Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

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.

Four-dimensional COAMPS Dynamic Initialization (FCDI) analyses with high temporal and spatial resolution GOES-16 Atmospheric Motion Vectors (AMVs) are utilized to analyze the development and rapid intensification of a mesovortex about 150 km to the south of the center of the subtropical cyclone Henri (2021). During the period of the unusual Henri westward track along 30°N, the FCDI z = 300 m wind vector analyses demonstrate highly asymmetric wind fields and a horse-shoe shaped isotach maximum that is about 75 km from the center, which are characteristics more consistent with the definition of a subtropical cyclone than of a tropical cyclone. Furthermore, the Henri westward track and the vertical wind shear have characteristics resembling a Rossby Wave Breaking conceptual model. The GOES-16 mesodomain AMVs allow the visualization of a series of outflow bursts in space and time in association with the southern mesovortex development and intensification. Then the FCDI analyses forced by those thousands of AMVs each 15 minutes depict the z = 13,910 m wind field responses and the subsequent z = 300 m wind field adjustments in the southern mesovortex. A second northern outflow burst displaced to the southeast of the main Henri vortex also led to a strong low-level mesovortex. It was when the two outflow bursts joined to create an eastward radial outflow all along the line between them that the southern mesovortex reached maximum intensity and maximum size. In contrast to the numerical model predictions of intensification, outflow from the mesovortex directed over the main Henri vortex led to a decrease in intensity.

General Eisenhower’s decisions to postpone and, one day later, to launch the “D-Day” invasion of Normandy are a gripping illustration of sequential decisions under uncertainty, suitable for any introductory decision analysis class. They’re also the archetypal example of weather-sensitive decision making using a forecast. This paper develops a framework for analyzing weather-sensitive decisions with a focus on the less-familiar strategic decisions that determine how forecasts are produced and what operational alternatives are available so that decision makers can extract value from forecasts. We tell the story of the decisions made in the months before D-Day regarding how to set up the forecasting process and the myriad decisions implicating nation-level resources that prepared Allied forces not just to invade, but to hold open that decision until the last possible hour so that Eisenhower and his staff could use the critical forecasts. Finally, we overview the current state of the weather-forecasting enterprise, the current challenges of interest to decision analysts, and what this means for decision analysts seeking opportunities to help the weather enterprise improve forecasts and to help operational decision makers extract more value from modern weather forecasts.

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