Cloud-resolving Model Simulations Research Articles

Humidity variability revealed by a sounding array and its implications for cloud representation in GCMs

AbstractSubgrid‐scale humidity variability is critical for statistical cloud schemes. The Atmospheric Radiation Measurement (ARM) sounding array, covering a comparable size to a grid box of current global climate models (GCMs), provides estimates of subgrid‐scale humidity variability. Using radiosonde measurements from ARM sounding arrays, humidity variabilities at a tropical and a midlatitude site are analyzed. Normalized moisture variance is small in the lower troposphere but tends to be large in the middle troposphere. Moisture variability dominates relative humidity (RH) variability at the tropical site, but the contribution by temperature variability cannot be ignored at the midlatitude site. Based on the analysis, a simple linear relationship between RH variance and mean is proposed. Cloud schemes assuming Gaussian distributions give comparable cloudiness as those assuming a beta distribution considering both moisture variance and skewness. A probability distribution function scheme assuming a Gaussian distribution of RH has more flexibility than a RH threshold scheme, which tends to overestimate cloudiness in the moist boundary layer over the tropics. Supersaturation with respect to ice needs to be allowed in the upper troposphere over the tropics to reduce the persistent overestimated cloudiness there. Similar comparison results are found from analysis of cloud resolving model simulations. The study suggests that measurements from sounding arrays would be valuable for statistical cloud scheme evaluation and development.

The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics

Abstract This study investigates how precipitation-driven cold pools aid the formation of wider clouds that are essential for a transition from shallow to deep convection. In connection with a temperature depression and a depletion of moisture inside developing cold pools, an accumulation of moisture in moist patches around the cold pools is observed. Convective clouds are formed on top of these moist patches. Larger moist patches form with time supporting more and larger clouds. Moreover, enhanced vertical lifting along the leading edges of the gravity current triggered by the cold pool is found. The interplay of moisture aggregation and lifting eventually promotes the formation of wider clouds that are less affected by entrainment and become deeper. These mechanisms are corroborated in a series of cloud-resolving model simulations representing different atmospheric environments. A positive feedback is observed in that, in an atmosphere in which cloud and rain formation is facilitated, stronger downdrafts will form. These stronger downdrafts lead to a stronger modification of the moisture field, which in turn favors further cloud development. This effect is not only observed in the transition phase but also active in prolonging the peak time of precipitation in the later stages of the diurnal cycle. These findings are used to propose a simple way for incorporating the effect of cold pools on cloud sizes and thereby entrainment rate into parameterization schemes for convection. Comparison of this parameterization to the cloud-resolving modeling output gives promising results.

The Improved NRL Tropical Cyclone Monitoring System with a Unified Microwave Brightness Temperature Calibration Scheme

The near real-time NRL global tropical cyclone (TC) monitoring system based on multiple satellite passive microwave (PMW) sensors is improved with a new inter-sensor calibration scheme to correct the biases caused by differences in these sensor’s high frequency channels. Since the PMW sensor 89 GHz channel is used in multiple current and near future operational and research satellites, a unified scheme to calibrate all satellite PMW sensor’s ice scattering channels to a common 89 GHz is created so that their brightness temperatures (TBs) will be consistent and permit more accurate manual and automated analyses. In order to develop a physically consistent calibration scheme, cloud resolving model simulations of a squall line system over the west Pacific coast and hurricane Bonnie in the Atlantic Ocean are applied to simulate the views from different PMW sensors. To clarify the complicated TB biases due to the competing nature of scattering and emission effects, a four-cloud based calibration scheme is developed (rain, non-rain, light rain, and cloudy). This new physically consistent inter-sensor calibration scheme is then evaluated with the synthetic TBs of hurricane Bonnie and a squall line as well as observed TCs. Results demonstrate the large TB biases up to 13 K for heavy rain situations before calibration between TMI and AMSR-E are reduced to less than 3 K after calibration. The comparison stats show that the overall bias and RMSE are reduced by 74% and 66% for hurricane Bonnie, and 98% and 85% for squall lines, respectively. For the observed hurricane Igor, the bias and RMSE decrease 41% and 25% respectively. This study demonstrates the importance of TB calibrations between PMW sensors in order to systematically monitor the global TC life cycles in terms of intensity, inner core structure and convective organization. A physics-based calibration scheme on TC’s TB corrections developed in this study is able to significantly reduce the biases between different PMW sensors.

Precipitation efficiency and its relationship to physical factors

The precipitation efficiency and its relationship to physical factors are examined by analyzing a two-dimensional cloud-resolving model simulation during TOGA COARE in this study. The basic physical factors include convective available potential energy, water—vapor convergence, vertical wind shear, cloud ratio, sea surface temperature, air temperature, and precipitable water. Precipitation efficiencies do not show a close relationship to air temperature nor to sea surface temperature nor to precipitable water. The precipitation efficiency increases as the water—vapor convergence rate increases and vertical wind shear weakens, whereas it decreases as the convective available potential energy dissipates and anvil clouds develop.

Multiscale Interactions in an Idealized Walker Circulation: Mean Circulation and Intraseasonal Variability

Abstract A high-resolution cloud-resolving model (CRM) simulation is developed here for a two-dimensional Walker circulation over a planetary-scale domain of 40 000 km for an extended period of several hundred days. The Walker cell emerges as the time-averaged statistical steady state with a prescribed sinusoidal sea surface temperature (SST) pattern with a mean temperature of 301.15 K and a horizontal variation of 4 K. The circulation exhibits intraseasonal variability on a time scale of about 20 days with quasi-periodic intensification of the circulation and broadening of the convective regime. This variability is closely tied to synoptic-scale systems associated with expansion and contraction of the Walker circulation. An index for the low-frequency variability is developed using an empirical orthogonal function (EOF) analysis and by regressing various dynamic fields on this index. The low-frequency oscillation has four main stages: a suppressed stage with strengthened midlevel circulation, an intensification phase, an active phase with strong upper-level circulation, and a weakening phase. Various physical processes occurring at these stages are discussed as well as the impact of organized convective systems on the large-scale flow.

A mass flux closure function in a GCM based on the Richardson number

A mass flux closure in a general circulation model (GCM) was developed in terms of the mean gradient Richardson number (GRN), which is defined as the ratio between the buoyancy and the shear-driven kinetic energy in the planetary boundary layer. The cloud resolving model (CRM) simulations using the tropical ocean and global atmosphere-coupled ocean–atmosphere response experiment forcing show that cloud-base mass flux is well correlated with the GRN. Using the CRM simulations, a mass flux closure function is formulated as an exponential function of the GRN and it is implemented in the Arakawa–Schubert convective scheme. The GCM simulations with the new mass flux closure are compared to those of the GCM with the conventional mass flux closure based on convective available potential energy. Because of the exponential function, the new closure permits convective precipitation only when the GRN has a sufficiently large value. When the GRN has a relatively small value, the convection is suppressed while the convective instability is released by large-scale precipitation. As a result, the ratio of convective precipitation to total precipitation is reduced and there is an increase in the frequency of heavy precipitation, more similar to the observations. The new closure also improves the diurnal cycle of precipitation due to a time delay of the large GRN with respect to convective instability.

Latent Heating and Mixing due to Entrainment in Tropical Deep Convection

Abstract Recent studies have noted the role of latent heating above the freezing level in reconciling Riehl and Malkus' hot tower hypothesis (HTH) with evidence of diluted tropical deep convective cores. This study evaluates recent modifications to the HTH through Lagrangian trajectory analysis of deep convective cores in an idealized, high-resolution cloud-resolving model (CRM) simulation that uses a sophisticated two-moment microphysical scheme. A line of tropical convective cells develops within a finer nested grid whose boundary conditions are obtained from a large-domain CRM simulation approaching radiative convective equilibrium (RCE). Microphysical impacts on latent heating and equivalent potential temperature (θe) are analyzed along trajectories ascending within convective regions of the high-resolution nested grid. Changes in θe along backward trajectories are partitioned into contributions from latent heating due to ice processes and a residual term that is shown to be an approximate representation of mixing. The simulations demonstrate that mixing with dry environmental air decreases θe along ascending trajectories below the freezing level, while latent heating due to freezing and vapor deposition increase θe above the freezing level. Latent heating contributions along trajectories from cloud nucleation, condensation, evaporation, freezing, deposition, and sublimation are also quantified. Finally, the source regions of trajectories reaching the upper troposphere are identified. Much of the air ascending within convective updrafts originates from above the lowest 2 km AGL, but the strongest updrafts are composed of air from closer to the surface. The importance of both boundary layer and midlevel inflow in moist environments is underscored in this study.

Comparison of Moist Static Energy and Budget between the GCM-Simulated Madden–Julian Oscillation and Observations over the Indian Ocean and Western Pacific

Abstract The moist static energy (MSE) anomalies and MSE budget associated with the Madden–Julian oscillation (MJO) simulated in the Iowa State University General Circulation Model (ISUGCM) over the Indian and Pacific Oceans are compared with observations. Different phase relationships between MJO 850-hPa zonal wind, precipitation, and surface latent heat flux are simulated over the Indian Ocean and western Pacific, which are greatly influenced by the convection closure, trigger conditions, and convective momentum transport (CMT). The moist static energy builds up from the lower troposphere 15–20 days before the peak of MJO precipitation, and reaches the maximum in the middle troposphere (500–600 hPa) near the peak of MJO precipitation. The gradual lower-tropospheric heating and moistening and the upward transport of moist static energy are important aspects of MJO events, which are documented in observational studies but poorly simulated in most GCMs. The trigger conditions for deep convection, obtained from the year-long cloud-resolving model (CRM) simulations, contribute to the striking difference between ISUGCM simulations with the original and modified convection schemes and play the major role in the improved MJO simulation in ISUGCM. Additionally, the budget analysis with the ISUGCM simulations shows the increase in MJO MSE is in phase with the horizontal advection of MSE over the western Pacific, while out of phase with the horizontal advection of MSE over the Indian Ocean. However, the NCEP analysis shows that the tendency of MJO MSE is in phase with the horizontal advection of MSE over both oceans.

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earth's surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density) plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with ~ 0.05 g·m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> detected at the surface, or an ~ 0.5-1.0-mm·h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

A simplified PDF parameterization of subgrid‐scale clouds and turbulence for cloud‐resolving models

Over the past decade a new type of global climate model (GCM) has emerged, which is known as a multiscale modeling framework (MMF). Colorado State University's MMF represents a coupling between the Community Atmosphere Model and the System for Atmospheric Modeling (SAM) to serve as the cloud‐resolving model (CRM) that replaces traditionally parameterized convection in GCMs. However, due to the high computational expense of the MMF, the grid size of the embedded CRM is typically limited to 4 km for long‐term climate simulations. With grid sizes this coarse, shallow convective processes and turbulence cannot be resolved and must still be parameterized within the context of the embedded CRM. This paper describes a computationally efficient closure that aims to better represent turbulence and shallow convective processes in coarse‐grid CRMs. The closure is based on the assumed probability density function (PDF) technique to serve as the subgrid‐scale (SGS) condensation scheme and turbulence closure that employs a diagnostic method to determine the needed input moments. This paper describes the scheme, as well as the formulation of the eddy length which is empirically determined from large eddy simulation (LES) data. CRM tests utilizing the closure yields good results when compared to LESs for two trade‐wind cumulus cases, a transition from stratocumulus to cumulus, and continental cumulus. This new closure improves the representation of clouds through the use of SGS condensation scheme and turbulence due to better representation of the buoyancy flux and dissipation rates. In addition, the scheme reduces the sensitivity of CRM simulations to horizontal grid spacing. The improvement when compared to the standard low‐order closure configuration of the SAM is especially striking.

Microphysical Processes Evident in Aerosol Forcing of Tropical Deep Convective Clouds

AbstractThis study investigates the effects of aerosols on tropical deep convective clouds (DCCs). A series of large-scale, two-dimensional cloud-resolving model simulations was completed, differing only in the concentration of aerosols available to act as cloud condensation nuclei (CCN). Polluted simulations contained more DCCs, wider storms, higher cloud tops, and more convective precipitation domainwide. Differences in warm cloud microphysics were largely consistent with the first and second aerosol indirect effects. The average surface precipitation produced in each DCC column decreased with increasing aerosol concentration. A detailed microphysical budget analysis showed that the reduction in collision and coalescence largely dominated the trend in average precipitation. The production of rain from ice, though it also decreased, became a more important contribution to precipitation as the aerosol concentration increased. The DCCs in polluted simulations contained more frequent extreme values of vertical velocity, but the average updraft speed decreased with increasing aerosols in DCCs above 6 km. An examination of the buoyancy term of the vertical velocity equation demonstrates that the drag associated with condensate loading is an important factor in determining the average updraft strength. The largest contributions to latent heating in DCCs were cloud nucleation and vapor deposition onto water and ice, but changes in latent heating were, on average, an order of magnitude smaller than those in the condensate loading term. The average updraft speed was largely affected by increased drag from condensate loading in more mature updrafts, while early storm updrafts experienced convective invigoration from increased latent heating.

A Comparison of the Water Budgets between Clouds from AMMA and TWP-ICE

AbstractTwo field campaigns, the African Monsoon Multidisciplinary Analysis (AMMA) and the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), took place in 2006 near Niamey, Niger, and Darwin, Northern Territory, Australia, providing extensive observations of mesoscale convective systems (MCSs) near a desert and a tropical coast, respectively. Under the constraint of their observations, three-dimensional cloud-resolving model simulations are carried out and presented in this paper to replicate the basic characteristics of the observed MCSs. All of the modeled MCSs exhibit a distinct structure having deep convective clouds accompanied by stratiform and anvil clouds. In contrast to the approximately 100-km-scale MCSs observed in TWP-ICE, the MCSs in AMMA have been successfully simulated with a scale of about 400 km.These modeled AMMA and TWP-ICE MCSs offer an opportunity to understand the structure and mechanism of MCSs. Comparing the water budgets between AMMA and TWP-ICE MCSs suggests that TWP-ICE convective clouds have stronger ascent while the mesoscale ascent outside convective clouds in AMMA is stronger. A case comparison, with the aid of sensitivity experiments, also suggests that vertical wind shear and ice crystal (or dust aerosol) concentration can significantly impact stratiform and anvil clouds (e.g., their areas) in MCSs. In addition, the obtained water budgets quantitatively describe the transport of water between convective, stratiform, and anvil regions as well as water sources/sinks from microphysical processes, providing information that can be used to help determine parameters in the convective and cloud parameterizations in general circulation models (GCMs).

Retrieving latent heating vertical structure from cloud and precipitation Profiles—Part I: Warm rain processes

An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages of hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water. Specifically, rain events are segregated into three rain types: warm, convective, and stratiform, based on their dynamical and thermodynamical characteristics. As the first of the series, only the warm rain LH algorithm is presented and evaluated here. The major microphysical processes of condensation and evaporation for warm rain are parameterized through traditional rain growth theory, with the aid of Cloud Resolving Model (CRM) simulations. The evaluation or the self-consistency tests indicate that the physical based retrievals capture the fundamental LH processes associated with the warm rain life cycle. There is no significant systematic bias in terms of convection strength, illustrated by the month-long CRM simulation as the mesoscale convective systems (MCSs) experience from initial, mature, to decay stages. The overall monthly-mean LH comparison showed that the total LH, as well as condensation heating and evaporation cooling components, agree with the CRM simulation.

Cloud-Resolving Model Simulations with One- and Two-Way Couplings via the Weak Temperature Gradient Approximation

AbstractA cloud-resolving model is modified to implement the weak temperature gradient approximation in order to simulate the interactions between tropical convection and the large-scale tropical circulation. The instantaneous domain-mean potential temperature is relaxed toward a reference profile obtained from a radiative–convective equilibrium simulation of the cloud-resolving model. For homogeneous surface conditions, the model state at equilibrium is a large-scale circulation with its descending branch in the simulated column. This is similar to the equilibrium state found in some other studies, but not all. For this model, the development of such a circulation is insensitive to the relaxation profile and the initial conditions.Two columns of the cloud-resolving model are fully coupled by relaxing the instantaneous domain-mean potential temperature in both columns toward each other. This configuration is energetically closed in contrast to the reference-column configuration. No mean large-scale circulation develops over homogeneous surface conditions, regardless of the relative area of the two columns. The sensitivity to nonuniform surface conditions is similar to that obtained in the reference-column configuration if the two simulated columns have very different areas, but it is markedly weaker for columns of comparable area. The weaker sensitivity can be understood as being a consequence of a formulation for which the energy budget is closed. The reference-column configuration has been used to study the convection in a local region under the influence of a large-scale circulation. The extension to a two-column configuration is proposed as a methodology for studying the influence on local convection of changes in remote convection.

Cloud-Resolving Model Simulations and a Simple Model of an Idealized Walker Cell

Abstract An idealized Walker cell with prescribed sea surface temperature (SST) and prescribed radiative cooling is studied using both a two-dimensional cloud-resolving model (CRM) and a simple conceptual model. In the CRM, for the same SST distribution, the width of the warm pool (area of strong precipitation) varies systematically with the magnitude of the radiative cooling, narrowing as radiative cooling is increased. The simple model is constructed to interpret these behaviors. Key aspects of the simple model include a surface wind determined from the boundary layer momentum budget, which in turn sets evaporation assuming a spatially uniform surface relative humidity, prescribed gross moist and dry stratification as a function of column water vapor and precipitation, and a gustiness enhancement on evaporation in areas of precipitation. It is found that the gustiness enhancement, likely due to mesoscale systems, creates a feedback that narrows the warm pool. This process has not been included in previous formulations of the simple model and its role is emphasized here.

Self-Organized Criticality and Homeostasis in Atmospheric Convective Organization

AbstractAtmospheric convection has a tendency to organize on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden–Julian oscillation. The present paper examines two major competing mechanisms of self-organization in a cloud-resolving model (CRM) simulation from a phenomenological thermodynamic point of view.The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with increasing column-integrated water, reminiscent of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as CRM experiments give mixed results.In this study, a CRM experiment over a large-scale domain with a constant sea surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms is further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes.

Evaluation of Hydrometeor Phase and Ice Properties in Cloud-Resolving Model Simulations of Tropical Deep Convection Using Radiance and Polarization Measurements

Abstract Satellite measurements are used to evaluate the glaciation, particle shape, and effective radius in cloud-resolving model simulations of tropical deep convection. Multidirectional polarized reflectances constrain the ice crystal geometry and the thermodynamic phase of the cloud tops, which in turn are used to calculate near-infrared reflectances so as to constrain the simulated ice effective radius, thereby avoiding inconsistencies between retrieval algorithms and model simulations. Liquid index values derived from Polarization and Directionality of the Earth’s Reflectances (POLDER) measurements indicate only ice-topped clouds at brightness temperatures (BTs) lower than −40°C, only liquid clouds at BT &amp;gt; −20°C, and both phases occurring at temperatures in between. Liquid index values calculated from model simulations generally reveal too many ice-topped clouds at BT &amp;gt; −20°C. The model assumption of platelike ice crystals with an aspect ratio of 0.7 is found consistent with POLDER measurements for BT &amp;lt; −40°C when very rough ice crystals are assumed, leading to an asymmetry parameter of 0.74, whereas measurements indicate more extreme aspect ratios of ~0.15 at higher temperatures, yielding an asymmetry parameter of 0.84. MODIS-retrieved ice effective radii are found to be 18–28 μm at BT &amp;lt; −40°C, but biased low by about 5 μm owing primarily to the assumption of pristine crystals in the retrieval. Simulated 2.13-μm reflectances at BT &amp;lt; −40°C are found to be about 0.05–0.1 too large compared to measurements, suggesting that model-simulated effective radii are 7–15 μm too small. Two simulations with contrasting ice nucleation schemes showed little difference in simulated effective radii at BT &amp;lt; −40°C, indicating that homogeneous nucleation is dominating in the simulations. Changes around −40°C in satellite observations suggest a change in cloud-top ice shape and/or size in natural deep convection possibly related to a change in the freezing mechanism.

Phase differences between rainfall and its sources in the tropical deep convective regime: A partitioning analysis based on the surface rainfall budget

A partitioning scheme based on surface rainfall processes is applied to a lag correlation analysis between tropical rainfall and its sources in this study. The rainfall sources include convective available potential energy (CAPE), water vapor source (water vapor convergence plus surface evaporation), and net condensation (condensation and deposition minus evaporation of rain). The analysis is carried out using a 21-day TOGA COARE cloud-resolving model simulation data. Maximum model domain mean surface rainfall leads the minimum mean CAPE by 6h and is phase locking with the maximum mean net condensation mainly through the rainfall associated with water vapor convergence. Maximum mean surface rainfall lags the maximum mean water vapor source by 3h mainly through the rainfall type associated with local atmospheric drying, water vapor divergence, and hydrometeor loss/convergence.

Control of deep convection by sub-cloud lifting processes: the ALP closure in the LMDZ5B general circulation model

Recently, a new conceptual framework for deep convection scheme triggering and closure has been developed and implemented in the LMDZ5B general circulation model, based on the idea that deep convection is controlled by sub-cloud lifting processes. Such processes include boundary-layer thermals and evaporatively-driven cold pools (wakes), which provide an available lifting energy that is compared to the convective inhibition to trigger deep convection, and an available lifting power (ALP) at cloud base, which is used to compute the convective mass flux assuming the updraft vertical velocity at the level of free convection. While the ALP closure was shown to delay the local hour of maximum precipitation over land in better agreement with observations, it results in an underestimation of the convection intensity over the tropical ocean both in the 1D and 3D configurations of the model. The specification of the updraft vertical velocity at the level of free convection appears to be a key aspect of the closure formulation, as it is weaker over tropical ocean than over land and weaker in moist mid-latitudes than semi-arid regions. We propose a formulation making this velocity increase with the level of free convection, so that the ALP closure is adapted to various environments. Cloud-resolving model simulations of observed oceanic and continental case studies are used to evaluate the representation of lifting processes and test the assumptions at the basis of the ALP closure formulation. Results favor closures based on the lifting power of sub-grid sub-cloud processes rather than those involving quasi-equilibrium with the large-scale environment. The new version of the model including boundary-layer thermals and cold pools coupled together with the deep convection scheme via the ALP closure significantly improves the representation of various observed case studies in 1D mode. It also substantially modifies precipitation patterns in the full 3D version of the model, including seasonal means, diurnal cycle and intraseasonal variability.

A limited area model (LAM) intercomparison study of a TWP‐ICE active monsoon mesoscale convective event

A limited area model (LAM) intercomparison study is conducted based on a tropical monsoonal deep convection case observed during the Tropical Warm Pool ‐ International Cloud Experiment (TWP‐ICE). The LAM simulations are compared with the variational analyses (VA) based on the Atmospheric Radiation Measurement (ARM) observations and the cloud resolving model (CRM) simulations forced by the VA. Driven by the ECMWF analyses or global model forecasts, LAMs are able to produce the large‐scale thermodynamic field reasonably well compared with the VA. However, the LAM simulated dynamic fields, such as the large‐scale horizontal divergence, vertical velocity, and cyclogenesis in the monsoonal trough, have a large inter‐model spread and deviate substantially from observations. Despite the differences in large‐scale forcing, there is certain consistency between the CRM and LAM simulations: stratiform (w ≤ 1 m s−1) ice clouds dominate the cloud fraction and convective (w &gt; 3 m s−1) clouds occupy less than 3 percent of the total cloudy area. But the hydrometeor content of stratiform ice clouds is only one tenth of that of convective and transitional (1 m s−1 &lt; w ≤ 3 m s−1) ice clouds. However, there is a large inter‐LAM spread in the simulated cloud fraction and hydrometeor mixing ratios. The inter‐LAM difference in solid phase hydrometeors (cloud ice, snow, and graupel) can be up to nearly a factor of 10. Among all the hydrometeor types, the stratiform ice clouds are simulated least consistently by the LAMs. The large inter‐LAM spread suggests that obtaining consistent and reliable dynamic and cloud fields remains a challenge for the LAM approach.