Storm Life Cycle Research Articles

Study of boundary layer parameterization simulation uncertainties of sand-dust storm windfield using high-resolution three-dimensional Doppler wind lidar data

The processes of dust emission, the development, and dissipation of sand and dust storms all exhibit dynamic and rapidly changing characteristics, posing significant challenges for us to accurately represent their complex behaviors in numerical simulations. In the numerical weather prediction model, the selection and optimization of planetary boundary layer (PBL) parameterization schemes have a direct impact on the simulation results of PBL wind fields, primarily due to the significant uncertainty in the fine-grained simulation of PBL wind field structure. To gain a deeper understanding of the sources of uncertainty in simulating sand-dust storms through vertical wind field structure simulations of the PBL, this study utilizes high-resolution 3D Doppler wind lidar (DWL) data. Focusing on sand-dust storm wind fields with distinctive regional characteristics in Inner Mongolia, China, it examines the turbulent momentum equation and assumptions of the PBL. A comprehensive and systematic evaluation was conducted on the characteristics of horizontal and vertical wind fields, wind shear, as well as the dynamic and thermodynamic differences that arise when simulating typical sand-dust storm wind fields using the Weather Research and Forecasting (WRF) Model with various PBL schemes. This evaluation focused on simulating the typical wind field of sand-dust storms during various stages, including dust generation, occurrence, development, and dissipation. The findings indicate that non-adiabatic heating plays a significant role in the sustainability and evolution of sand-dust storms. The wind shear index holds particular importance as it embodies the dynamic factor in the model. The PBL schemes such as Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2), A new version of asymmetric convective model (ACM2), and Grenier-Bretherton-McCaa (GBM), which factor in buoyancy effects, demonstrate more accurate wind shear simulations in sand-dust storms. Furthermore, the ACM2 scheme effectively replicates the fundamental variation characteristics of meteorological elements throughout the sand-dust storm lifecycle.

Towards improved short-term forecasting for Lake Victoria Basin: Part I – A radar-based convective mode analysis

Abstract East African countries benefit economically from the largest freshwater lake in Africa: Lake Victoria (LV). Around 30 million people live along its coastline and 5.4 million people subsist on its fishing industry. However, more than 1,000 fishermen die annually by high-wave conditions often produced by severe convective wind phenomena, which marks this lake one of the deadliest places in the world for hazardous weather impacts. The World Meteorological Organization launched the 3-year “HIGH impact Weather lAke sYstem” (HIGHWAY) project, with the main objective to reduce loss of lives and economic goods in the lake basin and improve the resilience of the local communities. The project conducted a field campaign in 2019 aiming to provide forecasters with high-resolution observations and to study the storm life cycle over the lake basin. The research discussed here used the S-band polarimetric Tanzania radar from the field campaign to investigate the diurnal cycle of the convective mode over the lake. We classified the lake storms occurring during the two wet seasons into six different convective modes and present their diurnal evolution, organization, and main radar-based attributes, thereby extending the knowledge of convection on the lake. The result is the creation of a “convection catalog for Lake Victoria,” using the operational forecast lake sectors, and defining the exact times for the different timeslots resulting from the HIGHWAY project for the marine forecast. This will inform methods to improve the marine operational forecasts for Lake Victoria, and to provide the basis for new Standard Operation Procedures (SOP) for severe weather surveillance and warning.

Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5

Abstract. Isolated deep convective cloud life cycle and seasonal changes in storm properties are observed for daytime events during the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Green Ocean Amazon Experiment (GoAmazon2014/5) campaign to understand controls on storm behavior. Storm life cycles are documented using surveillance radar from initiation through maturity and dissipation. Vertical air velocity estimates are obtained from radar wind profiler overpasses, with the storm environment informed by radiosondes. Dry-season storm conditions favored reduced morning shallow cloud coverage and larger low-level convective available potential energy (CAPE) than wet-season counterparts. The typical dry-season storm reached its peak intensity and size earlier in its life cycle compared with wet-season cells. These cells exhibited updrafts in core precipitation regions (Z>35 dBZ) to above the melting level as well as persistent downdrafts aloft within precipitation adjacent to their cores. Moreover, dry-season cells recorded more intense updrafts to earlier life cycle stages as well as a higher incidence of strong updrafts (i.e., >5 m s−1) at low levels. In contrast, wet-season storms were longer-lived and featured a higher incidence of moderate (i.e., 2–5 m s−1) updrafts aloft. These storms also favored a shift in their most intense properties to later life cycle stages. Strong downdrafts were less frequent within wet-season cells aloft, indicating a potential systematic difference in draft behaviors, as linked to graupel loading and other factors between the seasons. Results from a stochastic parcel model suggest that dry-season cells may expect stronger updrafts at low levels because of larger low-level CAPE in the dry season. Wet-season cells anticipate strong updrafts aloft because of larger free-tropospheric relative humidity and reduced entrainment-driven dilution. Enhanced dry-season downdrafts are partially attributed to increased evaporation, dry-air entrainment mixing, and negative buoyancy in regions adjacent to sampled dry-season cores.

Analyzing Tornado Warning Performance during Individual Storm Life Cycles

Abstract The National Weather Service plays a critical role in alerting the public when dangerous weather occurs. Tornado warnings are one of the most publicly visible products the NWS issues given the large societal impacts tornadoes can have. Understanding the performance of these warnings is crucial for providing adequate warning during tornadic events and improving overall warning performance. This study aims to understand warning performance during the lifetimes of individual storms (specifically in terms of probability of detection and lead time). For example, does probability of detection vary based on if the tornado was the first produced by the storm, or the last? We use tornado outbreak data from 2008 to 2014, archived NEXRAD radar data, and the NWS verification database to associate each tornado report with a storm object. This approach allows for an analysis of warning performance based on the chronological order of tornado occurrence within each storm. Results show that the probability of detection and lead time increase with later tornadoes in the storm; the first tornadoes of each storm are less likely to be warned and on average have less lead time. Probability of detection also decreases overnight, especially for first tornadoes and storms that only produce one tornado. These results are important for understanding how tornado warning performance varies during individual storm life cycles and how upstream forecast products (e.g., Storm Prediction Center tornado watches, mesoscale discussions, etc.) may increase warning confidence for the first tornado produced by each storm. Significance Statement In this study, we focus on better understanding real-time tornado warning performance on a storm-by-storm basis. This approach allows us to examine how warning performance can change based on the order of each tornado within its parent storm. Using tornado reports, warning products, and radar data during tornado outbreaks from 2008 to 2014, we find that probability of detection and lead time increase with later tornadoes produced by the same storm. In other words, for storms that produce multiple tornadoes, the first tornado is generally the least likely to be warned in advance; when it is warned in advance, it generally contains less lead time than subsequent tornadoes. These findings provide important new analyses of tornado warning performance, particularly for the first tornado of each storm, and will help inform strategies for improving warning performance.

Hailstorms and rainstorms versus supercells—a regional analysis of convective storm types in the Alpine region

The behaviour of severe thunderstorms, particularly supercells, in complex terrain is still poorly understood. Utilising 6 years of radar-, lightning- and radiosounding-based thunderstorm data in the domain of the Swiss radar network, we study different thunderstorm types in separate topographical regions. We classify the storms as ordinary thunderstorms, intense and severe rainstorms, hail and severe hailstorms and supercellular storms. After identifying the overlaps between the storm categories of rainstorms, hailstorms and supercells, the life cycles of several intensity metrics are investigated. This analysis allows the identification of predictors for intensification within severe storm life cycles. One of the most important predictors is the detection of a mesocyclone in a supercell before the onset or intensification of hail. We then divide the radar domain into sub-regions ranging from the Northwestern Po Valley, the Southern Prealps, main Alpine ridge, Northern Prealps, Swiss Plateau and Jura. This regional split separates storms in different terrain complexities. An investigation of the intensity distribution of storms in each region shows a clear intensity decrease over the main Alpine ridge, intermediate values over the moderately complex Prealpine regions and peaks for the flat Po Valley and Swiss Plateau. In contrast, the highest frequency of storms is found in the Prealpine regions on each side, with a lower frequency in the flat areas and a minimum in convective activity over the main Alpine ridge.

CYGNSS Storm-Centric Tropical Cyclone Gridded Wind Speed Product

Abstract The Cyclone Global Navigation Satellite System (CYGNSS) mission has generated several new ocean surface data products. Because of its high overpass rate and ability to measure surface wind speeds through weather, these data products are typically higher temporal resolution than traditional satellite tropical cyclone (TC) data products. However, the nature of the Global Navigation Satellite Systems reflectometry (GNSS-R) signal, which is essentially a single pixelwide measurement along the CYGNSS specular point (SP) track on the ground, necessitates aggregating the wind speed data over a period of time to accurately characterize TCs in terms of intensity and structure. The standard CYGNSS level 3 (L3) wind products are averaged over 1 h, which typically is not sufficient to produce an accurate characterization. A new L3 storm-centric gridded (SCG) wind speed product is presented here. It has been developed to improve upon the standard L3 algorithm for the purpose of providing better characterization of TC wind fields over their storm life cycle. This paper describes the L3 SCG algorithm, provides examples of L3 SCG wind fields, and discusses the potential uses and limitations of the new data product.

North Atlantic Tropical Cyclone Outer Size and Structure Remain Unchanged by the Late Twenty-First Century

Abstract There is a lack of consensus on whether North Atlantic tropical cyclone (TC) outer size and structure (i.e., change in outer winds with increasing radius from the TC) will differ by the late twenty-first century. Hence, this work seeks to examine whether North Atlantic TC outer wind field size and structure will change by the late twenty-first century using multiple simulations under CMIP3 SRES A1B and CMIP5 RCP4.5 scenarios. Specifically, our analysis examines data from the GFDL High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR) and two versions of the GFDL hurricane model downscaling climate model output. Our results show that projected North Atlantic TC outer size and structure remain unchanged by the late twenty-first century within nearly all HiFLOR and GFDL hurricane model simulations. Moreover, no significant regional outer size differences exist in the North Atlantic within most HiFLOR and GFDL hurricane model simulations. No changes between the control and late-twenty-first-century simulations exist over the storm life cycle in nearly all simulations. For the simulation that shows significant decreases in TC outer size, the changes are attributed to reductions in storm lifetime and outer size growth rates. The absence of differences in outer size among most simulations is consistent with the process that controls the theoretical upper bound of storm size (i.e., Rhines scaling), which is thermodynamically invariant. However, the lack of complete consensus among simulations for many of these conclusions suggests nontrivial uncertainty in our results.

Creating physically coherent and spatially correlated perturbations to initialize high‐resolution ensembles of simulated convection

AbstractThe use of ensembles for numerical weather prediction has become common during the last decade. For global models, the generation of initial‐condition perturbations has a number of well‐tested methodologies. In ensembles that predict convective storms explicitly (i.e., km), the generation of physically realistic perturbations is less well posed. This study introduces a technique to generate physically coherent and spatially correlated (PCSC) initial‐condition perturbations that are calibrated to the environment. Ensembles of idealized CM1 simulations, initialized with either PCSC perturbations (EXP_PCSC), spatially coherent random perturbations (EXP_3KM), or Gaussian white‐noise random perturbations (EXP_WHITE), are run for both a linear convective line of storms and a single “supercell” storm to demonstrate the utility of this new perturbation technique in diverse environments. PCSC perturbations are extracted from high‐resolution simulations of boundary‐layer turbulence and random perturbations are calibrated to be the same in magnitude as PCSC perturbations. EXP_PCSC simulations spawn turbulence fastest in this study. The simulated turbulence is more robust than in other experiments more than 1 hr into the simulation, because horizontal convective rolls enhance power at the largest scales. Random perturbations are slow to generate turbulence; this problem is exacerbated when the base model state flow is nonturbulent. Due to robust turbulence, EXP_PCSC ensemble spread increases fastest during the first simulation hour and remains largest throughout the remainder of the simulations. Although EXP_PCSC spread is the largest, the sensitivity of convection to the initial perturbations varies at different times in the storm life cycle. Storms appear more sensitive to perturbations added near the time of convective initiation.

Deep Convection Initiation, Growth, and Environments in the Complex Terrain of Central Argentina during CACTI

Abstract This study characterizes the wide range of deep convective cloud life cycles and their relationships with ambient environments observed during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign near the Sierras de Córdoba (SDC) range in central Argentina. We develop a novel convective cell tracking database for the entire field campaign using C-band polarimetric radar observations. The cell tracking database includes timing, location, area, depth, merge/split information, microphysical properties, collocated satellite-retrieved cloud properties, and sounding-derived environmental conditions. Results show that the SDC exerts a strong control on convection initiation (CI) and growth. CI preferentially occurs east of the SDC ridge during the afternoon, and cells often undergo upscale growth through the evening as they travel eastward toward the plains. Larger and more intense cells tend to occur in more unstable and humid low-level environments, and surface-based cells are stronger than elevated cells. Midtropospheric relative humidity and vertical wind shear also jointly affect the size and depth of the cells. Rapid cell area growth rates exhibit dependence on both large environmental wind shear and low-level moisture. Evolution of convective cell macro- and microphysical properties are strongly influenced by convective available potential energy and low-level humidity, as well as the presence of other cells in their vicinity. This cell tracking database demonstrates a framework that ties measurements from various platforms centering around convective life cycles to facilitate process understanding of factors that control convective evolution. Significance Statement The purpose of this study is to develop a framework that ties coordinated radar, satellite, and radiosonde measurements around tracking convective storm life cycles to facilitate process understanding of atmospheric environments that control storm evolution. The processes coupling storm life cycles and local environments remain inadequately understood and are poorly represented in weather and climate models. Our results demonstrate the importance of atmospheric instability, low- and midtropospheric moisture, changes of wind with height, and interactions among nearby storms in affecting the formation and growth of convective storms. The storm database developed in this work enables future studies for comprehensive exploration of processes that lead to improved mechanistic understanding of storm evolution and their representations in models.

Diagnosis and modelling of two destructive derecho events in European Russia in the summer of 2010

In the summer of 2010, European Russia experienced an unprecedented high air temperature, catastrophic wildfires, heavy air pollution, but also several severe convective storms. Two of them occurring on June 27 and July 29 had a particularly high intensity and resulted in unprecedented forest damage. In this study, we estimate storm-related forest damage using Landsat images and analyse the synoptic-scale and mesoscale peculiarities of these storms formation and evolution using satellite and reanalyses data, surface observations, and mesoscale numerical simulation. The total area of stand-replacing windthrow caused by these two storms amounts to 1250 km2. We found for both events that dark-coniferous and pine forests were more impacted than deciduous and re-grown forests. Damage track length exceeds 500 km for one storm and 600 km for another; therefore, we classify them as derecho events, which are documented for the first time in Russia. Formation of both derecho-producing mesoscale convective systems (MCSs) was triggered by fast-moving waves formed on the polar front under conditions of substantial temperature gradients on a western flank of long-lived blocking anticyclones in their termination dates. Backward trajectories analysis shows that advection from the Caspian Sea was one of the sources of high atmospheric water content during the MCSs formation. Both MCSs developed within environments of moderate to strong convective instability and extremely high wind shear due to strong midlevel jet stream. We performed convection-permitting simulation of storms using the WRF model started with the initial data of CFSR and ERA5 reanalysis. For the event of June 27, the simulations with both initial conditions underestimate the maximum wind gusts since the model reproduces only a squall line without dominating derecho-producing storm. For the event of July 29, the ERA5 based simulation successfully reproduced the main features of the storm life cycle, while the CFS-based simulation substantially underestimated the wind gusts and the storm-affected area. Our results highlight the importance of the atmospheric blocking influence on the convective severe storms formation and development, which deserves further research.

Comparing the Thermal Structures of Tropical Cyclones Derived From Suomi NPP ATMS and FY-3D Microwave Sounders

Accurate information on the thermal structures of tropical cyclones (TCs) is essential for monitoring and forecasting their intensity and location. In this study, a scene-dependent 1-D variation (SD1DVAR) algorithm is developed to retrieve atmospheric temperature and moisture profiles under all-weather conditions. In SD1DVAR, the background and observation error matrix varies according to the scattering intensity. Especially, the observation error matrix increases in precipitating atmospheres due to a larger uncertainty in the forward operator. With the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) satellite, SD1DVAR can retrieve better thermal structures in the storm life cycle than NOAA Microwave Integrated Retrieval System (MIRS). Comparing with the aircraft dropsonde observations, the temperature and humidity errors from SD1DVAR are about 3 K and 20%, respectively, whereas those from MIRS are around 4 K–5 K and 30%, respectively. SD1DVAR is also applied for Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) onboard FengYun-3D (FY-3D) satellite. The MWTS and MWHS data sets are first combined into a single Comprehensive MicroWave Suite (CMWS) data stream and then used to retrieve the hurricane thermal structures. It is shown that the hurricane structure from CMWS is very similar to that from ATMS. However, due to the availability of 118-GHz measurements from the CMWS, the hurricane temperature vertical structure is better resolved, and the humidity error is also reduced by about 5%.

Delayed Tornadogenesis Within New York State Severe Storms

Past observational research into tornadoes in the northeast United States (NEUS) has focused on integrated case studies of storm evolution or common supportive environmental conditions. A repeated theme in the former studies is the influence that the Hudson and Mohawk Valleys in New York State (NYS) may have on conditions supportive of tornado formation. Recent work regarding the latter has provided evidence that environments in these locations may indeed be more supportive of tornadoes than elsewhere in the NEUS. In this study, Weather Surveillance Radar–1988 Doppler data from 2008 to 2017 are used to investigate severe storm life cycles in NYS. Observed tornadic and non-tornadic severe cases were analyzed and compared to determine spatial and temporal differences in convective initiation (CI) points and severe event occurrence objectively within the storm paths. We find additional observational evidence supporting the hypothesis the Mohawk and Hudson Valley regions in NYS favor the occurrence of tornadogenesis: the substantially longer time it takes for storms that initiate in western NYS and Pennsylvania to become tornadic compared to storms that initiate in either central or eastern NYS. An analysis of approximate near-storm environments using the 13-km Rapid Refresh (RAP) is used to confirm that the long-lived storms encounter more tornado-favorable conditions leading up to tornadogenesis in the NYS valley regions.

The Observed Influence of Tropical Convection on the Saharan Dust Layer

AbstractInteractions between convection and the Saharan Air Layer in the tropical Atlantic Ocean are quantified using a novel compositing technique that leverages geostationary cloud observations to add temporal context to the polar orbiting CloudSat and the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites allowing aerosol optical depth (AOD) changes to be tracked throughout a typical convective storm life cycle. Four years of CALIPSO observations suggests that approximately 20% of the dust mass in every 10° longitude band between 10°W and 80°W is deposited into the ocean. Combining a new convective identification algorithm based on hourly geostationary cloud products with AODdust profiles along the CALIPSO track reveals that wet scavenging by convection is responsible for a significant fraction of this deposition across the Atlantic. Composites of 4 years of convective systems reveal that, on average, convection accounts for 15% ± 7% of the dust deposition in each longitude band relative to preconvective amounts, implying that dry deposition and scavenging by nonconvective events are responsible for the remaining 85% of dust removal. In addition, dust layers are detrained at upper levels of the atmosphere between 8 and 12 km by convective storms across the Atlantic. The dust budget analysis presented here indicates that convection lofts 1.5% ± 0.6% of dust aerosol mass to altitudes greater than 6 km. This may have significant implications for cloud formation downstream of convection since lofted dust particles can act as effective ice nucleating particles, altering cloud microphysical and radiative properties, latent heating, and precipitation rates.

Assessment of the Representation of West African Storm Lifecycles in Convection‐Permitting Simulations

AbstractConvection‐permitting models perform better at representing the diurnal cycle and the intermittency of convective rainfall over land than parameterized‐convection models. However, most of the previous model assessments have been from an Eulerian point of view, while key impacts of the rainfall depend on a storm‐relative perspective of the system lifecycle. Here a storm‐tracking algorithm is used to generate storm‐centered Lagrangian lifecycle statistics of precipitation over West Africa from regional climate model simulations and observations. Two versions of the Met Office Unified Model with and without convection parameterization at 4‐, 12‐, and 25‐km resolution were analyzed. In both of the parameterized‐convection simulations, storm lifetimes are too short compared to observations, and storms have no preferred propagation direction; the diurnal cycle of initiations and dissipations and the spatial distribution of storms are also inaccurate. The storms in the convection‐permitting simulations have more realistic diurnal cycles and lifetimes but are not as large as the largest observed storms. The convection‐permitting model storms propagate in the correct direction, although not as fast as observed storms, and they have a much improved spatial distribution. The rainfall rate of convection‐permitting storms is likely too intense compared to observations. The improved representation of the statistics of organized convective lifecycles shows that convection‐permitting models provide better simulation of a number of aspects of high‐impact weather, which are critical to climate impacts in this important geographic region, providing the high rainfall rates can be taken into account.

Convective initiation and storm life cycles in convection‐permitting simulations of the Met Office Unified Model over South Africa

Convective initiation is a challenge for convection‐permitting models due to its sensitivity to sub‐km processes. We evaluate the representation of convective storms and their initiation over South Africa during four summer months in Met Office Unified Model simulations at a 1.5‐km horizontal grid length. Storm size distributions from the model compare well with radar observations, but rainfall in the model is predominantly produced by large storms (50 km in diameter or larger) in the evening, whereas radar observations show that most rainfall occurs throughout the afternoon, from storms 10–50 km in diameter. In all months, the modelled maximum number of storm initiations occurs at least 2 hr prior to the radar‐observed maximum. However, the diurnal cycle of rainfall between the model and observations compares well, suggesting that the numerous storm initiations in the simulations do not produce much rainfall. Modelled storms are generally less intense than those in radar observations, especially in early summer. In February, when tropical influences dominate, the simulated storms are of similar intensity to observed storms. Simulated storms tend to reach their peak intensity in the first 15 min after initiation, then gradually become less intense as they grow. In radar observations, storms reach their peak intensity 15 min into their life cycle, stay intense as they grow larger, then gradually weaken after they have reached their maximum diameter. Two November case studies of severe convection are analysed in detail. A higher resolution grid length initiates convection slightly earlier (300 m as opposed to 1.5 km) with the same scientific settings. Two 1.5 km simulations that apply more subgrid mixing have delayed convective initiation. Analysis of soundings indicates little difference in the convective indices, suggesting that differences in convection may be attributed to the choice of subgrid mixing parameters.

Radar-Observed Bulk Microphysics of Midlatitude Leading-Line Trailing-Stratiform Mesoscale Convective Systems

AbstractIn 2013, all NEXRAD WSR-88D units in the United States were upgraded to dual polarization. Dual polarization allows for the identification of precipitation particle shape, size, orientation, and concentration. In this study, dual-polarization NEXRAD observations from 34 recent events are used to identify the bulk microphysical characteristics of a specific subset of mesoscale convective systems (MCSs), the leading-line trailing-stratiform (LLTS) MCS. NEXRAD observations are used to examine hydrometeor distributions in relative altitude to the 0°C level and as a function of storm life cycle, precipitation source (convective or stratiform), and storm environment. The analysis reveals that graupel particles are the most frequently classified hydrometeor class in a layer extending from the 0°C-level altitude to approximately 5 km above within the convective region. Below the 0°C level, rain is the most frequently classified hydrometeor, with small hail and graupel concentrations present throughout the LLTS system’s life cycle. The stratiform precipitation region contains small graupel concentrations in a shallow layer above the 0°C level, with pristine ice crystals being classified as the most frequently observed hydrometeor at higher altitudes and snow aggregates being classified as the most frequently observed hydrometeor at lower altitudes above the environmental 0°C level. Variations in most unstable convective available potential energy (MUCAPE) have the largest impact on the vertical distribution of hydrometeors, because more-unstable environments are characterized by a greater production of rimed ice.

An overview of the TROPICS NASA Earth Venture Mission.

The Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture‐Instrument (EVI‐3) program. The overarching goal for TROPICS is to provide nearly all‐weather observations of 3D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high‐value science investigations of tropical cyclones. TROPICS will provide rapid‐refresh microwave measurements (median refresh rate better than 60 min for the baseline mission) which can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm life cycle. TROPICS comprises six CubeSats in three low‐Earth orbital planes. Each CubeSat will host a high‐performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapour profiles using three channels near the 183 GHz water vapour absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher‐resolution water vapour channels), and a single channel near 205 GHz which is more sensitive to precipitation‐sized ice particles. This observing system offers an unprecedented combination of horizontal and temporal resolution to measure environmental and inner‐core conditions for tropical cyclones on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid‐update radiance or retrieval data. Launch readiness is currently projected for late 2019.

Convective Storm Life Cycle and Environments near the Sierras de Córdoba, Argentina

AbstractSatellite observations have revealed that some of the world’s most intense deep convective storms occur near the Sierras de Córdoba, Argentina, South America. A C-band, dual-polarization Doppler weather radar recently installed in the city of Córdoba in 2015 is now providing a high-resolution radar perspective of this intense convection. Radar data from two austral spring and summer seasons (2015–17) are used to document the convective life cycle, while reanalysis data are utilized to construct storm environments across this region. Most of the storms in the region are multicellular and initiate most frequently during the early afternoon and late evening hours near and just east of the Sierras de Córdoba. Annually, the peak occurrence of these storms is during the austral summer months of December, January, and February. These Córdoba radar-based statistics are shown to be comparable to statistics derived from Tropical Rainfall Measuring Mission Precipitation Radar data. While generally similar to storm environments in the United States, storm environments in central Argentina tend to be characterized by larger CAPE and weaker low-level vertical wind shear. One of the more intriguing results is the relatively fast transition from first storms to larger mesoscale convective systems, compared with locations in the central United States.

A 15‐year hail streak climatology for the Alpine region

In this study, we present a unique 15‐year hail streak climatology for Switzerland based on volumetric radar reflectivity. Two radar‐based hail detection products and an automatic thunderstorm‐tracking algorithm were reprocessed for the extended convective season (April–September) between 2002 and 2016. More than 1.1 million convective cells were automatically tracked over the full radar domain, and over 191,000 storms and 31,000 hail streaks in the considered subdomain were selected for analysis following consistency and robustness tests.The year‐to‐year variability in the number of hailstorms reveals two types of convective seasons: (a) a few seasons with hail frequency far above the average, and (b) all other years with an average number of hailstorms. A high number of hailstorms in a particular year is not correlated with a higher number of convective storms in general, but is related to a greater fraction of severe storms.Convection initiation, hail initiation, and hail frequency maxima are located along the southern and northern foothills over the pre‐Alpine area and over the Jura mountains. Few hail streaks are present over the Alpine main ridge. Hail streak frequency and location is found to be strongly dependent on the synoptic‐scale weather regimes. This is important for monthly and seasonal outlooks, as well as for climate modelling.Analysis of storm life cycles shows that: (a) the majority of hail swaths contain only a single hail streak, (b) severe storms follow a more rapid evolution during their initial stages than do less severe storms, and (c) severe storms produce more spatially extended hail streaks.Finally, significant seasonal and diurnal cycles are present in most of the considered storm characteristics.

The Identification of Hail Storms in the Early Stage Using Time Series Analysis

AbstractThis study investigates the characteristics of hail storms and cumulonimbus storms in China from 2005 to 2016. Ten features are proposed to identify storm cells that can produce hail, especially in the early stage of hail formation. These features describe hail storms based on three factors: the height and thickness of the cell core, the radar echo intensity, and the overhang structure and the horizontal reflectivity gradient. The 10 features are transformed into two‐dimensional comprehensive features by principal component analysis (PCA). The two comprehensive features are named the volume measurement comprehensive feature (VMCF) and the height‐gradient comprehensive feature (HGCF). Through an analysis of 49 hail cases and 35 heavy rainfall cases with S‐band radar data, the time series exhibit a distinct increase in VMCF or HGCF values in the early stage of a hail storm. However, the VMCF and HGCF values of heavy rainfall events remain relatively stable throughout the storm life cycle. An experiment involving real‐storm events, including 31 hail cases and 33 heavy rainfall cases, indicated that the probability of detection of hail storms was 93.33% and the false alarm ratio was 15.66%. In the cases that could be successfully identified as hail storms, 80.00% were detected within 18 min of reaching a hail storm reflectivity of 40 dBZ.