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: Improvements in the probabilistic prediction of tropical cyclone rapid intensification with passive microwave observations . Wea. Forecasting , 30 , 1016 – 1038 , https://doi.org/10.1175/WAF-D-14-00109.1 . 10.1175/WAF-D-14-00109.1 Ryglicki , D. R. , and R. E. Hart , 2015 : An investigation of center-finding techniques for tropical cyclones in mesoscale models . J. Appl. Meteor. Climatol. , 54 , 825 – 846 , https://doi.org/10.1175/JAMC-D-14-0106.1 . 10.1175/JAMC-D-14-0106.1 Ryglicki , D. R
: Improvements in the probabilistic prediction of tropical cyclone rapid intensification with passive microwave observations . Wea. Forecasting , 30 , 1016 – 1038 , https://doi.org/10.1175/WAF-D-14-00109.1 . 10.1175/WAF-D-14-00109.1 Ryglicki , D. R. , and R. E. Hart , 2015 : An investigation of center-finding techniques for tropical cyclones in mesoscale models . J. Appl. Meteor. Climatol. , 54 , 825 – 846 , https://doi.org/10.1175/JAMC-D-14-0106.1 . 10.1175/JAMC-D-14-0106.1 Ryglicki , D. R
few decades, intensity forecasts at long lead times (e.g., 48–120 h) have improved at a statistically significant rate. However, only marginal improvements have been made at shorter lead times (e.g., 24–48 h), suggesting that additional research is required to better understand the underlying mechanisms associated with TC intensification. In the case of eastern North Pacific Hurricane Patricia (2015), extreme rapid intensification was not well predicted by either global or mesoscale models
few decades, intensity forecasts at long lead times (e.g., 48–120 h) have improved at a statistically significant rate. However, only marginal improvements have been made at shorter lead times (e.g., 24–48 h), suggesting that additional research is required to better understand the underlying mechanisms associated with TC intensification. In the case of eastern North Pacific Hurricane Patricia (2015), extreme rapid intensification was not well predicted by either global or mesoscale models
improvements in the coverage, density, and quality of AMVs. These “enhanced” AMV datasets can better capture smaller-scale wind flows and provide information on TC-scale flow fields ( Velden et al. 2017 ). Wu et al. (2014 , 2015 ) used an ensemble Kalman filter method to assimilate enhanced AMV data into the mesoscale community Weather Research and Forecasting (WRF) Model. They found that initial analyses of TC vortex location, intensity, and structure are all improved, along with subsequent forecasts
improvements in the coverage, density, and quality of AMVs. These “enhanced” AMV datasets can better capture smaller-scale wind flows and provide information on TC-scale flow fields ( Velden et al. 2017 ). Wu et al. (2014 , 2015 ) used an ensemble Kalman filter method to assimilate enhanced AMV data into the mesoscale community Weather Research and Forecasting (WRF) Model. They found that initial analyses of TC vortex location, intensity, and structure are all improved, along with subsequent forecasts
underestimated the intensity at 1800 UTC 5 October, an alternate explanation is that the HIRAD had detected a mesoscale circulation that was not representative of the Joaquin inner-core circulation. Fig . 11. Forecasts of 10-m wind speed (m s −1 ; color scale below) at 1800 UTC 5 Oct 2015 across domain 3 of the COAMPS-TC model with initial conditions from the (left) Control–GFS and (right) SCDI–GFS analyses after 6 h of assimilating a special AMV dataset at 15-min intervals. 4. Example of SCDI analysis
underestimated the intensity at 1800 UTC 5 October, an alternate explanation is that the HIRAD had detected a mesoscale circulation that was not representative of the Joaquin inner-core circulation. Fig . 11. Forecasts of 10-m wind speed (m s −1 ; color scale below) at 1800 UTC 5 Oct 2015 across domain 3 of the COAMPS-TC model with initial conditions from the (left) Control–GFS and (right) SCDI–GFS analyses after 6 h of assimilating a special AMV dataset at 15-min intervals. 4. Example of SCDI analysis
1. Introduction Hurricane Patricia (2015) was an extraordinary storm in the eastern North Pacific basin that underwent an unprecedented rapid intensification (RI) process in which it intensified from a tropical storm, with maximum wind speeds of 30 m s −1 , to a category 5 hurricane, with maximum wind speeds of 95 m s −1 , in less than 36 h. While tropical cyclone (TC) track forecasts have been improving substantially over recent decades, and intensity forecast have also improved some in recent
1. Introduction Hurricane Patricia (2015) was an extraordinary storm in the eastern North Pacific basin that underwent an unprecedented rapid intensification (RI) process in which it intensified from a tropical storm, with maximum wind speeds of 30 m s −1 , to a category 5 hurricane, with maximum wind speeds of 95 m s −1 , in less than 36 h. While tropical cyclone (TC) track forecasts have been improving substantially over recent decades, and intensity forecast have also improved some in recent
understand changes in TC intensity and structure, and also to improve our ability to forecast TC intensity, recently, major field campaigns, including the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD) Intensity Forecast Experiments (IFEX; Rogers et al. 2006 , 2013 ), the National Aeronautics and Space Administration (NASA) Genesis and Rapid Intensification Processes (GRIP) field program ( Braun et al. 2013 ), and the National Science Foundation (NSF) Pre
understand changes in TC intensity and structure, and also to improve our ability to forecast TC intensity, recently, major field campaigns, including the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD) Intensity Forecast Experiments (IFEX; Rogers et al. 2006 , 2013 ), the National Aeronautics and Space Administration (NASA) Genesis and Rapid Intensification Processes (GRIP) field program ( Braun et al. 2013 ), and the National Science Foundation (NSF) Pre
speed (Vmax), and minimum sea level pressure (MSLP)] ( Thu and Krishnamurti 1992 ; Kurihara et al. 1995 , 1998 , Liu et al. 2000 , 2006 ; Pu and Braun 2001 ; Tallapragada et al. 2014 ). In the National Oceanic and Atmospheric Administration (NOAA) operational Hurricane Weather Research and Forecasting system (HWRF), vortex initialization (VI) contains two components: vortex relocation (VR) and vortex modification (VM), where VR corrects the storm location and VM modifies the storm intensity
speed (Vmax), and minimum sea level pressure (MSLP)] ( Thu and Krishnamurti 1992 ; Kurihara et al. 1995 , 1998 , Liu et al. 2000 , 2006 ; Pu and Braun 2001 ; Tallapragada et al. 2014 ). In the National Oceanic and Atmospheric Administration (NOAA) operational Hurricane Weather Research and Forecasting system (HWRF), vortex initialization (VI) contains two components: vortex relocation (VR) and vortex modification (VM), where VR corrects the storm location and VM modifies the storm intensity
years to construct guidelines for forecasters by relating specific features with current intensity. It has since been refined several times to add objective methods for estimating TC strength ( Dvorak 1984 ; Zehr 1989 ; Guard et al. 1992 ; Velden et al. 1998 ; Olander et al. 2004 ; Olander and Velden 2007 ). A modern version of the Dvorak technique, the advanced Dvorak technique (ADT), has even been used as a reanalysis tool for historical TC studies ( Velden et al. 2017 ). In addition to the
years to construct guidelines for forecasters by relating specific features with current intensity. It has since been refined several times to add objective methods for estimating TC strength ( Dvorak 1984 ; Zehr 1989 ; Guard et al. 1992 ; Velden et al. 1998 ; Olander et al. 2004 ; Olander and Velden 2007 ). A modern version of the Dvorak technique, the advanced Dvorak technique (ADT), has even been used as a reanalysis tool for historical TC studies ( Velden et al. 2017 ). In addition to the
-core data (Base). Studies of the impact of various sources of data on other aspects of the analysis and on track, structure, and intensity forecasts of Patricia are ongoing, including studies using the Navy’s operational tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC; Doyle et al. 2014 ). Fig . 15. Horizontal wind (shaded and vectors) and pressure (black contours) analyses at 1-km height for (a) HRD radar composite, (b) Back, (c) Base, (d) TCI, and (e
-core data (Base). Studies of the impact of various sources of data on other aspects of the analysis and on track, structure, and intensity forecasts of Patricia are ongoing, including studies using the Navy’s operational tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC; Doyle et al. 2014 ). Fig . 15. Horizontal wind (shaded and vectors) and pressure (black contours) analyses at 1-km height for (a) HRD radar composite, (b) Back, (c) Base, (d) TCI, and (e
questions in this study by conducting a series of cloud-permitting simulations with the Weather Research and Forecasting (WRF) Model. It should be pointed out that the abovementioned poor predictability of the RI and extraordinary intensity of Patricia has been of typical concern for many tropical cyclones (TCs) ( Tallapragada and Kieu 2014 ), despite significant improvements in hurricane models and rapid progress in predicting hurricane tracks during the recent decades ( Rappaport et al. 2009 ). In
questions in this study by conducting a series of cloud-permitting simulations with the Weather Research and Forecasting (WRF) Model. It should be pointed out that the abovementioned poor predictability of the RI and extraordinary intensity of Patricia has been of typical concern for many tropical cyclones (TCs) ( Tallapragada and Kieu 2014 ), despite significant improvements in hurricane models and rapid progress in predicting hurricane tracks during the recent decades ( Rappaport et al. 2009 ). In
