Cloud-resolving Model Research Articles

Examining the Kinematic Structures within which Lightning Flashes Are Initiated Using a Cloud-Resolving Model

Abstract Lightning is frequently initiated within the convective regions of thunderstorms, and so flash rates tend to follow trends in updraft speed and volume. It has been suggested that lightning production is linked to the turbulent flow generated by updrafts as turbulent eddies organize charged hydrometeors into complex charge structures. These complex charge structures consist of local regions of increased charge magnitudes between which flash-initiating electric fields may be generated. How turbulent kinematics influences lightning production, however, remains unclear. In this study, lightning flashes produced in a multicell and two supercell storms simulated using The Collaborative Model for Multiscale Atmospheric Simulation (COMMAS) were examined to identify the kinematic flow structures within which they occurred. By relating the structures of updrafts to thermals, initiated lightning flashes were expected to be located where the rate of strain and rotational flow are equal, or between updraft and eddy flow features. Results showed that the average lightning flash is initiated in kinematic flow structures dominated by vortical flow patterns, similar to those of thermals, and the structures’ kinematics are characterized by horizontal vorticity and vertical shearing. These kinematic features were common across all cases and demonstrated that where flash-initiating electric fields are generated is along the periphery of updrafts where turbulent eddies are produced. Careful consideration of flow structures near initiated flashes is consistent with those of thermals rising through a storm.

Intensification of Tilted Tropical Cyclones over Relatively Cool and Warm Oceans in Idealized Numerical Simulations

Abstract A cloud-resolving model is used to examine the intensification of tilted tropical cyclones from depression to hurricane strength over relatively cool and warm oceans under idealized conditions where environmental vertical wind shear has become minimal. Variation of the SST does not substantially change the time-averaged relationship between tilt and the radial length scale of the inner core, or between tilt and the azimuthal distribution of precipitation during the hurricane formation period (HFP). By contrast, for systems having similar structural parameters, the HFP lengthens superlinearly in association with a decline of the precipitation rate as the SST decreases from 30° to 26°C. In many simulations, hurricane formation progresses from a phase of slow or neutral intensification to fast spinup. The transition to fast spinup occurs after the magnitudes of tilt and convective asymmetry drop below certain SST-dependent levels following an alignment process explained in an earlier paper. For reasons examined herein, the alignment coincides with enhancements of lower–middle-tropospheric relative humidity and lower-tropospheric CAPE inward of the radius of maximum surface wind speed rm. Such moist-thermodynamic modifications appear to facilitate initiation of the faster mode of intensification, which involves contraction of rm and the characteristic radius of deep convection. The mean transitional values of the tilt magnitude and lower–middle-tropospheric relative humidity for SSTs of 28°–30°C are respectively higher and lower than their counterparts at 26°C. Greater magnitudes of the surface enthalpy flux and core deep-layer CAPE found at the higher SSTs plausibly compensate for less complete alignment and core humidification at the transition time.

Evaluating and Improving Scale‐Awareness of a Convective Parameterization Closure Using Cloud‐Resolving Model Simulations of Convection

AbstractThis study aims to evaluate a revised closure of the Zhang‐McFarlane (ZM) scheme for deep convection and to further improve its scale awareness. Output from two cloud‐resolving model (CRM) simulations of both midlatitude organized (MC3E) and tropical unorganized (TWP‐ICE) convection are used for the evaluation. By averaging the CRM output over different subdomain sizes from 64 to 4 km, convection‐associated fields are obtained to represent the fields at different horizontal resolutions of global climate models (GCMs). The convection parameterization closure is then tested using these fields. Results show that the cloud base mass flux Mb determined from the closure has a relatively good relationship with CRM‐simulated convection at coarse resolutions for both MC3E and TWP‐ICE, but their correlation degrades at higher resolutions, especially when approaching the gray zone scale under 10 km. The fluctuation of CAPE consumption rate per unit cloud base mass flux for different convective events is found to be an important factor affecting the correlation. When averaged over the base domain, the cloud base mass flux determined by the closure is found to increase with decreasing subdomain size, implying that the closure is not scale‐aware. To improve its scale‐awareness, a modified closure is designed to alleviate the overprediction of convection at high GCM resolutions. Results show that the modified closure has the scale‐aware ability to suppress the overprediction problem at high GCM resolutions for both MC3E and TWP‐ICE.

Evaluation of Mei-yu heavy-rainfall quantitative precipitation forecasts in Taiwan by a cloud-resolving model for three seasons of 2012–2014

Abstract. In this study, the performance of quantitative precipitation forecasts (QPFs) by the Cloud-Resolving Storm Simulator (CReSS) in Taiwan, at a horizontal grid spacing of 2.5 km and a domain size of 1500×1200 km2, in the range of 1–3 d during three Mei-yu seasons (May–June) of 2012–2014 is evaluated using categorical statistics, with an emphasis on heavy-rainfall events (≥100 mm per 24 h). The categorical statistics are chosen because the main hazards are landslides and floods in Taiwan, so predicting heavy rainfall at the correct location is important. The overall threat scores (TSs) of QPFs for all events on day 1 (0–24 h) are 0.18, 0.15, and 0.09 at thresholds of 100, 250, and 500 mm, respectively, and indicate considerable improvements at increased resolution compared to past results and 5 km models (TS < 0.1 at 100 mm and TS ≤ 0.02 at 250 mm). Moreover, the TSs are shown to be higher and the model more skillful in predicting larger events, in agreement with earlier findings for typhoons. After classification based on observed rainfall, the TSs of day − 1 QPFs for the largest 4 % of events by CReSS at 100, 250, and 500 mm (per 24 h) are 0.34, 0.24, and 0.16, respectively, and can reach 0.15 at 250 mm on day 2 (24–48 h) and 130 mm on day 3 (48–72 h). The larger events also exhibit higher probability of detection and lower false alarm ratio than smaller ones almost without exception across all thresholds. With the convection and terrain better resolved, the strength of the model is found to lie mainly in the topographic rainfall in Taiwan rather than migratory events that are more difficult to predict. Our results highlight the crucial importance of cloud-resolving capability and the size of fine mesh for heavy-rainfall QPFs in Taiwan.

Uncertainty in Aerosol Rainout Processes through the Case of the Radioactive Materials Emitted by the Fukushima Dai-ichi Nuclear Power Plant in March 2011

The process of an aerosol rainout in wet deposition induces large uncertainties among atmospheric aerosol simulations, especially for particles in the fine mode. In this study, we performed an intercomparison study of four different rainout schemes on the model (the nonhydrostatic icosahedral atmospheric model or NICAM) to simulate particulate Cs-137 in the emission scenario of the March 2011 accident at the Fukushima Dai-ichi Nuclear Power Plant. The schemes include global climate models (GCMs) approach with a simple tuning parameter to determine the scavenging coefficient, and another optimized for cloud resolving models (CRMs) to account for prognostic precipitation and realistic vertical transport. The third approach was the conventional method under the assumption of a pseudo-first-order approximation based on the surface precipitation flux. The fourth approach was involved in offline chemical transport models (CTMs) with a simplified parametric analysis approach to clouds and precipitation flux. In most experiments, statistical metrics of the Cs-137 concentrations using in-situ measurements were calculated to be within ±30 % (bias), 0.6–0.9 (correlation), 67–112 Bq m−3 (uncertainty), and < 40 % (precision within a factor of 10). The CRM-type method yielded the best results but required a lower limit of tuning parameters to compensate for the results. Both the GCM-type and the conventional methods were also useful by setting proper tuning parameters. The CTM-type yielded better correlation and lower uncertainty but larger negative bias. These analyses suggest the overestimation of the conversion rate from cloud droplets into raindrops by the NICAM. However, this cannot be resolved by simply interchanging cloud microphysics schemes. It was found that the sensitivity of the rainout scheme has a stronger influence on the Cs-137 concentration than the different treatments of cloud microphysics. Thus, to replicate the observed Cs-137 distribution, it is essential to have a better meteorological field as well as a proper rainout scheme.

Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator

Abstract. Large computer models are ubiquitous in the Earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties, and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case studies using ESEm to reduce parametric uncertainty in a general circulation model and explore precipitation sensitivity in a cloud-resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.

Cloud-scale modelling of the impact of deep convection on the fate of oceanic bromoform in the troposphere: a case study over the west coast of Borneo

Abstract. This paper presents a modelling study on the fate of CHBr3 and its product gases in the troposphere within the context of tropical deep convection. A cloud-scale case study was conducted along the west coast of Borneo, where several deep convective systems were triggered on the afternoon and early evening of 19 November 2011. These systems were sampled by the Falcon aircraft during the field campaign of the SHIVA project and analysed using a simulation with the cloud-resolving meteorological model C-CATT-BRAMS at 2×2 km resolution that represents the emissions, transport by large-scale flow, convection, photochemistry, and washout of CHBr3 and its product gases (PGs). We find that simulated CHBr3 mixing ratios and the observed values in the boundary layer and the outflow of the convective systems agree. However, the model underestimates the background CHBr3 mixing ratios in the upper troposphere, which suggests a missing source at the regional scale. An analysis of the simulated chemical speciation of bromine within and around each simulated convective system during the mature convective stage reveals that &gt;85 % of the bromine derived from CHBr3 and its PGs is transported vertically to the point of convective detrainment in the form of CHBr3 and that the remaining small fraction is in the form of organic PGs, principally insoluble brominated carbonyls produced from the photo-oxidation of CHBr3. The model simulates that within the boundary layer and free troposphere, the inorganic PGs are only present in soluble forms, i.e. HBr, HOBr, and BrONO2, and, consequently, within the convective clouds, the inorganic PGs are almost entirely removed by wet scavenging. We find that HBr is the most abundant PG in background lower-tropospheric air and that this prevalence of HBr is a result of the relatively low background tropospheric ozone levels at the regional scale. Contrary to a previous study in a different environment, for the conditions in the simulation, the insoluble Br2 species is hardly formed within the convective systems and therefore plays no significant role in the vertical transport of bromine. This likely results from the relatively small quantities of simulated inorganic bromine involved, the presence of HBr in large excess compared to HOBr and BrO, and the relatively efficient removal of soluble compounds within the convective column.

Evaluating Quantitative Precipitation Forecasts Using the 2.5 km CReSS Model for Typhoons in Taiwan: An Update through the 2015 Season

In this study, 24 h quantitative precipitation forecasts (QPFs) by a cloud-resolving model (with a grid spacing of 2.5 km) on days 1–3 for 29 typhoons in six seasons of 2010–2015 in Taiwan were examined using categorical scores and rain gauge data. The study represents an update from a previous study for 2010–2012, in order to produce more stable and robust statistics toward the high thresholds (typically with fewer sample points), which is our main focus of interest. This is important to better understand the model’s ability to predict such high-impact typhoon rainfall events. The overall threat scores (TS, defined as the fraction among all verification points that are correctly predicted to reach a given threshold to all points that are either observed or predicted to reach that threshold, or both) were 0.28 and 0.18 on day 1 (0–24 h) QPFs, 0.25 and 0.16 on day 2 (24–48 h) QPFs, and 0.15 and 0.08 on day 3 (48–72 h) QPFs at 350 mm and 500 mm, respectively, showing improvements over 5 km models. Moreover, as found previously, a strong dependence of higher TSs for larger rainfall events also existed, and the corresponding TSs at 350 and 500 mm for the top 5% of events were 0.39 and 0.25 on day 1, 0.38 and 0.21 on day 2, and 0.25 and 0.12 on day 3. Thus, for the top typhoon rainfall events that have the highest potential for hazards, the model exhibits an even higher ability for QPFs based on categorical scores. Furthermore, it is shown that the model has little tendency to overpredict or underpredict rainfall for all groups of events with different rainfall magnitude across all thresholds, except for some tendency to under-forecast for the largest event group on day 3. Some issues associated with categorical statistics to be aware of are also demonstrated and discussed.

SAM++: Porting the E3SM-MMF cloud resolving model using a C++ portability library

In this work, we demonstrate the process for porting the cloud resolving model (CRM) used in the Energy Exascale Earth System Model Multi-Scale Modeling Framework (E3SM-MMF) from its original Fortran code base to C++ code using a portability library. This porting process is performed using the Yet Another Kernel Library (YAKL), a simplified C++ portability library that specializes in Fortran porting. In particular, we detail our step-by-step approach for porting the System for Atmospheric Modeling (SAM), the CRM used in E3SM-MMF, using a hybrid Fortran/C++ framework that allows for systematic reproduction and correctness testing of gradually ported YAKL C++ code. Additionally, analysis is done on the performance of the ported code using OLCF’s Summit supercomputer.

Seasonal and Diurnal Variations of Cloud Systems over the Eastern Tibetan Plateau and East China: A Cloud-resolving Model Study

Seasonal and Diurnal Variations of Cloud Systems over the Eastern Tibetan Plateau and East China: A Cloud-resolving Model Study

On the formation mechanism of cirrus banding: radiosonde observations, numerical simulations, and stability analyses

AbstractThe structures and formation mechanisms of cirrus banding are investigated by analyzing radiosonde observations, conducting high-resolution numerical experiments, and performing linear stability analyses. In all 29 cases of cirrus bands that were analyzed, radiosonde observational data indicate that statically unstable layers exist. The detected banding clouds were aligned nearly parallel to the vertical shear vector in the unstable layer. In high-resolution numerical experiments using the cloud-resolving model SCALE-RM, cirrus bands forming in the outflow layer of a tropical cyclone are explicitly simulated. The existence of statically unstable layers and band-parallel background vertical wind shear are commonly identified in the simulations. Sensitivity experiments and heat budget analyses demonstrated that the unstable stratification within the cirrus clouds was maintained by the cloud-radiation interactions. To reveal the behavior of fluid instabilities in the cirrus bands, linear stability analyses in a basic state constructed from the radiosonde observations were performed. The fastest-growing disturbance is highly similar to that of the previously known thermal-shear instability in a uniform and isolated unstable layer and the results obtained by radiosonde observations and numerical simulations. All of the results consistently indicate that thermal-shear instability is responsible for the formation of cirrus banding. Our results not only follow previous modeling studies but also provide observational support, quantification of the destabilization by the cloud-radiation interactions, as well as a theoretical basis of the thermal-shear instability in a complex environment near cirrus bands.

Vertical profile of aerosol characteristics including activation over a rain shadow region in India

Unique airborne observations of aerosol size spectral and chemical characteristics over the peninsular Indian region are illustrated in this case study. Multimodal lognormal distributions were required to fit the observed in situ aerosol size distribution. The aerosol composition and mixing state was deduced from the single-particle analyses of aerosols using the transmission electron microscope and soot photometer coupled with satellite retrieved aerosol classification, and back trajectory analyses. Organic carbon was the most prominent aerosol type found at all altitudes. Refractory black carbon aerosols which constituted about 10–12% of the aerosols in the boundary layer were primarily internally mixed with both inorganic and organic coating. Other major aerosol types were dust and sea salt, with the latter primarily found below 2 km. Further, the cloud forming ability of in-situ aerosols is tested through a cloud condensation nuclei closure analysis. The effective hygroscopicity decreased above cloud base due to the absence of sea salt aerosols. The change in large-scale winds with altitude affected the aerosol composition and hygroscopicity. The multimodal aerosol size distribution and hygroscopicity parameter (κ = 0.18) obtained for the cloud base aerosols over the rain shadow region are useful for studying aerosol-cloud interactions using regional cloud-resolving models.

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

Influence of Sea Surface Temperature on a Mesoscale Convective System producing Extreme Rainfall over the Yellow Sea

AbstractAn extreme rainfall-producing linear mesoscale convective systems (MCSs) occurred over the Yellow Sea, Korea, on 13 August 2012, producing 430 mm of rainfall in less than 12 h, causing devastating flash floods and landslides. To understand the causative processes underlying this event, we examined the linear MCSs formation and development mechanisms using observations and cloud-resolving models. The organized linear MCSs produced extreme rainfall at Gunsan in a favorable large-scale environment. The synoptic environment showed the stationary surface front elongating from China to Korea; a southwesterly low-level jet transported the warm, moist air from low latitudes towards the front. In the upper-level synoptic environment, the trough and entrance regions of the upper-level jet were north of the heavy rainfall, promoting the development of convection. The extreme rainfall over the Gunsan area resulted from the back-building mode of the MCSs, in which new convective cells continued to pass over the same area while the entire convective system was nearly stationary. The sea surface temperature (SST) during the extreme rainfall events was abnormally 1°C higher than the 30-year climatological mean, and a local warm pool (&gt;28.5°C) existed where the convective cells were continuously initiated. Cloud-resolving models simulated the low-level convergence, and the latent heat flux was large in the local warm SST field. These induced MCSs formation and development, contributing to a significant rainfall increase over the Yellow Sea. The terrain’s influence on the large rainfall amount in the area was also noted.

Influence of Upper-Troposphere Stratification and Cloud-Radiation Interaction on Convective Overshoots in the Tropical Tropopause Layer

AbstractIt is still debated whether radiative heating observed in the tropical tropopause layer (TTL) is balanced primarily by cooling from convective overshoots, as in an entrainment layer, or by adiabatic cooling from large-scale eddy-driven upwelling. In this study, three-dimensional cloud-resolving model simulations of radiative-convective equilibrium were carried out with three different cloud microphysics schemes and 1-km horizontal resolution. We demonstrate that overshooting cooling in the TTL can be strongly modulated by upper-troposphere stratification. Two of the schemes produce a hard-landing scenario in which convective overshoots reach the TTL with frequent large vertical velocity leading to strong overshooting cooling (~ −0.2 K day-1). The third scheme produces a soft-landing scenario in which convective overshoots rarely reach the TTL with large vertical velocity and produce little overshooting cooling (~ −0.03 K day-1). The difference between the two scenarios is attributed to changes in the upper-troposphere stratification related to different atmospheric cloud radiative effects (ACRE). The microphysics scheme that produces the soft-landing scenario has much stronger ACRE in the upper troposphere leading to a ~3K warmer and more stable layer which acts as a buffer zone to slow down the convective updrafts. The stratification mechanism suggests the possibility for the ozone variation or eddy-driven upwelling in the TTL to modulate convective overshoots. We further test the sensitivity of overshooting cooling to changes in model resolution by increasing the horizontal resolution to 100 m. The corresponding change of overshooting cooling is much smaller compared with the difference between the hard-landing and soft-landing scenarios.

Characterizing Convection Schemes Using Their Responses to Imposed Tendency Perturbations

AbstractConvection is usually parameterized in global climate models, and there are often large discrepancies between results obtained with different convection schemes. Conventional methods of comparing convection schemes using observational cases or directly in three‐dimensional (3D) models do not always clearly identify parameterization strengths and weaknesses. In this paper we evaluate the response of parameterizations to various perturbations rather than their behavior under particular strong forcing. We use the linear response function method proposed by Kuang (2010) to compare 12 physical packages in five atmospheric models using single‐column model (SCM) simulations under idealized radiative‐convective equilibrium conditions. The models are forced with anomalous temperature and moisture tendencies. The temperature and moisture departures from equilibrium are compared with published results from a cloud‐resolving model (CRM). Results show that the procedure is capable of isolating the behavior of a convection scheme from other physics schemes. We identify areas of agreement but also substantial differences between convection schemes, some of which can be related to scheme design. Some aspects of the model linear responses are related to their RCE profiles (the relative humidity profile in particular), while others constitute independent diagnostics. All the SCMs show irregularities or discontinuities in behavior that are likely related to threshold‐related mechanisms used in the convection schemes, and which do not appear in the CRM. Our results highlight potential flaws in convection schemes and suggest possible new directions to explore for parameterization evaluation.

Dynamics of Simulated High-Shear, Low-CAPE Supercells

AbstractHigh-shear, low-CAPE environments prevalent in the southeastern United States account for a large fraction of tornadoes and pose challenges for operational meteorologists. Yet, existing knowledge of supercell dynamics, particularly in the context of cloud-resolving modeling, is dominated by moderate- to high-CAPE environments typical of the Great Plains. This study applies high-resolution modeling to clarify the behavior of supercells in the more poorly understood low-CAPE environments, and compares them to a benchmark simulation in a higher-CAPE environment. Simulated low-CAPE supercells’ main updrafts do not approach the theoretical equilibrium level; their largest vertical velocities result not from buoyancy, but from dynamic accelerations associated with low-level mesocyclones and vortices. Surprisingly, low-CAPE tornado-like vortex parcels also sometimes stop ascending near the vortex top instead of carrying large vorticity upward into the midlevel updraft, contributing to vortex shallowness. Each of these low-CAPE behaviors is attributed to dynamic perturbation pressure gradient accelerations that are maximized in low levels, which predominate when the buoyancy is small.

The Intensity-dependence of Tropical Cyclone Intensification Rate in a Simplified Energetically Based Dynamical System Model

AbstractIn this study, a simple energetically based dynamical system model of tropical cyclone (TC) intensification is modified to account for the observed dependence of the intensification rate (IR) on the storm intensity. According to the modified dynamical system model, the TC IR is controlled by the intensification potential (IP) and the weakening rate due to surface friction beneath the eyewall. The IP is determined primarily by the rate of change in the potential energy available for a TC to develop, which is a function of the thermodynamic conditions of the atmosphere and the underlying ocean, and the dynamical efficiency of the TC system. The latter depends strongly on the degree of convective organization within the eyewall and the inner-core inertial stability of the storm. At a relatively low TC intensity, the IP of the intensifying storm is larger than the frictional weakening rate, leading to an increase in the TC IR with TC intensity in this stage. As the storm reaches an intermediate intensity of 30-40 m s-1, the difference between IP and frictional weakening rate reaches its maximum, concurrent with the maximum IR. Later on, the IR decreases as the TC intensifies further because the frictional dissipation increases with TC intensity at a faster rate than the IP. Finally, the storm approaches its maximum potential intensity (MPI) and the IR becomes zero. The modified dynamical system model is validated with results from idealized simulations with an axisymmetric nonhydrostatic, cloud-resolving model.

Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment

AbstractThis study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

Intensification and Maintenance of a Double Warm-Core Structure in Typhoon Lan (2017) Simulated by a Cloud-Resolving Model

AbstractKnowledge of the development and maintenance processes of double warm cores in tropical cyclones is important for full understanding of the dynamics of storm intensity changes. During its mature stage, Typhoon Lan (2017) had a clear double warm-core structure, which was observed by dropsondes. In this study, to investigate the intensification and maintenance of the double warm-core structure, a numerical simulation of the storm is performed with a cloud-resolving model and verified by dropsonde and satellite observations. A potential temperature budget and backward trajectories are diagnosed to examine intensification and maintenance processes in the simulated eye. The budget analysis indicates that, during the most rapidly intensifying stage, a double warm core is enhanced by axisymmetric subsidence warming in the eye. In the mature stage, upper-core warming is mostly canceled by ventilation due to vertical wind shear, but the lower core continues to warm by asymmetric advection, possibly associated with dynamical instability in the eyewall. The results raise a topic of interest: it is difficult to fully explain the axisymmetric subsidence warming process during the most rapidly intensifying stage by the dynamical response in an axisymmetric balanced vortex. The back-trajectory analysis indicates that the air mass associated with the subsidence is partly induced by inward acceleration in subgradient regions (unbalanced processes) in the eyewall.