Abstract

This study uses a recently developed trajectory model to trace eyewall updrafts in a high-resolution Hurricane Wilma (2005) prediction to their roots in the maritime boundary layer (MBL) in order to better understand their thermodynamics and how they interact with the swirling winds. Out of 97 020 four-hour backward trajectories seeded from the upper troposphere, the 45% of them originating from the MBL are stratified into five subsamples binned by peak vertical velocity w_MAX. Of particular interest are the thermodynamic characteristics of parcels belonging to the w_MAX-Extreme subsample (i.e., those with w_MAX exceeding 20 m s⁻¹) that ascend through Wilma’s strongest convective burst (CB) cores. A vertical momentum budget computed along a selected w_MAX-Extreme trajectory confirms that the parcel possesses large positive buoyancy that more than compensates for negative hydrometeor loading to yield an upper-tropospheric w_MAX ~ 30 m s⁻¹. Comparing all 1170 w_MAX-Extreme trajectories with all 19 296 secondary circulation trajectories shows that the former tends to originate from the MBL where equivalent potential temperature θ_e and ocean surface heat and moisture fluxes are locally enhanced. The w_MAX-Extreme parcels become further differentiated from the background ascent in terms of their (i) greater updraft width and smaller θ_e reduction while ascending into the midtroposphere, implying lower environmental entrainment rates, and (ii) less hydrometeor loading in the z = 3–5-km layer. The Lagrangian analysis herein bridges two previous studies that focused separately on the importance of high SSTs and fusion latent heat release to the development of CBs, the latter of which may facilitate upper-level warm core development through their compensating subsidence.

Abstract

Hurricane Joaquin (2015) took a climatologically unusual track southwestward into the Bahamas before recurving sharply out to sea. Several operational forecast models, including the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS), struggled to maintain the southwest motion in their early cycles and instead forecast the storm to turn west and then northwest, striking the U.S. coast. Early cycle GFS track errors are diagnosed using a tropical cyclone (TC) motion error budget equation and found to result from the model 1) not maintaining a sufficiently strong mid- to upper-level ridge northwest of Joaquin, and 2) generating a shallow vortex that did not interact strongly with upper-level northeasterly steering winds. High-resolution model simulations are used to test the sensitivity of Joaquin’s track forecast to both error sources. A control (CTL) simulation, initialized with an analysis generated from cycled hybrid data assimilation, successfully reproduces Joaquin’s observed rapid intensification and southwestward-looping track. A comparison of CTL with sensitivity runs from perturbed analyses confirms that a sufficiently strong mid- to upper-level ridge northwest of Joaquin and a vortex deep enough to interact with northeasterly flows associated with this ridge are both necessary for steering Joaquin southwestward. Contraction and vertical alignment of the CTL vortex during the early forecast period may have also helped draw the low-level vortex center southward. The results indicate that for TCs developing in vertically sheared environments, improved inner-core sampling by means of cloudy radiances and aircraft reconnaissance missions may help reduce track forecast errors by improving the model estimate of vortex depth.

Abstract

When computing trajectories from model output, gridded winds are often temporally interpolated to a time step shorter than model output intervals to satisfy computational stability constraints. This study investigates whether trajectory accuracy may be improved for tropical cyclone (TC) applications by interpolating the model winds using advection correction (AC) instead of the traditional linear interpolation in time (LI) method. Originally developed for Doppler radar processing, AC algorithms interpolate data in a reference frame that moves with the pattern translation, or advective flow velocity. A previously developed trajectory AC implementation is modified here by extending it to three-dimensional (3D) flows, and the advective flows are defined in cylindrical rather than Cartesian coordinates. This AC algorithm is tested on two model-simulated TC cases, Hurricanes Joaquin (2015) and Wilma (2005). Several variations of the AC algorithm are compared to LI on a sample of 10 201 backward trajectories computed from the modeled 5-min output data, using reference trajectories computed from 1-min output to quantify position errors. Results show that AC of 3D wind vectors using advective flows defined as local gridpoint averages improves the accuracy of most trajectories, with more substantial improvements being found in the inner eyewall where the horizontal flows are dominated by rotating cyclonic wind perturbations. Furthermore, AC eliminates oscillations in vertical velocity along LI backward trajectories run through deep convective updrafts, leading to a ~2.5-km correction in parcel height after 20 min of integration.

Abstract

An automated neural network cloud classifier that functions over both land and ocean backgrounds is presented. Motivated by the development of a combined visible, infrared, and microwave rain-rate retrieval algorithm for use with data from the 1997 Tropical Rainfall Measuring Mission (TRMM), an automated cloud classification technique is sought to discern different types of clouds and, hence, different types of precipitating systems from Advanced Very High Resolution Radiometer (AVHRR) type imagery. When this technique is applied to TRMM visible–infrared imagery, it will allow the choice of a passive microwave rain-rate algorithm, which performs well for the observed precipitation type, theoretically increasing accuracy at the instantaneous level when compared with the use of any single microwave algorithm. A neural network classifier, selected because of the strengths of neural networks with respect to within-class variability and nonnormal cluster distributions, is developed, trained, and tested on AVHRR data received from three different polar-orbiting satellites and spanning the continental United States and adjacent waters, as well as portions of the Tropics from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The results are analyzed and suggestions are made for future work on this technique. The network selected the correct class for 96% of the training samples and 82% of the test samples, indicating that this type of approach to automated cloud classification holds considerable promise and is worthy of additional research and refinement.

Abstract

A number of field experiments and subsequent studies in the 1970s and 1980s have led to the belief that radiative processes play a more significant role in the evolution of tropical mesoscale convective systems (MCSS) than was once thought. In this study, an interactive radiative transfer scheme is incorporated into a two-dimensional version of the Pennsylvania State University-NCAR Mesoscale Model to simulate the evolution of these systems within a large-scale environment under a diurnally varying radiative influence. The radiative effects are examined in terms of the net rainfall, diurnal phasing, and the vertical distribution of diabatic heating within the systems. In addition, three current radiative forcing hypotheses are addressed.

Simulations of individual MCSs with radiation produced more rainfall than those without it. While runs with forced background meant all peaked after the same elapsed time regardless of diurnal initialization time, the peak rainfall rates that occurred at night were greater than those occurring during daytime hours. Without the imposed destabilizing influence of an initialized intertropical convergence zone, rainfall rates peaked near midnight in spite of significantly different model-run start times, and a distinct diurnal cycle was established.

Initialized deep stratiform and cirriform clouds developed mesoscale, edge-oriented convective organization due to the lateral gradients of radiative forcing at the cloud edges. Convective overturning within these mesoscale systems' own trailing anvil clouds was insignificant, and there was no evidence of active latent heating in the clouds great distances away from the convection. A simulation of an MCS with imposed horizontally uniform radiative cooling throughout the domain showed no significant differences in 12-h, domain-averaged rainfall from the control case. Cloud-cloud-free radiative differences tended to modulate the life cycles of the mesoscale circulations within the simulated MCSs, and to concentrate a slightly larger fraction of the total domain rainfall within the MCSs, but they did not significantly alter the MCS structures or net domain rainfall production.

Radiative processes in this study modulate the evolution of tropical mesoscale systems, and hence, tropical rainfall, primarily through large, domainwide destabilization. These simulations indicate that mesoscale radiative forcing through cloud-cloud-free radiative differences and direct destabilization of stratiform clouds is of lesser importance. Although horizontally varying radiative processes appear to play some role in determining the location of convection, they do not appear to have major effects upon either the total amount of or the diurnal variations in tropical rainfall.

Abstract

The impacts of the latent heat of fusion on the rapid intensification (RI) of Hurricane Wilma (2005) are examined by comparing a 72-h control simulation (CTL) of the storm to a sensitivity simulation in which the latent heat of deposition is reduced by removing fusion heating (NFUS). Results show that, while both storms undergo RI, the intensification rate is substantially reduced in NFUS. At peak intensity, NFUS is weaker than CTL by 30 hPa in minimum central pressure and by 12 m s⁻¹ in maximum surface winds. The reduced rate of surface pressure falls in NFUS appears to result hydrostatically from less upper-level warming in the eye. It is shown that CTL generates more inner-core convective bursts (CBs) during RI, with higher altitudes of peak vertical motion in the eyewall, compared to NFUS. The latent heat of fusion contributes positively to sufficient eyewall conditional instability to support CB updrafts. Slantwise soundings taken in CB updraft cores reveal moist adiabatic lapse rates until 200 hPa, where the updraft intensity peaks. These results suggest that CBs may impact hurricane intensification by inducing compensating subsidence of the lower-stratospheric air, and the authors conclude that the development of more CBs inside the upper-level radius of maximum wind and at the higher altitude of latent heating all appear to be favorable for the RI of Wilma.

Abstract

The development of convective cells within anvil precipitation, in a region of moderate convective activity that might be called a small mesoscale convective system, is described and discussed. The presence of precipitation-sized hydrometeors in the air as the convection develops makes early stages visible to radar that might not otherwise be seen. Two kinds of convective initiation are illustrated. In one, a vigorous cell is initiated over an outflow boundary, but within light precipitation. In the other, the initiation is evidently by an instability created by the melting layer, perhaps by a mechanism first discussed by Findeisen. In this latter type, the new convective elements are not severe but they generate supercooled cloud within the anvil, extend entirely through the anvil to altitudes above 12 km MSL, and produce graupel showers with rain at the ground exceeding 50 dBZ. The instability itself may be generated in large part by moistening and cooling the sounding by the falling precipitation.

Abstract

This study evaluates the impact of assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) bending angles from Formosa Satellite Mission-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) receiver satellites on Hurricane Weather Research and Forecasting (HWRF) model tropical cyclone (TC) forecasts. Launched in June 2019, the COSMIC-2 mission provides significantly higher tropics data coverage compared to its predecessor COSMIC constellation. GNSS RO measurements yield information about atmospheric pressure, temperature, and water vapor profiles. HWRF is cycled with and without COSMIC-2 bending angle data assimilation for six 2020 Atlantic hurricane cases. COSMIC-2 assimilation has little impact on HWRF track forecasts, consistent with HWRF’s design limiting cycled data assimilation impacts on surrounding large-scale flows; however, COSMIC-2 assimilation results in a statistically significant ~ 8-12 % mean absolute forecast error reduction in minimum central sea-level pressure for t = 36, 54, 60, and 108-120 hour lead times. Forecasts initialized from analyses assimilating COSMIC-2 observations also have a 1-4 % smaller 600-700 hPa specific humidity (SPFH) root-mean-squared-deviation compared to radiosondes and dropwindsondes for most lead times. While not all HWRF intensity forecasts benefit from COSMIC-2 assimilation, a few show notable improvement. For example, assimilating two COSMIC-2 profiles within the inner core of developing Hurricane Hanna (2020) increases 800-hPa SPFH by up to 1 g kg⁻¹ locally, helping correct a dry bias. The forecast initialized from this analysis better captures Hanna’s observed intensification rate, likely because its moister inner core facilitates development of persistent deep convection near the TC center, where diabatic heating is more efficiently converted to cyclonic wind kinetic energy.

Abstract

Observations taken over the period 8–10 March 1992 during the Storm-scale Operational and Research Meteorology Fronts Experiment Systems Test in the central United States are used to document the detailed low-level structure and evolution of a shallow, dry arctic front. The front was characterized by cloudy skies to its north side and clear skies to its south side. It was essentially two-dimensional in the zone of intense observations.

There was a significant diurnal cycle in the magnitude of the potential temperature gradient across both the subsynoptic and mesoscale frontal zones, but imposed upon an underlying, more gradual, increase over the three days. On the warm (cloudless) side., the temperature increased and decreased in response to the diurnal heating cycle, while on the cold (cloudy) side the shape of the temperature decrease from its warm-side value (first dropping rapidly and then slowly in an exponential-like manner) remained fairly steady. The authors attribute the strong diurnal variation in potential temperature gradient mostly to the effects of differential diabatic heating across the front due to differential cloud cover.

The front is described in terms of three scales: 1) a broad, subsynoptic frontal zone (∼250–300 km wide) of modest temperature and wind gradients; 2) a narrower mesoscale zone (∼15–20 km wide) with much larger gradients; and 3) a microscale zone of near-zero-order discontinuity (≤1–2 km wide). There was some narrowing (≲50 km) of the subsynoptic frontal zone, but the authors found no evidence for any significant contraction of this zone down to much smaller mesoscale sizes. In response to the differential diabatic heating, the strongest evolution occurred in the micro-mesoscale zone, where dual-Doppler radar and aircraft measurements revealed the development of a density-current-like structure in and behind the leading edge of cold air. Here the steepest gradients developed shortly after sunrise and then increased by an order of magnitude during the day, with leading-edge vorticity, divergence, and temperature gradients reaching maximum values of 10⁻² s⁻¹ and 8 K km⁻¹. A narrow updraft, marked by cumulus clouds, grew in intensity above the leading edge through the day to a maximum of 5–8 m s⁻¹. Stratus clouds lay in the cold air, their leading edge receding by noon to 10–20 km behind the cumulus line.

Abstract

This investigation examines the meso- and microscale aspects of the 9 March 1992 cold front that passed through Kansas during the daylight hours. The principal feature of this front is the relatively rapid frontogenesis that occurred. The total change in the cross-frontal temperature is about 6 K, with most of the change occurring between about 0820 and 1400 local time and over a relatively small subsection of the total frontal width. The surface data are able to resolve a sharp horizontal transition zone of 1–2 km. The principal physical processes that produce this frontogenesis are shown to be the cross-frontal differential sensible heating, associated with differential cloud cover, and the convergence of warm and cold air toward the front. The former process is responsible for an increase in the magnitude of the differential temperature change across the front; the latter process concentrates the existing temperature differential across an ever-decreasing transitional zone until a near discontinuity in the horizontal temperature distribution is essentially established during the period of a few hours. Two approaches are taken to demonstrate that these processes control the observed frontogenesis. First, surface data from an enhanced array, set up during the Storm-scale Operational and Research Meteorology Fronts Experiment System Test, are used to evaluate the terms that contribute to the time rate of change of the gradient of potential temperature, d|∇θ| / dt, following the motion of the front. Then, the processes of differential sensible heating and convergence are incorporated into a simple two-dimensional nonlinear model that serves to provide a forecast of the surface temperature and velocity fields from given initial conditions that are appropriate at the onset of the surface heating. Verification of the model predictions by observed data confirms that both processes contribute to the observed daytime frontogenesis on 9 March 1992. A critique of the model does. however, suggest that the accuracy of some quantitative evaluations could be improved.