Warm-season Mesoscale Convective System Research Articles

Trends in Warm Season Mesoscale Convective Systems Over Asia in 2001–2020

AbstractMesoscale convective systems (MCSs) frequently occur over Asia during the warm season, often producing intense precipitation with associated socioeconomic impacts. Here we reveal significant trends in MCS occurrence frequency and related precipitation in Asia during the warm season (March–September) in 2001–2020, using a tracking method that combines cloud and precipitation criteria with high‐resolution satellite data from the Global Precipitation Measurement mission. To examine whether there are differences between MCSs of different scales, both meso‐α scales (MαCSs) and meso‐β scales (MβCSs), with horizontal scales of 200–2,000 km and 20–200 km, are tracked. The distribution pattern of frequency and related precipitation of both MαCSs and MβCSs are quite similar and manifest positive trends over East Asia (EA) and Northeast Asia, and negative trend over Southeast Asia (SEA). The MCS precipitation trend contributes significantly to total precipitation trend, with MαCSs contributing the most. Our analysis indicates the trend in lower‐tropospheric water vapor flux convergence has a similar spatial pattern to the MCS frequency and related precipitation trend. Based on an atmospheric moisture flux decomposition analysis, the water vapor flux convergence trend can largely be explained by the change in horizontal wind convergence, while the specific humidity trend driven largely by temperature change plays a minor role. The trend in wind convergence in EA and SEA is possibly related to the evident trend in the lower‐tropospheric anticyclone over the western North Pacific and SEA, which might be due to the relatively stronger warming in the Indian Ocean during the past two decades.

Characteristics of Warm-season Mesoscale Convective Systems over the Yangtze-Huaihe River Basin (YHR)––comparison between radar and satellite

Characteristics of Warm-season Mesoscale Convective Systems over the Yangtze-Huaihe River Basin (YHR)––comparison between radar and satellite

Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

Land-atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture-precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture-precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture-precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

Warm-season mesoscale convective systems over eastern China: convection-permitting climate model simulation and observation

Warm-season mesoscale convective systems over eastern China: convection-permitting climate model simulation and observation

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the United States

AbstractA process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the United States. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation features at 12-, 25-, and 50-km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency, and intensity are found to be consistently underestimated in the central United States, particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while the MCS precipitation area is too large and its intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during the daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

Elucidating the Life Cycle of Warm-Season Mesoscale Convective Systems in Eastern China from the Himawari-8 Geostationary Satellite

The life cycle of mesoscale convective systems (MCSs) in eastern China is yet to be fully understood, mainly due to the lack of observations of high spatio-temporal resolution and objective methods. Here, we quantitatively analyze the properties of warm-season (from April to September of 2016) MCSs during their lifetimes using the Himawari-8 geostationary satellite, combined with ground-based radars and gauge measurements. Generally, the occurrence of satellite derived MCSs has a noon peak over the land and an early morning peak over the ocean, which is several hours earlier than the precipitation peak. The developing and dissipative stages are significantly longer as total durations of MCSs increase. Aided by three-dimensional radar mosaics, we find the fraction of convective cores over northern China is much lower when compared with those in central United States, indicating that the precipitation produced by broad stratiform clouds may be more important for northern China. When there exists a large amount of stratiform precipitation, it releases a large amount of latent heat and promotes the large-scale circulations, which favors the maintenance of MCSs. These findings provide quantitative results about the life cycle of warm-season MCSs in eastern China based on multiple data sources and large numbers of samples.

Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

AbstractIn this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

Synoptic Control of Convective Rainfall Rates and Cloud-to-Ground Lightning Frequencies in Warm-Season Mesoscale Convective Systems over North China

Abstract This study examines whether environmental conditions can control convective rainfall rates and cloud-to-ground (CG) lightning frequencies in mesoscale convective systems (MCSs) over north China (NC). A total of 60 identified MCSs over NC during June–August of 2008–13 were classified into 4 categories based on their high/low convective rainfall rates (HR/LR) and high/low CG lightning frequencies (HL/LL) (i.e., HRHL, HRLL, LRHL, and LRLL MCSs). MCSs with HR (HL) occurred most frequently in July (August), while those with LR or LL occurred most frequently in June; they followed closely seasonal changes. All MCSs were apt to form during afternoon hours. HRLL MCSs also formed during evening hours while HRHL MCSs could occur at any time of a day. A composite analysis of environmental conditions shows obvious differences and similarities among the HRHL, HRLL, and LRLL categories, while the LRHL MCSs exhibited little differences from the climatological mean because of its small sample size. Both the HRHL and HRLL MCSs occurred in the presence of upper-level anomalous divergence, a midlevel trough, and the lower-tropospheric southwesterly transport of tropical moist air. In contrast, LRLL MCSs took place as a result of daytime heating over mountainous regions, with little midlevel forcing over NC. The HRHL, HRLL, LRHL, and LRLL categories exhibited orders of the highest-to-smallest convective available potential energy and precipitable water but the smallest-to-largest convective inhibition and lifted indices. It is concluded that environmental conditions determine to some extent convective rainfall rates and CG lightning activity, although some other processes (e.g., cloud microphysics) also play certain roles, especially in CG lightning production.

Four-Dimensional Assimilation of Multitime Wind Profiles over a Single Station and Numerical Simulation of a Mesoscale Convective System Observed during IHOP_2002

Abstract This study examines the impact of assimilating multitime wind profiles over a single station on the numerical simulation of a warm season mesoscale convective system over the region from the Kansas and Oklahoma border to the Texas Panhandle, observed 12–13 June 2002 during the International H2O Project (IHOP_2002). Wind profile observations, obtained from Goddard Lidar Observatory for Winds (GLOW) are assimilated into an advanced research version of the Weather Research and Forecasting (WRF) model using its four-dimensional variational data assimilation (4DVAR) system. Results indicate that the assimilation of high temporal and vertical resolution GLOW wind profiles has a significant influence on the numerical simulation of the convective initiation and evolution. Besides the wind fields, the structure of the moisture fields associated with the convective system is also improved. Data assimilation has also resulted in a more accurate prediction of the locations and timing of the convection initiations; as a consequence, the skill of quantitative precipitation forecasting is enhanced greatly. The positive impact of 4DVAR assimilation of multitime wind profiles over a single station on the mesoscale prediction in this study presents a successful procession of the traditional technique in time to space conversion. However, when the data from conventional networks are assimilated into the model with GLOW wind profiles, the data impact is not compatible with that from the assimilation of GLOW wind profiles only, implying the need for a high temporal and spatial resolution wind profile network in order to achieve reasonable mesoscale analysis and forecasting.

A warm season climatology of mesoscale convective systems in the Mediterranean basin using satellite data

A 3-year climatology of isolated warm season mesoscale convective systems (MCSs) was built for the Mediterranean basin using Meteosat Second Generation infrared imagery and an objective identification and tracking algorithm. A dataset of 4,718 MCS trajectories was constructed for the warm season of the period 2005–2007, which in turn was split into two subsets (deep and weak convective) according to the intensity of convection using a discriminant parameter in the MCS properties. Several parameters related to geographical, temporal, radiative, morphological, and motion related properties were calculated for each MCS. The majority of MCSs are mainly continental and strongly correlated with orography showing an increased formation from April to June when maximum is found. Initiation and dissipation time revealed a distinct diurnal cycle having a strong correlation with the typical diurnal heating cycle of the atmosphere. On average, a typical isolated MCS in the Mediterranean basin initiates between 14:00 and 17:00 local solar time, tends to be small with elongated shape, short-lived, usually moving toward northeast to southeast with a mean velocity of 36 km/h. When comparing the two MCS subsets, some notable differences were revealed. Weak convective MCSs initiate earlier, move faster, travel longer, tend to reach slightly smaller sizes, are more linear, present higher cloud top temperatures, and have lower fractions of convective cloud type areas than deep convective systems.

Influence of Initial Conditions on the WRF–ARW Model QPF Response to Physical Parameterization Changes

Abstract To assist in optimizing a mixed-physics ensemble for warm season mesoscale convective system rainfall forecasting, the impact of various physical schemes as well as their interactions on rainfall when different initializations were used has been investigated. For this purpose, high-resolution Weather Research and Forecasting (WRF) model simulations of eight International H2O Project events were performed. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer (PBL) schemes were used. All cases were initialized with both Local Analyses and Prediction System (LAPS) “hot” start analyses and 40-km Eta Model analyses. To evaluate the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall under the two different initial conditions, the factor separation method was used. The sensitivity to the use of various physical schemes and their interactions was found to be dependent on the initialization dataset. Runs initialized with Eta analyses appeared to be influenced by the use of the Betts–Miller–Janjić scheme in that model’s assimilation system, which tended to reduce the WRF’s sensitivity to changes in the microphysical scheme compared with that present when LAPS analyses were used for initialization. In addition, differences in initialized thermodynamics resulted in changes in sensitivity to PBL and convective schemes. With both initialization datasets, the greatest sensitivity to the simulated rain rate was due to changes in the convective scheme. However, for rain volume, substantial sensitivity was present due to changes in both the physical parameterizations and the initial datasets.

Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts

Abstract This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-yr period on a contiguous U.S. domain. Specifically, the quantitative precipitation forecast (QPF)–probability relationship found recently by Gallus and Segal in 10-km grid spacing model runs for 20 warm season mesoscale convective systems is tested over this much larger temporal and spatial dataset. A 1-yr period was used to investigate the QPF–probability relationship, and the predictive capability of this relationship was then tested on an independent 1-yr sample of data. The same relationship of a substantial increase in the likelihood of observed rainfall exceeding a specified threshold in areas where model runs forecasted higher rainfall amounts is found to hold over all seasons. Rainfall is less likely to occur in those areas where the models indicate none than it is elsewhere in the domain; it is more likely to occur in those regions where rainfall is predicted, especially where the predicted rainfall amounts are largest. The probability of rainfall forecasts based on this relationship are found to possess skill as measured by relative operating characteristic curves, reliability diagrams, and Brier skill scores. Skillful forecasts from the technique exist throughout the 48-h periods for which Eta and AVN output were available. The results suggest that this forecasting tool might assist forecasters throughout the year in a wide variety of weather events and not only in areas of difficult-to-forecast convective systems.

Does Increased Predicted Warm-Season Rainfall Indicate Enhanced Likelihood of Rain Occurrence?

Abstract The likelihood of simulated rainfall above a specified threshold being observed is evaluated as a function of the amounts predicted by two mesoscale models. Evaluations are performed for 20 warm-season mesoscale convective system events over the upper Midwest of the United States. Simulations were performed using 10-km versions of the National Centers for Environmental Prediction Eta Model and the Weather Research and Forecasting (WRF) model, with two different convective parameterizations tested in both models. It was found that, despite large differences in the biases of these different models and configurations, a robust relationship was present whereby a substantial increase in the likelihood of observed rainfall exceeding a specified threshold occurred in areas where the model runs forecast higher rainfall amounts. Rainfall was found to be less likely to occur in those areas where the models indicated no rainfall than it was elsewhere in the domain; it was more likely to occur in those regions where rainfall was predicted, especially where the predicted rainfall amounts were largest. The probability of rainfall relative-operating-characteristic and relative-operating-level curves showed that probabilistic forecasts determined from quantitative precipitation forecast values had skill comparable to the skill obtained using more traditional methods in which probabilities are based on the fraction of ensemble members experiencing rainfall. When the entire sample of cases was broken into training and test sets, the probability forecasts of the test sets evidenced good reliability. The relationship noted should provide some additional guidelines to operational forecasters. The results imply that the tested models are better able to indicate the regions where atmospheric processes are most favorable for convective rainfall (where the models generate enhanced amounts) than they are able to predict accurately the rainfall amounts that will be observed.

Mesoscale Convective Systems in the Southeast United States during 1994–95: A Survey

A preliminary survey of mesoscale convective systems (MCSs) in the southeastern United States is presented. MCSs are identified and characterized by means of high-resolution, digital, composite radar reflectivity data. Surveys of this kind are needed to give forecasters better guidance in their real-time assessment of MCS evolution, severe weather potential, and quantitative precipitation. The average lifetime and maximum length of the nearly 400 MCSs included in this survey are 9 h and 350 km, respectively. MCSs are more common in the summer months, when small and short-lived MCSs dominate. In winter larger and longer-lived systems occur more frequently. Because cold-season MCSs, which are about half as numerous as warm-season MCSs, are larger in size and duration, the MCS probability at any location is about constant throughout the year. In summer MCSs occur more commonly in the afternoon, approximately in phase with thunderstorm activity, but the amplitude of the diurnal cycle is small compared to that of observed thunderstorms. Some characteristic echo patterns are discussed.