Cloud Shield Research Articles

Hypervelocity impact against aluminium Whipple shields in the shatter regime with systematic parameter variation: An experimental and numerical study

Aluminium Whipple shields are commonly used to protect spacecraft against hypervelocity impacts (HVIs) from orbital debris and micrometeoroids. Since numerical models nowadays are vital in the design process of protective shields, experimental studies of HVI are important to ensure that the numerical methods are robust and capable of accurately describing a range of impact conditions and material responses. The shatter regime is the transition velocity range between ballistic impact and hypervelocity impact, typically defined from 3 to 7 km/s. In this region, the debris cloud generated by the impact transitions from a few large, solid fragments at the lower end of the velocity range, to a high number of smaller fragments and partial melting of the projectile at the higher velocities. In this study, an experimental campaign of 22 normal impacts of spherical AA1100 projectiles on AA6061-T6 Whipple shields is performed, where the impact velocity and bumper thickness are systematically varied to study the change in debris cloud characteristics and shield damage. Impact velocities from 2.6 to 5.0 km/s are investigated, combined with bumper thicknesses of 1.0, 1.5 and 2.0 mm. Analysis of the experimental results is conducted using high-speed camera footage of the debris clouds and post-impact analysis of bumpers and rear walls. A numerical model is then established using the Smoothed Particle Hydrodynamics (SPH) method in the IMPETUS Solver, and the numerical results are compared to the experimental data. The simulations are able to capture the main trends found in the experimental study, and show a similar level of damage as the experiments when varying the impact velocity and bumper thickness. The simulations have somewhat smaller fragments generated in the debris cloud than in the experiments, leading to slightly less damage inflicted on the rear wall.

Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations

AbstractIn this study, we evaluate mesoscale convective system (MCS) simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25° horizontal resolution. We track MCSs consistently in the model and observations using PyFLEXTRKR algorithm, which defines MCSs based on both cloud top brightness temperature (Tb) and surface precipitation. Results from using only Tb to define MCSs are also discussed to understand the impact of different MCS tracking algorithms on MCS evaluation and provide additional insights into model errors in simulating MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in tropical and extratropical regions. This is mainly attributed to the underestimated MCS genesis and underestimated precipitation intensity in EAMv2. Comparing the two MCS tracking methods, simulated MCS precipitation is increased if MCSs are defined with only cloud top Tb. The Tb‐based MCS tracking method, however, includes cloud systems with very weak precipitation. This illustrates the model issues in simulating heavy precipitation even though the convective cloud shield is overall well simulated from the moist convective processes. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. The new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are not significantly improved. This suggests that simulating MCSs still remain a challenge for the next version of E3SM.

Direct Collapse Supermassive Black Holes from Relic Particle Decay.

We investigate the formation of high-redshift supermassive black holes (SMBHs) via the direct collapse of baryonic clouds, where the unwanted formation of molecular hydrogen is successfully suppressed by a Lyman-Werner (LW) photon background from relic particle decay. We improve on existing studies by dynamically simulating the collapse, accounting for the adiabatic contraction of the DM halo, as well as the insitu production of the LW photons within the cloud which reduce the impact of the cloud's shielding. We find a viable parameter space where the decay of either some of the dark matter or all of a subdominant decaying species successfully allows direct collapse of the cloud to a SMBH.

Galactic Superbubbles in 3D: Wind Formation and Cloud Shielding

Abstract Galactic superbubbles are triggered by stellar feedback in the discs of star-forming galaxies. They are important in launching galactic winds, which play a key role in regulating the mass and energy exchange in galaxies. Observations can only reveal projected information and the 3D structure of such winds is quite complex. Therefore, numerical simulations are required to further our understanding of such structures. Here, we describe hydrodynamical simulations targeting two spatial scales. Large-scale superbubble models reveal supernova-driven outflows, and their subsequent merging, which leads to galactic wind formation. Additionally, the turbulence parameter σt not only affects disc formation, but also influences mass and energy characteristics, controlling gas distribution and the injection rate in the simulated star formation zone. Small-scale wind-multicloud models indicate that isolated clouds are susceptible to instabilities, leading to fragmentation and dense gas destruction. In contrast, in closer cloud configurations, the condensation mechanism becomes important owing to hydrodynamic shielding, which helps to maintain the cold material throughout the evolution of the system. These simulations provide a comprehensive picture of galactic winds, showing how large-scale superbubble dynamics create the environment where small-scale wind-multicloud interactions shape the interstellar and circumgalactic media, ultimately regulating galaxy evolution.

Thunderstorms coming up against the wind on 11 June 2023 – the development of a mesoscale convective system over southern England

AbstractOn 11 June 2023, a mesoscale convective system (MCS) developed over the southern UK producing heavy rainfall and numerous lightning strikes. The MCS formed from clusters of relatively small‐scale thundery showers south and west of the London area. These showers then merged together and grew upscale to form an organised convective system of the leading‐line trailing stratiform type with a large quasi‐circular cloud shield. Both surface‐based and elevated convection appears to have been involved. Heavy rainfall caused localised surface water flooding with a number of stations in southern England reporting event totals in excess of 1 inch (25.4mm).

A study of extreme rainfall events and urban flooding over Hyderabad, October 2020

The present study analyses and describes the evolution of the Mesoscale Convective Complex (MCC) and its atmospheric conditions during Extreme rainfall event in Hyderabad, on 13th October 2020. This extreme weather event was a mesoscale event embedded in a synoptic-scale system. During the second week of October 2020, a depression formed over the west-central Bay of Bengal (BoB) and travelled north-westwards through peninsular India, causing heavy rains in Andhra Pradesh and Telangana states of India on October 13-14. On October 13, many parts of Hyderabad and Cyberabad received more than 300 mm of rain within 24 hrs. Satellite imagery suggests that this mesoscale system constituted a unique set of structured convection those reported in MCC. This MCC has a cloud shield with a continuous low IR temperature of less than - 33 °C over an area of more than 100000 km2 and a cloud shield with a continuous low IR temperature of less than -54 °C over an area of more than 50000 km2 over Hyderabad with a life cycle of about 9 hours. This MCC featured multi cellular characteristics, showing that there was significant low-level moisture in its environment, as well as a mix of vigorous updrafts, implying significant rainfall rates over Hyderabad. The synoptic features suggest that with high precipitable water, the long axis of low-level moisture convergence at 0850 hPa and large horizontal vorticity at 0925 hPa were oriented parallel to the system's mean wind flow. In this case, a clusters of thunderstorms arose in the area of moisture convergence which prolonged the duration of extremely heavy rainfall. The high rain rate, relatively sluggish storm motion, and prolonged back-building over the same locations for several hours are likely to blame for the heavy rainfall accumulations that were observed. The hydrological conditions compounded the effects of the torrential rain, resulting in a natural hazard.

Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme

Abstract. Since 2017 the Tropospheric Monitoring Instrument (TROPOMI) on board ESA's Copernicus Sentinel-5 satellite (S5-P) has provided the operational carbon monoxide (CO) data product with daily global coverage on a spatial resolution of 5.5×7 km2. The European Centre for Medium-Range Weather Forecasts (ECMWF) plans to assimilate the retrieved total columns and the corresponding vertical sensitivities in the Copernicus Atmosphere Monitoring Service Integrated Forecasting System (CAMS-IFS) to improve forecasts of the atmospheric chemical composition. The TROPOMI data will primarily constrain the vertical integrated CO field of CAMS-IFS but to a lesser extent also its vertical CO distribution. For clear-sky conditions, the vertical sensitivity of the TROPOMI CO data product is useful throughout the atmosphere, but for cloudy scenes it varies due to cloud shielding and light scattering. To assess the profile information, we deploy an a posteriori profile retrieval that combines an ensemble of TROPOMI CO column retrievals with different vertical sensitivities to obtain a vertical CO profile that is then a representative average for the chosen spatial and temporal domain. We demonstrate the approach on three CO pollution cases. For the so-called “Rabbit Foot Fire” in Idaho on 12 August 2018, we estimate a CO profile showing the pollution at an altitude of about 5 km in good agreement with airborne in situ measurements of the Biomass Burning Flux Measurements of Trace Gases and Aerosol (BB-FLUX) field campaign. The distinct CO enhancement in a plume aloft (length =212 km, width =34 km), decoupled from the ground, is sensed by TROPOMI but is not present in the CAMS-IFS model. For a large-scale event, we analyzed the CO pollution from Siberian wildfires that took place from 14 to 17 August 2018. The TROPOMI data estimate the height of the pollution plume over Canada at 7 km in agreement with CAMS-IFS. However, CAMS-IFS underestimates the enhanced CO vertical column densities sensed by TROPOMI within the plume by more than 100 ppb. Finally, we study the seasonal biomass burning in the Amazon. During the burning season the CO profile retrieved from the TROPOMI measurements (1–15 August 2019) agrees well with the one of CAMS-IFS with a similar vertical shape between ground and 14 km altitude. Hence, our results indicate that assimilating TROPOMI CO retrieval with different vertical sensitivities (e.g., under clear-sky and cloudy conditions) provides information about the vertical distribution of CO.

Planet formation via pebble accretion in externally photoevaporating discs

ABSTRACT We demonstrate that planet formation via pebble accretion is sensitive to external photoevaporation of the outer disc. In pebble accretion, planets grow by accreting from a flux of solids (pebbles) that radially drift inwards from the pebble production front. If external photoevaporation truncates the outer disc fast enough, it can shorten the time before the pebble production front reaches the disc outer edge, cutting off the supply of pebble flux for accretion, hence limiting the pebble mass reservoir for planet growth. Conversely, cloud shielding can protect the disc from strong external photoevaporation and preserve the pebble reservoir. Because grain growth and drift can occur quickly, shielding even on a short time-scale (<1 Myr) can have a non-linear impact on the properties of planets growing by pebble accretion. For example, a $10^{-3}\, \mathrm{ M}_{\oplus }$ planetary seed at 25 au stays at 25 au with a lunar mass if the disc is immediately irradiated by a 103 G0 field, but grows and migrates to be approximately Earth-like in both mass and orbital radius if the disc is shielded for just 1 Myr. In NGC 2024, external photoevaporation is thought to happen to discs that are <0.5 Myr old, which coupled with the results here suggests that the exact planetary parameters can be very sensitive to the star-forming environment. Universal shielding for time-scales of at least ${\sim} 1.5\,$ Myr would be required to completely nullify the environmental impact on planetary architectures.

Mesoscale Convective Systems in DYAMOND Global Convection‐Permitting Simulations

AbstractThis study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.

Comparison of Lake Extraction and Classification Methods for the Tibetan Plateau Based on Topographic-Spectral Information

Accurate identification and extraction of lake boundaries are the basis of the accurate assessment of lake changes and their responses to climate change. To reduce the effects of lake ice and snow cover, mountain shadows, cloud and fog shielding, alluvial and proluvial deposits, and shoals on the extraction of lake boundaries on the Tibetan Plateau, this study developed an RNSS water index to increase the contrast between the lake and similar surface objects of the spectral curve, and constructed a new method flow for lake extraction on the Tibetan Plateau based on image synthesis, topographic-spectral feature indexes, and machine learning algorithms. The lake extraction effects of three common machine learning classification algorithms were compared: the Cart decision tree, random forest (RF), and gradient boosting decision tree (GBDT). The results show that the new lake extraction method based on topographic-spectral characteristics and the GBDT classification method had the highest extraction accuracy for Tibetan Plateau lakes in 2016 and 2021. Its overall accuracy, Kappa coefficient, user’s accuracy, and producer’s accuracy for 2016 and 2021 were 99.81%, 0.887, 83.55%, 94.67% and 99.88%, 0.933, 89.18%, 98.24%, respectively, and the total area of lake extraction was the most consistent with the validation datasets. The three classification methods can effectively extract lakes covered by ice and snow, and the extraction effect was ranked as GBDT > RF > Cart. The lake extraction effect under mountain shadow was ranked as Cart > GBDT > RF, and the lake extraction effect under alluvial deposits and shoals was ranked as GBDT > RF > Cart. The results may provide technical support for extracting lakes from long time series and reveal the impact of climate change on Tibetan Plateau lakes.

Towards a Unified Setup to Simulate Mid‐Latitude and Tropical Mesoscale Convective Systems at Kilometer‐Scales

AbstractMesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid‐latitudes and are responsible for high‐impact weather worldwide. Studies showed that deficiencies in simulating mid‐latitude MCSs in state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these models can also improve tropical MCSs and whether we can find model settings that perform well in both regions is understudied. We take advantage of high‐quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the US Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4 km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large‐scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellor‐Yamada‐Janjic PBL scheme.

A Simple Model for Tropical Convective Cloud Shield Area Growth and Decay Rates Informed by Geostationary IR, GPM, and Aqua/AIRS Satellite Data

AbstractDeep convective system maximum areal extent is driven by the stratiform anvil area since convective area fractions are much less than unity when systems reach peak size. It is important to understand the processes that drive system size given the impact large systems have on rainfall and that of anvils on high cloud feedbacks. Using satellite diabatic heating and convective‐stratiform information mapped to convective systems, composite analyses suggest that system maximum sizes occur at the temporal mid‐point of system lifecycles with both maximum size and duration correlating with peak heating above the melting level. However, variations in system growth rates exist, with the overall smooth composites emerging as the average of highly variable system trajectories. Thus, this study focuses on understanding convective system growth rates on short (30‐min) timescales via development of a simple analytical source—sink model that predicts system area changes. Growth occurs when detrained convective mass (inferred from the vertical gradient of diabatic heating and temperature lapse rates) and/or generation of convective area exceeds a sink term whose magnitude is proportional to the current cloud shield size. The model works well for systems over land and ocean, and for systems characterized by varying degrees of convective organization and duration (1.5–35 hr, with correlations often >0.8 across lifetime bins). The model may serve as a useful foundation for improved understanding of processes driving changes in tropics‐wide convective system cloud shields, and further supports conceptual development and evaluation of prognostic climate model stratiform anvil area parameterizations.

Integrated damage, visual, remote sensing, and environmental analysis of a strong tornado in southern Brazil

On 20 April 2015 a strong tornado struck the city of Xanxerê located in western Santa Catarina (SC) state, in southern Brazil. The tornado destroyed several buildings, causing almost 100 injuries, four fatalities, and R$ 104 million in damage (approximately USD$ 34.6 million according to 2015 dollar quotation), making it one of the most damaging tornadoes in Brazil's history. This study provides an integrated damage, visual, remote sensing, and environmental analysis of the tornado event. Medium-resolution satellite imagery and in situ photographs of the damage show that the tornado caused high-end F2 damage on the Fujita scale across a 4.9-km-long path in the northern portion of Xanxerê. Videos of the tornado and its parent storm reveal the existence of a low-level mesocyclone and rear-flank downdraft, indicating that the storm was a supercell. Horizontal vortices, which are occasionally observed in strong tornadoes but rarely documented in Brazilian tornadoes, were also observed in the videos. The supercell developed in a warm and moist air mass characterized by moderate buoyancy and weak mid-level lapse rates. The mid- and upper-tropospheric forcing for synoptic-scale ascent was weak but the prevailing zonal flow was moderately strong, providing sufficient deep-layer shear for supercell development. A key component of the synoptic-scale environment was the presence of a northerly low-level jet stream that promoted warm moist advection into western SC in addition to increasing the low-level vertical wind shear in the region. On the mesoscale, the presence of a broad cloud shield from a decaying mesoscale convective system (MCS) preceding the supercell formation hampered daytime radiative heating over western SC resulting in low dewpoint depression and, thus, lower lifting condensation levels around Xanxerê. Remote sensing and surface data suggest that the MCS-induced outflow boundary may have been responsible for the initiation of the supercell. The complex subtropical environment of the Xanxerê tornado differs in many aspects from well-documented North American tornadic environments and highlights the need for more studies addressing distinctions between the atmospheric conditions that are conducive to tornadic activity in the two continents.

Local Impacts and Surface Characteristics of Cold Pools Wind Gust Observed from Thunderstorm

Cold pools and associated wind storms are frequent occurrences in Southwestern Nigeria, especially during the early monsoon phase. The associated surface wind gust frequently destroys properties resulting in economic losses. Two case events were investigated in this study; one event occurred in May 2019 and the other occurred in March 2020, both in southwestern Nigeria. The National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Prediction (NCEP)/Climate Prediction Center (CPC) Infrared brightness temperatures and CPC Morphing technique (CMORPH) rainfall products were analysed alongside in-situ observations from the Nigerian Meteorological Agency (NiMET). Other data sources analysed are the National Aeronautics and Space Administration (NASA) Prediction Of Worldwide Energy Resources (POWER) and the World Wide Lightning Location Network (WWLLN). Cold pools were identified in the impacted communities as indicated by surface characteristics investigated from the in-situ observations. There was a sudden change in wind direction, with a simultaneous drop in temperature accompanied by increasing wind speed. Pressure and humidity were observed to change in the same period. Thunderstorms were also present in the impacted communities, as observed by the in-situ observations, in both case events. The presence of lightning as observed by WWLLN agrees with the in-situ thunderstorms. The cloud characteristics showed the presence of cloud shields, by their brightness temperature, over the impacted communities during the period of the cold pools in both case events. The systems were raining at the time of the observations in both cases, consistent with the in-situ thunderstorm observations. The communities were heavily impacted with several properties destroyed in the events. These early monsoon seasonal windstorms require a forecasting tool for their prediction and this study presents an eye-opener for further investigation and innovative research to address the menace.

Improvement of Heavy Rainfall Simulated with SST Adjustment Associated with Mesoscale Convective Complexes Related to Severe Flash Flood in Luwu, Sulawesi, Indonesia

Flash flooding is an important issue as it has a devastating impact over a short time and in a limited area. However, predicting flash floods is challenging because they are connected to convection systems that rapidly evolve and require a high-resolution forecasting system. In addition, modeling a case study of a mesoscale convective complex (MCC) is the key to improving our understanding of the heavy rainfall systems that trigger flash floods. In this study, we aim at improving modeling skills to simulate a heavy rainfall system related to flash-flood-producing MCCs. We simulated a heavy rainfall event related to a severe flash flood in Luwu, Sulawesi, Indonesia, on 13 July 2020. This flood was preceded by persistent heavy rainfall from 11 to 13 July 2020. In this case, we investigated the role of sea surface temperature (SST) in producing the persistent heavy rainfall over the region. Therefore, we explore the physical and dynamic processes that caused the heavy rainfall using a convection-permitting model with 1 km resolution and an experiment comparing the situation with and without updated SST. The results show that the heavy rainfall was modulated by the development of a pair of MCCs during the night. The pair of MCCs was triggered by a meso-low-pressure system with an anti-cyclonic circulation anomaly over the Makassar Strait and was maintained by the warm front passing between the sea and land over central Sulawesi. This front was characterized by moist–warm and cold–dry low-level air, which may have helped extend the lifetime of the MCCs. The north-westward propagation of the MCCs was due to the interaction between predominantly a south-easterly monsoon and SST anomalies. This study suggested that the long-lived (>10 h) MCCs (>80,000 km2 cloud shield) and persistent precipitation are reproduced well in the updated SST scenario in the WRF model. This relatively simple technique in the running model provides a new strategy for improving flash flood forecasting by better predicting rainfall as an input in the hydrological model. Our findings also indicated a long-lived MCC maintained by back-building mechanisms from night to morning inland as an exceptional MCC, which does not correspond to a previous study.

Ship target detection of unmanned surface vehicle base on EfficientDet

The autonomous navigation of unmanned surface vehicles (USV) depends mainly on effective ship target detection to the nearby water area. The difficulty of target detection for USV derives from the complexity of the external environment, such as the light reflection and the cloud or mist shield. Accordingly, this paper proposes a target detection technology for USV on the basis of the EfficientDet algorithm. The ship features fusion is performed by Bi-directional Feature Pyra-mid Network (BiFPN), in which the pre-trained EfficientNet via ImageNet is taken as the backbone network, then the detection speed is increased by group normalization. Compared with the Faster-RCNN and Yolo V3, the ship target detection accuracy is greatly improved to 87.5% in complex environments. The algorithm can be applied to the identification of dynamic targets on the sea, which provides a key reference for the autonomous navigation of USV and the military threats assessment on the sea surface.

Evaluation of synthetic satellite images computed from radiative transfer models over a region of South America using WRF and GOES‐13/16 observations

AbstractSynthetic infrared GOES‐13 observations are generated from a high‐resolution (4 km) Weather Research and Forecasting (WRF) model run over Argentina for a meteorological event of deep moist convection using two different radiative transfer models. The fast operational Community Radiative Transfer Model (CRTM) and the physics‐based research model Atmospheric Radiative Transfer Simulator (ARTS) are compared with the available observations. CRTM shows good results at a low computational cost, and is a good candidate for operational use in the region. CRTM and ARTS synthetic satellite images show differences due to the treatment of the bulk scattering properties of the frozen hydrometeor species, especially around the cloud shield. With this WRF+CRTM configuration, a long‐term evaluation is conducted over 12 hr forecasts from one month of data in a region of the South American autumn with four different initializations at 0000, 0600, 1200 and 1800 UTC, as operational at the National Meteorological Service of Argentina. The simulated and observed GOES‐16 Advanced Baseline Imager (ABI) brightness temperatures (BTs) in the 6.9 m channel show good agreement with an averaged bias of K (RMSE 21.7 K), whereas the performances in the IR window channels show slightly larger averaged BT differences of 3.5 K (RMSE 15.2 K). BT differences between the 6.9 and 10.3 m channels indicate that the WRF+CRTM simulations underestimate low to mid‐level clouds and to a lesser extent high‐level clouds. In the BT (10.3 m) range between approximately 215 and 230 K, there is an overestimation of clouds with BT differences above 0 K between 6.9 and 10.3 m. This could be due to the misrepresentation of upper‐level clouds.

Evaluation of Fengyun-4A Lightning Mapping Imager (LMI) Performance during Multiple Convective Episodes over Beijing

This study investigates the characteristics of space-borne Lightning Mapping Imager (LMI) lightning products and their relationships with cloud properties using ground-based total lightning observations from the Beijing Broadband Lightning Network (BLNET) and cloud information from S-band Doppler radar data. LMI showed generally consistent lightning spatial distributions with those of BLNET, and yielded a considerable lightning detection capability over regions with complex terrain. The ratios between the LMI events, groups and flashes were approximately 9:3:1, and the number of LMI-detected flashes was roughly one order of magnitude smaller than the number of BLNET-detected flashes. However, in different convective episodes, the LMI detection capability was likely to be affected by cloud properties, especially in strongly electrified convective episodes associated with frequent lightning discharging and thick cloud depth. As a result, LMI tended to detect lightning flashes located in weaker and shallower cloud portions associated with fewer cloud shielding effects. With reference to the BLNET total lightning data as the ground truth of observation (both intra-cloud lightning and cloud-to-ground lightning flashes), the LMI event-based detection efficiency (DE) was estimated to reach 28% under rational spatiotemporal matching criteria (1.5 s and 65 km) over Beijing. In terms of LMI flash-based DE, it was much reduced compared with event-based DE. The LMI flash-based ranged between 1.5% and 3.5% with 1.5 s and 35–65 km matching scales. For 330 ms and 35 km, the spatiotemporal matching criteria used to evaluate Geostationary Lightning Mapper (GLM), the LMI flash-based DE was smaller (<1%).

The behavior of high-CAPE (convective available potential energy) summer convection in large-domain large-eddy simulations with ICON

Abstract. Current state-of-the-art regional numerical weather prediction (NWP) models employ kilometer-scale horizontal grid resolutions, thereby simulating convection within the grey zone. Increasing resolution leads to resolving the 3D motion field and has been shown to improve the representation of clouds and precipitation. Using a hectometer-scale model in forecasting mode on a large domain therefore offers a chance to study processes that require the simulation of the 3D motion field at small horizontal scales, such as deep summertime moist convection, a notorious problem in NWP. We use the ICOsahedral Nonhydrostatic weather and climate model in large-eddy simulation mode (ICON-LEM) to simulate deep moist convection and distinguish between scattered, large-scale dynamically forced, and frontal convection. We use different ground- and satellite-based observational data sets, which supply information on ice water content and path, ice cloud cover, and cloud-top height on a similar scale as the simulations, in order to evaluate and constrain our model simulations. We find that the timing and geometric extent of the convectively generated cloud shield agree well with observations, while the lifetime of the convective anvil was, at least in one case, significantly overestimated. Given the large uncertainties of individual ice water path observations, we use a suite of observations in order to better constrain the simulations. ICON-LEM simulates a cloud ice water path that lies between the different observational data sets, but simulations appear to be biased towards a large frozen water path (all frozen hydrometeors). Modifications of parameters within the microphysical scheme have little effect on the bias in the frozen water path and the longevity of the anvil. In particular, one of our convective days appeared to be very sensitive to the initial and boundary conditions, which had a large impact on the convective triggering but little impact on the high frozen water path and long anvil lifetime bias. Based on this limited set of sensitivity experiments, the evolution of locally forced convection appears to depend more on the uncertainty of the large-scale dynamical state based on data assimilation than of microphysical parameters. Overall, we judge ICON-LEM simulations of deep moist convection to be very close to observations regarding the timing, geometrical structure, and cloud ice water path of the convective anvil, but other frozen hydrometeors, in particular graupel, are likely overestimated. Therefore, ICON-LEM supplies important information for weather forecasting and forms a good basis for parameterization development based on physical processes or machine learning.

Securing an Internet of Things from Distributed Denial of Service and Mirai Botnet Attacks Using a Novel Hybrid Detection and Mitigation Mechanism

Internet of Things (IoT) has become more familiar in all applications and industrial fields such as medical, military, transportation, etc. It has some limitations because of the attack model in the transmission or communication channel. Moreover, one of the deadliest attacks is known as a Distributed Denial of Service Attack (DDoS). The Presence of DDoS in network layer cause huge damage in data transmission channel that ends in data loss or collapse. To address this issue the current research focused on an innovative detection and mitigation of Mirai and DDoS attack in IoT environment. Initially, number of IoT devices is arranged with the help of a novel Hybrid Strawberry and African Buffalo Optimization (HSBABO). Consequently, the types of DDoS attacks are launched in the developed IoT network. Moreover, the presence of strawberry and African Buffalo fitness is utilized to detect and specify the attack types. Subsequently a novel MCELIECE encryption with Cloud Shield scheme is developed to prevent the low and high rate DDoS attack in the Internet of Things. Finally, the proposed model attained 94% of attack detection accuracy, 3% of false negative rate and 5.5% of false positive rate.