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It is argued that a sixth static stability state, moist absolute instability, can be created and maintained over mesoscale areas of the atmosphere. Examination of over 130 000 soundings and a numerical simulation of an observed event are employed to support the arguments in favor of the existence of moist absolutely unstable layers (MAULs).
Although MAULs were found in many different synoptic environments, of particular interest in the present study are the deep (≥ 100 mb) layers that occur in conjunction with mesoscale convective systems (MCSs). A conceptual model is proposed to explain how moist absolute instability is created and maintained as MCSs develop. The conceptual model states that strong, mesoscale, nonbuoyancy-driven ascent brings a conditionally unstable environmental layer to saturation faster than small-scale, buoyancy-driven convective elements are able to overturn and remove the unstable state. Moreover, since lifting of a moist absolutely unstable layer warms the environment, the temperature difference between the environment and vertically displaced parcels is reduced, thereby decreasing the buoyancy of convective parcels and helping to maintain the moist absolutely unstable layer.
Output from a high-resolution numerical simulation of an event exhibiting this unstable structure supports the conceptual model. In particular, the model indicates that MAULs can exist for periods greater than 30 min over horizontal scales up to hundreds of kilometers along the axis of the convective region of MCSs, and tens of kilometers across the convective region.
The existence of moist absolute instability suggests that some MCSs are best characterized as slabs of saturated, turbulent flow rather than a collection of discrete cumulonimbus clouds separated by subsaturated areas. The processes in MAULs also help to explain how an initially unsaturated, stably stratified, midlevel environment is transformed into the mesoscale area of saturated moist-neutral conditions commonly observed in the stratiform region of mesoscale convective systems.
It is argued that a sixth static stability state, moist absolute instability, can be created and maintained over mesoscale areas of the atmosphere. Examination of over 130 000 soundings and a numerical simulation of an observed event are employed to support the arguments in favor of the existence of moist absolutely unstable layers (MAULs).
Although MAULs were found in many different synoptic environments, of particular interest in the present study are the deep (≥ 100 mb) layers that occur in conjunction with mesoscale convective systems (MCSs). A conceptual model is proposed to explain how moist absolute instability is created and maintained as MCSs develop. The conceptual model states that strong, mesoscale, nonbuoyancy-driven ascent brings a conditionally unstable environmental layer to saturation faster than small-scale, buoyancy-driven convective elements are able to overturn and remove the unstable state. Moreover, since lifting of a moist absolutely unstable layer warms the environment, the temperature difference between the environment and vertically displaced parcels is reduced, thereby decreasing the buoyancy of convective parcels and helping to maintain the moist absolutely unstable layer.
Output from a high-resolution numerical simulation of an event exhibiting this unstable structure supports the conceptual model. In particular, the model indicates that MAULs can exist for periods greater than 30 min over horizontal scales up to hundreds of kilometers along the axis of the convective region of MCSs, and tens of kilometers across the convective region.
The existence of moist absolute instability suggests that some MCSs are best characterized as slabs of saturated, turbulent flow rather than a collection of discrete cumulonimbus clouds separated by subsaturated areas. The processes in MAULs also help to explain how an initially unsaturated, stably stratified, midlevel environment is transformed into the mesoscale area of saturated moist-neutral conditions commonly observed in the stratiform region of mesoscale convective systems.
Abstract
Unique data from seven flights of the Coyote small unmanned aircraft system (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA’s P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (>1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (<150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes and suggest opportunities for future work using these promising new observing platforms.
Abstract
Unique data from seven flights of the Coyote small unmanned aircraft system (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA’s P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (>1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (<150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes and suggest opportunities for future work using these promising new observing platforms.
Abstract
Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.
Abstract
Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.
