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This study synthesizes the results of 13 high-resolution simulations of deep convective updrafts forming over idealized terrain using environments observed during the RELAMPAGO and CACTI field projects. Using composite soundings from multiple observed cases, and variations upon them, we explore the sensitivity of updraft properties (e.g., size, buoyancy, and vertical pressure gradient forces) to influences of environmental relative humidity, wind shear, and mesoscale orographic forcing that support or suppress deep convection initiation (CI). Emphasis is placed on differentiating physical processes affecting the development of updrafts (e.g., entrainment-driven dilution of updrafts) in environments typifying observed successful and null (i.e., no CI despite affirmative operational forecasts) CI events. Thermally induced mesoscale orographic lift favors the production of deep updrafts originating from ∼1- to 2-km-wide boundary layer thermals. Simulations without terrain forcing required much larger (∼5-km-wide) thermals to yield precipitating convection. CI outcome was quite sensitive to environmental relative humidity; updrafts with increased buoyancy, depth, and intensity thrived in otherwise inhospitable environments by simply increasing the free-tropospheric relative humidity. This implicates the entrainment of free-tropospheric air into updrafts as a prominent governor of CI, consistent with previous studies. Sensitivity of CI to the environmental wind is manifested by 1) low-level flow affecting the strength and depth of mesoscale convergence along the terrain, and 2) clouds encountering updraft-suppressing pressure gradient forces while interacting with vertical wind shear in the free troposphere. Among the ensemble of thermals occurring in each simulation, the widest deep updrafts in each simulation were the most sensitive to environmental influences.

Satellite radar altimeters like CryoSat‐2 estimate sea ice thickness by measuring the return‐time of transmitted radar pulses, reflected from the sea ice and ocean surface, to measure the radar freeboard. Converting freeboard to thickness requires an assumption regarding the fractional depth of the snowpack from which the radar waves backscatter (α)$(\\alpha )$ . We derive sea ice thickness from CryoSat‐2 radar freeboard data with incremental values for α$\\alpha $ , for the 2010–2021 winter periods. By comparing these to sea ice thickness estimates derived from upward‐looking sonar moorings, we find that α$\\alpha $values between 35%–80% result in the best representation of interannual variability observed over first‐year ice, reduced to <${< } $ 55% over multi‐year ice. The underestimating bias in retrievals caused by optimizing this metric can be removed by reducing the waveform retracking threshold to 20%–50%. Our results pave the way for a new generation of ‘partial penetration’ sea ice thickness products from radar altimeters. Plain Language Summary Satellite altimeters like CryoSat‐2 can be used to estimate sea ice thickness by estimating how far sea ice floes stick out above the waterline. This is done by measuring the time taken for radar waves to travel to the surface of the ice floe and back to the altimeter. All current winter sea ice thickness estimates assume that the radar waves return entirely from the sea ice surface, and not from the overlying snow cover. A growing body of research suggests this may not be the case, with weather and snow conditions affecting the fraction of the detected radar power that comes from the ice surface. We consider how well CryoSat‐2 estimates capture whether the ice is thicker or thinner than usual at a given time of year. We find that its skill is highest when we assume that 35%–80% of the radar power comes from the sea ice surface, and 20%–65% comes from the snow surface. However, improving this aspect of skill makes the sea ice thickness estimates too low. To address this, we show that a simple change in the waveform processing method can counter this bias. Key Points CryoSat‐2 retrievals of sea ice thickness have historically been tuned to minimize bias rather than to capture interannual variability We use upward‐looking sonar moorings to tune the treatment of both waveform retracking and snowpack penetration by radar waves Tuning to optimize interannual variability indicates partial penetration for all retracking thresholds

The Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) and Cloud, Aerosol, and Complex Terrain Interactions (CACTI) projects deployed a high-spatiotemporal-resolution radiosonde network to examine environments supporting deep convection in the complex terrain of central Argentina. This study aims to characterize atmospheric profiles most representative of the near-cloud environment (in time and space) to identify the mesoscale ingredients affecting storm initiation and growth. Spatiotemporal autocorrelation analysis of the soundings reveals that there is considerable environmental heterogeneity, with boundary layer thermodynamic and kinematic fields becoming statistically uncorrelated on scales of 1–2 h and 30 km. Using this as guidance, we examine a variety of environmental parameters derived from soundings collected within close proximity (30 km in space and 30 min in time) of 44 events over 9 days where the atmosphere either: 1) supported the initiation of sustained precipitating convection, 2) yielded weak and short-lived precipitating convection, or 3) produced no precipitating convection in disagreement with numerical forecasts from convection-allowing models (i.e., Null events). There are large statistical differences between the Null event environments and those supporting any convective precipitation. Null event profiles contained larger convective available potential energy, but had low free-tropospheric relative humidity, higher freezing levels, and evidence of limited horizontal convergence near the terrain at low levels that likely suppressed deep convective growth. We also present evidence from the radiosonde and satellite measurements that flow–terrain interactions may yield gravity wave activity that affects CI outcome.

This article introduces a novel hypothesis for the role of vertical wind shear (“shear”) in deep convection initiation (DCI). In this hypothesis, initial moist updrafts that exceed a width and shear threshold will “root” within a progressively deeper steering current with time, increase their low-level cloud-relative flow and inflow, widen, and subsequently reduce their susceptibility to entrainment-driven dilution, evolving toward a quasi-steady self-sustaining state. In contrast, initial updrafts that do not exceed the aforementioned thresholds experience suppressed growth by shear-induced downward pressure gradient accelerations, will not root in a deep-enough steering current to increase their inflow, will narrow with time, and will succumb to entrainment-driven dilution. In the latter case, an externally driven lifting mechanism is required to sustain deep convection, and deep convection will not persist in the absence of such lifting mechanism. A theoretical model is developed from the equations of motion to further explore this hypothesis. The model indicates that shear generally suppresses DCI, raising the initial subcloud updraft width that is necessary for it to occur. However, there is a pronounced bifurcation in updraft growth in the model after the onset of convection. Sufficiently wide initial updrafts grow and eventually achieve a steady state. In contrast, insufficiently wide initial updrafts shrink with time and eventually decay completely without external support. A sharp initial updraft radius threshold discriminates between these two outcomes. Thus, consistent with our hypothesis and observations, shear inhibits DCI in some situations, but facilitates it in others.

Data from scanning radars, radiosondes, and vertical profilers deployed during three field campaigns are analyzed to study interactions between cloud-scale updrafts associated with initiating deep moist convection and the surrounding environment. Three cases are analyzed in which the radar networks permitted dual-Doppler wind retrievals in clear air preceding and during the onset of surface precipitation. These observations capture the evolution of (i) the mesoscale and boundary layer flow, and (ii) low-level updrafts associated with deep moist convection initiation (CI) events yielding sustained or short-lived precipitating storms. The elimination of convective inhibition did not distinguish between sustained and unsustained CI events, though the vertical distribution of convective available potential energy may have played a role. The clearest signal differentiating the initiation of sustained versus unsustained precipitating deep convection was the depth of the low-level horizontal wind convergence associated with the mesoscale flow feature triggering CI, a sharp surface wind shift boundary, or orographic upslope flow. The depth of the boundary layer relative to the height of the LFC failed to be a consistent indicator of CI potential. Widths of the earliest detectable low-level updrafts associated with sustained precipitating deep convection were ~3–5 km, larger than updrafts associated with surrounding boundary layer turbulence (~1–3 km wide). It is hypothesized that updrafts of this larger size are important for initiating cells to survive the destructive effects of buoyancy dilution via entrainment.

This study evaluates a hypothesis for the role of vertical wind shear in deep convection initiation (DCI) that was introduced in Part I by examining behavior of a series of numerical simulations. The hypothesis states, “Initial moist updrafts that exceed a width and shear threshold will ‘root’ within a progressively deeper steering current with time, increase their low-level cloud-relative flow and inflow, widen, and subsequently reduce their susceptibility to entrainment-driven dilution, evolving toward a quasi-steady self-sustaining state.” A theoretical model that embodied key elements of the hypothesis was developed in Part I, and the behavior of this model was explored within a multidimensional environmental parameter space. Remarkably similar behavior is evident in the simulations studied here to that of the theoretical model, both in terms of the temporal evolution of DCI and in the sensitivity of DCI to environmental parameters. Notably, both the simulations and theoretical model experience a bifurcation in outcomes, whereby nascent clouds that are narrower than a given initial radius R 0 threshold quickly decay and those above the R 0 threshold undergo DCI. An important assumption in the theoretical model, which states that the cloud-relative flow of the background environment V CR determines cloud radius R , is scrutinized in the simulations. It is shown that storm-induced inflow is small relative to V CR beyond a few kilometers from the updraft edge, and V CR therefore plays a predominant role in transporting conditionally unstable air to the updraft. Thus, the critical role of V CR in determining R is validated.

Background/Objectives: Antibiotic-resistant Staphylococcus aureus represents a growing threat in the modern world, and new antibiotic targets are needed for its successful treatment. One such potential target is the pyridoxal-5′-phosphate (PLP)-dependent cysteine desulfurase (SaSufS) of the SUF-like iron–sulfur (Fe-S) cluster biogenesis pathway upon which S. aureus relies exclusively for Fe-S synthesis. The current methods for measuring the activity of this protein have allowed for its recent characterization, but they are hampered by their use of chemical reagents which require long incubation times and may cause undesired side reactions. This problem highlights a need for the development of a rapid quantitative assay for the characterization of SaSufS in the presence of potential inhibitors. Methods: A spectrophotometric assay based on the well-documented absorbance of PLP intermediates at 340 nm was both compared to an established alanine detection assay and used to effectively measure the activity of SaSufS incubated in the absence and presence of the PLP-binding inhibitors, D-cycloserine (DCS) and L-cycloserine (LCS) as proof of concept. Methicillin-resistant S. aureus strain LAC was also grown in the presence of these inhibitors. Results: The Michaelis–Menten parameters kcat and Km of SaSufS were determined using the alanine detection assay and compared to corresponding intermediate-based values obtained spectrophotometrically in the absence and presence of the reducing agent tris(2-carboxyethyl)phosphine (TCEP). These data revealed the formation of both an intermediate that achieves steady-state during continued enzyme turnover and an intermediate that likely accumulates upon the stoppage of the catalytic cycle during the second turnover. The spectrophotometric method was then utilized to determine the half maximal inhibitory concentration (IC50) values for DCS and LCS binding to SaSufS, which are 2170 ± 920 and 62 ± 23 μM, respectively. Both inhibitors of SaSufS were also found to inhibit the growth of S. aureus. Conclusions: Together, this work offers a spectrophotometric method for the analysis of new inhibitors of SufS and lays the groundwork for the future development of novel antibiotics targeting cysteine desulfurases.

A lack of routine environmental observations located near deepening cumulus congestus clouds limits verification of important theorized and simulated updraft–environment interaction processes occurring during deep convection initiation (CI). We analyze radiosonde profiles collected during several hundred CI events near a mountain range in central Argentina during the CACTI field campaign. Statistical analyses illustrate environmental conditions supporting radar-observed CI outcomes that span a spectrum of convective cell depths, widths, and durations, as well as events lacking precipitating convection. Tested environmental factors include a large variety of sounding-derived measurements of CAPE, CIN, moisture, terrain-relative winds, vertical shear, and lifted parcel properties, with supplemental model reanalysis of background larger-scale vertical motion. CAPE and CIN metrics do not consistently differentiate CI success from failure. Only a few environmental factors contain consistent monotonic relationships among the spectrum of cloud depths achieved during CI: (i) the depth and strength of background ascent, and (ii) the component of low-level flow oriented parallel to the ridgeline. These metrics suggest that the ability of the surrounding flow to lift parcels to their LFC and terrain-modified flow are consistently relevant processes for CI. Low- to midlevel relative humidity strongly discriminated between CI and non-CI events, likely reflecting entrainment-driven dilution processes. However, we could not confidently conclude that relative humidity similarly discriminated robust from marginal CI events. Circumstantial evidence was found linking cell width, an important cloud property governing the probability of CI, to LCL height, boundary layer depth, depth and magnitude of the CIN layer, and ambient wind shear.

The newly developed expendable digital dropsonde (XDD) allows for high spatial and temporal resolution data collection in tropical cyclones (TCs). In 2015, a total of 725 XDDs were launched into Hurricanes Marty (27–28 September), Joaquin (2–5 October), and Patricia (20–23 October) as part of the Tropical Cyclone Intensity (TCI) experiment. These dropsondes were launched from a NASA WB-57 at altitudes above 18 km, capturing the full depth of the TCs to the tropopause. This study documents the vertical velocity distributions observed in TCI using the XDDs and examines the distributions altitudinally, radially, and azimuthally. The strongest mean or median XDD-derived vertical velocities observed during TCI occurred in the upper levels and within the cores of the three TCs. There was little azimuthal signal in the vertical velocity distribution, likely due to sampling asymmetries and noise in the data. Downdrafts were strongest in Joaquin, while updrafts were strongest in Patricia, especially within the eyewall on 23 October. Patricia also had an impressive low-level (<2 km) updraft that exceeded 10 m s−1 associated with a shallow, overturning, radial circulation in the secondary eyewall.

The newly developed Expendable Digital Dropsondes (XDDs) allow for high spatial and temporal resolution observations of the kinematic and thermodynamic structures in tropical cyclones (TCs). It is important to evaluate both the temporal and spatial autocorrelations within the recorded data to address concerns about spatial interpolation, statistical significance of individual data points, and launch-rate spatial requirements for future dropsonde studies in TCs. Data from 437 XDDs launched into Hurricanes Marty (27–28 September), Joaquin (2–5 October), and Patricia (20–23 October) during the 2015 Tropical Cyclone Intensity (TCI) experiment are used to compute temporal and spatial autocorrelations for vertical velocity, temperature, horizontal wind speed, and equivalent potential temperature. All of the examined variables had temporal autocorrelation scales between approximately 10 and 40 s, with most between 20 and 30 s. Most of the spatial autocorrelation scales were estimated to be 3–10 km. The temporal autocorrelation scales for vertical velocity, horizontal wind speed, and equivalent potential temperature were correlated with updraft depth. Vertical velocity usually had the smallest mean, and median, temporal and estimated spatial autocorrelation scales of approximately 20 s and 3–6 km, respectively. The estimated horizontal scales are below the median sounding spacing and suggest that an increase in the launch rate of the XDDs by a factor of 3–4 from the TCI sampling rate is needed to adequately depict TC kinematics and structure in transects of soundings. The results also indicate that current temporal sampling rates are adequate to depict TC kinematics and structure in a single sounding.