Search

Boundary layer cloud transformations at high latitudes play a key role for the Arctic climate and are partially controlled by large-scale dynamics such as subsidence. While measuring large-scale and mesoscale divergence on spatial scales on the order of 100 km has proven notoriously difficult, recent airborne campaigns in the subtropics have successfully applied measurement techniques using multiple dropsonde releases in circular flight patterns. In this paper, it is shown that this method can also be effectively applied at high latitudes, in spite of the considerable differences in atmospheric dynamics compared to the subtropics. To show the applicability, data collected during the airborne High Altitude and Long Range Research Aircraft–Transregional Collaborative Research Center TRR 172-Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms [HALO–(AC)3] field campaign near Svalbard in spring 2022 were analyzed, where several flight patterns involving multiple dropsonde launches were realized by two aircraft. This study presents a first overview of the results. We find that the method indeed yields reliable estimates of mesoscale gradients in the Arctic, producing robust vertical profiles of horizontal divergence and, consequently, subsidence. Sensitivity to aspects of the method is investigated, including dependence on sampling area and the divergence calculation. Significance Statement: The aim of this work is to report encouraging results with a recently proposed aircraft-based method for measuring mesoscale vertical motions at high latitudes. Dropsonde data from the recent High Altitude and Long Range Research Aircraft–Transregional Collaborative Research Center TRR 172-Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms [HALO–(AC)3] campaign are used for this purpose. The method has so far mainly been applied at subtropical to midlatitudes, but not in the Arctic, where the weather and climate conditions are very different. Gaining insight is significant because vertical winds play a key role in the Arctic climate system, including airmass transformations and the behavior of clouds and precipitation. The results motivate the use of the measured vertical winds in follow-up studies with process models. [ABSTRACT FROM AUTHOR]

The spatial variability of moist static energy (MSE) and its column‐integral (CMSE) around tropical cyclones (TCs) are known to help prognose TC development. Though limited in number and spatial coverage per TC, modeling work suggests that dropsondes, when strategically deployed, can reliably capture radial MSE and CMSE variability. This study uses North Atlantic upper‐level reconnaissance dropsondes from 1996 to 2021 to produce the most extensive observational analysis of MSE structure in TCs to date. MSE and CMSE decrease with distance from the TC center. MSE spatial variability is larger in Category 1 and 2 hurricanes compared to tropical storms, and generally largest after a TC's lifetime maximum intensity. Moisture dominates the MSE spatial variability but temperature contributes in the upper levels near the TC center. While differences in MSE spatial variability between weakening and intensifying TCs are less clear, raw MSE tends to be greater in intensifying TCs at most radii and vertical levels. Plain Language Summary: Moist static energy (MSE) is a thermodynamic variable combining contributions from temperature, water vapor, and gravity. MSE has been useful in describing processes important for atmospheric convection and tropical cyclone (TC) development. This study investigates the average MSE structure of observed Atlantic TCs using measurements from dropsondes, which are instruments dropped into TCs from Hurricane Hunter aircraft. MSE decreases with distance from the TC center, largely due to reduced moisture at large radii, though reduced temperature is important at higher altitudes. Further analysis was performed according to TC intensity and the rate of TC intensity change. MSE decreases more quickly from the TC center in Category 1 and 2 hurricanes compared to tropical storms. Intensifying and weakening TCs do not show substantial differences in how MSE varies in space. Instead, the MSE itself is larger in intensifying storms at most altitudes and distances, especially farther from the TC center. Key Points: Moist static energy (MSE) and its column integral decrease with distance from the TC center in observationsMoisture dominates the spatial variability of MSE but temperature contributes at upper levels near the TC centerMSE spatial variability is larger in Category 1–2 hurricanes than tropical storms and MSE itself is larger in more rapidly intensifying TCs [ABSTRACT FROM AUTHOR]

Satellites provide the largest dataset for monitoring the earth system and constraining analyses in numerical weather prediction models. A significant challenge for utilizing satellite radiances is the accurate estimation of their biases. High-accuracy nonradiance data are commonly employed to anchor radiance bias corrections. However, aside from the impacts of radio occultation data in the stratosphere, the influence of other types of "anchor" observation data on radiance assimilation remains unclear. This study provides an assessment of impacts of dropsonde data collected during the Atmospheric River (AR) Reconnaissance program, which samples ARs over the northeast Pacific, on the radiance assimilation using the Global Forecast System (GFS) and Global Data Assimilation System at the National Centers for Environmental Prediction. The assimilation of this dropsonde dataset has proven crucial for providing enhanced anchoring for bias corrections and improving the model background, leading to an increase of ∼5%–10% in the number of assimilated microwave radiance in the lower troposphere/midtroposphere over the northeast Pacific and North America. The impact on tropospheric infrared radiance is not only small but also beneficial. Impacts of dropsondes on the use of stratospheric channels are minimal due to the absence of dropsonde observations at certain altitudes, such as aircraft flight levels (e.g., 150 hPa). Results in this study underscore the usefulness of dropsondes, along with other conventional data, in optimizing the assimilation of satellite radiance. This study reinforces the importance of a diverse observing network for accurate weather forecasting and highlights the specific benefits derived from integrating dropsonde data into radiance assimilation processes. Significance Statement: This study aims to evaluate the impact of aircraft reconnaissance dropsondes on the assimilation of satellite radiance data, utilizing observations from the 2020 Atmospheric River Reconnaissance program. The key findings reveal a substantial enhancement in the model first guess and improved estimates of radiance biases. Notably, there is a significant 5%–10% increase in microwave radiance observations over the northeastern Pacific and North America, with positive yet modest effects observed in tropospheric infrared radiance. These findings underscore the crucial role of atmospheric river reconnaissance dropsondes as anchor data, enhancing the assimilation of radiance observations. In essence, the inclusion of these dropsondes in routine networks is particularly valuable for optimizing data assimilation in regions with sparse observational data. [ABSTRACT FROM AUTHOR]

This study presents a method to diagnose radial ventilation, the horizontal flux of relatively low-θe air into tropical cyclones, from dropsonde observations. We used this method to investigate ventilation changes over three consecutive sampling periods in Hurricane Sam (2021), which underwent substantial intensity changes over 3 days. During the first and last periods, coinciding with intensification, the ventilation was relatively small due to a lack of spatial correlation between radial flow and θe azimuthal asymmetries. During the second period, coinciding with weakening, the ventilation was relatively large. The increased ventilation was caused by greater shear associated with an upper-level trough, tilting the vortex, along with dry, low-θe air wrapping in upshear. The spatial correlation of the radial inflow and anomalously low-θe air resulted in large ventilation at mid- to upper levels. Additionally, at low to midlevels, there was evidence of mesoscale inflow of low-θe air in the stationary band complex. The location of these radial ventilation pathways and their effects on Sam's intensity are consistent with previous idealized and real-case modeling studies. More generally, this method offers a way to monitor ventilation changes in tropical cyclones, particularly when there is full-troposphere sampling around and within a tropical cyclone's core. Significance Statement: Ventilation, the injection of relatively dry and/or cool air into a tropical cyclone, may weaken a storm. In contrast, the lack of ventilation is favorable for intensification. The purpose of this study is to present a method to diagnose ventilation using aircraft dropsonde observations. Using dropsonde observations collected in Hurricane Sam (2021), there was a period of increased lateral ventilation in two regions around the storm that coincided with when the storm rapidly weakened. The results suggest that monitoring ventilation from dropsonde observations, when available, may be useful for anticipating ventilation-induced intensity changes in tropical cyclones and further studying ventilation pathways. [ABSTRACT FROM AUTHOR]

During a 6-day intensive observing period in January 2021, Atmospheric River Reconnaissance (AR Recon) aircraft sampled a series of atmospheric rivers (ARs) over the northeastern Pacific that caused heavy precipitation over coastal California and the Sierra Nevada. Using these observations, data denial experiments were conducted with a regional modeling and data assimilation system to explore the impacts of research flight frequency and spatial resolution of dropsondes on model analyses and forecasts. Results indicate that dropsondes significantly improve the representation of ARs in the model analyses and positively impact the forecast skill of ARs and quantitative precipitation forecasts (QPF), particularly for lead times > 1 day. Both reduced mission frequency and reduced dropsonde horizontal resolution degrade forecast skill. On the other hand, experiments that assimilated only G-IV data and experiments that assimilated both G-IV and C-130 data show better forecast skill than experiments that only assimilated C-130 data, suggesting that the additional information provided by G-IV data is necessary for improving forecast skill. Although this is a case study, the 6-day period studied encompassed multiple AR events that are representative of typical AR behavior. Therefore, the results indicate that future operational AR Recon missions incorporate daily mission or back-to-back flights, maintain current dropsonde spacing, support high-resolution data transfer capacity on the C-130s, and utilize G-IV aircraft in addition to C-130s. [ABSTRACT FROM AUTHOR]

This study describes the research-to-operations process leading to a recent change in tropical cyclone (TC) reconnaissance sampling patterns as well as observing-system experiments that evaluated the impact of that change on numerical weather prediction model forecasts of TCs. A valuable part of this effort was having close, multipronged connections between the TC research and operational TC prediction communities at the National Oceanic and Atmospheric Administration (NOAA). Related to this work, NOAA's Atlantic Oceanographic and Meteorological Laboratory (AOML) and National Hurricane Center (NHC) have a long history of close collaboration to improve TC reconnaissance. Similar connections between AOML and NOAA's Environmental Modeling Center (EMC) also laid a foundation for the observing-system experiments conducted here. More specifically, AOML and NHC collaborated in 2018 to change how NHC uses NOAA's Gulfstream-IV (G-IV) jet during TC synoptic surveillance missions. That change added a second circumnavigation at approximately 1.5° from TC centers, when possible. Preliminary experiments suggest that the change improved track forecasts, though the intensity results are more mixed. Despite the somewhat small sample size over a 3-yr period, the track improvement does agree with prior work. This effort has led to additional work to more fully examine G-IV sampling strategies. [ABSTRACT FROM AUTHOR]

Atmospheric River Reconnaissance has held field campaigns during cool seasons since 2016. These campaigns have provided thousands of dropsonde data profiles, which are assimilated into multiple global operational numerical weather prediction models. Data denial experiments, conducted by running a parallel set of forecasts that exclude the dropsonde information, allow testing of the impact of the dropsonde data on model analyses and the subsequent forecasts. Here, we investigate the differences in skill between the control forecasts (with dropsonde data assimilated) and denial forecasts (without dropsonde data assimilated) in terms of both precipitation and integrated vapor transport (IVT) at multiple thresholds. The differences are considered in the times and locations where there is a reasonable expectation of influence of an intensive observation period (IOP). Results for 2019 and 2020 from both the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the National Centers for Environmental Prediction (NCEP) global model show improvements with the added information from the dropsondes. In particular, significant improvements in the control forecast IVT generally occur in both models, especially at higher values. Significant improvements in the control forecast precipitation also generally occur in both models, but the improvements vary depending on the lead time and metrics used. Significance Statement: Atmospheric River Reconnaissance is a program that uses targeted aircraft flights over the northeast Pacific to take measurements of meteorological fields. These data are then ingested into global weather models with the intent of improving the initial conditions and resulting forecasts along the U.S. West Coast. The impacts of these observations on two global numerical weather models were investigated to determine their influence on the forecasts. The integrated vapor transport, a measure of both wind and humidity, saw significant improvements in both models with the additional observations. Precipitation forecasts were also improved, but with differing results between the two models. [ABSTRACT FROM AUTHOR]

The global positioning system dropwindsonde has provided thousands of high-resolution kinematic and thermodynamic soundings in and around tropical cyclones (TCs) since 1997. These data have revolutionized the understanding of TC structure, improved forecasts, and validated observations from remote sensing platforms. About 400 peer-reviewed studies on TCs using these data have been published to date. This paper reviews the history of dropwindsonde observations, changes to dropwindsonde technology since it was first used in TCs in 1982, and how the data have improved forecasting and changed our understanding of TCs. [ABSTRACT FROM AUTHOR]

This study conducts the first large-sample comparison of the impact of dropsondes in the tropical cyclone (TC) inner core, vortex, and environment on NWP-model TC forecasts. We analyze six observing-system experiments, focusing on four sensitivity experiments that denied dropsonde observations within annuli corresponding with natural breakpoints in reconnaissance sampling. These are evaluated against two other experiments detailed in a recent parallel study: one that assimilated and another that denied dropsonde observations. Experiments used a basin-scale, multistorm configuration of the Hurricane Weather Research and Forecasting (HWRF) Model and covered active periods of the 2017–20 North Atlantic hurricane seasons. Analysis focused on forecasts initialized with dropsondes that used mesoscale error covariance derived from a cycled HWRF ensemble, as these forecasts were where dropsondes had the greatest benefits in the parallel study. Some results generally support findings of previous research, while others are novel. Most notable was that removing dropsondes anywhere, particularly from the vortex, substantially degraded forecasts of maximum sustained winds. Removing in-vortex dropsondes also degraded outer-wind-radii forecasts in many instances. As such, in-vortex dropsondes contribute to a majority of the overall impacts of the dropsonde observing system. Additionally, track forecasts of weak TCs benefited more from environmental sampling, while track forecasts of strong TCs benefited more from in-vortex sampling. Finally, inner-core-only sampling strategies should be avoided, supporting a change made to the U.S. Air Force Reserve's sampling strategy in 2018 that added dropsondes outside of the inner core. Significance Statement: This study uses a regional hurricane model to conduct the most comprehensive assessment to date of the impact of dropsondes at different distances away from the center of a tropical cyclone (TC) on TC forecasts. The main finding is that in-vortex dropsondes are most important for intensity and outer-wind-radii forecasts. Particularly notable is the impact of dropsondes on TC maximum wind speed forecasts, as reducing sampling anywhere would degrade those forecasts. [ABSTRACT FROM AUTHOR]

This study comprehensively assesses the overall impact of dropsondes on tropical cyclone (TC) forecasts. We compare two experiments to quantify dropsonde impact: one that assimilated and another that denied dropsonde observations. These experiments used a basin-scale, multistorm configuration of the Hurricane Weather Research and Forecasting Model (HWRF) and covered active North Atlantic basin periods during the 2017-20 hurricane seasons. The importance of a sufficiently large sample size as well as thoroughly understanding the error distribution by stratifying results are highlighted by this work. Overall, dropsondes directly improved forecasts during sampled periods and indirectly impacted forecasts during unsampled periods. Benefits for forecasts of track, intensity, and outer wind radii were more pronounced during sampled periods. The forecast improvements of outer wind radii were most notable given the impact that TC size has on TC-hazards forecasts. Additionally, robustly observing the inner- and near-core region was necessary for hurricane-force wind radii forecasts. Yet, these benefits were heavily dependent on the data assimilation (DA) system quality. More specifically, dropsondes only improved forecasts when the analysis used mesoscale error covariance derived from a cycled HWRF ensemble, suggesting that it is a vital DA component. Further, while forecast improvements were found regardless of initial classification and in steady-state TCs, TCs undergoing an intensity change had diminished benefits. The diminished benefits during intensity change probably reflect continued DA deficiencies. Thus, improving DA system quality and observing system limitations would likely enhance dropsonde impacts. [ABSTRACT FROM AUTHOR]

The synoptic environment around tropical cyclones plays a significant role in vortex evolution. To capture the environment, the operational and research communities calculate diagnostic quantities. To aid with applications and research, the Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) combines disparate data sources. A key part of TC PRIMED is the environmental context. Often, environmental diagnostics come from multiple sources. However, TC PRIMED uses the European Centre for Medium-Range Weather Forecasts fifth-generation reanalysis (ERA5) product to provide a more complete representation of the storm environment from a single source. Reanalysis products usually poorly resolve tropical cyclones and their surrounding environment. To understand the uncertainty of large-scale diagnostics, ERA5 is compared to the Statistical Hurricane Intensity Prediction Scheme developmental dataset and the National Oceanic and Atmospheric Administration Gulfstream IV-SP dropwindsondes. This analysis highlights biases in the ERA5 environmental diagnostic quantities. Thermodynamic fields show the largest biases. The boundary layer exhibits a cold temperature bias that limits the amount of convective instability; also, the upper troposphere contains temperature biases and shows a high relative humidity bias. However, the upper-troposphere large-scale kinematic fields and derived metrics are low biased. In the lower troposphere, the temperature gradient and advection calculated from the thermal wind suggest that the low-level wind field is not representative of the observed distribution. These diagnostics comparisons provide uncertainty so that users of TC PRIMED can assess the implications for specific research and operational applications. [ABSTRACT FROM AUTHOR]

This study reviews the recent addition of dropwindsonde wind data near the tropical cyclone (TC) center as well as the first-time addition of high-density, flight-level reconnaissance observations (HDOBs) into the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). The main finding is that the additional data have profound positive impacts on subsequent TC track forecasts. For TCs in the North Atlantic (NATL) basin, statistically significant improvements in track extend through 4–5 days during reconnaissance periods. Further assessment suggests that greater improvements might also be expected at days 6–7. This study also explores the importance of comprehensively assessing data impact. For example, model or data assimilation changes can affect the so-called "early" and "late" versions of the forecast very differently. It is also important to explore different ways to describe the error statistics. In several instances the impacts of the additional data strongly differ depending on whether one examines the mean or median errors. The results demonstrate the tremendous potential for further improving TC forecasts. The data added here were already operationally transmitted and assimilated by other systems at NCEP, and many further improvements likely await with improved use of these and other reconnaissance observations. This demonstrates the need of not only investing in data assimilation improvements, but also enhancements to observational systems in order to reach next-generation hurricane forecasting goals. Significance Statement: This study demonstrates that data gathered from reconnaissance missions into tropical cyclones substantially improves tropical cyclone track forecasts. [ABSTRACT FROM AUTHOR]

Interactions between clouds, water vapor, radiation, and circulation influence tropical cyclone (TC) development. Many of these interactions can be quantified by understanding tendencies of the spatial variance of moist static energy (MSE). Dropsondes from aircraft reconnaissance sample profiles needed to compute MSE at fine vertical resolution, and may be useful in analyzing these feedbacks on TCs in situ. However, dropsondes are spatially sparse, and sample limited column depths depending on the type of reconnaissance mission. We use idealized convection‐permitting simulations to examine how MSE variability, and the feedbacks that influence it, are resolved using selected patterns of grid points meant to resemble dropsonde launch points in reconnaissance flight patterns. We first examine the column depth necessary to capture the MSE variability of the full atmosphere. We then study how these simulated flight patterns depict MSE variance and its relevant diabatic feedbacks in TCs of varying structure and intensity. Plain Language Summary: Interactions between clouds, water vapor, radiation, and circulation influence tropical cyclones (TCs). These interactions can be quantified by understanding how moisture, or moist static energy (MSE), varies spatially. Hurricane Hunter aircraft missions use dropsondes, instruments that collect the necessary data to compute MSE as they descend. This offers an observational tool to study cloud‐water vapor‐radiation‐circulation interactions in TCs. However, only 20–40 dropsondes are released per mission, and they only sample the atmosphere below the aircraft's flight level. We examine several simulations of TCs, where patterns of grid points are chosen to resemble dropsonde release points. We calculate how MSE varies spatially and the mechanisms that influence it. With these simulations, we reveal the depth of the atmosphere needed for effective sampling, and how sensitive calculations are to the density and spatial distribution of data. Key Points: Sampling the full troposphere is necessary to sufficiently capture the moist static energy variability of the full atmospheric columnCalculations of this variability and the feedbacks that influence it are impacted by radial coverage and spatial distribution of dataFull resolution of tropical cyclone moist static energy requires inner‐core sampling not regularly conducted by upper‐air reconnaissance [ABSTRACT FROM AUTHOR]

The airborne stepped frequency microwave radiometer (SFMR) provides the measurements of 10-m ocean surface wind speed in high and extreme wind conditions. These winds are calibrated using the surface-adjusted wind estimates from the so-called dropsondes. The surface-adjusted winds are obtained from layer-averaged winds scaled to 10-m altitude to eliminate the local surface variability not associated with the storm strength. The SFMR measurements and, consequently, the surface-adjusted dropsonde winds represent a possible reference for satellite instrument and model calibration/validation at high and extreme wind conditions. To this end, representativeness errors that those measurements may introduce need to be taken into account to ensure that the storm variability is correctly resolved in satellite retrievals and modeling. In this work, we compare the SFMR winds with the dropsonde surface-adjusted winds derived from the so-called WL150 algorithm, which uses the lowest 150-m layer between 10 and 350 m. We use nine years of data from 2009 to 2017. We focus on the effects of the layer altitude and thickness. Our analysis shows that the layer altitude has a significant impact on dropsonde/SFMR wind comparisons. Moreover, the averaged winds obtained from layers thinner than the nominal 150 m and closer to the surface are more representative of the SFMR surface wind speed than the WL150 speeds. We also find that the surface-adjusted winds are more representative of 10-km horizontally averaged SFMR winds. We conclude that for calibration/validation purposes, the WL150 algorithm can introduce noise, and the use of actual 10-m dropsonde measurements should be further investigated. [ABSTRACT FROM AUTHOR]

The sporadic formation of short-lived convective clouds in the eye of Tropical Cyclone (TC) Trami (2018) is investigated using dropsonde data and simulation results from a coupled atmosphere–ocean model. According to the satellite data, top height of the convective clouds exceeds 9 km above mean sea level, considerably taller than that of typical hub clouds (2–3 km). These clouds are located 10–30 km away from the TC center. Hence, these convective clouds are called deep eye clouds (DECs) in this study. The dropsonde data reveal an increase in relative humidity in the eye region during the formation of DECs. Short-lived convective clouds are simulated up to the middle troposphere in the eye region in the coupled model. Investigation of thermodynamic conditions shows a weakened low-level warm core and associated favorable conditions for convection in the eye region during the formation of DECs. DECs are formed after the weakening and outward displacement of convective heating within the eyewall. To elucidate the influence of the changes in convective heating within the eyewall on the formation of DECs, we calculate secondary circulation and associated adiabatic warming induced by convective heating within the eyewall using the Sawyer–Eliassen equation. In the eye region, weakening of subsidence and associated vertical potential temperature advection is observed as DECs are formed. This suggests that the weakening and outward displacement of convective heating within the eyewall create favorable conditions for the sporadic formation of DECs. [ABSTRACT FROM AUTHOR]

Large-eddy simulation (LES) is able to capture key boundary layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LESs. We derive these quantities from measurements and reanalysis obtained for two cold-air outbreak (CAO) events during Phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) in February–March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from ERA5 data agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time-evolving heat fluxes, wind, and advective tendencies profiles from ERA5 data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LESs. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol–cloud–meteorology interactions using LES informed and evaluated by ACTIVATE field measurements. [ABSTRACT FROM AUTHOR]

Recent studies have shown that extreme wind gusts are ubiquitous within the eyewall of intense tropical cyclones (TCs). These gusts pose a substantial hazard to human life and property, but both the short-term (i.e., during the passage of a single TC) and long-term (over many years) risk of encountering such a gust at a given location is poorly understood. Here, simulated tower data from large-eddy simulations of idealized TCs in a quiescent (i.e., no mean flow or vertical wind shear) environment are used to estimate these risks for the offshore region of the United States. For both a category 5 TC and a category 3 TC, there is a radial region where nearly all simulated towers experience near-surface (the lowest 200 m) 3-s gusts exceeding 70 m s−1 within a 10-min period; on average, these towers respectively sample peak 3-s gusts of 110 and 80 m s−1. Analysis of an observational dropsonde database supports the idealized simulations, and indicates that offshore structures (such as wind turbines) in the eyewall of a major hurricane are likely to encounter damaging wind speeds. This result is then incorporated into an estimate of the long-term risk, using analyses of the return period for major hurricanes from both a best-track database and a statistical–dynamical model forced by reanalysis. For much of the nearshore region of the Gulf of Mexico and southeastern U.S. coasts, this analysis yields an estimate of a 30%–60% probability of any given point experiencing at least one 70 m s−1 gust within a 30-yr period. [ABSTRACT FROM AUTHOR]

Landfalling atmospheric rivers (ARs) over the western US are responsible for ∼30%–50% of the annual precipitation, and their accurate forecasts are essential for aiding water management decisions and reducing flood risks. Sparse coverage of conventional observations over the Pacific Ocean, which can cause inadequate upstream initial conditions for numerical weather prediction models, may limit the improvement of forecast skill for these events. A targeted field program called AR Reconnaissance (Recon) was initiated in 2016 to better understand and reduce forecast errors of landfalling ARs at 1–5 days lead times. During the winter seasons of 2016, 2018, and 2019, 15 Intensive Observation Periods (IOPs) sampled the upstream conditions for landfalling ARs. This study evaluates the impact on forecast accuracy of assimilating these dropsonde data. Data denial experiments with (WithDROP) and without (NoDROP) dropsonde data were conducted using the Weather Research and Forecasting model with the Gridpoint Statistical Interpolation four‐dimensional ensemble variational system. Comparisons between the 15 paired NoDROP and WithDROP experiments demonstrate that AR Recon dropsondes reduced the root‐mean‐square error in integrated vapor transport (IVT) and inland precipitation for more than 70% of the IOPs, averaged over all forecast lead times from 1 to 6 days. Dropsondes have improved the spatial pattern of forecasts of IVT and precipitation in all 15 IOPs. Significant improvements in skill are found beyond the short range (1–2 days). IOP sequences (i.e., back‐to‐back IOPs every other day) show the most improvement of inland precipitation forecast skill. Plain Language Summary: Atmospheric rivers (ARs) are long and narrow corridors of water vapor transport in the atmosphere from the tropics to higher latitudes. Up to half of the annual precipitation in the western US states is related to landfalling ARs. Therefore, accurate forecasts of these events are important to reduce socio‐economic damage from the associated high‐impact weather and to better manage water resources over the western US. However, the forecast accuracy can be limited by sparse observations upstream over the Pacific Ocean. To fill observation gaps and improve forecast skills, a weather reconnaissance mission called Atmospheric River Reconnaissance was initiated in 2016 to release dropsondes from aircraft in key upstream sensitive regions. This study assesses the value of these observations in improving the initial conditions and the forecast skill of a regional model operated at the Center for Western Weather and Water Extremes for near real‐time weather forecasts. We found that the use of these additional observations collected during 2016, 2018, and 2019 has a positive impact on reducing the forecast error of water vapor transport within the Northeastern Pacific domain and the inland precipitation skill over the western US. These observations have more impact in poorly forecasted cases. Key Points: Dropsondes have reduced the forecast error of water vapor transport over the Northeast Pacific with continuous improvement out to day 3Dropsondes overall improved the precipitation forecast over the US West Coast in 11 out of 15 Intensive Observation Periods (IOPs)IOP sequences (i.e., back‐to‐back IOPs every other day) have the most positive impact on improving the precipitation forecast skill [ABSTRACT FROM AUTHOR]

The formation of tropical cyclones (TCs) in unfavorable large-scale environments remains a challenge for TC forecasting. Tropical Storm (TS) Cindy (2017) formed at 1800 UTC 20 June 2017 in the Gulf of Mexico despite strong vertical wind shear, low midtropospheric relative humidity, and poorly organized convection. A key to TC genesis is the initial development of a warm core within an emergent cyclonic vortex, a process that occurs on small spatial scales and is often difficult to observe. TS Cindy was observed during the Convective Processes Experiment (CPEX) field campaign in 2017 by the NASA DC-8 aircraft, equipped with a Doppler wind lidar, precipitation radar, and GPS dropsondes. This study combines CPEX observations and a cloud-resolving, fully coupled atmosphere–wave–ocean numerical simulation to investigate the formation of TS Cindy. Prior to TC genesis, a shallow cyclonic circulation was embedded in a deep layer of west-southwesterly flow associated with an upper-level trough. Within the disturbance, a warm and dry anomaly was observed by dropsondes near the center of the cyclonic circulation, with a maximum at about the 2.5-km level. In the coupled model simulation, the temperature perturbation reached 5°C along with a dewpoint temperature depression of 8°C. Backward trajectory analysis shows that subsidence is primarily associated with a thermally indirect circulation along the western flank of the storm. Air parcels descend more than 1000 m toward the lower troposphere while warming up by 9°–12°C. The subsidence-induced virtual temperature perturbation in the 1.5–3.5-km layer accounts for 50% of the sea level pressure depression. Subsidence warming, therefore, played a key role in the genesis of TS Cindy. [ABSTRACT FROM AUTHOR]

We use estimates of mesoscale vertical velocity and collocated cloud measurements from the second Next-Generation Aircraft Remote Sensing for Validation campaign (NARVAL2) in the tropical North Atlantic to show the observed impact of mesoscale vertical motion on tropical clouds. Our results not only confirm previously untested hypotheses about the role of dynamics being nonnegligible in determining cloudiness, but go further to show that at the mesoscale, the dynamics has a more dominant control on cloudiness variability than thermodynamics. A simple mass-flux estimate reveals that mesoscale vertical velocity at the subcloud-layer top explains much of the variations in peak shallow cumulus cloud fraction. In contrast, we find that thermodynamic cloud-controlling factors, such as humidity and stability, are unable to explain the variations in cloudiness at the mesoscale. Thus, capturing the observed variability of cloudiness may require not only a consideration of thermodynamic factors, but also dynamic ones such as the mesoscale vertical velocity. Significance Statement: Knowing how low clouds link to atmospheric circulation over a few hundred kilometers will reduce current uncertainties in the sensitivity of Earth's climate to warming. Such investigations have previously been limited by lack of circulation measurements at the mesoscale. However, using measurements now available from a recent field campaign over the tropical North Atlantic along with cloud measurements, we demonstrate how atmospheric vertical motion especially in the lower layers can influence the extent and structure of clouds. We find that the kinematics have a more dominant control on low-level cloudiness than conventionally studied thermodynamics. Our results show why it is important to focus attention to the circulation to improve our understanding of the variability in cloudiness. [ABSTRACT FROM AUTHOR]

Abstract Recent high‐resolution dropsonde observations from the 2010 Concordiasi field campaign in austral spring season show that surface‐based inversions (SBIs) over Antarctica are frequently eroded, with well‐mixed boundary layers occurring 33% and 18% of the time in West and East Antarctica, respectively. In this study, using the dropsonde observations, we evaluate the performance of the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA2) in representing the Antarctic boundary layer thermodynamic structure. Results show that MERRA2 has a good overall representation of the Antarctic surface stability and correctly predicts 82% of the SBIs. However, an underprediction of less stable boundary layer occurrence, especially over the elevated East Antarctic plateau, is favored during conditions of increased lower tropospheric stability associated with model dynamics, indicating difficulty in parameterizing turbulence in very stable boundary layers. In addition, a lower tropospheric cool bias (first model level and above) is observed in the MERRA2 reanalysis, especially over West Antarctica, which amplifies in the boundary layer during mixed conditions. The near‐surface cold bias is most pronounced when the model fails to predict mixed layers over West Antarctica and is expected to negatively impact the representation of surface energy budget and melt processes.

Understanding momentum exchange at the air–sea interface is important for accurate hurricane predictions and understanding fundamental storm dynamics. One method for estimating air–sea momentum transfer in high winds is the flux-profile method, which infers surface momentum fluxes and the corresponding drag coefficient from mean velocity profiles obtained from either dropsondes or meteorological towers, under the assumption that the boundary layer wind profile at low altitudes exhibits a logarithmic profile with height. In this study, we use dropsonde data from reconnaissance aircraft, as well as "virtual sondes" from a turbulence-resolving simulation of an intense tropical cyclone, to critically analyze the diagnosis of drag coefficient CD at hurricane-force wind speeds. In particular, the "rolloff" of the drag coefficient, where CD decreases at 10-m wind speeds > 35 m s−1, is called into question based on uncertainty due to relatively low sample size and a lack of robustness of the flux-profile method at high winds. In addition, multiple factors appear to favor an underestimate of CD at hurricane-force winds relative to their true values, including uncertainty in the height of recorded dropsonde data, in violation of Monin–Obukhov similarity theory near the eyewall, and the short vertical extent of the logarithmic layer. Due to these and other related sources of uncertainty, it is likely that a quantitative limit has been reached in inferring the specific values of u* and CD using the flux-profile method, while at the same time the potential for underestimation may cast doubt on the CD–U10 relationship inferred from this method at high winds. [ABSTRACT FROM AUTHOR]

During the Dynamics of the MJO (DYNAMO) field campaign, radiosonde launches were regularly conducted from three small islands/atolls (Malé and Gan, Maldives, and Diego Garcia, British Indian Ocean Territory) as part of a large-scale sounding network. Comparison of island upsondes with nearby and near-contemporaneous dropsondes over the ocean provides evidence for the magnitude and scope of the islands' influence on the surrounding atmosphere and on the island upsonde profiles. The island's impact on the upsonde data is most prominent in the lowest 200 m. Noting that the vertical gradients of temperature, moisture, and winds over the ocean are generally constant in the lowest 0.5 km of dropsondes, a simple procedure was constructed to adjust the upsonde profiles in the lowest few hundred meters to resemble the atmospheric structures over the open ocean. This procedure was applied to the soundings from the three islands mentioned above for the October–December 2011 period of DYNAMO. As a result of this procedure, the adjusted diurnal cycle amplitude of surface temperature is reduced fivefold, resembling that over the ocean, and low-level wind speeds are increased in ~90% of the island soundings. Examination of the impact of these sounding adjustments shows that dynamical and budget fields are primarily affected by adjustments to the wind field, whereas convective parameters are sensitive to the adjustments in thermodynamic fields. Although the impact of the adjustments is generally small (on the order of a few percent), intraseasonal wind regime changes result in some systematic variations in divergence and vertical motion over the sounding arrays. [ABSTRACT FROM AUTHOR]

This work investigates how the relationship between tropical cyclone (TC) tornadoes and ambient (i.e., synoptic-scale) deep-tropospheric (i.e., 850-200-hPa) vertical wind shear (VWS) varies between coastal and inland environments. Observed U.S. TC tornado track data are used to study tornado frequency and location, while dropsonde and radiosonde data are used to analyze convective-scale environments. To study the variability in the TC tornado--VWS relationship, these data are categorized by both 1) their distance from the coast and 2) reanalysis-derived VWS magnitude. The analysis shows that TCs produce coastal tornadoes regardless of VWS magnitude primarily in their downshear sector, with tornadoesmost frequently occurring in strongly sheared cases. Inland tornadoes, including the most damaging cases, primarily occur in strongly sheared TCs within the outer radii of the downshear-right quadrant. Consistent with these patterns, dropsondes and coastal radiosondes show that the downshear-right quadrant of strongly sheared TCs has the most favorable combination of enhanced lower-tropospheric near-surface speed shear and veering, and reduced lower-tropospheric thermodynamic stability for tornadic supercells. Despite the weaker intensity farther inland, these kinematic conditions are even more favorable in inland environments within the downshear-right quadrant of strongly sheared TCs, due to the strengthened veering of the ambient winds and the lack of changes in the TC outer tangential wind field strength. The constructive superposition of the ambient and TC winds may be particularly important to inland tornado occurrence. Together, these results will allow forecasters to anticipate how the frequency and location of tornadoes and, more broadly, convection may change as TCs move inland. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are responsible for intense winter rainfall events impacting the U.S. West Coast, and have been studied extensively during CalWater and AR Recon field programs (2014-20). A unique set of 858 dropsondes deployed in lines transecting 33 ARs are analyzed, and integrated vapor transport (IVT) is used to define five regions: core, cold and warm sectors, and non-AR cold and warm sides. The core is defined as having at least 80% of the maximum IVT in the transect. Remaining dropsondes with IVT. 250 kgm-1 s-1 are assigned to cold or warm sectors, and those outside of this threshold form non-AR sides. The mean widths of the three AR sectors are approximately 280 km. However, the core contains roughly 50% of all the water vapor transport (i.e., the total IVT), while the others each contain roughly 25%. A low-level jet occurs most often in the core and warm sector with mean maximum wind speeds of 28.3 and 21.7ms-1, comparable to previous studies, although with heights approximately 300mlower than previously reported. The core exhibits characteristics most favorable for adiabatic lifting to saturation by the California coastal range. On average, stability in the core is moist neutral, with considerable variability around the mean. A relaxed squared moist Brunt-Väisälä frequency threshold shows; 8%-12% of core profiles exhibiting near-moist neutrality. The vertical distribution of IVT, which modulates orographic precipitation, varied across AR sectors, with 75%of IVT residing below 3115 m in the core. [ABSTRACT FROM AUTHOR]

This study estimates the random error variances and standard deviations (STDs) for four datasets: Global Hawk (GH) dropsondes (DROP), the High-Altitude Monolithic Microwave Integrated Circuit Sounding Radiometer (HAMSR) aboard the GH, the fifth European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), and the Hurricane Weather Research and Forecasting (HWRF) Model, using the three-cornered hat (3CH) method. These estimates are made during the 2016 Sensing Hazards with Operational Unmanned Technology (SHOUT) season in the environment of four tropical cyclones from August to October. For temperature and specific and relative humidity, the ERA5, HWRF, and DROP datasets all have similar magnitudes of errors, with ERA5 having the smallest. The error STDs of temperature and specific humidity are less than 0.8K and 1.0 g kg-1 over most of the troposphere, while relative humidity error STDs increase from less than 5% near the surface to between 10% and 20% in the upper troposphere. The HAMSR bias-corrected data have larger errors, with estimated error STDs of temperature and specific humidity in the lower troposphere between 1.5 and 2.0K and between 1.5 and 2.5 g kg-1. HAMSR's relative humidity error STD increases from approximately 10% in the lower troposphere to 30% in the upper troposphere. The 3CH method error estimates are generally consistent with prior independent estimates of errors and uncertainties for the HAMSR and dropsonde datasets, although they are somewhat larger, likely due to the inclusion of representativeness errors (differences associated with different spatial and temporal scales represented by the data). [ABSTRACT FROM AUTHOR]

Combined airborne, shipboard, and satellite measurements provide the first observational assessment of all major terms of the vertically integrated water vapor (IWV) budget for a 150 km 3 160 km region within the core of a strong atmospheric river over the northeastern Pacific Ocean centered on 1930UTC 5 February 2015. Column-integrated moisture flux convergence is estimated from eight dropsonde profiles, and surface rain rate is estimated from tail Doppler radar reflectivity measurements. Dynamical convergence of water vapor (2.20 ± 0.12mmh-1) nearly balances estimated precipitation (2.47 ± 0.41mmh-1), but surface evaporation (0.0 ± 0.05mmh-1) is negligible. Advection of drier air into the budget region (-1.5060.-1mmh-1) causesIWV tendency from the sum of all terms to be negative (-1.6660.45mmh-1). An independent estimate of IWV tendency obtained from the difference between IWV measured by dropsonde and retrieved by satellite 3 h earlier is less negative (20.52 ± 0.24mmh-1), suggesting the presence of substantial temporal variability that is smoothed out when averaging over several hours. The calculation of budget terms for various combinations of dropsonde subsets indicates the presence of substantial spatial variability at ;50-km scales for precipitation, moisture flux convergence, and IWV tendency that is smoothed out when averaging over the full budget region. Across subregions, surface rain rate is linearly proportional to dynamical convergence of water vapor. These observational results improve our understanding of the thermodynamic and kinematic processes that control IWV in atmospheric rivers and the scales at which they occur. [ABSTRACT FROM AUTHOR]

This paper develops a method to estimate the shallow-convective mass flux M at the top of the subcloud layer as a residual of the subcloud-layer mass budget. The ability of the mass-budget estimate to reproduce the mass flux diagnosed directly from the cloud-core area fraction and vertical velocity is tested using real-case large-eddy simulations over the tropical Atlantic. We find that M reproduces well the magnitude, diurnal cycle, and day-to-day variability of the core-sampled mass flux, with an average root-mean-square error of less than 30% of the mean. The average M across the four winter days analyzed is 12 mm s−1, where the entrainment rate E contributes on average 14 mm s−1 and the large-scale vertical velocity W contributes −2 mm s−1. We find that day-to-day variations in M are mostly explained by variations in W, whereas E is very similar among the different days analyzed. Instead E exhibits a pronounced diurnal cycle, with a minimum of about 10 mm s−1 around sunset and a maximum of about 18 mm s−1 around sunrise. Application of the method to dropsonde data from an airborne field campaign in August 2016 yields the first measurements of the mass flux derived from the mass budget, and supports the result that the variability in M is mostly due to the variability in W. Our analyses thus suggest a strong coupling between the day-to-day variability in shallow convective mixing (as measured by M) and the large-scale circulation (as measured by W). Application of the method to the EUREC4A field campaign will help evaluate this coupling, and assess its implications for cloud-base cloudiness. [ABSTRACT FROM AUTHOR]

The pre-cold-frontal low-level jet (LLJ) is an important contributor for water vapor transport within atmospheric rivers, though its dynamics are not completely understood. The present study investigates the LLJ using dropsonde observations from 24 cross-atmospheric river transects taken during the CalWater-2014, 2015 and the AR-Recon 2016, 2018 field campaigns. It is found that the LLJ, located at ~1-km elevation ahead of the cold front, has an average maximum wind speed of 30 m s−1 and is strongly supergeostrophic with an average ageostrophic component of 6 m s−1. The alongfront ageostrophy occurs within the atmospheric layer (750–1250 m) known to strongly control orographic precipitation associated with atmospheric rivers. The ERA5 reanalysis product is used to both validate the observed geostrophic winds and investigate the supergeostrophic jet dynamics. The comparison demonstrates that there is no systematic bias in the observed geostrophic wind but that the ERA5 LLJ total wind field is generally biased low by an amount consistent with the observed ageostrophy. One of the few cases in which the ERA5 produces an ageostrophic LLJ occurs on 13 February 2016, which is used to investigate the dynamical processes responsible for the ageostrophy. This analysis demonstrates that the isallobaric (pressure tendency) term serves to accelerate the ageostrophic jet, and the Coriolis torque and advective tendency terms serve to propagate the jet normal to the LLJ. Therefore, if a model is to accurately represent the LLJ, it must adequately resolve processes contributing toward the pressure tendencies along the cold front. [ABSTRACT FROM AUTHOR]

Diverse observations, such as the High Definition Sounding System (HDSS) dropsonde observations from the Tropical Cyclone Intensity (TCI) program, the Tail Doppler Radar (TDR), Stepped Frequency Microwave Radiometer (SFMR), and flight-level observations from the Intensity Forecasting Experiment (IFEX) program, and the atmospheric motion vectors (AMVs) from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) simultaneously depicted the three-dimensional (3D) structure of Hurricane Patricia (2015). Experiments are conducted to understand the relative impacts of each of these observation types on Patricia's analysis and prediction using the Gridpoint Statistical Interpolation (GSI)-based ensemble-variational data assimilation system for the Hurricane Weather Research and Forecasting (HWRF) Model. In comparing the impacts of assimilating each dataset individually, results suggest that 1) the assimilation of 3D observations produces better TC structure analysis than the assimilation of two-dimensional (2D) observations; 2) the analysis from assimilating observations collected from platforms that only sample momentum fields produces a less improved forecast with either short-lived impacts or slower intensity spinup as compared to the forecast produced after assimilating observations collected from platforms that sample both momentum and thermal fields; and 3) the structure forecast tends to benefit more from the assimilation of inner-core observations than the corresponding intensity forecast, which implies better verification metrics are needed for future TC forecast evaluation. [ABSTRACT FROM AUTHOR]

Atmospheric rivers, often associated with impactful weather along the west coast of North America, can be a challenge to forecast even on short time scales. This is attributed, at least in part, to the scarcity of eastern Pacific in situ observations. We examine the impact of assimilating dropsonde observations collected during the Atmospheric River (AR) Reconnaissance 2018 field program on the Navy Global Environmental Model (NAVGEM) analyses and forecasts. We compare NAVGEM's representation of the ARs to the observations, and examine whether the observation–background difference statistics are similar to the observation error variance specified in the data assimilation system. Forecast sensitivity observation impact is determined for each dropsonde variable, and compared to the impacts of the North American radiosonde network. We find that the reconnaissance soundings have significant beneficial impact, with per observation impact more than double that of the North American radiosonde network. Temperature and wind observations have larger total and per observation impact than moisture observations. In our experiment, the 24-h global forecast error reduction from the reconnaissance soundings can be comparable to the reduction from the North American radiosonde network for the field program dates that include at least two flights. [ABSTRACT FROM AUTHOR]

The increase of the vertical scaling exponent of the horizontal wind Hv(s) with altitude from the surface of the Pacific Ocean to 13 km altitude, as observed by GPS dropsondes, is investigated. An explanation is offered in terms of the decrease of gravitational force and decrease of quenching efficiency of excited photofragments from ozone photodissociation with increasing altitude (decreasing pressure). Turbulent scaling is examined in both the vertical from dropsondes and horizontal from aircraft observations; the scaling exponents H for both wind speed and temperature in both coordinates are positively correlated with traditional measures of jet stream strength. Interpretation of the results indicates that persistence of molecular velocity after collision induces symmetry breaking emergence of hydrodynamic flow via the mechanism first modelled by Alder and Wainwright, enabled by the Gibbs free energy carried by the highest speed molecules. It is suggested that the combined effects have the potential to address the cold bias in numerical models of the global atmosphere.

Recent high‐resolution dropsonde observations from the 2010 Concordiasi field campaign in austral spring season show that surface‐based inversions (SBIs) over Antarctica are frequently eroded, with well‐mixed boundary layers occurring 33% and 18% of the time in West and East Antarctica, respectively. In this study, using the dropsonde observations, we evaluate the performance of the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA2) in representing the Antarctic boundary layer thermodynamic structure. Results show that MERRA2 has a good overall representation of the Antarctic surface stability and correctly predicts 82% of the SBIs. However, an underprediction of less stable boundary layer occurrence, especially over the elevated East Antarctic plateau, is favored during conditions of increased lower tropospheric stability associated with model dynamics, indicating difficulty in parameterizing turbulence in very stable boundary layers. In addition, a lower tropospheric cool bias (first model level and above) is observed in the MERRA2 reanalysis, especially over West Antarctica, which amplifies in the boundary layer during mixed conditions. The near‐surface cold bias is most pronounced when the model fails to predict mixed layers over West Antarctica and is expected to negatively impact the representation of surface energy budget and melt processes. Key Points: MERRA2 has good skill in representing the frequency of less stable and stable Antarctic boundary layersThe model underpredicts turbulence and the frequency of less stable boundary layers especially over elevated regions of East AntarcticaRepercussions of missing boundary layer turbulent processes are more severe for the representation of West Antarctic surface processes [ABSTRACT FROM AUTHOR]

The thermodynamic impacts of downdraft-induced cooling/drying and downstream recovery via surface enthalpy fluxes within tropical cyclones (TCs) were investigated using dropsonde observations collected from 1996 to 2017. This study focused on relatively weak TCs (tropical depression, tropical storm, category 1 hurricane) that were subjected to moderate (4.5–11.0 m s−1) levels of environmental vertical wind shear. The dropsonde data were analyzed in a shear-relative framework and binned according to TC intensity change in the 24 h following the dropsonde observation time, allowing for comparison between storms that underwent different intensity changes. Moisture and temperature asymmetries in the lower troposphere yielded a relative maximum in lower-tropospheric conditional instability in the downshear quadrants and a relative minimum in instability in the upshear quadrants, regardless of intensity change. However, the instability increased as the intensification rate increased, particularly in the downshear quadrants. This was due to increased boundary layer moist entropy relative to the temperature profile above the boundary layer. Additionally, significantly larger surface enthalpy fluxes were observed as the intensification rate increased, particularly in the upshear quadrants. These results suggest that in intensifying storms, enhanced surface enthalpy fluxes in the upshear quadrants allow downdraft-modified boundary layer air to recover moisture and heat more effectively as it is advected cyclonically around the storm. By the time the air reaches the downshear quadrants, the lower-tropospheric conditional instability is enhanced, which is speculated to be more favorable for updraft growth and deep convection. [ABSTRACT FROM AUTHOR]

Observations from the Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT), Genesis and Rapid Intensification Processes (GRIP), and Intensity Forecast Experiment (IFEX) field campaigns are analyzed to investigate the mesoscale processes leading to the tropical cyclogenesis of Hurricane Karl (2010). Research aircraft missions provided Doppler radar, in situ flight level tropical cyclogenesis of Hurricane Karl (2010). Research aircraft missions provided Doppler radar, in situ flight level, and dropsonde data documenting the structural changes of the predepression disturbance. Following the pre-Karl wave pouch, variational analyses at the meso-β and meso-α scales suggest that the convective cycle in Karl alternately built the low- and midlevel circulations leading to genesis episodically rather than through a sustained lowering of the convective mass flux from increased stabilization. Convective bursts that erupt in the vorticity-rich environment of the recirculating pouch region enhance the low-level meso-β- and meso-α-scale circulation through vortex stretching. As the convection wanes, the resulting stratiform precipitation strengthens the midlevel circulation through convergence associated with ice microphysical processes, protecting the disturbance from the intrusion of dry environmental air. Once the column saturation fraction returns to a critical value, a subsequent convective burst below the midlevel circulation further enhances the low-level circulation, and the convective cycle repeats. The analyses suggest that the onset of deep convection and associated low-level spinup were closely related to the coupling of the vorticity and moisture fields at low and midlevels. Our interpretation of the observational analysis presented in this study reaffirms a primary role of deep convection in the genesis process and provides a hypothesis for the supporting role of stratiform precipitation and the midlevel vortex. [ABSTRACT FROM AUTHOR]

The axisymmetric structure of the inner-core hurricane boundary layer (BL) during intensification [IN; intensity tendency ≥20 kt (24 h)−1, where 1 kt ≈ 0.5144 m s−1], weakening [WE; intensity tendency <−10 kt (24 h)−1], and steady-state [SS; the remainder] periods are analyzed using composites of GPS dropwindsondes from reconnaissance missions between 1998 and 2015. A total of 3091 dropsondes were composited for analysis below 2.5-km elevation—1086 during IN, 1042 during WE, and 963 during SS. In nonintensifying hurricanes, the low-level tangential wind is greater outside the radius of maximum wind (RMW) than for intensifying hurricanes, implying higher inertial stability (I2) at those radii for nonintensifying hurricanes. Differences in tangential wind structure (and I2) between the groups also imply differences in secondary circulation. The IN radial inflow layer is of nearly equal or greater thickness than nonintensifying groups, and all groups show an inflow maximum just outside the RMW. Nonintensifying hurricanes have stronger inflow outside the eyewall region, likely associated with frictionally forced ascent out of the BL and enhanced subsidence into the BL at radii outside the RMW. Equivalent potential temperatures (θe) and conditional stability are highest inside the RMW of nonintensifying storms, which is potentially related to TC intensity. At greater radii, inflow layer θe is lowest in WE hurricanes, suggesting greater subsidence or more convective downdrafts at those radii compared to IN and SS hurricanes. Comparisons of prior observational and theoretical studies are highlighted, especially those relating BL structure to large-scale vortex structure, convection, and intensity. [ABSTRACT FROM AUTHOR]

The dropsondes released during the Tropical Cyclone Intensity (TCI) field campaign provide high-resolution kinematic and thermodynamic measurements of tropical cyclones within the upper-level outflow and inner core. This study investigates the impact of these upper-level TCI dropsondes on analyses and prediction of Hurricane Patricia (2015) during its rapid intensification (RI) phase using an ensemble–variational data assimilation system. In the baseline experiment (BASE), both kinematic and thermodynamic observations of TCI dropsondes at all levels except the upper levels are assimilated. The upper-level wind and thermodynamic observations are assimilated in additional experiments to investigate their respective impacts. Compared to BASE, assimilating TCI upper-level wind observations improves the accuracy of outflow analyses verified against independent atmospheric motion vector (AMV) observations. It also strengthens the tangential and radial wind near the upper-level eyewall. The inertial stability within the upper-level eyewall is enhanced, and the maximum outflow is more aligned toward the inner core. Additionally, the analyses including the upper-level thermodynamic observations produce a warmer and drier core at high levels. Assimilating both upper-level kinematic and thermodynamic observations also improves the RI forecast. Compared to BASE, assimilating the upper-level wind induces more upright and inward-located eyewall convection, resulting in more latent heat release closer to the warm core. This process leads to stronger inner-core warming. Additionally, the initial warmer upper-level inner core produced by assimilating TCI thermodynamic observations also intensifies the convection and latent heat release within the eyewall, thus further contributing to the improved intensity forecasts. [ABSTRACT FROM AUTHOR]

Aircraft reconnaissance missions remain the primary means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and partially rely on regions of highest uncertainty in the Global Ensemble Forecast System. Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft flight track for a prospective mission. AOML's Hurricane Research Division has developed a system for performing regional observing system simulation experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasting. This study focuses on improving existing targeting methods by investigating the impact of proposed aircraft observing system designs through various sensitivity studies. G-IV dropsonde retrievals were simulated from a regional nature run, covering the life cycle of a rapidly intensifying Atlantic hurricane. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms, where dropsondes released closer to the vortex–environment interface provide the largest impact on the track forecast. All dropsonde configurations provide a positive 2-day impact on intensity forecasts by improving the environmental conditions known to impact tropical cyclone intensity. [ABSTRACT FROM AUTHOR]

Operational numerical models failed to predict the record-setting rapid intensification and rapid overwater weakening of Hurricane Patricia (2015) in the eastern North Pacific basin, resulting in large intensity forecast errors. In an effort to better understand the mesoscale processes contributing to Patricia's rapid intensity changes, we analyze high-resolution aircraft observations collected on 22–23 October. Spline-based variational analyses are created from observations collected via in situ measurements, Doppler radar, and full-tropospheric dropsonde profiles as part of the Office of Naval Research Tropical Cyclone Intensity (TCI) experiment and the National Oceanic and Atmospheric Administration Intensity Forecasting Experiment (IFEX). We present the first full-tropospheric calculation of the dry, axisymmetric Ertel's potential vorticity (PV) in a tropical cyclone without relying on balance assumptions. Detailed analyses reveal the formation of a "hollow tower" PV structure as Patricia rapidly approached its maximum intensity, and a subsequent breakdown of this structure during Patricia's rapid overwater weakening phase. Transforming the axisymmetric PV analyses from radius–height to potential radius–isentropic coordinates reveals that Patricia's rapid intensification was closely related to the distribution of diabatic heating and eddy mixing. During Patricia's rapid overwater weakening phase, eddy mixing processes are hypothesized to be the primary factor rearranging the PV distribution near the eye–eyewall region, diluting the PV previously confined to the hollow tower while approximately conserving the absolute circulation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Measurements of vertical profiles of areal-mean mass divergence, vorticity, and vertical velocity, based on dropsondes distributed over an area of 25 000 km2, are presented. The dropsondes were released with high frequency along circular flight patterns during an airborne field campaign taking place over the tropical Atlantic near Barbados. Vertical profiles of the area-averaged mass divergence and vorticity were computed from the horizontal wind profiles, and the area-averaged vertical velocity was then inferred from the divergence. The consistency of measurements over pairs of circles flown within the same air mass demonstrated the reproducibility of the measurements, and showed that they characterize the environmental conditions on the scale of the measurement, rather than being dominated by measurement error or small-scale wind variability. The estimates from dropsondes were found to be consistent with the observed cloud field, with Lagrangian estimates of the mean vertical velocity inferred from the free-tropospheric humidity field, and with the mean vertical velocity derived from simulations using an atmospheric model representing kilometer-scale motions and initialized with meteorological analyses. In trade wind–like conditions, the divergence and vorticity profiles exhibit a rich vertical structure and a significant variability in space and time. Yet a few features appear to be robust, such as the presence of layers of mass convergence at the top of moist layers, extrema of the area-averaged vertical velocity at the top of the subcloud layer and in the midtroposphere, and minima around the trade inversion near 2 km. The analysis of spatial and temporal autocorrelation scales suggests that the divergent mass field measured from dropsondes is representative of the environment of shallow clouds. [ABSTRACT FROM AUTHOR]

Blowing snow is a frequent and widespread phenomenon over most of Antarctica. The transport and sublimation of blowing snow are important for the mass balance of the Antarctic ice sheet, and the latter is a major contributor to the hydrological cycle in high-latitude regions. Although much is known about blowing snow from surface observations, knowledge of the thermodynamic structure of deep (>50 m) blowing-snow layers is lacking. Here, dropsonde measurements are used to investigate the temperature, moisture, and wind structure of deep blowing-snow layers over Antarctica. The temperature lapse rate within the blowing-snow layer is at times close to dry adiabatic and is on average between dry and moist adiabatic. Initiation of blowing snow causes the surface temperature to increase to a degree proportional to the depth of the blowing-snow layer. The relative humidity with respect to ice is generally largest near the surface (but less than 100%) and decreases with height, reaching a minimum near the top of the layer. These findings are at odds with the generally accepted theory that blowing-snow sublimation will cool and eventually saturate the layer. The observations support the conclusion that high levels of wind-shear-induced turbulence cause mixing and entrainment of warmer air from above the blowing-snow layer, which suppresses humidity and produces the observed well-mixed temperature structure within the layer. The results may have important consequences for understanding the mass balance of the Antarctic ice sheet and the moisture budget of the atmosphere in high latitudes. [ABSTRACT FROM AUTHOR]

Extreme updrafts (≥10 m s−1) and wind gusts (≥90 m s−1) are ubiquitous within the low-level eyewall of intense tropical cyclones (TCs). Previous studies suggest that both of these features are associated with coherent subkilometer-scale vortices. Here, over 100 000 "virtual" dropsonde trajectories are examined within a large-eddy simulation (31.25-m horizontal grid spacing) of a category 5 hurricane in order to gain insight into the nature of these features and to better understand and interpret dropsonde observations. At such a high resolution, profiles of wind speed and vertical velocity from the virtual sondes are difficult to distinguish from those of real dropsondes. PDFs of the strength of updrafts and wind gusts compare well between the simulated and observed dropsondes, as do the respective range of heights over which these features are found. Individual simulated updrafts can be tracked for periods of up to several minutes, revealing structures that are both coherent and rapidly evolving. It appears that the updrafts are closely associated with vortices and wind speed maxima, consistent with previous studies. The peak instantaneous wind gusts in the simulations (up to 150 m s−1) are substantially stronger than have ever been observed. Using the virtual sondes, it is demonstrated that the probability of sampling such extremes is vanishingly small, and it is argued that actual intense TCs might also be characterized by gusts of these magnitudes. [ABSTRACT FROM AUTHOR]

Abstract The existence of the super-gradient-wind region, where the tangential winds are larger than the gradient wind, has been widely observed inside the hurricane boundary layer. Hence, the extensively used log-law or power-law wind profiles under near-neutral conditions may be inappropriate to characterize the boundary layer winds associated with hurricanes. Recent development in the wind measurement techniques overland together with the abundance of data over ocean enabled a further investigation on the boundary layer wind structure of hurricanes before/after landfall. In this study, a semi-empirical model for mean wind velocity profile of landfalling hurricanes has been developed based on the data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network operated by the National Weather Service and the Global Positioning System (GPS) dropsondes collected by the National Hurricane Center and Hurricane Research Division. The proposed mathematical representation of engineering wind profile consists of a logarithmic function of the height z normalized by surface roughness z 0 (z / z 0) and an empirical function of z normalized by the height of maximum wind δ (z / δ). In addition, the consideration of wind direction in terms of the inflow angle is integrated in the boundary layer wind profile. Field-measurement wind data for both overland and over-ocean conditions have been employed to demonstrate the accuracy of simulation and convenience in use of the developed semi-empirical model for mean wind velocity profile of landfalling hurricanes. Highlights • A semi-empirical model for mean wind velocity profile of landfalling hurricanes has been developed. • The model consists of a logarithmic function of height z and an empirical function of z normalized by height of maximum wind. • The proposed height of maximum wind highlights the contribution from both the inertial stability and surface roughness. • Consideration of wind direction in terms of inflow angle is integrated in the boundary layer wind profile. • Wind data for both overland and over-ocean conditions have been employed to develop the semi-empirical wind profile model. [ABSTRACT FROM AUTHOR]

This study demonstrates that Global Hawk unmanned aircraft system dropwindsondes and Atmospheric Infrared Sounder (AIRS) observations can be complementary in sampling a tropical cyclone (TC). The assimilation of both datasets in a regional ensemble data assimilation system shows that the cumulative impact of both datasets is greater than either one alone because of the presence of mutually independent information content. The experiment that assimilates both datasets has smaller position and intensity errors in the mean analysis than those with individual datasets. The improvements in track and intensity forecasts that result from combining both datasets also indicate synergistic benefits. Overall, superior track and intensity forecasts are evident. This study suggests that polar-orbiting satellite spatial coverage should be considered in operational reconnaissance mission planning in order to achieve further improvements in TC analyses and forecasts. [ABSTRACT FROM AUTHOR]

A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individualARtransports~5×108 kg s-1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on -1 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERAInterim (MERRA-2), which indicates a mean error of -2% (-8%) in AR width and +3% (-1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and;6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts. [ABSTRACT FROM AUTHOR]

The inner-core thermodynamic structure of Hurricane Edouard (2014) is explored, primarily through an examination of both high-altitude dropsondes deployed during NASA's Hurricane and Severe Storm Sentinel (HS3) and a 60-member convection-permitting ensemble initialized with an ensemble Kalman filter. The 7-day forecasts are initialized coincident with Edouard's tropical depression designation and include Edouard's significant intensification to a major hurricane. Ten-member ensemble groups are created based on timing of near-rapid intensification (RI) onset, and the associated composite inner-core temperature structures are analyzed. It is found that at Edouard's peak intensity, in both the observations and the simulations, the maximum inner-core perturbation temperature (~10-12 K) occurs in the midlevels (~4-8 km). In addition, in all composite groups that significantly intensify, the evolution of the area-averaged inner-core perturbation temperatures indicate that weak to moderate warming (at most 4K) begins to occur in the low to midlevels (~2-6 km); 24-48 h prior to RI, and this warming significantly strengthens and deepens (up to; 8km); 24 h after RI has begun. Despite broad similarities in the evolution of Edouard's warm core in these composites, variability in the height and strength of the maximum perturbation temperature and in the overall development of the inner-core temperature structure are present among the members of the composite groups (despite similar intensity time series). This result and concomitant correlation analyses suggest that the strength and height of the maximum perturbation temperature is not a significant causal factor for RI onset in this ensemble. Fluctuations in inner-core temperature structure occur either in tandem with or after significant intensity changes. [ABSTRACT FROM AUTHOR]