Convective Clusters Research Articles

Aerosol-Cloud-Precipitation Interactions in the Context of Convective Self-Aggregation.

We investigate the sensitivity of self‐aggregated radiative‐convective‐equilibrium cloud‐resolving model simulations to the cloud condensation nuclei (CCN) concentration. Experiments were conducted on a long (2,000‐km × 120‐km) channel domain, allowing the emergence of multiple convective clusters and dry regions of subsidence. Increasing the CCN concentration leads to increased moisture in the dry regions, increased midlevel and upper level clouds, decreased radiative cooling, and decreased precipitation. We find that these trends follow from a decrease in the strength of the self‐aggregation as measured by the moist static energy (MSE) variance. In our simulations, precipitation is correlated, both locally and in total, with the distribution of MSE anomalies. We thus quantify changes in the adiabatic/diabatic contributions to MSE anomalies (Wing & Emanuel, 2014, https://doi.org/10.1002/2013MS000269) and relate those changes to changes in precipitation. Through a simple two‐column conceptual model, we argue that the reduction in precipitation can be explained thermodynamically by the reduction in mean net radiative cooling and mechanistically by the weakening of the area‐weighted radiatively driven subsidence velocity—defined as the ratio of the total radiative cooling over the dry regions and the static stability. We interpret the system's response to increasing CCN as a thermodynamically constrained realization of an aerosol indirect effect on clouds and precipitation.

Climatology of easterly wave disturbances over the tropical South Atlantic

A 21-year climatology of Easterly Waves Disturbances (EWDs) over the tropical South Atlantic (TSA) has been examined using data from the European Centers for Medium-Range Weather Forecasting interim reanalysis (ERAI) and satellite data. This includes the frequency distribution of EWDs and their interannual variability. The large-scale environment associated with EWDs has been investigated for the coastal region of Northeast Brazil (NEB) for the rainy (April–August) season using a composite analysis. EWDs were first identified in ERAI, resulting in 518 observed cases. These were found to show notable interannual variability with around 16–40 episodes each year and with an average lifetime of 4–6 days. Of the identified EWDs, 97% reached the coast of NEB, of which 64% were convective in nature and 14% moved across the NEB region and reached the Amazon. The annual occurrence of EWDs seems to be lower (higher) during El Nino (La Nina). The monthly occurrence of EWDs shows higher activity in the rainy season. EWDs originate in association with four types of system: cold fronts, convective clusters from the west coast of Africa, Intertropical Convergence Zone and Tropical Upper Tropospheric Cyclonic Vortices. The composite analysis indicates strong relative vorticity and divergence anomalies at low levels, as well as in the vertical profiles of relative humidity and vertical velocity (omega). The precipitation composites show that the EWDs propagate between the TSA and NEB and contribute at least 60% of the total rainfall over the east coast of NEB throughout the rainy season.

Objective Quantification of Convective Clustering Observed During the AMIE/DYNAMO Two‐Day Rain Episodes

AbstractOne critical bottleneck in developing and evaluating ways to represent the mesoscale organization of convection in cumulus parameterization schemes is that there is no single accepted method of objectively quantifying the degree of convective organization or clustering from observations. This study addresses this need using high‐quality S‐PolKa radar data from the Atmospheric Radiation Measurement Madden‐Julian Oscillation Investigation Experiment/Dynamics of the Madden‐Julian Oscillation (AMIE/DYNAMO) field campaign. We first identify convective elements (contiguous convective echoes [CCEs]) from radar reflectivity observations using the rain type classification algorithm of Powell et al. (2016, https://doi.org/10.1175/JTECH‐D‐15‐0135.1). Then we apply scalar clustering metrics, including the organization index (Iorg) of Tompkins and Semie, to the radar CCEs to test their ability of quantifying convective clustering during the observed two‐day rain episodes. Our results show two distinct phases of convective clustering during the two‐day rain episodes, with each phase covering about 10 hr before (Phase 1) and after (Phase 2) the time of peak rain rate. In Phase 1 clustering, the number of CCEs increases and convective cells cluster as new cells form preferentially near existing convective entities. The number of CCEs decreases as the environment stabilizes in Phase 2 clustering, during which already clustered cells with associated stratiform clouds are preferred over the isolated ones. Iorg is capable of capturing convective clustering in both phases. The possible mechanisms for convective clustering are discussed, including cold pool‐updraft feedback, moisture‐convection interaction, and mesoscale circulations. Our results suggest that parameterizations of convective organization should represent the feedback processes that are responsible for the convective clustering during both phases.

A Method for Identifying Midlatitude Mesoscale Convective Systems in Radar Mosaics. Part I: Segmentation and Classification

AbstractThis research evaluates the ability of image-processing and select machine-learning algorithms to identify midlatitude mesoscale convective systems (MCSs) in radar-reflectivity images for the conterminous United States. The process used in this study is composed of two parts: segmentation and classification. Segmentation is performed by identifying contiguous or semicontiguous regions of deep, moist convection that are organized on a horizontal scale of at least 100 km. The second part, classification, is performed by first compiling a database of thousands of precipitation clusters and then subjectively assigning each sample one of the following labels: 1) midlatitude MCS, 2) unorganized convective cluster, 3) tropical system, 4) synoptic system, or 5) ground clutter and/or noise. The attributes of each sample, along with their assigned label, are used to train three machine-learning algorithms: random forest, gradient boosting, and “XGBoost.” Results using a testing dataset suggest that the algorithms can distinguish between MCS and non-MCS samples with a high probability of detection and low probability of false detection. Further, the trained algorithm predictions are well calibrated, allowing reliable probabilistic classification. The utility of this two-step procedure is illustrated by generating spatial frequency maps of automatically identified precipitation clusters that are stratified by using various reflectivity and probabilistic prediction thresholds. These results suggest that machine learning can add value by limiting the amount of false-positive (non-MCS) samples that are not removed by segmentation alone.

Differences among three types of tropical deep convective clusters observed from A-Train satellites

Deep convective clusters (DCCs) constitute a complex regime with a variety of types of cloud parameterization in multiple global climate models (GCMs). This study develops a method to identify tropical DCCs and presents regional differences in cloud occurrence, surface precipitation and a vertical survey of ice water content among separated DCCs, connected DCCs and mesoscale convective systems (MCSs) determined by collocating data from MODIS, AMSR-E, CPR and CALIOP instruments on board A-Train satellites. The results reveal that separated DCCs and MCSs occur frequently over East Asia, while connected DCCs are more common over the warm pool of the West Pacific in June-August and over South America in December-February. Higher surface convective precipitation rates occur more frequently in MCSs than in separated and connected DCCs in non-monsoon areas. However, connected DCCs have a large ice water content (IWC) at 10–15 km similar to that of MCSs, and these clusters are more intense than those in separated DCCs. Remarkably large anvil-stratiform clouds connected with multiple deep convective cores in connected DCCs can be easily confused with MCSs if the cloud top brightness temperature in the horizontal view is the only parameter being considered. Combined observational data of surface precipitation of DCCs will be helpful for distinguishing connected DCCs and MCSs.

Convectively Driven Tropopause‐Level Cooling and Its Influences on Stratospheric Moisture

AbstractCharacteristics of the tropopause‐level cooling associated with tropical deep convection are examined using CloudSat radar and Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) GPS radio occultation measurements. Extreme deep convection is sampled based on the cloud top height (>17 km) from CloudSat, and colocated temperature profiles from COSMIC are composited around the deep convection. Response of moisture to the tropopause‐level cooling is also examined in the upper troposphere and lower stratosphere using microwave limb sounder measurements. The composite temperature shows an anomalous warming in the troposphere and a significant cooling near the tropopause (at 16–19 km) when deep convection occurs over the western Pacific, particularly during periods with active Madden‐Julian Oscillation (MJO). The composite of the tropopause cooling has a large horizontal scale (~6,000 km in longitude) with minimum temperature anomaly of ~ −2 K, and it lasts more than 2 weeks with support of mesoscale convective clusters embedded within the envelope of the MJO. The water vapor anomalies show strong correlation with the temperature anomalies (i.e., dry anomaly in the cold anomaly), showing that the convectively driven tropopause cooling actively dehydrate the lower stratosphere in the western Pacific region. The moisture is also affected by anomalous Matsuno‐Gill‐type circulation associated with the cold anomaly, in which dry air spreads over a wide range in the tropical tropopause layer (TTL). These results suggest that convectively driven tropopause cooling and associated transient circulation play an important role in the large‐scale dehydration process in the TTL.

Wind–Flux Feedbacks and Convective Organization during the November 2011 MJO Event in a High-Resolution Model

The November 2011 Madden–Julian oscillation (MJO) event during the Dynamics of the MJO (DYNAMO) field campaign is simulated with the Regional Atmospheric Modeling System (RAMS) cloud-resolving model to examine the relationship between precipitation and surface latent heat flux (LHFLX) for deep convective clusters within the MJO and to discern the importance of surface LHFLX for organizing MJO convection. First, a simulation similar in size to the DYNAMO northern sounding array was run with interactive surface fluxes. Composites for precipitation, surface LHFLX, wind speed, wind vectors, and near-surface specific humidity are described for various-sized convective clusters during different MJO regimes. The precipitation–LHFLX relationship generally evolves as follows for an individual cluster. About 2 h before cluster identification, the maximum LHFLX occurs upwind of maximum precipitation. As cluster identification time is approached, LHFLX and precipitation maxima become coincident. At and after the cluster is identified, maximum LHFLXs move downwind of the precipitation maximum with a local minimum in LHFLXs behind the precipitation maximum. Sensitivity simulations with spatially homogenized LHFLXs were then run to determine the impacts of local LHFLX feedbacks on convective organization. Using area-averaged convective versus stratiform precipitation fraction and a simple convective aggregation index to quantify organization, no systematic difference in convective organization was detected between the control and sensitivity simulations, suggesting that local LHFLX variability is not important to convective organization in this model. Implications of these results are discussed.

The environment of aggregated deep convection

AbstractIn this study, the environment of aggregated deep convection is investigated using a vector vorticity equation cloud‐resolving model (VVM). Idealized experiments are performed under various environmental moisture with or without imposed vertical wind shear. Convective aggregation is then evaluated through diagnosing the 3‐D size of an individual cloud from the model output using a six‐connected segmentation method. The aggregated convection is recognized by a distinct mode with larger size in the cloud‐size distribution. The results suggest that aggregated convection tends to develop when column relative humidity (CRH) is larger than 80% (67%) in nonshear (shear) cases. In addition, the degree of aggregation further increases with the increase of CRH. This aggregation process may be caused by an increasing probability of multicellular cloud structure under a moister environment. The results also suggest that there are at least five convective cores of such system. Analyses of precipitation distribution suggest that the most extreme instantaneous grid point precipitation mainly occurs within the largest convective clusters.

Comparison of simulated and observed convective gravity waves

AbstractGravity waves (GWs) from convection have horizontal wavelengths typically shorter than 100 km. Resolving these waves in state‐of‐the‐art atmospheric models still remains challenging. Also, their time‐dependent excitation process cannot be represented by a common GW drag parametrization with static launch distribution. Thus, the aim of this paper is to investigate the excitation and three‐dimensional propagation of GWs forced by deep convection in the troposphere and estimate their influence on the middle atmosphere. For that purpose, the GW ray tracer Gravity‐wave Regional Or Global Ray Tracer (GROGRAT) has been coupled to the Yonsei convective GW source model. The remaining free model parameters have been constrained by measurements. This work led to a coupled convective GW model representing convective GWs forced from small cells of deep convection up to large‐scale convective clusters. In order to compare our simulation results with observed global distributions of momentum flux, limitations of satellite instruments were taken into account: The observational filter of a limb‐viewing satellite instrument restricts measurements of GWs to waves with horizontal wavelengths longer than 100 km. Convective GWs, however, often have shorter wavelengths. This effect is taken into account when comparing simulated and observable GW spectra. We find good overall agreement between simulated and observed GW global distributions, if superimposed with a nonorographic background spectrum for higher‐latitude coverage. Our findings indicate that parts of the convective GW spectrum can indeed be observed by limb‐sounding satellites.

Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences

The anvil productivities of tropical deep convection are investigated and compared among eight climatological regions using 4 yr of collocated and combined CloudSat and CALIPSO data. For all regions, the convective clusters become deeper while they become wider and tend to be composed of multiple rainy cores. Two strong detrainment layers from deep convection are observed at 6–8 km and above 10 km, which is consistent with the trimodal characteristics of tropical convection that are associated with different divergence, cloud detrainment, and fractional cloudiness. The anvil productivity of tropical deep convection depends on the convection scale, convective life stage or intensity, and large-scale environment. Anvil ice mass ratio related to the whole cluster starts to level off or decrease when the cluster effective scales Weff (the dimension of an equivalent rectangular with the same volume and height as the original cluster) increase to about 200 km wide, while the ratios of anvil scale and volume keep increasing from 0.4 to 0.6 and 0.15 to 0.4, respectively. The anvil clouds above 12 km can count for more than 20% of cluster volume, or more than 50% of total anvil volume, but they only count less than about 2% of total ice mass in the cluster. Anvil production of younger convection of the same Weff is higher than that of the decaying convection. The regional difference in the composite anvil productivities of tropical convective clusters sorted by Weff is subtle, while the occurrence frequencies of different scales of convection vary substantially.

Characteristics and environmental conditions of quasi‐stationary convective clusters during the warm season in Japan

The characteristics and environmental properties of warm‐season quasi‐stationary convective clusters (QSCCs) in Japan were statistically investigated using operational weather radar and upper‐air sounding data from May to October during 2005–2012. The characteristics of the environmental conditions for the development of QSCCs were described through a comparison with those for no‐rain cases. We identified 4133 QSCCs over the Japanese major islands. By compiling numerous QSCC samples, the horizontal scales of QSCCs with a circular shape are about 20 km on average with a maximum of 72 km, indicating that warm‐season QSCCs in Japan are meso‐β‐scale phenomena. The analyses of the environmental conditions for the QSCC and no‐rain cases showed that the amount of moisture in the lower layer controls the stability condition for the development of the QSCCs, and that the magnitudes of the wind shear and the helicity in the lower troposphere distinguish the kinematic environments for the development of the QSCCs. An increase in the middle‐level moisture leads to a larger amount of precipitable water vapour in the QSCC environments, suggesting that atmospheric moistening before the development stage of convection plays an important role in the development of the QSCCs. Additionally, the precipitation intensity has a higher correlation with the convective instability, whereas the precipitation area correlates with the shear intensity. A comparison between slower‐ and faster‐moving CCs indicated that the precipitation intensity of the slower‐moving CCs is stronger. This feature is related to a higher convective instability for the slower‐moving ones.

Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences

Tropical deep convection’s intensity and their anvil productivity are investigated and compared among 8 climatological regions with 4-year collocated and combined CloudSat and CALIPSO data. For all 8 regions, the convective clusters become deeper, while they become wider and tend to be composed of multiple rainy cores. Among 8 regions, convective clusters at the same scale over EP and AT tend to have less but wider rainy cores than those at WP, MA and IO, while those over AF, IO, MA and AM tend to have higher cloud top than those over ocean. For convective clusters less than 300 km wide over AF and MA, the rainy cores pump more ice mass of larger particles to the mid- and upper troposphere in strong updrafts.The total anvil clouds detrained from convection counts for 0.4 to 0.8 of the cluster horizontal scale, 0.2 to 0.6 of the cluster cross section volume, and 0.05 to 0.20 of the cluster ice mass, depending on the cluster scales and height. There are two main detrainment layers. When the convective clusters is less than about 100 km, the anvil clouds are mainly detrained at about 6-8 km with a spreading ratio (ratio of maximum cluster width to convection rainy core width) less than 1.5. When convective clusters becomes 100 km or wider, it reaches the dominate detrainment layer at about 12 km, the detrainment index increase from 2 to more 6. Among 8 regions, convection clusters in MA produce the most anvil volume fraction. The more the ice mass is pumped upward in the anvil clouds till clusters are about 500 km wider. Nevertheless, the anvil ice mass pumped above 15 km is less than 0.1% of the total ice mass in the convective cluster.

A Role of Environmental Shear on the Organization Mode of Quasi-Stationary Convective Clusters during the Warm Season in Japan

A Role of Environmental Shear on the Organization Mode of Quasi-Stationary Convective Clusters during the Warm Season in Japan

The Evolution of Dropsonde-Derived Kinematic and Thermodynamic Structures in Developing and Nondeveloping Atlantic Tropical Convective Systems

Abstract The processes by which tropical cyclones evolve from loosely organized convective clusters are still poorly understood. Because of the data-sparse regions in which tropical cyclones form, observational studies of tropical cyclogenesis are often more difficult than studies of land-based convective phenomena. As a result, many studies of tropical cyclogenesis are limited to either a few case studies or rely on simulations. The 2010 PREDICT and GRIP field experiments have provided a new opportunity to gain insight into these processes using unusually dense observations in both time and space. The present study aims at using these recent datasets to perform a detailed analysis of the three-dimensional evolution of both kinematic and thermodynamic fields in both developing and nondeveloping tropical convective systems in the western Atlantic. Five tropical convective systems are analyzed in this study: two nondeveloping, two developing, and one dissipating system. Although the analysis necessarily includes only a very limited number of cases, the results suggest that the convectively active nondeveloping systems and developing systems examined here have similar kinematic structures. The most notable difference is the distribution of humidity and the impacts this distribution has on the thermodynamics of the system. Displacements between the upper-level warm anomaly, responsible for midlevel vorticity generation, and the midlevel vorticity maximum are observed in both developing and nondeveloping cases. In the nondeveloping case the displacement appears to be caused by mid- and upper-level dry air. Further work is needed to fully understand the cause of these displacements and their relation to tropical cyclogenesis.

Characteristics of tropopause‐penetrating convection determined by TRMM and COSMIC GPS radio occultation measurements

AbstractDistribution and influence of convection in the upper troposphere and lower stratosphere have been investigated case by case or on regional to global scale. However, previous studies were limited by using proxies for convection or the bias of the tropopause data. Here the tropopause‐penetrating convection is investigated based on the sole use of observational products from Tropical Rainfall Measuring Mission (TRMM) precipitation radar data and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). The result shows that the frequency of precipitation‐top heights above the monthly mean tropopause in the tropics is reduced logarithmically if the cold‐point tropopause is adopted instead of the lapse‐rate tropopause. Using the collocated COSMIC and precipitation radar observations, the tropopause‐penetrating convection, i.e., the convection with the precipitation‐top height above the lapse‐rate tropopause, can be found over the summer monsoon regions and some continental regions. The averaged relative precipitation‐top heights of tropopause‐penetrating convective clusters are about 0.2–0.5 km without significant land‐ocean difference, while equivalent radii of clusters are 2.7–3.5 km over land and 0.2–0.5 km larger than those over ocean. These areal and vertical extents are smaller than those reported by previous studies. Furthermore, the collocated temperature profiles show that the tropopause‐penetrating convection generates warming in the upper troposphere and cooling near the lapse‐rate tropopause and in the lower stratosphere. Moreover, the tropopause‐penetrating convection leads to a rapid (within 20 min) lift of the lapse‐rate tropopause by the adiabatic lofting within the convection (within a 10 km radius).

Tropical Cyclone Mekkhala’s (2008) Formation over the South China Sea: Mesoscale, Synoptic-Scale, and Large-Scale Contributions

Abstract Tropical cyclone formation close to the coastline of the Asian continent presents a significant threat to heavily populated coastal countries. A case study of Tropical Storm Mekkhala (2008) that developed off the coast of Vietnam is presented using the high-resolution analyses of the European Centre for Medium-Range Weather Forecasts/Year of Tropical Convection and multiple satellite observations. The authors have analyzed contributions to the formation from large-scale intraseasonal variability, synoptic perturbations, and mesoscale convective systems (MCSs). Within a large-scale westerly wind burst (WWB) associated with the Madden–Julian oscillation (MJO), synoptic perturbations generated by two preceding tropical cyclones initiated the pre-Mekkhala low-level vortex over the Philippine Sea. Typhoon Hagupit produced a synoptic-scale wave train that contributed to the development of Jangmi, but likely suppressed the Mekkhala formation. The low-level vortex of the pre-Mekkhala disturbance was then initiated in a confluent zone between northeasterlies in advance of Typhoon Jangmi and the WWB. A key contribution to the development of Mekkhala was from diurnally varying MCSs that were invigorated in the WWB. The oceanic MCSs, which typically develop off the west coast of the Philippines in the morning and dissipate in the afternoon, were prolonged beyond the regular diurnal cycle. A combination with the MCSs developing downstream of the Philippines led to the critical structure change of the oceanic convective cluster, which implies the critical role of mesoscale processes. Therefore, the diurnally varying mesoscale convective processes over both the ocean and land are shown to have an essential role in the formation of Mekkhala in conjunction with large-scale MJO and the synoptic-scale TC influences.

Impact of South China Sea Cold Surges and Typhoon Peipah on Initiating Cyclone Sidr in the Bay of Bengal

In the present study, an attempt was made to understand the role of South China Sea (SCS) convection associated with northerly cold surges and Typhoon Peipah in initiating Cyclone Sidr in the Bay of Bengal (BoB). The variation of air sea fluxes during the entire history of Cyclone Sidr tracking before its landfall over Bangladesh was also studied. The presence of cold surges in the north SCS associated with heavy rainfall episodes has been noticed at the southern Gulf of Tonkin coast prior to the formation of Typhoon Peipah. Subsequently, these surges migrated south, which resulted in intensification of a deep convection on reaching the Vietnamese coast. During the same period in the western Pacific, Typhoon Peipah developed, propagating in the westward direction and entering the SCS. Analysis of geostationary water vapour images, mean sea level pressure, and surface wind maps clearly depicted the transport of convective cloud clusters, moisture, and westward momentum from Typhoon Peipah to the deep convection cells over the SCS. Consequently, the existing deep convection over the Vietnamese coast resulted in a westward direction and entered the Gulf of Thailand and Andaman Sea. The availability of higher latent heat fluxes, warmer sea surface temperatures, and suitable atmospheric conditions over this region favoured the formation of a tropical depression in the Andaman Sea. This depression further intensified in the southeast BoB, resulting in the formation of Cyclone Sidr. NCEP/NCAR wind fields and air-sea fluxes revealed left asymmetry surface winds and higher latent heat flux on the left side of the track during the intensification phase of Sidr.

Adjoint Sensitivity and Predictability of Tropical Cyclogenesis

Abstract The sensitivity of tropical cyclogenesis and subsequent intensification is explored by applying small perturbations to the initial state in the presence of organized mesoscale convection and synoptic-scale forcing using the adjoint and tangent linear models for the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). The forward, adjoint, and tangent linear models are used to compare and contrast predictability characteristics for the disturbance that became Typhoon Nuri and a nondeveloping organized convective cluster in the western Pacific during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Tropical Cyclone Structure-2008 (TCS-08) experiments. The adjoint diagnostics indicate that the intensity (e.g., maximum surface wind speed, minimum surface pressure) of a tropical disturbance is very sensitive to perturbations in the moisture and temperature fields and to a lesser degree the wind fields. The highest-resolution adjoint simulations (grid increment of 13 km) indicate that the most efficient intensification is through moistening in the lower and middle levels and heating in banded regions that are coincident with vorticity maxima in the initial state. Optimal adjoint perturbations exhibit rapid growth for the Nuri case and only modest growth for the nondeveloping system. The adjoint results suggest that Nuri was near the threshold for development, indicative of low predictability. The low-level sensitivity maximum and tendency for optimal perturbation growth to extend vertically through the troposphere are consistent with a “bottom up” development process of TC genesis, although a secondary midlevel sensitivity maximum is present as well. Growth originates at small scales and projects onto the scale of the vortex, a manifestation of perturbations that project onto organized convection embedded in regions of cyclonic vorticity.

A Clustering Approach to Compare Cloud Model Simulations to Satellite Observations

Abstract Cloud-resolving models (CRMs) offer an important pathway to interpret satellite observations of microphysical properties of storms. High-frequency microwave brightness temperatures (Tbs) respond to precipitating-sized ice particles and can therefore be compared with simulated Tbs at the same frequencies. By clustering the Tb vectors at these frequencies, the scene can be classified into distinct microphysical regimes (in other words, cloud types). A convective storm over the Amazon observed by the Tropical Rainfall Measuring Mission (TRMM) is simulated using the Regional Atmospheric Modeling System (RAMS) in a semi-ideal setting, and four regimes are defined within the scene using cluster analysis: the “clear sky/thin cirrus” cluster, the “cloudy” cluster, the “stratiform anvil” cluster, and the “convective” cluster. Cluster-by-cluster comparisons between the observations and the simulations disclose biases in the model that are consistent with an overproduction of supercooled water and an excess of large hail particles. While other problems cannot be completely ruled out, the method does provide some guidance to assess microphysical fidelity within each cluster or cloud type. Guided by the apparent model/observational discrepancies in the convective cloud cluster, the hail size parameter was adjusted in order to produce a greater number of smaller hail particles consistent with the observations. While the work cannot define microphysical errors in an unambiguously fashion, the cluster analysis is seen as useful to isolate individual microphysical inconsistencies that can then be addressed within each cluster of cloud type.

An Orography-Associated Extreme Rainfall Event during TiMREX: Initiation, Storm Evolution, and Maintenance

Abstract This study investigates a long-duration mesoscale system with extremely heavy rainfall over southwest Taiwan during the Terrain-influenced Monsoon Rainfall Experiment (TiMREX). This mesoscale convective system develops offshore and stays quasi-stationary over the upstream ocean and southwest coast of Taiwan. New convection keeps developing upstream offshore but decays or dies after moving into the island, dropping the heaviest rain over the upstream ocean and coastal regions. Warm, moist, unstable conditions and a low-level jet (LLJ) are found only over the upstream ocean, while the island of Taiwan is under the control of a weak cold pool. The LLJ is lifted upward at the boundary between the cold pool and LLJ. Most convective clusters supporting the long-lived rainy mesoscale system are initiated and develop along that boundary. The initiation and maintenance is thought to be a “back-building–quasi-stationary” process. The cold pool forms from previous persistent precipitation with a temperature depression of 2°–4°C in the lowest 500 m, while the high terrain in Taiwan is thought to trap the cold pool from spreading or moving. As a result, the orography of Taiwan is “extended” to the upstream ocean and plays an indirect effect on the long-duration mesoscale system.