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Abstract Operational forecast models are necessary for the prediction of weather events in real time. Verification of these models must be performed to assess model skills and areas in need of improvement, particularly with different types of weather events that may occur. Despite the devastating impacts that can be caused by tropical cyclones (TCs) that undergo extratropical transition (ET) and become post-tropical cyclones (PTCs), these storms have not been extensively studied in the context of short-term weather prediction. This study completes the first analysis of the Global Forecast System (GFS) and a preoperational version of the newly operational Hurricane Analysis and Forecast System (HAFS) models in forecasting the occurrence of ET and the rainfall associated with ET storms in the North Atlantic basin. GFS’s skill exceeds that of HAFS in forecasting the occurrence of ET, but HAFS tends to have lower track and rain-rate errors in the fully tropical phase of ET storms’ life cycles. Both models simulate rain rates that are often too high near the storm center and fail to capture the larger area of moderate rain rates that greatly contributes to total rainfall accumulation. The discrepancies in rain rates between the models and Integrated Multi-satellitE Retrievals for GPM (IMERG) could be attributed to the models’ tendency to keep storms too intense and too compact with an overly strong warm core, even throughout the ET process. 

In a tropical cyclone (TC), turbulence not only exists in the planetary boundary layer (PBL) but also can be generated above the PBL by the cloud processes in the eyewall and rainbands. It is found that the Hurricane Analysis and Forecast System (HAFS), a new multi-scale operational model for TC prediction, fails to capture the intense turbulent mixing in eyewall and rainband clouds due to a poor estimation of static stability in clouds. The problem is fixed by including the effects of multi-phase water in the stability calculation. Simulations of 21 TCs and tropical storms in the North Atlantic basin of 2016–2019 hurricane seasons totaling 118 forecast cycles show that the stability correction substantially improves HAFS's skill in predicting storm track and intensity. Analyses of HAFS's simulations of Hurricane Michael (2018) show that the positive tendency of vortex's tangential wind resulting from the radially inward transport of absolute vorticity dominates the eddy correlation tendencies induced by the model-resolved asymmetric eddies and serves as a main mechanism for the rapid intensification of Michael. The sub-grid scale (SGS) turbulent transport above the PBL in the eyewall plays a pivotal role in initiating a positive feedback among the eyewall convection, mean secondary overturning circulation, vortex acceleration via the inward transport of absolute vorticity, surface evaporation, and radial convergence of moisture in the PBL. Without the SGS transport above the PBL, the model-resolved vertical transport alone may not be sufficient in initiating the positive feedback underlying the rapid intensification of TCs. 

Abstract Tropical cyclone (TC) precipitation poses serious hazards including freshwater flooding. High-resolution hurricane models predict the location and intensity of TC rainfall, which can influence local evacuation and preparedness policies. This study evaluates 0–72-h precipitation forecasts from two experimental models, the Hurricane Analysis and Forecast System (HAFS) model and the basin-scale Hurricane Weather Research and Forecasting (HWRF-B) Model, for 2020 North Atlantic landfalling TCs. We use an object-based method that quantifies the shape and size of the forecast and observed precipitation. Precipitation objects are then compared for light, moderate, and heavy precipitation using spatial metrics (e.g., area, perimeter, elongation). Results show that both models forecast precipitation that is too connected, too close to the TC center, and too enclosed around the TC center. Collectively, these spatial biases suggest that the model forecasts are too intense even though there is a negative intensity bias for both models, indicating there may be an inconsistency between the precipitation configuration and the maximum sustained winds in the model forecasts. The HAFS model struggles with forecasting stratiform versus convective precipitation and with the representation of lighter (stratiform) precipitation during the first 6 h after initialization. No such spinup issues are seen in the HWRF-B forecasts, which instead exhibit systematic biases at all lead times and systematic issues across all rain-rate thresholds. Future work will investigate spinup issues in the HAFS model forecast and how the microphysics parameterization affects the representation of precipitation in both models. 

The FV3GFS is the current operational Global Forecast System (GFS) at the National Centers for Environmental Prediction (NCEP), which combines a finite-volume cubed sphere dynamical core (FV3) and GFS physics. In this study, FV3GFS is used to gain understanding of rapid intensification (RI) of tropical cyclones (TCs) in shear. The analysis demonstrates the importance of TC structure in a complex system like Hurricane Michael, which intensified to a category 5 hurricane over the Gulf of Mexico despite over 20 kt (10 m s⁻¹) of vertical wind shear. Michael’s RI is examined using a global-nest FV3GFS ensemble with the nest at 3-km resolution. The ensemble shows a range of peak intensities from 77 to 159 kt (40–82 m s⁻¹). Precipitation symmetry, vortex tilt, moisture, and other aspects of Michael’s evolution are compared through composites of stronger and weaker members. The 850–200-hPa vertical shear is 22 kt (11 m s⁻¹) in the mean of both strong and weak members during the early stage. Tilt and moisture are two distinguishing factors between strong and weak members. The relationship between vortex tilt and humidification is complex, and other studies have shown both are important for sheared intensification. Here, it is shown that tilt reduction leads to upshear humidification and is thus a driving factor for intensification. A stronger initial vortex and early evolution of the vortex also appear to be the key to members that are able to resist the sheared environment.