Mesoscale Convective Research Articles

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

AbstractAccurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model (E3SM) simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with and without superparameterization (SP) are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, the superparameterized model (SP‐E3SM) better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large‐scale environments, featuring enhanced atmospheric low‐level moisture and larger moisture transport to the central US relative to E3SM. However, SP‐E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large‐scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large‐scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

The Role of Mesoscale Convective Systems in Precipitation in the Tibetan Plateau Region

AbstractMesoscale convective systems (MCSs) have been identified as an important source of precipitation in the Tibetan Plateau (TP) region. However, the characteristics and structure of MCS‐induced precipitation are not well understood in this location. Infrared (IR) satellite imagery has been used for MCS tracking, but cirrus clouds or cold surfaces can lead to false MCS classification over mountain regions. Here, we combine brightness temperatures from IR imagery with satellite precipitation estimates from GPM IMERG and track MCSs over the TP, at the boundary of the TP (TPB), and in the surrounding lower‐elevation plains (LE), between 2000 and 2019. In most parts of LE and TPB, MCSs produced 50%–80% of the total summer precipitation (60%–90% of summer heavy precipitation), whereas MCSs over the TP account for below 10% of the total summer precipitation (10%–30% of summer heavy precipitation). Our results also show that MCSs that produce the largest amounts of heavy precipitation are characterized by longevity and large extents rather than by high intensities. These are mainly located in the populous areas south and east of the TP. A tracking of meso‐β convective systems over the TP shows that small‐scale convection makes a large contribution to total and heavy precipitation. This suggests that more localized convective systems are important for the regional water cycle over the higher terrain and highlights the importance of convective‐scale modeling to improve our understanding of precipitation dynamics in the TP region.

Soil Moisture Influence on the Incidence of Summer Mesoscale Convective Systems in the U.S. Great Plains

Abstract Mesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004–16. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e., only non-squall-line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ∼100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located southwest (northeast) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

AbstractMesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

Spatiotemporal variation of mesoscale convective system type persistent elongated convective system (PECS) in Indonesia

Research on Mesoscale Convective Systems (MCS) in Indonesia has been studied to identify the characteristics and distribution of MCS. Persistent Elongated Convective System (PECS) is one of the MCS types that can cause extreme weather. However, identifying the spatial and temporal variations of PECS in Indonesia has not been studied further. This study examines the Persistent Elongated Convective System (PECS) in Maritime Continent from 2010-2014. MERG Dataset with brightness temperature is used to identify PECS and input Grab ‘Em Tag ‘Em Graph ‘Em (GTG) tracking algorithm to gain a better understanding of spatiotemporal variation in Indonesia. Flood data from BNPB in Indonesia is used to find out the correlation between flood and PECS events in Indonesia. PECS events in 2010-2014 are 5574 events, which the transitional period (MAM and SON) has the most PECS events and longest duration of life. The PECS spread in the early morning on land and sea, while on day and nighttime, it is concentrated on land for the area of Java, Papua, and Southern Kalimantan. Java and Papua have the largest concentrated PECS events. The life phase of the PECS has two peaks or semidiurnal cycles, in the morning and nighttime. There are differences in peak times for each phase of the PECS on land and sea. In Indonesia, PECS has the smallest average maximum area than in the USA and China but has the longest duration and largest eccentricity. Based on flood data from BNPB, during 2010-2014, Java has the most flood. According to flood data and PECS events in Java, there is 6.72% of flood coincided with PECS events during the period.

Properties of Mesoscale Convective Systems Throughout Their Lifetimes Using IMERG, GPM, WWLLN, and a Simplified Tracking Algorithm

AbstractMesoscale convective systems (MCSs) occur frequently over the tropics and mid‐latitudes and have a large impact on the local precipitation amounts as well as large‐scale circulation through their modulation of the vertical diabatic heating profile. To fully understand and quantify these effects, MCSs must be studied throughout their lifetimes at both mid‐ and tropical latitudes, over both land and ocean. This can be accomplished by tracking the storm using a global scale data set of precipitation and using this information to composite collocated active sensor measurements to produce a detailed analysis of storm properties along the lifetime of the MCS. To do this, we utilize precipitation features (PFs) produced using observations from the Global Precipitation Measurement (GPM) mission's core satellite and from Integrated Multi‐satellitE Retrievals for GPM data by grouping contiguous raining pixels in both data sets. We propose a simplified tracking algorithm to track systems throughout their lifetimes. Lightning data from the World Wide Lightning Location Network are collocated to these tracks along with GPM PFs. These are then composited relative to the time step along the track that has the greatest number of lightning flashes, which is used as a proxy for MCSs with lightning reaching the maximum convective intensity. We then examine various radar variables for tropical and mid‐latitude systems of varying lifetimes over both land and ocean in order to determine the differences and similarities between these types of systems.

On the diurnal cycle of rainfall and convection over Lake Victoria and its catchment. Part 1: Rainfall and Mesoscale Convective Systems

AbstractThis article examines the diurnal cycle of lake-effect rains over Lake Victoria and of rainfall in the surrounding catchment. The analysis focuses on four months, which represent the two wet seasons (April and November) and the two dry seasons (February and July). Lake-effect rains are strongest in April, weakest in July. In all cases there is a nocturnal rainfall maximum over the lake and a daytime maximum over the catchment, with the transition between rainfall over the lake and over the catchment occurring between 1200 and 1500 LST. During the night the surrounding catchment is mostly dry. Conversely, little to no rain falls over the lake during the afternoon and early evening. In most cases the maximum over the lake occurs at either 0600 or 0900 LST and the maximum over the catchment occurs around 1500 to 1800 LST. The diurnal cycle of Mesoscale Convective Systems (MCSs) parallels that of over-lake rainfall. MCS initiation generally begins over the catchment around 1500 LST and increases at 1800 LST. MCS initiation over the lake begins around 0300 LST and continues until 1200 LST. While some MCSs originate over the highlands to the east of the lake, most originate in situ over the lake. Maximum MCS activity over the lake occurs at 0600 LST and is associated with the systems that initiate in situ.

Sensitivity of Upper Atmosphere to Different Characteristics of Flow Bursts in the Auroral Zone.

Meso‐scale plasma convection and particle precipitation could be significant momentum and energy sources for the ionosphere‐thermosphere (I‐T) system. Following our previous work on the I‐T response to a typical midnight flow burst, flow bursts with different characteristics (lifetime, size, and speed) have been examined systematically with Global Ionosphere‐Thermosphere Model (GITM) simulations in this study. Differences between simulations with and without additional flow bursts are used to illustrate the impact of flow bursts on the I‐T system. The neutral density perturbation due to a flow burst increases with the lifetime, size, and flow speed of the flow burst. It was found that the neutral density perturbation is most sensitive to the size of a flow burst, increasing from ∼0.3% to ∼1.3% when the size changes from 80 to 200 km. A westward‐eastward asymmetry has been identified in neutral density, wind, and temperature perturbations, which may be due to the changing of the forcing location in geographic coordinates and the asymmetrical background state of the I‐T system. In addition to midnight flow bursts, simulations with flow bursts centered at noon, dawn, and dusk have also been carried out. A flow burst centered at noon (12.0 Local Time [LT], 73°N) produces the weakest perturbation, and a flow burst centered at dusk (18.0 LT, 71°N) produces the strongest. Single‐cell and two‐cell flow bursts induce very similar neutral density perturbation patterns.

Growth of Mesoscale Convective Systems in Observations and a Seasonal Convection-Permitting Simulation over Argentina

AbstractA 6.5-month, convection-permitting simulation is conducted over Argentina covering the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations and Clouds, Aerosols, and Complex Terrain Interactions (RELAMPAGO-CACTI) field campaign and is compared with observations to evaluate mesoscale convective system (MCS) growth prediction. Observed and simulated MCSs are consistently identified, tracked, and separated into growth, mature, and decay stages using top-of-the-atmosphere infrared brightness temperature and surface rainfall. Simulated MCS number, lifetime, seasonal and diurnal cycles, and various cloud-shield characteristics including growth rate are similar to those observed. However, the simulation produces smaller rainfall areas, greater proportions of heavy rainfall, and faster system propagations. Rainfall area is significantly underestimated for long-lived MCSs but not for shorter-lived MCSs, and rain rates are always overestimated. These differences result from a combination of model and satellite retrieval biases, in which simulated MCS rain rates are shifted from light to heavy, while satellite-retrieved rainfall is too frequent relative to rain gauge estimates. However, the simulation reproduces satellite-retrieved MCS cloud-shield evolution well, supporting its usage to examine environmental controls on MCS growth. MCS initiation locations are associated with removal of convective inhibition more than maximized low-level moisture convergence or instability. Rapid growth is associated with a stronger upper-level jet (ULJ) and a deeper northwestern Argentinean low that causes a stronger northerly low-level jet (LLJ), increasing heat and moisture fluxes, low-level vertical wind shear, baroclinicity, and instability. Sustained growth corresponds to similar LLJ, baroclinicity, and instability conditions but is less sensitive to the ULJ, large-scale vertical motion, or low-level shear. Growth sustenance controls MCS maximum extent more than growth rate.

Impact of Ensemble-Variational Data Assimilation in Heavy Rain Forecast over Brazilian Northeast

The Brazilian Northeast (BNE) is located in the tropical region of Brazil. It is bounded by the Atlantic Ocean, and its climate and vegetation are strongly affected by continental plateaus. The plateaus keep the humid air masses to the east and are responsible for the rain episodes, and at the west side the northeastern hinterland and dry air masses are observed. This work is a case study that aims to evaluate the impact of updating the model initial condition using the 3DEnVar (Three-Dimensional Ensemble Variational) system in heavy rain episodes associated with Mesoscale Convective Systems (MCS). The results were compared to 3DVar (Three-Dimensional Variational) and EnSRF (Ensemble Square Root Filter) systems and with no data assimilation. The study enclosed two MCS cases occurring on 14 and 24 January 2017. For that purpose, the RMS (Regional Modeling System) version 3.0.0, maintained by the Center for Weather Forecasting and Climate Studies (CPTEC), used two components: the Weather Research and Forecasting (WRF) mesoscale model and the GSI (Gridpoint Statistical Interpolation) data assimilation system. Currently, the RMS provides the WRF initial conditions by using 3DVar data assimilation methodology. The 3DVar uses a climatological covariance matrix to minimize model errors. In this work, the 3DEnVar updates the RMS climatological covariance matrix through the forecast members based on the errors of the day. This work evaluated the improvements in the detection and estimation of 24 h accumulated precipitation in MCS events. The statistic index RMSE (Root Mean Square Error) showed that the hybrid data assimilation system (3DEnVar) performed better in reproducing the precipitation in the MCS occurred on 14 January 2017. On 24 January 2017, the EnSRF was the best system for improving the WRF forecast. In general, the BIAS showed that the WRF initialized with different initial conditions overestimated the 24 h accumulated precipitation. Therefore, the viability of using a hybrid system may depend on the hybrid algorithm that can modify the weights attributed to the EnSRF and 3DVar matrix in the GSI over the assimilation cycles.

A Simple Lagrangian Parcel Model for the Initiation of Summer-time Mesoscale Convective Systems over the Central United States

AbstractMesoscale convective systems (MCSs) account for more than 50% of summer-time precipitation over the central United States (US) and have a significant impact on local weather and hydrologic cycle. It is hypothesized that the inadequate treatment of MCSs is responsible for the longstanding warm and dry bias over the central US in coarse-resolution general circulation model (GCM) simulations. In particular, a better understanding of MCS initiation is still lacking. Here a single-column Lagrangian parcel model is first developed to simulate the basic features of a rising parcel. This simple model demonstrates the collective effects of boundary layer moistening and dynamical lifting in triggering convective initiation and reproduces successfully its early afternoon peak with surface equivalent potential temperature as a controlling factor. It also predicts that convection is harder to trigger in the future climate under global warming, consistent with the results from convection-permitting regional climate simulations. Then a multi-column model that includes an array of single-column models aligned in the east-west direction and incorporates idealized cold pool interaction mechanisms is developed. The multi-column model captures readily the cold pool induced upscale growth feature in MCS genesis from initially scattered convection that is organized into a mesoscale cluster in a few hours. It also highlights the crucial role of lifting effects due to cold pool collision and spreading, subsidence effect, and gust front propagation speed in controlling the final size of mesoscale clusters and cold pool regions. This simple model should be useful for understanding fundamental mechanisms of MCS initiation and providing guidance for improving MCS simulations in GCMs.

Mesoscale Convective Systems Dominate the Energetics of the South Asian Summer Monsoon Onset

AbstractThe rapid onset of the South Asian summer monsoon (SASM) is featured as an abrupt increase of rainfall and atmospheric column‐integrated moist static energy (MSE). Using convection‐permitting simulations, a novel cloud tracking technique, and an MSE budget, the relative roles of mesoscale convective systems (MCSs) and non‐MCS deep convection in the SASM onset energetics are studied. The analysis shows MCSs greatly contribute to the sudden increases of rainfall, diabatic MSE sources, and the subsequent enhanced export of column‐integrated MSE during the rapid onset phase. A “diabatic sources‐energy export” plane analysis delineates the different roles of MCSs and non‐MCS deep convection. Although deep convection always leads to a net energy export, mesoscale organization of deep convection dominates the convection‐associated positive feedbacks that accelerate the energy cycle of the SASM onset. Sensitivity experiment shows that the results are insensitive to the model resolutions.

A Preliminary Study on the Organizational Modes of Mesoscale Convective Systems Associated With Warm‐Sector Heavy Rainfall in South China

AbstractThis work examines the organizational modes of mesoscale convective systems (MCSs) associated with warm‐sector heavy rainfall events in South China based on composite radar reflectivities during April–June from 2007 to 2020. The results showed that these MCSs can be classified into the nonlinear mode (NL) and eight linear modes: trailing stratiform precipitation (TS), no stratiform precipitation (NS), leading stratiform precipitation (LS), parallel stratiform precipitation (PS), embedded lines (EL), bow echoes (BE), training line/adjoining stratiform (TL/AS), and multiple rain bands (MRB). The NL mode accounts for 40% of the total, while linear modes account for 60%, with the TS mode being the most frequent linear mode. The detailed features of the top three most frequent organizational modes (NL, TS, and NS) were examined in this work. First, the MCSs of the top three organizational modes have different formation modes. Eighty‐four percent of NL systems and 77% of TS systems form via the broken areal mode, while 83% of NS systems form via the broken line mode. Second, relative to TS and NS systems, NL systems develop faster and have shorter lifespans but slower movements with higher 3‐h and 6‐h maximum precipitation values. Third, environmental analysis indicates that the Total Totals index (TTI) is significantly different among all the top three organizational modes, with the highest value in TS mode and the lowest value in NS mode. These features are apparently different from their counterparts in central East China due to different synoptic environments.

Rainrate Estimation from FY-4A Cloud Top Temperature for Mesoscale Convective Systems by Using Machine Learning Algorithm

Satellite rainrate estimation is a great challenge, especially in mesoscale convective systems (MCSs), which is mainly due to the absence of a direct physical connection between observable cloud parameters and surface rainrate. The machine learning technique was employed in this study to estimate rainrate in the MCS domain via using cloud top temperature (CTT) derived from a geostationary satellite. Five kinds of machine learning models were investigated, i.e., polynomial regression, support vector machine, decision tree, random forest, and multilayer perceptron, and the precipitation of Climate Prediction Center morphing technique (CMORPH) was used as the reference. A total of 31 CTT related features were designed to be the potential inputs for training an algorithm, and they were all proved to have a positive contribution in modulating the algorithm. Random forest (RF) shows the best performance among the five kinds of models. By combining the classification and regression schemes of the RF model, an RF-based hybrid algorithm was proposed first to discriminate the rainy pixel and then estimate its rainrate. For the MCS samples considered in this study, such an algorithm generates the best estimation, and its accuracy is definitely higher than the operational precipitation product of FY-4A. These results demonstrate the promising feasibility of applying a machine learning technique to solve the satellite precipitation retrieval problem.

Environmental and Internal Controls on Lagrangian Transitions from Closed Cell Mesoscale Cellular Convection over Subtropical Oceans

AbstractClassifications of mesoscale cellular convection (MCC) for marine boundary layer clouds are produced using a supervised neural network algorithm applied to MODIS daytime liquid water path data. The classifier, used in prior studies, distinguishes closed, open, and cellular but disorganized MCC. This work uses trajectories in four eastern subtropical ocean basins to compare meteorological variables and the structures of boundary layers for trajectories that begin as closed cells but evolve into either open cells or disorganized cells or remain closed cells over one afternoon–afternoon cycle. Results show contrasts between the trajectory sets: Trajectories for MCC that remain closed cells are more frequently observed nearer coasts, whereas trajectories that break into open and disorganized cells begin farther offshore. The frequency at which closed cells transition to open cells is seasonally invariant. The fraction of trajectories that stay as closed MCC varies throughout the year in opposition to those that break into disorganized cells, so that their annual cycles are 180° out of phase. Trajectories remain as closed cell more frequently in austral spring and boreal summer when the trade inversion is stronger. The closed–disorganized MCC breakup is associated with weaker subsidence, a weaker inversion, a drier free troposphere, and enhanced nighttime boundary layer deepening, consistent with a warming–drying mechanism. The closed–open transition occurs in meteorological conditions similar to closed–closed trajectories. However, prior to the transition, the closed–open trajectories exhibit stronger surface winds and lower cloud droplet concentrations and rain more heavily overnight. Results suggest that multiple, independent mechanisms drive changes in cloud amount and morphology.

Long-Lived Mesoscale Convective Systems over Eastern South Africa

AbstractA climatology of large, long-lived mesoscale convective systems (MCSs) over eastern South Africa for the extended austral summer (September–April) from 1985 to 2008 is presented. On average, 63 MCSs occur here in summer, but with considerable interannual variability in frequency. The systems mainly occur between November and March, with a December peak. This seasonal cycle in MCS activity is shown to coincide with favorable CAPE and vertical shear profiles across the domain. Most systems tend to occur along the eastern escarpment and adjacent warm waters of the northern Agulhas Current with a nocturnal life cycle. Typically, initiation begins in the early afternoon, MCS status is reached midafternoon, maximum extent early in the night, and termination around midnight or shortly thereafter. It is found that most MCSs initiate over land, but systems that initiate over the ocean tend to last longer than those that develop over land. The results also show that there are differences in the seasonal cycle between continental and oceanic MCSs, with oceanic systems containing two intraseasonal peaks (December and April). There is a relatively strong positive relationship between the southern annular mode (SAM) and early summer MCS frequency. For the late summer, the frequency of MCSs appears related to the strength of the Mascarene high and Mozambique Channel trough, which modulate the inflow of moisture into eastern South Africa and the stability of the lower atmosphere over the region.

The atmospheric controls of extreme convective events over the southern Arabian Peninsula during the spring season

Mesoscale Convective Systems (MCSs) over the southern Arabian Peninsula are more common during the spring months of March and April. In this paper, the processes behind such severe convective events and their local-scale impacts are investigated using reanalysis data, satellite-derived and observational products. The analysis of 95 MCS events from 2000 to 2020 revealed that they are triggered by low-level wind convergence and moisture advection from the Arabian Sea, Arabian Gulf and/or Red Sea. An equatorward displacement and strengthening of the subtropical jet also precondition the environment, as does the presence of a mid-level trough. The latter is generally part of a large-scale pattern of anomalies that are equivalent barotropic in nature, and therefore likely a response to tropical or subtropical forcing. At more local-scale, a drying of the mid-troposphere between 850 and 250 hPa typically by 50%, a reduction of the upper-level winds by about 5 m s−1, and an increase in the upper-tropospheric temperature on average by 2–3 K, are typically observed during MCS events. Over the 21-year period, a statistically significant increase in the MCSs' duration over southeast Arabian Peninsula has been found, suggesting that such extreme events may be even more impactful in a warming world.

Wavelet Analysis of Properties of Marine Boundary Layer Mesoscale Cells Observed From AMSR‐E

AbstractMarine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two‐dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate (RR) from Advanced Microwave Scanning Radiometer for Earth Observing System in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co‐)variability between CWP, WVP, and RR in 160 × 160 km2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine‐learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, RR, and potential environmental controlling factors to be analyzed across a very large set of cases. The results show that the cell wavelength is most commonly 40–80 km. Cell‐scale CWP perturbations are good predictors of the WVP and RR perturbations. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

Life cycle resolved observation of radiative properties of mesoscale convective systems

AbstractThe evolution of radiative properties (outgoing longwave radiation, OLR, and albedo at the top of the atmosphere) over Mesoscale Convective System (MCS) life cycle is assessed using five years of Scanner for Radiation Budget (ScaRaB) radiometer onboard the Megha-Tropiques satellites merged with geostationary infrared images. The MCS life cycle is documented using a tracking algorithm. A composite approach is then implemented to document the evolution of radiative properties at each life stage at the scale of the tropical belt, in continental and oceanic regions and in specific regions. Independently of the considered region the composites share similarities with a unique maximum in albedo and a unique minimum in OLR, values of which differ depending on the environment as well as the amplitude of both parameters over the life cycle. The unique precessing orbit of the Megha-Tropiques satellite allows a consideration of the albedo as a function of the local time of observation showing that the magnitude of the albedo signal is mainly controlled by the solar zenithal angle.Sensitivity tests allow to the quantification of the impact of an error in radiative properties showing that even small errors lead to substantial increment on the instantaneous cloud radiative effect. All together these elements point toward the subtle balance between life cycle, cloud radiative properties and phasing within the diurnal cycle to build the atmospheric radiative budget in oceanic or continental regions.

European extreme precipitation: The effects of spatio-temporal resolution of the data

European wintertime precipitation is known to be skilfully estimated in reanalysis data and model simulations since it is highly correlated with large scale, low frequency modes of variability, namely the North Atlantic Oscillation (NAO). Since the NAO is mainly a wintertime mode of variability, the skill of estimating precipitation becomes more limited in other seasons, most importantly in summer, when precipitation is mainly a result of mesoscale convection. In this study, we use the Weather Research and Forecast (WRF) model, to show the added value of using a high resolution, convection-permitting model to estimate precipitation extremes. The results show that WRF succeeds to correct the failure of ERA-Interim reanalysis to capture the positive trends over the last decades of European extreme precipitation in summer and transition seasons, that are indicated by observational data (E-OBS) and previous literature. Partial improvements are evident using ERA5 reanalysis, specifically in Spring and in Autumn. In winter, changes in European extreme precipitation over the last decades are dominated by variations in the NAO index, and are well reproduced both in reanalysis data and in the high resolution WRF downscaling.