Investigation of Light Scattering and Digital Holographic Imaging to Measure Liquid Phase Cloud Droplets

The measurement of cloud microphysical parameters plays an important role in describing characteristics of liquid phase clouds and investigating mutual relationships between clouds and precipitation. In this paper, cloud microphysical parameters at Liupan Mountain Weather Station in Ningxia are measured with a high-resolution coaxial digital holographic imager and a fog monitor 120. There are differences in the measurement results between the two instruments. The number concentration measured by the digital holographic imager is about 1.5 times that of the fog monitor 120. However, their Pearson correlation coefficient is above 0.9. Through analysis, we found that the measurement results of the digital holographic imager and fog monitor 120 are differences in 2–4 µm and 7–50µm. For the droplets with the diameters of 4–7 µm, their measurement results have good consistency. By analyzing the influence of wind field and detection sensitivity on the measurement principle, the reasons which caused the difference are proposed. Advice is given to observe topographic clouds by using the above two instruments. In addition, the differences in liquid water content and visibility are analyzed due to the absence of small and large droplets. The study provides data support for improving the accuracy of instruments in measuring cloud droplets and is useful for research in the field of cloud microphysical processes.

Modelling dynamically driven global cloud formation microphysics in the HAT-P-1b atmosphere

ABSTRACT Insight into the formation and global distribution of cloud particles in exoplanet atmospheres continues to be a key problem to tackle going into the JWST era. Understanding microphysical cloud processes and atmospheric feedback mechanisms in three-dimensional (3D) has proven to be a challenging prospect for exoplaneteers. In an effort to address the large computational burden of coupling these models in 3D simulations, we develop an open source, lightweight, and efficient microphysical cloud model for exoplanet atmospheres. ‘Mini-cloud’ is a microphysical based cloud model for exoplanet condensate clouds that can be coupled to contemporary general circulation models (GCMs) and other time-dependent simulations. We couple mini-cloud to the Exo-FMS GCM and use a prime JWST target, the hot Jupiter HAT-P-1b, as a test case for the cloud formation module. After 1000+ of days of integration with mini-cloud, our results show a complex 3D cloud structure with cloud properties relating closely the dynamical and temperature properties of the atmosphere. Current transit and emission spectra data are best fit with a reduced cloud particle number density compared to the nominal simulation, with our simulated JWST NIRISS SOSS spectra showing promising prospects for characterizing the atmosphere in detail. Overall, our study is another small step in first principles 3D exoplanet cloud formation microphysical modelling. We suggest that additional physics not included in the present model, such as coagulation, are required to reduce the number density of particles to appropriately observed levels.

Observational study of relationships between entrainment rate, homogeneity of mixing, and cloud droplet relative dispersion

The entrainment–mixing process is key to the cloud's dynamical and microphysical processes. However, to the best of our knowledge, no study has quantitatively linked entrainment rate and homogeneity of mixing. Additionally, their combined effects on cloud droplet relative dispersion and physical mechanisms are even more unclear. This study analyzed the aircraft measurements of cumulus clouds collected in the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign to identify these relationships. The relationship between the entrainment rate and homogeneous mixing degree was found to be moderately positive, and the underlying mechanisms related to mixing and evaporation time scales and environmental relative humidity were explored. The relationship between relative dispersion and entrainment rate changes from positive to negative with increasing entrainment rate, depending on the dominance of evaporation of large or small droplets. The relative dispersion first increases and then decreases with increasing homogeneous mixing degree, validating the results of previous model simulations. The results shed new light on understanding the interactions between cloud microphysics and cloud dynamics through turbulent entrainment and mixing processes.

A study of cloud microphysical processes and a mesoscale environment in a heavy rainfall case over Yan’an

A cloud-resolved numerical simulation was carried out for an extreme rainfall case in Yan’an, a city in arid and semi-arid regions in northwest China, on 3–4 September 2021, by using Mesoscale Weather Research and Forecasting Model. The Auto Weather Station and Doppler radar were applied to verify simulated results. The characteristics of mesoscale cloud environment and cloud microphysical processes were analyzed. Then, the quantitative rainwater mass budget and latent heat budget of microphysical conversions about water condensates calculated in Yan’an. The possible mechanism by which cloud microphysics affected the rainstorm was investigated and discussed. It was found that: (1) There was positive feedback between mesoscale cloud environment and cloud microphysical processes, especially diabatic heating processes due to ice phase particles conversions. (2) The process of snow conversions processes was the most important process of this heavy rainfall in Yan’an. It not only promoted the production of rain, but also contributed to the enhancement of updraft through latent heat release and produced positive feedback to other microphysical processes in cloud. (3) Heavy rainfall in arid regions of China is mostly cold-type precipitation, mainly manifested by snow-dominated cloud microphysical processes producing deep convection.

Impacts of microphysical parameterizations on banded convective system in convection-permitting simulation: a case study

The representation of cloud microphysical processes in models has always been a challenge leading to uncertainty in convective simulations. This paper evaluates the effect of cloud microphysical parameterizations on the simulation of mesoscale convective systems (MCSs) through a realistic banded convection process. A series of numerical simulation experiments are performed using the Weather Research and Forecasting (WRF) model at a convection-permitting scale with a 3 km horizontal grid spacing. Specifically, four experiments considering different hydrometeor species within the WRF single-moment-microphysics schemes (WSMMPs) are conducted, and three additional sensitivity tests change the graupel particle properties. The results indicate that the significant differences in the times of convection initiation across the experiments reach 120 min, and more hydrometeor species may lead to later convection initiation. Moreover, the frozen graupel hydrometeor characteristics can appreciably alter the simulated convective morphology, even more than other hydrometeor species. When the graupel becomes smaller (such as Graupel-like), the fall speed of the graupel particles decreases. Therefore, more numerous graupel particles reside in clouds for a longer time, and experience more atmospheric diabatic heating and cooling effects. As a result, the simulated convective systems exhibit strong banded convective echo characteristics, the surface 10-m wind gust increases, and the cold pools associated with additional melting and evaporation become stronger, accelerating the propagation of the system. In contrast, larger and less abundant graupels (e.g., Hail-like) have a faster fall speed, and the atmospheric diabatic heating and cooling decrease by shortening the duration of their residence time within the clouds, resulting in a weak quasi-linear convective system, weak surface 10-m wind gust, unobvious cold pool, and slower propagation. Comparisons of the experiments further demonstrate that the fall speeds of frozen graupel particles largely impact the vertical distribution of the hydrometeors and the related microphysical processes.

Comparative study of bin and bulk microphysical schemes in simulating a heavy snowfall event that occurred in Beijing during the 2022 Winter Olympic Games

A heavy snowfall event that struck Beijing during February 12-13, 2022, affected some of the training sessions and events of the Winter Olympic Games. This heavy snowfall event was simulated using the Advanced Research Weather Research and Forecasting Model with both the two-moment bulk scheme (BULK) and the spectral bin microphysics scheme (BIN), and the differences in surface precipitation, radar reflectivity, and cloud microphysics processes were compared and analyzed. It was found that surface precipitation was dominated by solid precipitation particles. The 24-h accumulated precipitation of the BULK simulation was larger than that of the BIN simulation, but both were smaller than that observed. The BIN simulation was closer to the observations in terms of the trends of variation in precipitation rate and radar reflectivity during the period of heavy precipitation. The maximum and minimum vertical velocities of the BIN simulation were notably higher than those of the BULK simulation, and the water vapor content of the BIN scheme at the heights of the −10 to −20°C levels and above the −38°C level was substantially higher than that of the BULK scheme. The contents of cloud water and snow simulated by the BIN scheme were much higher than those simulated by the BULK scheme. The nucleation of ice crystals in the middle and high layers of the BULK scheme was obvious, whereas such a process was not evident in the BIN scheme. The net production rate of ice crystals and snow simulated by the BULK scheme was stronger near the surface than that simulated by the BIN scheme, and a second peak in the conversion rate existed at heights very close to the surface below 1 km, which might account for the greater intensity of precipitation in the BULK scheme. The latent heat simulated by the BULK scheme was larger (smaller) than that simulated by the BIN scheme below (above) the height of 2 km.

Comparison of the simulated outcomes of aerosol–cloud interaction by a meteorological model with and without an interactive chemistry module

With the general rise of computational capacities and the continued efforts to improve computational efficiencies, more and more studies have been utilizing state-of-the-art atmospheric models that enable cloud-resolving simulations over a global domain. Microphysical processes inside clouds, however, are on a scale much smaller than that of a cloud itself, and therefore resolving clouds in a model is not equivalent to resolving cloud microphysical processes. When aerosol–cloud interaction (ACI) is studied, chemistry models enable the prognostic calculations for chemical species, including aerosols, which can perturb cloud microphysics and eventually impact clouds and climate. The large drawback of these models is the high computational cost required for tracking chemical species in space and time that may not be affordable in some studies. As a result, some studies have used non-chemistry models with prescribed cloud droplet number concentrations n_c and compared multiple simulations with different n_c to assess the impacts of varying aerosol concentrations on clouds. In this study we assess whether the same or similar ACI can be simulated when the aerosol number is increased in a chemistry model and when n_c is raised in a non-chemistry model. A case study has been conducted over the Maritime Continent in September 2015 when an extremely large number of aerosols were observed due to fires under a dry condition brought by a strong El Niño. The comparison of the simulations by the chemistry and non-chemistry models shows that the aerosol-driven enhancement of rainfall in the chemistry simulations was not present in the non-chemistry simulations, even with prescribed n_c with certain spatial variation based on the chemistry runs. Therefore, simulated ACI may largely differ depending on the manner by which an increase or decrease of aerosols is represented in a model. The result suggests the further need for powerful computational capabilities and the pursuit of a rigorous means to incorporate aerosol species in a non-chemistry model.

Convective Impact on the Global Lower Stratospheric Water Vapor Budget

AbstractWater vapor in the stratosphere is primarily controlled by temperatures in the tropical upper troposphere and lower stratosphere. However, the direct impact of deep convection on the global lower stratospheric water vapor budget is still an actively debated issue. Two complementary modeling approaches are used to investigate the convective impact in boreal winter and summer. Convective influence is diagnosed by tracing trajectories through convective cloud top altitude fields derived from global rainfall and brightness temperature data. Backward trajectory model simulations coupled with a detailed treatment of cloud microphysical processes indicate that convection moistens the global lower stratosphere by approximately 0.3 ppmv in boreal winter and summer 2010. The diurnal peak in convection is responsible for about half of the total convective moistening during winter and nearly all of the convective moistening during summer. Deep convective clouds overshooting the tropopause have relatively minor effect on global lower stratospheric water vapor. A forward trajectory model coupled with a simplified cloud module is used to estimate the relative magnitude of the interannual variability of the convective impact. Combining the results from the two models, we find that the convective impact on the global lower stratospheric water vapor during 2006–2016 is approximately 0.3 ppmv with year‐to‐year variations of up to 0.1 ppmv. An important mechanism of convective hydration of the lower stratosphere is via the detrainment of saturated air and ice into the tropical uppermost troposphere and the subsequent upward transport of some of these moist air parcels across relatively warm and subsaturated tropopause.

A Bin and a Bulk Microphysics Scheme Can Be More Alike Than Two Bin Schemes

AbstractBin and bulk schemes are the two primary methods to parameterize cloud microphysical processes. This study attempts to reveal how their structural differences (size‐resolved vs. moment‐resolved) manifest in terms of cloud and precipitation properties. We use a bulk scheme, the Arbitrary Moment Predictor (AMP), which uses process parameterizations identical to those in a bin scheme but predicts only moments of the size distribution like a bulk scheme. As such, differences between simulations using AMP's bin scheme and simulations using AMP itself must come from their structural differences. In one‐dimensional kinematic simulations, the overall difference between AMP (bulk) and bin schemes is found to be small. Full‐microphysics AMP and bin simulations have similar mean liquid water path (mean percent difference <4%), but AMP simulates significantly lower mean precipitation rate (−35%) than the bin scheme due to slower precipitation onset. Individual processes are also tested. Condensation is represented almost perfectly with AMP, and only small AMP‐bin differences emerge due to nucleation, evaporation, and sedimentation. Collision‐coalescence is the single biggest reason for AMP‐bin divergence. Closer inspection shows that this divergence is primarily a result of autoconversion and not of accretion. In full microphysics simulations, lowering the diameter threshold separating cloud and rain category in AMP from to reduces the largest AMP‐bin difference to ∼10%, making the effect of structural differences between AMP (and perhaps triple‐moment bulk schemes generally) and bin even smaller than the parameterization differences between the two bin schemes.

Microphysical processes under different hourly rainfall intensities in super typhoon Rammasun

High-resolution numerical simulation data of super typhoon Rammasun simulated by the Weather Research and Forecasting (WRF) Model was used to study the cloud microphysical processes under different hourly rainfall intensities. The grid points in the gale circle were categorized into four types (0–5, 5–20, 20–50, and 50- mm) based on hourly rainfall. The precipitation and microphysical characteristics under different types were investigated by diagnostic and statistical methods. The results showed that on the eve of the first landfall, extremely hourly heavy precipitation (50- mm type) was significantly enhanced compared to other types. The vertical movement was significantly reduced to the middle and lower troposphere which was very conducive to the relative movement and interaction of hydrometeors with the enhancement of the collision processes. The rainfall in the 5–20 and 20–50 mm types both mostly accounted for about 40% of the total rainfall in the gale circle, while that of the 0–5 and 50- mm types were generally smaller than the former two. As the rainfall intensity increased, the absolute conversion rates of all major cloud microphysical processes had shown increasing trends, especially the non-uniformity of Cnd (the condensation of water vapor to cloud water), Pracw (the accretion of cloud water by rain) and Dgacw (the accretion of cloud water by graupel). The relative contribution of Pgmlt (the melting of graupel) increased slightly and then decreased significantly from the 20–50 mm type (36.28%) to the 50- mm type (25.06%), while that of Pracw had significantly increased especially from the 20–50 mm type (41.77%) to the 50- mm type (50.97%), which was related to the upward motion characteristics.