Abstract

This study utilizes an extremely high spatial resolution GOES-16 atmospheric motion vector (AMV) dataset processed at 15 min intervals in a modified version of our original dynamic initialization technique to analyze and forecast a rapid intensification (RI) event in Hurricane Irma (2017). The most important modifications are a more time-efficient dynamic initialization technique and adding a near-surface wind field adjustment as a low-level constraint on the distribution of deep convection relative to the translating center. With the new technique, the Coupled Ocean/Atmospheric Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model initial wind field at 12.86 km elevation quickly adjusts to the cirrus-level GOES-16 AMVs to better detect the Irma outflow magnitude and areal extent every 15 min, and predicts direct connections to adjacent synoptic circulations much better than a dynamic initialization with only lower-resolution hourly GOES-13 AMVs and also better than a cold-start COAMPS-TC initialization with a bogus vortex. Furthermore, only with the GOES-16 AMVs does the COAMPS-TC model accurately predict the timing of an intermediate 12 h constant-intensity period between two segments of the Irma RI. By comparison, HWRF model study of the Irma case that utilized the same GOES-16 AMV dataset predicted a continuous RI without the intermediate constant-intensity period, and predicted more limited outflow areal extents without strong direct connections with adjacent synoptic circulations.

Highlights

  • This contribution to this special issue on data assimilation for tropical cyclone (TC) forecasts will focus on the opportunities for improved initial conditions utilizing high spatial and temporal resolution atmospheric motion vectors (AMVs) that are derivable from the new-generation geostationary meteorological satellite GOES-16

  • Recall that the primary objective of this study is to demonstrate the impact of first complete 6 h dataset of high-density GOES-16 AMVs on the FCDI analysis at 18 UTC 3 September

  • The Satellite Consensus (SATCON) intensities in terms of minimum sea-level pressure (MSLP) for Hurricane Irma are shown in Figure 5, and are compared with the National Hurricane Center (NHC) working best-track (WBT) intensities that are only available at 6 h synoptic times

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Summary

Introduction

This contribution to this special issue on data assimilation for tropical cyclone (TC) forecasts will focus on the opportunities for improved initial conditions utilizing high spatial and temporal resolution atmospheric motion vectors (AMVs) that are derivable from the new-generation geostationary meteorological satellite GOES-16. Exciting opportunities exist to observe, monitor, and analyze the Irma RI event with the high In their contribution to this special issue on data assimilation for tropical cyclone forecasts, Lewis spatial resolution GOES-16 AMVs. The lower-resolution hourly AMVs from the GOES-13 do detect et al (2020) [6] explore different strategies for assimilation of this special GOES-16 AMV dataset to multiple outflow regions in the 150–200 mb layer (Figure 1, green vectors) and the 200–250 mb layer improve the Hurricane Weather Research Forecast (HWRF) track, intensity, and structure (i.e., wind (blue vectors), but with the exception of several small wind vectors near the center, only at large distances radii) forecasts.

New FCDI Dynamic Initialization Technique
Expansion of Domain 2 and 3 for the FCDI
Three ofof
Addition of Surface Wind Adjustment
Simplified FCDI without Upscaling to NAVGEM
Flowchart as in in Figure
Summary of Modifications to the Elsberry et al Approach
Characteristics of the Irma RI Event
AMV-Based FCDI Analyses for Initialization
September from six-hourCOAMPS-TC
September evident in Figure
18 UTC 3and
COAMPS-TC Forecasts from AMV-Based FCDI Analyses
September as inasFigure
Comparison with HWRF Initialization and Forecasts
September track initiated to the Irmabetween
Summary
Concluding Remarks
Report
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