scholarly journals A new aircraft hurricane wind climatology and applications in assessing the predictive skill of tropical cyclone intensity using high-resolution ensemble forecasts

2015 ◽  
Vol 42 (14) ◽  
pp. 6043-6050 ◽  
Author(s):  
Falko Judt ◽  
Shuyi S. Chen
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Tropical Cyclone Intensity ◽  
Ensemble Forecasts ◽  
Cyclone Intensity ◽  
Predictive Skill ◽  
Hurricane Wind ◽  
Wind Climatology

scholarly journals The Impact of Targeted Dropwindsonde Observations on Tropical Cyclone Intensity Forecasts of Four Weak Systems during PREDICT

2014 ◽  
Vol 142 (8) ◽  
pp. 2860-2878 ◽  
Author(s):  
Ryan D. Torn
Keyword(s):  
Tropical Cyclone ◽  
Meridional Wind ◽  
Horizontal Wind ◽  
Small Subset ◽  
Tropical Cyclone Intensity ◽  
Ensemble Forecasts ◽  
Cyclone Intensity ◽  
Intensity Forecast ◽  
Tropical Cyclone Intensity Forecasts ◽  
The Impact

Abstract The value of assimilating targeted dropwindsonde observations meant to improve tropical cyclone intensity forecasts is evaluated using data collected during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field project and a cycling ensemble Kalman filter. For each of the four initialization times studied, four different sets of Weather Research and Forecasting Model (WRF) ensemble forecasts are produced: one without any dropwindsonde data, one with all dropwindsonde data assimilated, one where a small subset of “targeted” dropwindsondes are identified using the ensemble-based sensitivity method, and a set of randomly selected dropwindsondes. For all four cases, the assimilation of dropwindsondes leads to an improved intensity forecast, with the targeted dropwindsonde experiment recovering at least 80% of the difference between the experiment where all dropwindsondes and no dropwindsondes are assimilated. By contrast, assimilating randomly selected dropwindsondes leads to a smaller impact in three of the four cases. In general, zonal and meridional wind observations at or below 700 hPa have the largest impact on the forecast due to the large sensitivity of the intensity forecast to the horizontal wind components at these levels and relatively large ensemble standard deviation relative to the assumed observation errors.

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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