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NASA NTRS2021

GOES-16 Observations of Rapidly-Intensifying Tropical Cyclones: Hurricanes Harvey (2017), Maria (2017), And Michael (2018)

This study utilizes brightness temperatures (Tb’s) observed by the infrared longwave window band (Ch 14; 11.2 m) from the Geostationary Operational Environmental Satellite-16 (GOES-16) to examine the structure of Hurricanes Harvey, Maria, and Michael throughout their lifetimes. During the times leading up to their rapid intensifications (RI), two-dimensional inner-core structures are examined to analyze the strength and location of the developing convection. Moderate vertical wind shear in the environments of Harvey and Michael induced a pronounced convective asymmetry prior to RI, followed by a rapid axisymmetrization that occurred essentially in conjunction with RI. The evolutions of the tropical cyclones’ (TCs’) coldest Tb’s indicate that the inner-core convective activity began to increase in the 12 h prior to RI onset, primarily in 2–4-h substantial “bursts”, while substantial convection dominated essentially the entirety of the region within 100 km of the surface center within 12 h of the onset of intensification. Azimuthally averaged Tb evolutions illustrate the development of each TCs’ eye and eyewall, the variability of the radial extent of the central dense overcast associated with the diurnal cycle, as well as details of the evolving convective structures throughout intensification. Hövmoller diagrams of data at constant radii reveal areas of cold Tb’s propagating around the TCs on timescales of 2–3-h. The examination of these features in a deep-layer shear-relative sense reveals that they initiate primarily downshear of the TCs’ surface centers. As RI is reached, these areas of convection are able to propagate into the upshear quadrants, which helps facilitate the onset of more substantial intensification.

Hurricanes↗
NASA NTRS2021

The Influence of Direct Radiative Forcing Versus Indirect Sea Surface Temperature Warming on Southern Hemisphere Subtropical Anticyclones Under Global Warming

Southern hemisphere subtropical anticyclones are projected to change in a warmer climate during both austral summer and winter. A recent study of CMIP 5 & 6 projections found a combination of local diabatic heating changes and static-stability-induced changes in baroclinic eddy growth as the dominant drivers. Yet the underlying mechanisms forcing these changes still remain uninvestigated. This study aims to enhance our mechanistic understanding of what drives these Southern Hemisphere anticyclones changes during both seasons. Using an AGCM, we decompose the response to CO2-induced warming into two components: (1) the fast atmospheric response to direct CO2 radiative forcing, and (2) the slow atmospheric response due to indirect sea surface temperature warming. Additionally, we isolate the influence of tropical diabatic heating with AGCM added heating experiments. As a complement to our numerical AGCM experiments, we analyze the Atmospheric and Cloud Feedback Model Intercomparison Project experiments. Results from sensitivity experiments show that slow subtropical sea surface temperature warming primarily forces the projected changes in subtropical anticyclones through baroclinicity change. Fast CO2 atmospheric radiative forcing on the other hand plays a secondary role, with the most notable exception being the South Atlantic subtropical anticyclone in austral winter, where it opposes the forcing by sea surface temperature changes resulting in a muted net response. Lastly, we find that tropical diabatic heating changes only significantly influence Southern Hemisphere subtropical anticyclone changes through tropospheric wind shear changes during austral winter.

Subtropical anticyclone↗
NASA NTRS2022

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗
NASA NTRSDate not supplied

Analyzing the Tropical Cyclone Diurnal Cycle using GPM, TROPICS, and other Spaceborne Observations

Tropical cyclones (TCs) exhibit a distinct diurnal cycle of high clouds and rainfall, marked by an expansion of the TC cirrus canopy during the day and enhanced rainfall overnight. Recent modeling work also has uncovered a diurnal cycle of low-level radial and tangential winds in simulated storms, marked by an expansion of the surface wind field overnight and into the morning, along with increasing maximum wind speed in the eyewall. These results suggest that diurnal changes in radiative heating tendencies not only affect upper-level cirrus clouds and precipitating convection, but also the low-level circulation. This presentation will characterize expansions of the TC rain field using the Global Precipitation Measurement (GPM) Mission’s Integrated Multi-Satellite Retrievals for GPM (IMERG) half-hourly precipitation estimates. The Level 3 IMERG-Final rainfall data are azimuthally averaged about TC center positions in the Atlantic and Eastern Pacific basins, accounting for asymmetries due to vertical wind shear and storm motion. Preliminary results indicate that the TC rain field expands overnight and through the morning, reaching its maximum extent during the afternoon. This evolution is considerably asymmetric, however, with expansion favored downshear of the storm center. The results are broadly consistent with previous work that characterized the TC diurnal cycle using other observations and simulations. A similar analysis is performed using microphysical retrievals from the GPM Goddard Profiling algorithm and lightning data from the Geostationary Lightning Mapper to understand the relationship between the diurnal cycle, ice microphsyics, and lightning. Finally, with the ongoing Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, we will discuss our plans to leverage TROPICS for enhanced observation of the TC diurnal cycle.

Patrick Duran↗
NASA NTRSDate not supplied

Toward The Development of Hailstorm Climatologies Derived From Reanalyses and Infared/Passive Microwave Satellite Imagers

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) and Meteosat series, provide both historical and near-real-time observations of cloud top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to United States Next Generation Weather Radar- (NEXRAD-) estimated Maximum Expected Size of Hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are specifically designed to make hail likelihood distinctions based on satellite-indicated points of deep convection within environments favorable for storm development. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. This presentation demonstrates that statistical distributions of convective parameters from satellite and reanalysis show separation between non-severe/severe hailstorm classes for predictors including overshooting cloud top temperature and area characteristics, convective available potential energy, vertical wind shear, 500 hPa temperature, mid-level lapse rate, precipitable water, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a hail likelihood metric with a critical success index of 0.504 and Heidke skill score of 0.403, which is exceptional among recent analogous hail studies. Furthermore, applications of the DNN to select case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-year GOES-12/13 image database to derive a hail frequency and severity climatology, which denotes the Central Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied. Opportunities for training and applying DNN-based hailstorm predictions to recently developed GOES-8/10/12/13/16 and Meteosat Second Generation convective storm detection and characterization climatologies over South America and South Africa, respectively, will also be presented.

Kristopher Bedka↗
NASA NTRSDate not supplied

Understanding the Vertical Slope of Mesoscale Snow Band Reflectivity Signatures

Mesoscale snow bands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The ongoing NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign observed several instances of mesoscale snow bands during January and February of 2020 and 2022. These snow bands were sampled by a combination of airborne (NASA ER-2 and P-3) and ground-based remote sensing and in-situ instruments. Along-band cross sections of these snow bands reveal that many of them are vertically sloped. Our preliminary analysis into one of these snow bands suggests that the vertical slope is not maintained by isentropic lift and does not appear to be tied to horizontal deformation. A combined analysis of the reflectivity and wind retrievals from the ER-2 radars raises the possibility that these features could be produced by vertical wind shear layers deforming fall streaks into bands that extend hundreds of kilometers. The present study will focus on extending our preliminary analysis to additional cases and understanding the mechanisms that support these features using a combination of radar data, in-situ aircraft measurements, and numerical modeling.

Charles Helms↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are a phenomenon that occurs in many mesoscale and synoptic weather systems, including tropical cyclones. TCBs are defined as "Bands of clouds oriented perpendicular to the flow in which they are embedded" (NOAA) and can be associated with low static stability and high environmental vertical wind shear in the upper levels (Kawashima 2021). TCBs in tropical cyclones are of particular interest due to their apparent occurrence and potential linkage to the tropical cyclone diurnal cycle, stronger tropical cyclones, and rapid intensification, where rapid intensification is an intensification rate of 30 knots or more in 24 hours (NHC).

John Mark Mayhall↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are bands of upper-level clouds that are regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle, but these hypothesized relationships have not been rigorously tested due to the difficulty of objectively identifying TCBs in satellite images. This presentation describes a machine learning technique that successfully identifies TCBs in imagery from the GOES-16 Advanced Baseline Imager. The technique uses a convolutional neural network (CNN) that assigns a probability of each pixel in the image being associated with a TCB. Using the CNN, a database of TCBs from 2018 to 2022 was developed for the Atlantic basin. Statistics using this database will be presented, including the relationship between TCBs and deep-layer vertical wind shear, intensity change, and the TC diurnal cycle.

John Mark Mayhall↗
NASA NTRS1974

Impact of combustion products from Space Shuttle launches on ambient air quality

The present work describes some multilayer diffusion models and a computer program for these models developed to predict the impact of ground clouds formed during Space Shuttle launches on ambient air quality. The diffusion models are based on the Gaussian plume equation for an instantaneous volume source. Cloud growth is estimated on the basis of measurable meteorological parameters: standard deviation of the wind azimuth angle, standard deviation of wind elevation angle, vertical wind-speed shear, vertical wind-direction shear, and depth of the surface mixing layer. Calculations using these models indicate that Space Shuttle launches under a variety of meteorological regimes at Kennedy Space Center and Vandenberg AFB are unlikely to endanger the exposure standards for HCl; similar results have been obtained for CO and Al2O3. However, the possibility that precipitation scavenging of the ground cloud might result in an acidic rain that could damage vegetation has not been investigated.

Dumbauld, R. K.↗
NASA NTRS1998

Seasonal Cycles of Meridional Overturning and Heat Transport of the Indian Ocean

A general circulation model of the Indian Ocean is fitted to monthly averaged climatological temperatures, salinities, and surface fluxes using the adjoint method. Interannual variability is minimized by penalizing the temporal drift from one seasonal cycle to another during a two-year integration. The resultant meridional overturning and heat transport display large seasonal variations, with maximum amplitudes of 18 and 22 (x 10(exp 6) cubic m/s) for the overturning and 1.8 and 1.4 (x 10(exp 15) W) for heat transport near 10 S and 10 N, respectively. A dynamical decomposition of the overturning and heat transport shows that the time-varying Ekman How plus its barotropic compensation can explain a large part of the seasonal variations in overturning and heat transport. The maximum variations at 10 deg N and 10 deg S are associated with monsoon reversal over the northern Indian Ocean and changes of the easterlies over the southern Indian Ocean. An external mode with variable topography has a moderate contribution where the Somali Current and the corresponding gyre reverse direction seasonally. Contribution front vertical shear (thermal wind and ageostrophic shear) is dominant near the southern boundary and large near the Somali Current latitudes. The dominant balance in the zonally integrated heat budget is between heat storage change and heat transport convergence except south of 15 S. Optimization with seasonal forcings improves estimates of sea surface temperatures, but the annual average overturning and heat transport are very similar to previous results with annual mean forcings. The annual average heat transport consists of roughly equal contributions from time-mean and time-varying fields of meridional velocities and temperatures in the northern Indian Ocean. indicating a significant rectification to the heat transport due to the time-varying fields. The time-mean and time-varying contributions are primarily due to the overturning and horizontal gyre, respectively. Inclusion of TOPEX data enhances the seasonal cycles of the estimated overturning and heat transport in the central Indian Ocean significantly and improves the estimated equatorial zonal flows but leads 10 unrealistic estimates of the velocity structure near the Indonesian Throughflow region, most likely owing to the deficiencies in the lateral boundary conditions.

Lee, Tong↗
NASA NTRS2006

Final Report for The Creation of a Physics-based Ground-effect Model, Phase 2 - Inclusion of the Effects of Wind, Stratification, and Shear into the New Ground Effect Model

The reduction of the separation of the leading and following aircrafts is desirable to enhance the airport capacity provided that there is a physics-based operational model applicable to all regions of the flight domain (out of ground effect, OGE; near ground effect, NGE; and in ground effect, IGE) and that the quality of the quantitative input from the measurements of the prevailing atmospheric conditions and the quality of the total airport operations regarding the safety and the sound interpretation of the prevailing conditions match the quality of the analysis and numerical simulations. In the absence of an analytical solution, the physics of the flow is best expressed by a mathematical model based on numerical simulations, field and laboratory experiments, and heuristic reasoning. This report deals with the creation of a sound physics-based real-time IGE model of the aircraft wake vortices subjected to crosswind, stratification and shear.

Sarpkaya, Turgut↗
NASA NTRS1992

Velocity shear generation of solar wind turbulence

A two-dimensional incompressible MHD spectral code is used to show that shear-driven turbulence is a possible means for producing many observed properties of the evolution of the magnetic and velocity fluctuations in the solar wind and, in particular, the evolution of the cross helicity ('Alfvenicity') at small scales. It is shown that large-scale shear can nonlinearly produce a cascade to smaller scale fluctuations even when the linear Kelvin-Helmholtz mode is stable, and that a roughly power law inertial range is established by this process. The evolution found is similar to that seen in some other simulations of MHD turbulence.

Roberts, D. A.↗
NASA NTRS2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario

Jingyi Chen↗
NASA NTRS2011

Long-Term Evolution of the Aerosol Debris Cloud Produced by the 2009 Impact on Jupiter

We present a study of the long-term evolution of the cloud of aerosols produced in the atmosphere of Jupiter by the impact of an object on 19 July 2009. The work is based on images obtained during 5 months from the impact to 31 December 2009 taken in visible continuum wavelengths and from 20 July 2009 to 28 May 2010 taken in near-infrared deep hydrogen-methane absorption bands at 2.1-2.3 micron. The impact cloud expanded zonally from approximately 5000 km (July 19) to 225,000 km (29 October, about 180 deg in longitude), remaining meridionally localized within a latitude band from 53.5 deg S to 61.5 deg S planetographic latitude. During the first two months after its formation the site showed heterogeneous structure with 500-1000 km sized embedded spots. Later the reflectivity of the debris field became more homogeneous due to clump mergers. The cloud was mainly dispersed in longitude by the dominant zonal winds and their meridional shear, during the initial stages, localized motions may have been induced by thermal perturbation caused by the impact's energy deposition. The tracking of individual spots within the impact cloud shows that the westward jet at 56.5 deg S latitude increases its eastward velocity with altitude above the tropopause by 5- 10 m/s. The corresponding vertical wind shear is low, about 1 m/s per scale height in agreement with previous thermal wind estimations. We found evidence for discrete localized meridional motions with speeds of 1-2 m/s. Two numerical models are used to simulate the observed cloud dispersion. One is a pure advection of the aerosols by the winds and their shears. The other uses the EPIC code, a nonlinear calculation of the evolution of the potential vorticity field generated by a heat pulse that simulates the impact. Both models reproduce the observed global structure of the cloud and the dominant zonal dispersion of the aerosols, but not the details of the cloud morphology. The reflectivity of the impact cloud decreased exponentially with a characteristic timescale of 15 days; we can explain this behavior with a radiative transfer model of the cloud optical depth coupled to an advection model of the cloud dispersion by the wind shears. The expected sedimentation time in the stratosphere (altitude levels 5-100 mbar) for the small aerosol particles forming the cloud is 45-200 days, thus aerosols were removed vertically over the long term following their zonal dispersion. No evidence of the cloud was detected 10 months after the impact.

Sanchez-Lavega, A.↗
NASA NTRS1983

Measuring Surface-Shear Stress in a Wind Tunnel

Two-wire skin friction gage gives both magnitude and direction of mean and fluctuating stresses. Heated wires lie at surface of gage, measure airflow by cooling effect. Wires perpendicular to each other to measure flow direction as well as magnitude. Used successfully in various turbulent flow fields, including separating three-dimensional boundary layer over cone at high angle of incidence.

Lemos, F.↗
NASA NTRS2012

Determining the Probability of Violating Upper-Level Wind Constraints for the Launch of Minuteman III Ballistic Missiles at Vandenberg Air Force Base

The 30th Operational Support Squadron Weather Flight (30 OSSWF) provides comprehensive weather services to the space program at Vandenberg Air Force Base (VAFB) in California. One of their responsibilities is to monitor upper-level winds to ensure safe launch operations of the Minuteman Ill ballistic missile. The 30 OSSWF tasked the Applied Meteorology Unit (AMU) to analyze VAFB sounding data with the goal of determining the probability of violating (PoV) their upper-level thresholds for wind speed and shear constraints specific to this launch vehicle, and to develop a tool that will calculate the PoV of each constraint on the day of launch. In order to calculate the probability of exceeding each constraint, the AMU collected and analyzed historical data from VAFB. The historical sounding data were retrieved from the National Oceanic and Atmospheric Administration Earth System Research Laboratory archive for the years 1994-2011 and then stratified into four sub-seasons: January-March, April-June, July-September, and October-December. The AMU determined the theoretical distributions that best fit the maximum wind speed and maximum wind shear datasets and applied this information when calculating the averages and standard deviations needed for the historical and real-time PoV calculations. In addition, the AMU included forecast sounding data from the Rapid Refresh model. This information provides further insight for the launch weather officers (LWOs) when determining if a wind constraint violation will occur over the next few hours on the day of launch. The AMU developed an interactive graphical user interface (GUI) in Microsoft Excel using Visual Basic for Applications. The GUI displays the critical sounding data easily and quickly for LWOs on day of launch. This tool will replace the existing one used by the 30 OSSWF, assist the LWOs in determining the probability of exceeding specific wind threshold values, and help to improve the overall upper winds forecast for the launch customer. This presentation will describe how the AMU calculated the historical and real-time PoV values for the specific upper-level wind launch constraints and outline the development of the interactive GUI display.

Shafer, Jaclyn A.↗
NASA NTRS1986

Biogeochemical cycling in the ocean. Part 1: Introduction to the effects of upwelling along the west coast of North America

Coastal upwelling is examined as it relates to the cycling of chemical species in coastal waters along the west coast of North America. The temporal and spatial features of upwelling phenomena in the Eastern boundary regions of the North Pacific Ocean are presented and discussed in terms of upwelling episodes. Climate conditions affecting upwelling include: thermal effects, wind-induced shear stress which moves surface layers, and the curl of the wind stress vector which is thought to affect the extent and nature of upwelling and the formation of offshore convergent downwelling fronts. These effects and the interaction of sunlight and upwelled nutrients which result in a biological bloom in surface waters is modeled analytically. The roles of biological and chemical species, including the effects of predation, are discussed in that context, and relevant remote sensing and in situ observations are presented. Climatological, oceanographic, biological, physical, chemical events, and processes that pertain to biogeochemical cycling are presented and described by a set of partial differential equations. Simple preliminary results are obtained and are compared with data. Thus a fairly general framework has been laid where the many facets of biogeochemical cycling in coastal upwelled waters can be examined in their relationship to one another, and to the whole, to whatever level of detail or approximation is warranted or desired.

Howe, John T.↗
NASA NTRS2000

Cloud Microphysics in Hurricane Outflows: Observations in 'Bonnie' (1998) at 12 km Altitude

The water balance of a hurricane is controlled by boundary layer inflow, near vertical motion in the eyewall causing coalescence precipitation at above and residual ice precipitation at below freezing temperatures, and cirrus outflow at below -40 C aloft. In this paper we address the question of efficiency of water removal by this cirrus outflow which is important for the release of latent heat at high altitudes and its role in the dynamic flow at that level. During NASA's 1998 Convection and Moisture Experiment campaign we acquired microphysical outflow data in order to (1) determine the release and redistribution of latent heat near the top of hurricanes, (2) aid in TRMM algorithm development for remote sensing of precipitation, and (3) determine the optical/radiative characteristics of hurricane outflow. The data were acquired with Particle Measuring Systems two dimensional imaging spectrometers. On 23 August and again during the hurricane's landfall on 26 August, 1998, the NASA DC-8 aircraft penetrated hurricane 'Bonnie' four times each near 200 hPa pressure altitude. The eye crossing times were determined by (1) zero counts of cloud particles, (2) approximately 5 C increases in static and potential temperatures, and (3) minima in speeds and changes of direction of horizontal winds. The vertical winds showed shear between -6 m per second and +4 m per second and tangential winds approached 30 m per second in the eyewall. The particle volumes in the eyewall (determined by the pixels the particles shadowed in the direction of flight [x-direction] and normally to it by the number of diodes that they shadowed [y-direction]) ranged between 0.5 and 5.0 cubic centimeters per cubic meter. With a particle density near 0.2 g per cubic centimeter (determined from in situ melting and evaporation on a surface collector), the 1.0 g per meter corresponding mass of cloud ice ranged between 0.27 and 2.7 g per kilograms yielding horizontal fluxes between 8.1 and 81 g per square meters per second. The outflow ice was concentrated in crystals of a modal size of 190 micrometers. The particle size distributions were heavily skewed toward sizes with 98% of all cirrus particles smaller than the modal size comprising, however, only 20% of the mass. Thus the smaller than modal size particles dominantly affected the optical/radiative characteristics of the cloud, whereas the larger than modal size crystals determined the ice mass, hence dominated latent heating. Questions to be addressed relate to the origin of individual ice particles as the hurricane evolved and the likelihood of pristine and aggregate particle formation under the complicated conditions of rotation and outflow in the eyewall.

Pueschel, Rudolf F.↗