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Sim D. Aberson, Jun A. Zhang, and Kelly Nuñez Ocasio

Abstract

During a routine penetration into Hurricane Felix late on 2 September 2007, NOAA42 encountered extreme turbulence and graupel, flight-level horizontal wind gusts of over 83 m s−1, and vertical wind speeds varying from 10 m s−1 downward to 31 m s−1 upward and back to nearly 7 m s−1 downward within 1 min. This led the plane to rise nearly 300 m and then return to its original level within that time. Though a dropwindsonde was released during this event, the radars and data systems on board the aircraft were rendered inoperable, limiting the amount of data obtained.

The feature observed during the flight is shown to be similar to that encountered during flights into Hurricanes Hugo (1989) and Patricia (2015), and by a dropwindsonde released into a misovortex in Hurricane Isabel (2003). This paper describes a unique dataset of a small-scale feature that appears to be prevalent in very intense tropical cyclones, providing new evidence for eye–eyewall mixing processes that may be related to intensity change.

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Sim D. Aberson, Michael T. Montgomery, Michael Bell, and Michael Black

An unprecedented dataset of category-5 Hurricane Isabel was collected on 12–14 September 2003. This two-part series focuses on novel dynamical and thermodynamical aspects of Isabel's innercore structure on 13 September. In Part I, using a composite of dropwindsonde and in situ aircraft data, the authors suggested that the axisymmetric structure of Isabel showed that the storm was superintense. Mesocyclones seen clearly in satellite imagery within the eye of Hurricane Isabel are hypothesized to mix high-entropy air at low levels in the eye into the eyewall, stimulating explosive convective development and a concomitant local horizontal wind acceleration.

Part II focuses on a unique set of observations into an extraordinary small- (miso) scale cyclonic feature inside of the inner edge of the eyewall of Hurricane Isabel. A dropwindsonde released into this feature measured the strongest known horizontal wind in a tropical cyclone. This particular observation is discussed in the context of concurrent observations from airborne Doppler radar and other airborne instruments. These observations show wind even stronger than the system-scale superintense wind suggested in Part I. Speculation on the frequency of occurrence of these “little whirls” and their potentially catastrophic impacts are presented.

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Sim D. Aberson, Kathryn J. Sellwood, and Paul A. Leighton

Abstract

Current practice is to transmit dropwindsonde data from aircraft using the TEMP-DROP format, which provides only the release location and time with 0.1° latitude × 0.1° longitude (about 11 km) and 1-h resolutions, respectively. The current dropwindsonde has a fall speed of approximately 15 m s−1, so the instrument will be advected faster horizontally than it will descend if the wind speed exceeds this value. Where wind speeds are greatest, such as in tropical cyclones, this will introduce large errors in the location of the observations, especially near the surface. A technique to calculate the correct time and location of each observation in the TEMP-DROP message is introduced. The mean differences between the calculated and reported locations are about 0.5 km for distance and 15 s for time, or <1% of the error size for distance and <10% for time.

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Jie Tang, Jun A. Zhang, Sim D. Aberson, Frank D. Marks, and Xiaotu Lei

Abstract

This study analyzes the fast-response (20 Hz) wind data collected by a multilevel tower during the landfalls of Tropical Storm Lionrock (1006), Typhoon Fanapi (1011), and Typhoon Megi (1015) in 2010. Turbulent momentum fluxes are calculated using the standard eddy-correlation method. Vertical eddy diffusivity K m and mixing length are estimated using the directly measured momentum fluxes and mean-wind profiles. It is found that the momentum flux increases with wind speed at all four levels. The eddy diffusivity calculated using the direct-flux method is compared to that using a theoretical method in which the vertical eddy diffusivity is formulated as a linear function of the friction velocity and height. It is found that below ~60 m, K m can be approximately parameterized using this theoretical method, though this method overestimates K m for higher altitude, indicating that the surface-layer depth is close to 60 m in the tropical cyclones studied here. It is also found that K m at each level varies with wind direction during landfalls: K m estimated based on observations with landward fetch is significantly larger than that estimated using data with seaward fetch. This result suggests that different parameterizations of K m should be used in the boundary layer schemes of numerical models forecasting tropical cyclones over land versus over the ocean.

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Tomislava Vukicevic, Altuğ Aksoy, Paul Reasor, Sim D. Aberson, Kathryn J. Sellwood, and Frank Marks

Abstract

In this study the properties and causes of systematic errors in high-resolution data assimilation of inner-core tropical cyclone (TC) observations were investigated using the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS). Although a recent study by Aksoy et al. demonstrated overall good performance of HEDAS for 83 cases from 2008 to 2011 using airborne observations from research and operational aircraft, some systematic errors were identified in the analyses with respect to independent observation-based estimates. The axisymmetric primary circulation intensity was underestimated for hurricane cases and the secondary circulation was systematically weaker for all cases. The diagnostic analysis in this study shows that the underestimate of primary circulation was caused by the systematic spindown of the vortex core in the short-term forecasts during the cycling with observations. This tendency bias was associated with the systematic errors in the secondary circulation, temperature, and humidity. The biases were reoccurring in each cycle during the assimilation because of the inconsistency between the strength of primary and secondary circulation during the short-term forecasts, the impact of model error in planetary boundary layer dynamics, and the effect of forecast tendency bias on the background error correlations. Although limited to the current analysis the findings in this study point to a generic problem of mutual dependence of short-term forecast tendency and state estimate errors in the data assimilation of TC core observations. The results indicate that such coupling of errors in the assimilation would also lead to short-term intensity forecast bias after the assimilation for the same reasons.

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Altuğ Aksoy, Sylvie Lorsolo, Tomislava Vukicevic, Kathryn J. Sellwood, Sim D. Aberson, and Fuqing Zhang

Abstract

Within the National Oceanic and Atmospheric Administration, the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory has developed the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) to assimilate hurricane inner-core observations for high-resolution vortex initialization. HEDAS is based on a serial implementation of the square root ensemble Kalman filter. HWRF is configured with a horizontal grid spacing of km on the outer/inner domains. In this preliminary study, airborne Doppler radar radial wind observations are simulated from a higher-resolution km version of the same model with other modifications that resulted in appreciable model error.

A 24-h nature run simulation of Hurricane Paloma was initialized at 1200 UTC 7 November 2008 and produced a realistic, category-2-strength hurricane vortex. The impact of assimilating Doppler wind observations is assessed in observation space as well as in model space. It is observed that while the assimilation of Doppler wind observations results in significant improvements in the overall vortex structure, a general bias in the average error statistics persists because of the underestimation of overall intensity. A general deficiency in ensemble spread is also evident. While covariance inflation/relaxation and observation thinning result in improved ensemble spread, these do not translate into improvements in overall error statistics. These results strongly suggest a need to include in the ensemble a representation of forecast error growth from other sources such as model error.

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Mark Demaria, Sim D. Aberson, Katsuyuki V. Ooyama, and Stephen J. Lord

Abstract

A numerical method for analysing and forecasting a wide range of horizontal scales of motion is tested in a barotropic hurricane track forecast model. The numerical method uses cubic B-spline representations of variables on nested domains. The spline representation is used for the objective analysis of observations and the solution of the prediction equations (shallow-water equations on a Mercator projection). This analysis and forecasting system is referred to as VICBAR (Vic Ooyama barotropic model).

The VICBAR model was tested in near real time during the 1989 and 1990 Atlantic hurricane seasons. For the 1989 season, VICBAR had skill comparable to, or greater than, that of the operational track forecast models. For the, 1990 season, VICBAR had skill comparable to that of the operational track-forecast models. During both 1989 and 1990, VICBAR had considerably more skill for forecasts of hurricanes than for forecasts of tropical storms.

For the 1990 season, VICBAR was generalized to include time-dependent boundary conditions from a global forecast model. These boundary conditions improve the longer-range forecasts (60–72 h). The skill of VICBAR is sensitive to the choice of the background field used in the objective analysis and the fields used to apply the boundary conditions. The use of background fields and boundary-condition fields from a 12-h-old global model forecast significantly reduces the VICBAR skill (versus the use of fields from the current global forecast).

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Chun-Chieh Wu, Shin-Gan Chen, Chung-Chuan Yang, Po-Hsiung Lin, and Sim D. Aberson

Abstract

In 2008, abundant dropwindsonde data were collected during both reconnaissance and surveillance flights in and around tropical cyclones (TCs) in the western North Pacific basin under the framework of The Observing System Research and Predictability Experiment (THORPEX)–Pacific Asian Regional Campaign (T-PARC). The National Centers for Environmental Prediction Global Forecast System (GFS) showed significant track improvements for Typhoon Sinlaku (2008) after the assimilation of dropwindsonde data. For this particular typhoon, the potential vorticity (PV) diagnosis is adopted to understand the key factors affecting the track. A data denial run initialized at 0000 UTC 10 September is examined to evaluate how the extra data collected during T-PARC improve GFS track forecasts.

A quantitative analysis of the steering flow based on the PV diagnosis indicates that the Pacific subtropical high to the east of Sinlaku is a primary factor that advects Sinlaku northwestward, while the monsoon trough plays a secondary role. The assimilation of dropwindsonde data improves the structure and intensity of the initial vortex and maintains the forecast vortex structure in the vertical. The difference in the vertical extent of the vortices could be regarded as a cause for the discrepancy in steering flow between runs with and without the dropwindsonde data. This paper highlights the importance of improved analyses of the vertical TC structure, and thus of a representative steering flow in the deep troposphere during the forecasts.

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Zhaoxia Pu, Xuanli Li, Christopher S. Velden, Sim D. Aberson, and W. Timothy Liu

Abstract

Dropwindsonde, Geostationary Operational Environmental Satellite-11 (GOES-11) rapid-scan atmospheric motion vectors, and NASA Quick Scatterometer (QuikSCAT) near-surface wind data collected during NASA’s Tropical Cloud Systems and Processes (TCSP) field experiment in July 2005 were assimilated into an advanced research version of the Weather Research and Forecasting (WRF) model using its three-dimensional variational data assimilation (3DVAR) system. The impacts of the mesoscale data assimilation on WRF numerical simulation of Tropical Storms Cindy and Gert (2005) near landfall are examined. Sensitivity of the forecasts to the assimilation of each single data type is investigated. Specifically, different 3DVAR strategies with different analysis update cycles and resolutions are compared in order to identify the better methodology for assimilating the data from research aircraft and satellite for tropical cyclone study.

The results presented herein indicate the following. 1) Assimilation of dropwindsonde and satellite wind data into the WRF model improves the forecasts of the two tropical storms up to the landfall time. The QuikSCAT wind information is very important for improving the storm track forecast, whereas the dropwindsonde and GOES-11 wind data are also necessary for improved forecasts of intensity and precipitation. 2) Data assimilation also improves the quantitative precipitation forecasts (QPFs) near landfall of the tropical storms. 3) A 1-h rapid-update analysis cycle at high resolution (9 km) provides more accurate tropical cyclone forecasts than a regular 6-h analysis cycle at coarse (27 km) resolution. The high-resolution rapidly updated 3DVAR analysis cycle might be a practical way to assimilate the data collected from tropical cyclone field experiments.

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James L. Franklin, Steven E. Feuer, John Kaplan, and Sim D. Aberson

Abstract

In 1982, the National Oceanic and Atmospheric Administration's Hurricane Research Division began a series of experiments to collect Omega dropwindsonde (ODW) observations within about 1000 km of the center of tropical cyclones. By 1992, 16 ODW datasets had been collected in 10 Atlantic basin hurricanes and tropical storms. Objective wind analyses for each dataset 10 levels from 100 mb to the surface, have been produced using a consistent set of analysis parameters. The objective analyses, which resolve synoptic-scale features in the storm environment with an accuracy and confidence unattainable from routine operational analyses, have been used to examine relationships between a tropical cyclone's motion and its surrounding synoptic-scale flow.

Tropical cyclone motion is found to be consistent with barotropic steering of the vortex by the surrounding flow within 3° latitude (333 km) of the cyclone center. At this radius, the surrounding deep-layer-mean flow explains over 90% of the variance in vortex motion. The analyses show vorticity asymmetries that strongly resemble the β gyres common to barotropic models, although other synoptic features in the environment make isolation of these gyres from the wind fields difficult. A reasonably strong relationship is found between the motion of the vortex (relative to its large scale surrounding flow) and the absolute vorticity gradient of the vortex environment.

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