Understanding Impacts of Outflow on Tropical Cyclone Formation and Rapid Intensity and Structure Changes with Data Assimilation and High-resolution Numerical Simulations

2013 ◽  
Author(s):  
Zhaoxia Pu
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Data Assimilation ◽  
Numerical Simulations ◽  
Tropical Cyclone Formation ◽  
Structure Changes

scholarly journals Analysis of Tropical Storm Formation Based on Ensemble Data Assimilation and High-Resolution Numerical Simulations of a Nondeveloping Disturbance

2016 ◽  
Vol 144 (10) ◽  
pp. 3631-3649 ◽  
Author(s):  
Andrew B. Penny ◽  
Joshua P. Hacker ◽  
Patrick A. Harr
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Simulations ◽  
Doppler Radar ◽  
Vertical Wind Shear ◽  
Heating Rates ◽  
Low Level ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
The Impact

A nondeveloping tropical disturbance, identified as TCS025, was observed during three intensive observing periods during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC)/Tropical Cyclone Structure-2008 (TCS-08) field experiment. The low-level circulation of the disturbance was relatively weak, asymmetric, and displaced a considerable distance from the midlevel circulation. An ensemble of high-resolution numerical simulations initialized from global model analyses was used to further examine TCS025. These simulations tended to unrealistically overdevelop the TCS025 disturbance. This study extends that work by examining the impact of assimilating in situ observations of TCS025 and dual-Doppler radial velocities from the airborne Electra Doppler Radar (ELDORA) using the Data Assimilation Research Testbed (DART) ensemble data assimilation system. The assimilation of observations results in a more accurate vortex structure that is consistent with the observational analysis. In addition, forecasts initialized from the state of the ensemble after data assimilation exhibit less development than both the control simulation and an ensemble of forecasts without prior data assimilation. A composite analysis of developing and nondeveloping forecasts from the ensemble reveals that convection was more active in developing simulations, especially near the low-level circulation center. This led to larger diabatic heating rates, spinup of the low-level circulation from vorticity stretching, and greater alignment of the low- and midlevel vorticity centers. In contrast, nondeveloping simulations exhibited less convection, and the circulation was more heavily impacted by vertical wind shear.

scholarly journals The Impact of Aircraft Dropsonde and Satellite Wind Data on Numerical Simulations of Two Landfalling Tropical Storms during the Tropical Cloud Systems and Processes Experiment

2008 ◽  
Vol 23 (1) ◽  
pp. 62-79 ◽  
Author(s):  
Zhaoxia Pu ◽  
Xuanli Li ◽  
Christopher S. Velden ◽  
Sim D. Aberson ◽  
W. Timothy Liu
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Data Assimilation ◽  
Wrf Model ◽  
Wind Data ◽  
Tropical Storms ◽  
Track Forecast ◽  
Near Surface ◽  
Cloud Systems ◽  
The Impact

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.

scholarly journals Assimilation of High-Resolution Tropical Cyclone Observations with an Ensemble Kalman Filter Using NOAA/AOML/HRD’s HEDAS: Evaluation of the 2008–11 Vortex-Scale Analyses

2013 ◽  
Vol 141 (6) ◽  
pp. 1842-1865 ◽  
Author(s):  
Altuğ Aksoy ◽  
Sim D. Aberson ◽  
Tomislava Vukicevic ◽  
Kathryn J. Sellwood ◽  
Sylvie Lorsolo ◽  
...  
Keyword(s):  
Kalman Filter ◽  
High Resolution ◽  
Tropical Cyclone ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Inner Core ◽  
Weather Research And Forecasting ◽  
Planetary Boundary Layer Parameterization ◽  
Data Assimilation Technique ◽  
Horizontal Grid

Abstract The Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) is developed to assimilate tropical cyclone inner-core observations for high-resolution vortex initialization. It is based on a serial implementation of the square root ensemble Kalman filter (EnKF). In this study, HWRF is used in an experimental configuration with horizontal grid spacing of 9 (3) km on the outer (inner) domain. HEDAS is applied to 83 cases from years 2008 to 2011. With the exception of two Hurricane Hilary (2011) cases in the eastern North Pacific basin, all cases are observed in the Atlantic basin. Observed storm intensity for these cases ranges from tropical depression to category-4 hurricane. Overall, it is found that high-resolution tropical cyclone observations, when assimilated with an advanced data assimilation technique such as the EnKF, result in analyses of the primary circulation that are realistic in terms of intensity, wavenumber-0 radial structure, as well as wavenumber-1 azimuthal structure. Representing the secondary circulation in the analyses is found to be more challenging with systematic errors in the magnitude and depth of the low-level radial inflow. This is believed to result from a model bias in the experimental HWRF caused by the overdiffusive nature of the planetary boundary layer parameterization utilized. Thermodynamic deviations from the observed structure are believed to be caused by both an imbalance between the number of the kinematic and thermodynamic observations in general and the suboptimal ensemble covariances between kinematic and thermodynamic fields. Future plans are discussed to address these challenges.

scholarly journals Numerical Simulation of Rapid Weakening of Hurricane Joaquin with Assimilation of High-Definition Sounding System Dropsondes during the Tropical Cyclone Intensity Experiment: Comparison of Three- and Four-Dimensional Ensemble–Variational Data Assimilation

2019 ◽  
Vol 34 (3) ◽  
pp. 521-538 ◽  
Author(s):  
Shixuan Zhang ◽  
Zhaoxia Pu
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Data Assimilation ◽  
Inner Core ◽  
Surface Wind ◽  
Naval Research ◽  
Tropical Cyclone Intensity ◽  
High Definition ◽  
Background Error ◽  
Cyclone Intensity

Abstract Observations from High-Definition Sounding System (HDSS) dropsondes, collected for Hurricane Joaquin during the Office of Naval Research Tropical Cyclone Intensity (TCI) field experiment in 2015, are assimilated into the NCEP Hurricane Weather Research and Forecasting (HWRF) Model. The Gridpoint Statistical Interpolation (GSI)-based hybrid three-dimensional and four-dimensional ensemble–variational (3DEnVar and 4DEnVar) data assimilation configurations are compared. The assimilation of HDSS dropsonde observations can help HWRF initialization by generating consistent analysis between wind and pressure fields and can also compensate for the initial maximum surface wind errors in the absence of initial vortex intensity correction. Compared with GSI–3DEnVar, the assimilation of HDSS dropsonde observations using GSI–4DEnVar generates a more realistic initial vortex intensity and reproduces the rapid weakening (RW) of Hurricane Joaquin, suggesting that the assimilation of high-resolution inner-core observations (e.g., HDSS dropsonde data) based on an advanced data assimilation method (e.g., 4DEnVar) can potentially outperform the vortex initialization scheme currently used in HWRF. Additionally, the assimilation of HDSS dropsonde observations can improve the simulation of vortex structure changes and the accuracy of the vertical motion within the TC inner-core region, which is essential to the successful simulation of the RW of Hurricane Joaquin with HWRF. Additional experiments with GSI–4DEnVar in different configurations also indicate that the performance of GSI–4DEnVar can be further improved with a high-resolution background error covariance and a denser observational bin.

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