Cold Pool Research Articles

Simulation and Analysis of the Mesoscale Vortex Affecting the “21·7” Extreme Rainstorm in Henan

From 17 to 22 July 2021, the “21·7” extreme rainfall event (“21·7” ERE) hit Henan Province, breaking the record for mainland China with a maximum hourly rainfall of 201.9 mm at the Zhengzhou station. The long-lived (20 h) mesoscale Huang-Huai vortex (HHV) was an important system that directly affected the major rainfall stage, including the extreme hourly rainfall. This study investigates the formation and development mechanism of the HHV, as well as its association with the simulation of extreme hourly rainfall through numerical simulations. The simulated rainfall and radar composite reflectivity were in good agreement with the observations, thus effectively reproducing the generation and developmental process of the HHV. The analysis results showed that the HHV initially formed at 850 hPa on 19 July at 1800 UTC and eventually developed to 550 hPa. The positive feedback formed by the horizontal convergence and vertical vorticity transport was the main mechanism leading to the generation and deepening of the HHV. The stretching effect (STR) term played an absolutely dominant role in the increase in the vorticity tendency, and it primarily originated from the coupling effect of boundary layer jets (BLJs) and synoptic-weather-system-related low-level jets (SLLJs). The accurate simulation of the HHV allowed the early rainfall to reasonably reproduce the surface cold pool near the Zhengzhou station, and then the cooperation of the SLLJs, the BLJs, and the cold pool made the simulated extreme hourly rainfall exactly close to the Zhengzhou station, but with a weaker intensity, due to the fact that the HHV moved northeastward after its formation, resulting in a narrow range of southerly flow in southern Henan, which is not conducive to convective triggering in the southerly flow.

The role of the cold pool in a mountain-to-plain and plain-to-mountain squall line case in the south of the Yangtze River in China

A squall line event that occurred in the south of the Yangtze River in China on 4 May 2020 was simulated using the WRF model and 3DVAR data assimilation. The radar radial wind, reflectivity, and conventional observation data were assimilated in a cycling interval of 15 min. The main findings from the examination of the development mechanisms of the squall line are as follows. The simulation effectively reproduced the development and evolution of the squall line. The squall line strengthened from the Wuling Mountains to the Dongting Lake Plain, moved eastwards and developed to its strongest stage over the plains, before weakening from thereon to the Mulianjiu Mountains. When the squall line moved from the mountains to the plains, the convergence of the airflow in front of the squall line increased because of the strengthening of the near-surface easterly airflow over the plains. Concurrently, the intensity of the cold pool behind the squall line decreased, while the low-level vertical wind shear over the plains increased. This reduced the gap between the cold pool and vertical wind shear. The low-level upward airflow in front of the cold pool tended to be vertical, which was conducive to the development and maintenance of the squall line. When the squall line moved eastwards from the plains to the mountains, the convergence of the airflow in front of the squall line weakened because of the weakening of the surface easterly airflow over the mountains. Concurrently, the intensity of the cold pool behind the squall line increased, while the low-level vertical wind shear in front of the squall line significantly declined. The intensity of the cold pool significantly exceeded the low-level vertical wind shear, inducing a tendency for the low-level upward airflow in front of the cold pool to tilt towards the cold pool, which was not conducive to the development and maintenance of the squall line. This was a reason why the squall line moved eastwards faster after going up the mountains. Based on these observational and simulation results, physical conceptual models for the enhancement of squall lines from the mountains to the plains and their weakening from the plains to the mountains have been preliminarily developed.

The Development of Atmospheric Bores in Non‐Uniform Baroclinic Environments and Their Roles in the Maintenance, Structure, and Evolution of an MCS

AbstractThis study used radar observations and a high‐resolution numerical simulation to explore the interactions between an mesoscale convective system (MCS), cold pool outflows, and atmospheric bores in a non‐uniform baroclinic environment. The bores were generated by a nocturnal MCS that occurred on 2–3 June 2017 over the southern North China Plain. The goal of this investigation is to determine how the structure of bores varied within this non‐uniform environment and whether and how the bores would maintain the MCS and alter its structure. To the southwest of the MCS, where there was large CAPE and a well‐mixed boundary layer, discrete convection initiation occurred behind a single radar fine line (RFL) maintaining the propagation of the MCS. To the southeast of the MCS, multiple RFLs were found suggesting the generation of an undular bore in an environment containing an intense nocturnal stable boundary layer with dry upper layers and little CAPE. Hydraulic and nonlinear theory were applied to the simulation of the MCS revealing that the differences in the bore evolution depended on both the characteristics of the cold pool and the variations in the ambient environment. Thus, the characteristics of the ambient environment and the associated differences in bore structure impacted the maintenance and organization of the MCS. This study implies the importance of an accurate representation of the low‐level ambient environment and the microphysics and kinematics within the MCS to accurately simulate and forecast cold pools, the generation and evolution of bores, and their impact on nocturnal MCSs.

Detecting Cold Pool Family Trees in Convection Resolving Simulations

AbstractRecent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them in time, thereby distinguishing their active gust fronts and the “offspring” rain cells generated nearby. To accomplish these tasks, CoolDeTA utilizes a combination of thermodynamic and dynamical variables and examines the spatial and temporal relationships between cold pools and rain events. We demonstrate that CoolDeTA can reconstruct CP family trees. Using CoolDeTA we can contrast radiative convective equilibrium (RCE) and diurnal cycle CP dynamics, as well as cases with vertical wind shear and without. We show that the results obtained are consistent with a conceptual model where CP triggering of children rain cells follows a simple birth rate, proportional to a CP's gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing—resulting in essentially run‐away mesoscale excitations generated by a single parent rain cell and its CP.

A Parameterization for Cloud Organization and Propagation by Evaporation‐Driven Cold Pool Edges

AbstractWhen the negatively buoyant air in the cloud downdrafts reaches the surface, it spreads out horizontally, producing cold pools. A cold pool can trigger new convective cells. However, when combined with the ambient vertical wind shear, it can also connect and upscale them into large mesoscale convective systems (MCS). Given the broad spectrum of scales of the atmospheric phenomenon involving the interaction between cold pools and the MCS, a parameterization was designed here. Then, it is coupled with a classical convection parameterization to be applied in an atmospheric model with an insufficient spatial resolution to explicitly resolve convection and the sub‐cloud layer. A new scalar quantity related to the deficit of moist static energy detrained by the downdrafts mass flux is proposed. This quantity is subject to grid‐scale advection, mixing, and a sink term representing dissipation processes. The model is then applied to simulate moist convection development over a large portion of tropical land in the Amazon Basin in a wet and dry‐to‐wet 10‐days period. Our results show that the cold pool edge parameterization improves the organization, longevity, propagation, and severity of simulated MCS over the Amazon and other different continental areas.

U‐Net Segmentation for the Detection of Convective Cold Pools From Cloud and Rainfall Fields

AbstractConvective cold pools (CPs) mediate interactions between convective rain cells and help organize thunderstorm clusters, in particular mesoscale convective systems and extreme rainfall events. Unfortunately, the observational detection of CPs on a large scale has been hampered by the lack of relevant near‐surface data. Unlike numerical studies, where fields, such as virtual temperature or wind, are available at high resolution and frequently used to detect CPs, observational studies mainly identify CPs based on surface time series, for example, from weather stations or research vessels—thus limiting studies to a regional scope. To expand to a global scope, we here develop and evaluate a methodology for CP detection that relies exclusively on data with (a) global availability and (b) high spatiotemporal resolution. We trained convolutional neural networks to segment CPs in high‐resolution cloud‐resolving simulation output by deliberately restricting ourselves to only cloud top temperature and rainfall fields. Apart from simulations, such data are readily available from geostationary satellites that fulfill both (a) and (b). The networks employ a U‐Net architecture, popular with image segmentation, where spatial correlations at various scales must be learned. Despite the restriction imposed, the trained networks systematically identify CP pixels. Looking ahead, our methodology aims to reliably detect CPs over tropical land from space‐borne sensors on a global scale. As it also provides information on the spatial extent and the relative positioning of CPs over time, our method may unveil the role of CPs in convective organization.

Morphology and growth of convective cold pools observed by a dense station network in Germany

AbstractThis study explores the morphology of convective cold pools, that is, their size, shape, and structure, as well as factors controlling their growth using surface‐based observations of the Field Experiment on Sub‐mesoscale Spatio Temporal Variability in Lindenberg (FESSTVaL). FESSTVaL featured a dense network of 99 custom‐built, low‐cost measurement stations covering a circular area of 30 km in diameter at sub‐mesoscale resolution (distances between 0.1 and 4.8 km) and was held at the Lindenberg Observatory near Berlin (Germany) from May–August 2021. The station network sampled 42 cold‐pool events during the 103‐day measurement period. The morphological properties of cold pools are derived by interpolating the temperature observations spatially to a Cartesian grid and defining cold pools as individual objects at a given time with a temperature perturbation stronger than K. The sample of 1232 cold‐pool objects with extents sufficiently captured by the network has a median equivalent diameter of 8.5 km. The objects exhibit aspect ratios between 1.5 and 1.6 independent of their size and strength, meaning they are generally not circularly shaped. On average, is strongest at the cold‐pool center and decreases linearly towards the edge. For the growth phase of four selected events, the cold‐pool object area scales linearly with the radar‐observed, area‐integrated rainfall accumulation, while the object‐mean temperature perturbation strengthens most efficiently early in the life cycle. The global, radial expansion velocity decreases as the cold pool gets stronger and larger, in contradiction of density‐current theory. Instead, is a better predictor of the expansion rate. These findings identify cold‐air import by precipitation, through both evaporative cooling and convective downdrafts, as the dominant driver of the observed growth.

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

AbstractThis study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (Nd). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that Nd is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low Nd characterizes the open cellular structure with a high in‐cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open‐cell clouds produce larger and deeper cold pools compared to closed‐cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

Overlap between the Mid-Atlantic Bight Cold Pool and offshore wind lease areas

AbstractThe Mid-Atlantic Cold Pool is a seasonal mass of cold bottom water that extends throughout the Mid-Atlantic Bight (MAB). Formed from rapid vernal surface warming, the Cold Pool dissipates in the fall due to mixing events such as storms. The Cold Pool supports a myriad of MAB coastal ecosystems and economically valuable commercial and recreational fisheries. Offshore wind energy has been rapidly developing within the MAB in recent years. Studies in Europe demonstrate that offshore wind farms can impact ocean mixing and hence seasonal stratification; there is, however, limited information on how MAB wind development will affect the Cold Pool. Seasonal overlap between the Cold Pool and pre-construction wind lease areas at varying distances from shore in the MAB was evaluated using output from a data-assimilative ocean model. Results highlight overlap periods as well as a thermal gradient that persists after bottom temperatures warm above the threshold typically used to identify the Cold Pool. These results also demonstrate cross-shelf variability in Cold Pool evolution. This work highlights the need for more focused ocean modeling studies and observations of wind farm effects on the MAB coastal environment.

Effects of a preexisting cold pool on the initiation of an extreme rainfall in southern Xinjiang

On June 15, 2021, the Hotan region of southern Xinjiang was hit by an extreme rainfall event. A numerical simulation of the storm process, with a resolution of 3 km, was conducted to analyze the initiation mechanism of the rainfall. The results show that lifting conditions play a crucial role in triggering convection, compared to moisture and stratification conditions. The easterly jet changes the direction in the western part of the Tarim Basin and speeds up, creating a zone of high wind speeds in front of Kunlun Mountain's northern slope, which provides favorable conditions for convection initiation. A remarkable feature during this process is the effect of a preexisting distant cold pool on the southern slope of Tianshan Mountain. The cold pool impedes the easterly development of the easterly airflow in the basin, causing it to turn northward, and accelerates the mountain front airflow in front of Kunlun Mountain. The inner dynamic mechanism is a strengthening of the low-level horizontal pressure gradient between the cold pool and the low-pressure belt along Kunlun Mountain. The numerical sensitivity experiments also highlight the key role the distant cold pool plays in the development of the high-speed wind belt ahead of the mountain and causes convection to start 4 h earlier. These results will serve as a valuable reference for future studies on the formation process of convection and improve the understanding of precipitation forecast in arid and semi-arid regions.

Using Radiosonde Observations to Assess the “Three Ingredients Method” to Forecast QLCS Mesovortices

Abstract A technique used widely to forecast the potential for QLCS mesovortices is known as the “Three Ingredients Method” (3IM). The 3IM states that mesovortices are favored where 1) the QLCS cold pool and ambient low-level shear are said to be nearly balanced or slightly shear dominant, 2) where the component of the 0–3-km wind shear normal to the convective line is ≥30 kt (1 kt ≈ 0.51 m s−1), and 3) where a rear-inflow jet or enhanced outflow causes a surge or bow along the convective line. Despite its widespread use in operational settings, this method has received little evaluation in formal literature. To evaluate the 3IM, radiosonde observations are compared to radar-observed QLCS properties. The distance between the gust front and high reflectivity in the leading convective line (the “U-to-R distance”), the presence of rear-inflow surges, and mesovortices (MVs) were each assessed across 1820 line segments within 50 observed QLCSs. Although 0–3-km line-normal wind shear is statistically different between MV-genesis and null segments, values are ≤30 kt for 44% of MV-genesis segments. The 0–6-km line-normal wind shear also shows strong discrimination between MV-genesis and null segments and displays the best linear relationship of the U-to-R distance (a measure of system balance) among layers tested, although the scatter and overlap in distributions suggest that many factors can impact MV genesis (as expected). Overall, most MVs occur where the U-to-R distance lies between −5 and 5 km in the presence of a rear-inflow surge, along with positive 0–1-km wind shear, 0–3-km wind shear > 10 kt, and 0–6-km wind shear > 20 kt (all line-normal). Significance Statement Near the leading edge of thunderstorm lines, areas of rotation that can produce tornadoes and strong winds (“mesovortices”) often develop rapidly. Despite advances in understanding mesovortices, few operational guidelines exist to anticipate their genesis. One popular method used to forecast mesovortices—the “Three Ingredients Method”—is evaluated in this study. Our work confirms the importance of two of the ingredients—a surge of outflow winds and thunderstorms that stay nearly atop the leading edge of the outflow. However, we find that many mesovortices occur below the threshold of low-level wind shear ascribed by the forecast method. Refinements to the method are suggested, including the favorable distance between the leading edge of the outflow and thunderstorm updrafts and lower bounds of wind shear over multiple layers, below which mesovortices may be unlikely.

Assessing Memory in Convection Schemes Using Idealized Tests

AbstractTwo assumptions commonly applied in convection schemes—the diagnostic and quasi‐equilibrium assumptions—imply that convective activity (e.g., convective precipitation) is controlled only by the large‐scale (macrostate) environment at the time. In contrast, numerical experiments indicate a “memory” or dependence of convection also on its own previous activity whereby subgrid‐scale (microstate) structures boost but are also boosted by convection. In this study we investigated this memory by comparing single‐column model behavior in two idealized tests previously executed by a cloud‐resolving model (CRM). Conventional convection schemes that employ the diagnostic assumption fail to reproduce the CRM behavior. The memory‐capable org and Laboratoire de Météorologie Dynamique Zoom cold pool schemes partially capture the behavior, but fail to fully exhibit the strong reinforcing feedbacks implied by the CRM. Analysis of this failure suggests that it is because the CRM supports a linear (or superlinear) dependence of the subgrid structure growth rate on the precipitation rate, while the org scheme assumes a sublinear dependence. Among varying versions of the org scheme, the growth rate of the org variable representing subgrid structure is strongly associated with memory strength. These results demonstrate the importance of parameterizing convective memory, and the ability of idealized tests to reveal shortcomings of convection schemes and constrain model structural assumptions.

The Role of Passive Cloud Volumes in the Transition From Shallow to Deep Atmospheric Convection

AbstractProperly capturing the transition from shallow to deep convection remains a major shortcoming of numerical weather and climate models due to poor understanding of the physical processes controlling this transition. Although recent studies suggest shallow preconditioning and cold pool feedbacks to be important, these studies are unable to explain the initial phase of the transition. We identify an additional mechanism, namely the interaction between passive cloud volumes (PCV)—old cumulus cloud volumes in the decaying stage—and updrafts, and discuss the potential role of this mechanism in the transition from shallow to deep convection. We show that the number of updrafts interacting with PCV is very large during the transition and the updrafts better preserve their buoyancy due to entrainment of much moister air. We argue that PCV might play an important role in the transition and cumulus parameterizations could therefore benefit from including them.

The Atmospheric Boundary Layer and the Initiation of the MJO

Abstract The Indian Ocean is a frequent site for the initiation of the Madden–Julian oscillation (MJO). The evolution of convection during MJO initiation is intimately linked to the subcloud atmospheric mixed layer (ML). Much of the air entering developing cumulus clouds passes through the cloud base; hence, the properties of the ML are critical in determining the nature of cloud development. The properties and depth of the ML are influenced by horizontal advection, precipitation-driven cold pools, and vertical motion. To address ML behavior during the initiation of the MJO, data from the 2011/12 Dynamics of the MJO Experiment (DYNAMO) are utilized. Observations from the research vessel Revelle are used to document the ML and its modification during the time leading up to the onset phase of the October MJO. The mixed layer depth increased from ∼500 to ∼700 m during the 1–12 October suppressed period, allowing a greater proportion of boundary layer thermals to reach the lifting condensation level and hence promote cloud growth. The ML heat budget defines an equilibrium mixed layer depth that accurately diagnoses the mixed layer depth over the DYNAMO convectively suppressed period, provided that horizontal advection is included. The advection at the Revelle is significantly influenced by low-level convective outflows from the southern ITCZ. The findings also demonstrate a connection between cirrus clouds and their remote impact on ML depth and convective development through a reduction in the ML radiative cooling rate. The emergent behavior of the equilibrium mixed layer has implications for simulating the MJO with models with parameterized cloud and turbulent-scale motions.

Effects of Ocean-Land Thermal Contrast on the Organized Cloud: Preliminary Results from a Squall Line Case on Hainan Island

Using the high-resolution numerical weather research and forecasting (WRF) model, study the squall line process that occurred on Hainan Island on 22 April 2020. The findings indicate that high terrain blocks the swift accumulation of water vapor carried by the sea breeze and aids in preserving the accumulated water vapor. According to the sensitivity experiment, terrain height has minimal impact on the macroscopic effects of mesoscale weather processes. However, it does influence where the sea breeze converges. During this process, the ocean-land thermal contrast not only takes the main responsibility for the sea breeze but also leads to uplift motion, which affects the formation, intensity, and duration of the squall line. Additionally, the unstable conditions suggest that a thermal and dynamic environment promote the scale of this squall line. Utilizing the Rotunno–Klemp–Weisman theory (RKW), this study analyzes the effects of the cold pool and vertical wind shear. The analysis reveals that significant vertical wind shear at lower levels and the ground-cold pool contribute to the sustenance and growth of the squall line system. This squall line process has had the greatest impact on the Haikou area due to the strong low-level vertical wind shear and prolonged interaction with the cold pool. When the interaction between the cold pool and the vertical wind shear weakens, the squall dissipates.

Cloud Botany: Shallow Cumulus Clouds in an Ensemble of Idealized Large‐Domain Large‐Eddy Simulations of the Trades

AbstractSmall shallow cumulus clouds (<1 km) over the tropical oceans appear to possess the ability to self‐organize into mesoscale (10–100 km) patterns. To better understand the processes leading to such self‐organized convection, we present Cloud Botany, an ensemble of 103 large‐eddy simulations on domains of 150 km, produced by the Dutch Atmospheric Large Eddy Simulation model on supercomputer Fugaku. Each simulation is run in an idealized, fixed, larger‐scale environment, controlled by six free parameters. We vary these over characteristic ranges for the winter trades, including parameter combinations observed during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign. In contrast to simulation setups striving for maximum realism, Cloud Botany provides a platform for studying idealized, and therefore more clearly interpretable causal relationships between conditions in the larger‐scale environment and patterns in mesoscale, self‐organized shallow convection. We find that any simulation that supports cumulus clouds eventually develops mesoscale patterns in their cloud fields. We also find a rich variety in these patterns as our control parameters change, including cold pools lined by cloudy arcs, bands of cross‐wind clouds and aggregated patches, sometimes topped by thin anvils. Many of these features are similar to cloud patterns found in nature. The published data set consists of raw simulation output on full 3D grids and 2D cross‐sections, as well as post‐processed quantities aggregated over the vertical (2D), horizontal (1D) and all spatial dimensions (time‐series). The data set is directly accessible from Python through the use of the EUREC4A intake catalog.

Multiscale Analysis of a Record-Breaking Predecessor Rain Event Ahead of Typhoon Danas (2019) in Jiangsu, China

On 17 July 2019, an unusually intense rainfall occurred in the central-eastern part of Jiangsu Province in China, resulting in a record-breaking daily precipitation of 286.4 mm at the Rugao station, not seen since 1961. A comprehensive analysis was conducted on various multiscale characteristics of the initial rain event, such as the large-scale surroundings, moisture transport, triggering and maintenance mechanisms, and microphysical characteristics. Multi-sources of data were utilized, such as reanalysis data, automatic weather stations, wind-profiling radar, laser-optical Particle Size Velocity instruments, soundings, S-band dual-polarization radar, and a Lagrangian model. The findings suggest that the intense precipitation in Rugao resulted from the convergence of the warm and moist airflow from Typhoon Danas and the cold air moving southward from the north, along with the ample moisture and energy provided by the circulation of Typhoon Danas. Convection, which showed good consistency with the intense precipitation process, was initiated by mesoscale temperature gradients and wind field convergence. This was associated with the intrusion of a near-surface cold pool and the maintenance of a ground convergence line in the Rugao area. This convection exemplified a standard system of warm clouds with high precipitation efficacy. It had a high concentration of raindrops, especially large ones, resulting in record-breaking precipitation in a short amount of time.

Air‐Sea Heat Fluxes Associated With Convective Cold Pools

AbstractHigh‐resolution air‐sea observations collected by a suite of remotely‐piloted uncrewed surface vehicles (USV) provide new insight on surface latent and sensible heat fluxes associated with convective cold pools over the eastern Pacific Intertropical Convergence Zone (ITCZ). Convective cold pools are linked to isolated, heavily precipitating cells over the ocean that yield downdrafts of evaporatively‐cooled air that spreads out horizontally in all directions and are characterized by strong air temperature gradients and horizontal wind speeds. Cold pool frontal signatures are identified based on air temperature depression criteria of −1.5°C in 10 min or less, resulting in a total of 276 events observed within the eastern Pacific ITCZ across 590 total seadays of data from 10 drones over the course of 3 years. Composite analysis reveals enhanced latent and sensible heat fluxes from the ocean to the atmosphere immediately following the frontal passage, and a decomposition of the bulk flux formulas indicates that variations in latent heat flux are largely influenced by the anomalous wind field (i.e., the cold pool gust front) acting on the mean background air‐sea moisture gradient, while variations in sensible heat flux are largely influenced by the mean background wind acting on the anomalous air‐sea temperature gradient (i.e., the cold pool temperature front). High‐frequency variations in wind speed and velocity are further explored in the context of “gustiness” and averaging intervals used in bulk flux algorithms. A case study is also presented for a convective cold pool event captured by a traveling mesoscale network, or mesonet, of USVs.

What caused the unseasonal extreme dust storm in Uzbekistan during November 2021?

An unseasonal dust storm hit large parts of Central Asia on 4–5 November 2021, setting records for the column aerosol burden and fine particulate concentration in Tashkent, Uzbekistan. The dust event originated from an agropastoral region in southern Kazakhstan, where the soil erodibility was enhanced by a prolonged agricultural drought resulting from La Niña-related precipitation deficit and persistent high atmospheric evaporative demand. The dust outbreak was triggered by sustained postfrontal northerly winds during an extreme cold air outbreak. The cold air and dust outbreaks were preceded by a chain of processes consisting of recurrent synoptic-scale transient Rossby wave packets over the North Pacific and North Atlantic, upper-level wave breaking and blocking over Greenland, followed by high-latitude blocking over Northern Europe and West Siberia, and the equatorward shift of a tropopause polar vortex and cold pool into southern Kazakhstan. Our study suggests that the historic dust storm in Uzbekistan was a compound weather event driven by cold extreme, high winds, and drought precondition.

FESSTVaL: The Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg

Abstract Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.