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The Hurricane Weather Research and Forecasting Model (HWRF) was the flagship hurricane model at NOAA's National Centers for Environmental Prediction for 16 years and a state-of-the-art tool for tropical cyclone (TC) intensity prediction at the National Weather Service and across the globe. HWRF was a joint development between NOAA research and operations, specifically the Environmental Modeling Center and the Atlantic Oceanographic and Meteorological Laboratory. Significant support also came from the National Hurricane Center, Developmental Testbed Center, University Corporation for Atmospheric Research, universities, cooperative institutes, and the TC community. In the North Atlantic basin, where most improvement efforts focused, HWRF intensity forecast errors decreased by 45%–50% at many lead times between 2007 and 2022. These large improvements resulted from increases in horizontal and vertical resolution, as well as advances in model physics and data assimilation. HWRF intensity forecasts performed particularly well over the Gulf of Mexico in recent years, providing useful guidance for a large number of impactful landfalling hurricanes. Such advances were made possible not only by significant gains in computing but also through substantial investment from the Hurricane Forecast Improvement Program. SIGNIFICANCE STATEMENT: HWRF is considered one of the most important and successful ocean-coupled, regional numerical weather prediction models. This work documents HWRF forecast performance for TCs in the North Atlantic since its operational inception (2007–22). Track, intensity, and storm size (wind radii) forecasts all showed significant error reductions and skill improvements, including 45%–50% lower intensity errors. HWRF intensity forecasts showed marked improvement for rapid intensification events, especially in the Gulf of Mexico, where numerous impactful TCs made landfall throughout HWRF's lifetime. HWRF's impressive performance led to its expanded use as guidance for official TC forecasts and as a research tool across the TC community. These successes paved the way for NOAA's next-generation hurricane model, the Hurricane Analysis and Forecast System. [ABSTRACT FROM AUTHOR]

Development of accurate planetary boundary layer (PBL) parameterizations in high-wind conditions is crucial for improving tropical cyclone (TC) forecasts. Given that eddy-diffusivity mass-flux (EDMF)-type PBL schemes are designed for nonhurricane boundary layers, this study examines the uncertainty of MF parameterizations in hurricane conditions by performing three-dimensional idealized simulations. Results show that the surface-driven MF plays a dominant role in the nonlocal turbulent fluxes and is comparable to the magnitude of downgradient momentum fluxes in the middle portion of TC boundary layers outside the radius of maximum wind (RMW); in contrast, the stratocumulus-top-driven MF is comparably negligible and exerts a marginal impact on TC simulations. To represent the impact of vertical wind shear on damping rising thermal plumes, a new approach of tapering surface-driven MF based on the surface stability parameter is proposed, aiming to retain the surface-driven MF only in unstable boundary layers. Compared to a traditional approach of MF tapering based on 10-m wind speeds, the new approach is physically more appealing as both shear and buoyancy forcings are considered and the width of the effective zone responds to diurnal variations of surface buoyancy forcing. Compared to the experiments retaining the original MF components, using either approach of MF tapering can lead to a stronger and more compact inner core due to enhanced boundary layer inflow outside the RMW; nevertheless, the radius of gale-force wind and inflow layer depth are only notably reduced using the new approach. Comparison to observations and further discussions on MF parameterizations in high-wind conditions are provided. [ABSTRACT FROM AUTHOR]

Continuous development and evaluation of planetary boundary layer (PBL) parameterizations in hurricane conditions are crucial for improving tropical cyclone (TC) forecasts. A turbulence kinetic energy (TKE)-based eddy-diffusivity mass-flux (EDMF-TKE) PBL scheme, implemented in NOAA's Hurricane Analysis and Forecast System (HAFS), was recently improved in hurricane conditions using large-eddy simulations. This study evaluates the performance of HAFS TC forecasts with the original (experiment HAFA) and modified EDMF-TKE (experiment HAFY) based on a large sample of cases during the 2021 North Atlantic hurricane season. Results indicate that intensity and structure forecast skill was better overall in HAFY than in HAFA, including during rapid intensification. Composite analyses demonstrate that HAFY produces shallower and stronger boundary layer inflow, especially within 1–3 times the radius of maximum wind (RMW). Stronger inflow and more moisture in the boundary layer contribute to stronger moisture convergence near the RMW. These boundary layer characteristics are consistent with stronger, deeper, and more compact TC vortices in HAFY than in HAFA. Nevertheless, track skill in HAFY is slightly reduced, which is in part attributable to the cross-track error from a few early cycles of Hurricane Henri that exhibited ∼400 n mi (1 n mi = 1.852 km) track error at longer lead times. Sensitivity experiments based on HAFY demonstrate that turning off cumulus schemes notably reduces the track errors of Henri while turning off the deep cumulus scheme reduces the intensity errors. This finding hints at the necessity of unifying the mass fluxes in PBL and cumulus schemes in future model physics development. [ABSTRACT FROM AUTHOR]

Accurately representing boundary layer turbulent processes in numerical models is critical to improve tropical cyclone forecasts. A new turbulence kinetic energy (TKE)-based moist eddy-diffusivity mass-flux (EDMF-TKE) planetary boundary layer scheme has been implemented in NOAA's Hurricane Analysis and Forecast System (HAFS). This study evaluates EDMF-TKE in hurricane conditions based on a recently developed framework using large-eddy simulation (LES). Single-column modeling tests indicate that EDMF-TKE produces much greater TKE values below 500-m height than LES benchmark runs in different high-wind conditions. To improve these results, two parameters in the TKE scheme were modified to ensure a match between the PBL and surface-layer parameterizations. Additional improvements were made by reducing the maximum allowable mixing length to 40 m based on LES and observations, by adopting a different definition of boundary layer height, and by reducing nonlocal mass fluxes in high-wind conditions. With these modifications, the profiles of TKE, eddy viscosity, and winds compare much better with LES results. Three-dimensional idealized simulations and an ensemble of HAFS forecasts of Hurricane Michael (2018) consistently show that the modified EDMF-TKE tends to produce a stronger vortex with a smaller radius of maximum wind than the original EDMF-TKE, while the radius of gale-force wind is unaffected. The modified EDMF-TKE code produces smaller eddy viscosity within the boundary layer compared to the original code, which contributes to stronger inflow, especially within the annulus of 1–3 times the radius of maximum wind. The modified EDMF-TKE shows promise to improve forecast skill of rapid intensification in sheared environments. [ABSTRACT FROM AUTHOR]

Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA's Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA's Aircraft Operations Center, who maintain and operate the WP-3D and Gulfstream IV-SP (G-IV) Hurricane Hunter aircraft, and NCEP's National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data's impact in model forecasts. This summary article not only highlights recent IFEX contributions toward improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the next generation of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs. [ABSTRACT FROM AUTHOR]

The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA's Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlantic version of GFDL's System for High‐resolution prediction on Earth‐to‐Local Domains (T-SHiELD). HAFS-globalnest produced the highest track forecast skill compared to several operational and experimental models, while T-SHiELD showed promising track skills as well. The intensity forecasts from HAFS-globalnest generally had a positive bias at longer lead times primarily due to the lack of ocean coupling, while T-SHiELD had a much smaller intensity bias particularly at longer forecast lead times. With the introduction of a modified planetary boundary layer scheme and an increased number of vertical levels, particularly in the boundary layer, HAFS forecasts of storm size had a smaller positive bias than occurred in the 2019 version of HAFS-globalnest. Despite track forecasts that were comparable to the operational GFS and HWRF, both HAFS-globalnest and T-SHiELD suffered from a persistent right-of-track bias in several cases at the 4–5-day forecast lead times. The reasons for this bias were related to the strength of the subtropical ridge over the western North Atlantic and are continuing to be investigated and diagnosed. A few key case studies from this very active hurricane season, including Hurricanes Laura and Delta, were examined. [ABSTRACT FROM AUTHOR]

Boundary layer turbulent processes affect tropical cyclone (TC) structure and intensity change. However, uncertainties in the parameterization of the planetary boundary layer (PBL) under high-wind conditions remain challenging, mostly due to limited observations. This study presents and evaluates a framework of numerical simulation that can be used for a small-domain [O(5)-km] large-eddy simulation (LES) and single-column modeling (SCM) to study the TC boundary layer. The framework builds upon a previous study that uses a few input parameters to represent the TC vortex and adds a simple nudging term for temperature and moisture to account for the complex thermodynamic processes in TCs. The reference thermodynamic profiles at different wind speeds are retrieved from a composite analysis of dropsonde observations of mature hurricanes. Results from LES show that most of the turbulence kinetic energy and vertical momentum flux is associated with resolved processes when horizontal grid spacing is O(10) m. Comparison to observations of turbulence variables such as momentum flux, effective eddy viscosity, and turbulence length scale show that LES produces reasonable results but highlight areas where further observations are necessary. LES results also demonstrate that compared to a classic Ekman-type boundary layer, the TC boundary layer is shallower, develops steady conditions much quicker, and exhibits stronger wind speed near the surface. The utility of this framework is further highlighted by evaluating a first-order PBL parameterization, suggesting that an asymptotic turbulence length scale of 40 m produces a good match to LES results. [ABSTRACT FROM AUTHOR]

Horizontal grid spacings of numerical weather prediction models are rapidly approaching O(1) km and have become comparable with the dominant length scales of flows in the boundary layer; within such "gray-zones," conventional planetary boundary layer (PBL) parameterization schemes start to violate basic design assumptions. Scale-aware PBL schemes have been developed recently to address the gray-zone issue. By performing WRF simulations of Hurricane Earl (2010) at subkilometer grid spacings, this study investigates the effect of the scale-aware Shin–Hong (SH) scheme on the tropical cyclone (TC) intensification and structural changes in comparison to the non-scale-aware YSU scheme it is built upon. Results indicate that SH tends to produce a stronger TC with a more compact inner core than YSU. At early stages, scale-aware coefficients in SH gradually decrease as the diagnosed boundary layer height exceeds the horizontal grid spacing. This scale-aware effect is most prominent for nonlocal subgrid-scale vertical turbulent fluxes, in the nonprecipitation regions radially outside of a vortex-tilt-related convective rainband, and from the early stage through the middle of the rapid intensification (RI) phase. Both the scale awareness and different parameterization of the nonlocal turbulent heat flux in SH reduce the parameterized vertical turbulent mixing, which further induces stronger radial inflows and helps retain more water vapor in the boundary layer. The resulting stronger moisture convergence and diabatic heating near the TC center account for a faster inner-core contraction before RI onset and higher intensification rates during the RI period. Potential issues of applying these two PBL schemes in TC simulations and suggestions for improvements are discussed. [ABSTRACT FROM AUTHOR]

NOAA's Hurricane Analysis and Forecast System (HAFS) is an evolving FV3-based hurricane modeling system that is expected to replace the operational hurricane models at the National Weather Service. Supported by the Hurricane Forecast Improvement Program (HFIP), global-nested and regional versions of HAFS were run in real time in 2019 to create the first baseline for the HAFS advancement. In this study, forecasts from the global-nested configuration of HAFS (HAFS-globalnest) are evaluated and compared with other operational and experimental models. The forecasts by HAFS-globalnest covered the period from July through October during the 2019 hurricane season. Tropical cyclone (TC) track, intensity, and structure forecast verifications are examined. HAFS-globalnest showed track skill superior to several operational hurricane models and comparable intensity and structure skill, although the skill in predicting rapid intensification was slightly inferior to the operational model skill. HAFS-globalnest correctly predicted that Hurricane Dorian would slow and turn north in the Bahamas and also correctly predicted structural features in other TCs such as a sting jet in Hurricane Humberto during extratropical transition. Humberto was also a case where HAFS-globalnest had better track forecasts than a regional version of HAFS (HAFS-SAR) due to a better representation of the large-scale flow. These examples and others are examined through comparisons with airborne tail Doppler radar from the NOAAWP-3D to provide a more detailed evaluation of TC structure prediction. The results from this realtime experiment motivate several future model improvements, and highlight the promise of HAFS-globalnest for improved TC prediction. [ABSTRACT FROM AUTHOR]

Improving physical parameterizations in forecast models is essential for hurricane prediction. This study documents the upgrade of horizontal diffusion parameterization in the Hurricane Weather Research and Forecasting (HWRF)Model and evaluates the impact of this upgrade on hurricane forecasts. The horizontal mixing lengthLhwasmodifiedbasedonaircraft observations and extensive idealized and real-case numerical experiments. Following an earlier work by the first two authors, who focused on understanding howthe horizontal diffusion parameterization worked in HWRF and its dynamical influence on hurricane intensification using idealized simulations, a series of sensitivity experiments was conducted to simulate Hurricane Earl (2010) in which only Lh was varied. Results from the Earl forecasts confirmed the findings from previous theoretical and idealized numerical studies, in that both the simulatedmaximumintensity and intensity change rate are dependent on Lh. Comparisons between the modeled and observed structure of Hurricane Earl, such as storm size, boundary layer heights, warm-core height and temperature anomaly, and eyewall slope, suggested that the Lh used in the HWRF Model should be decreased. Lowering Lh in HWRF has a positive impact on hurricane prediction based on over 200 retrospective forecasts of 10 Atlantic storms. Biases in both stormintensity and stormsize are significantly reducedwith the modified Lh. [ABSTRACT FROM AUTHOR]

The Hurricane Weather Research and Forecasting (HWRF) Model is a dynamical model that has shown annual improvements in its tropical cyclone (TC) track forecasts as a result of various modifications. This study focuses on an experimental version of HWRF, called the basin-scale HWRF (HWRF-B), configured with 1) a large, static outer domain to cover multiple TC basins and 2) multiple sets of high-resolution movable nests to produce forecasts for several TCs simultaneously. Although HWRF-B and the operational HWRF produced comparable average track errors for the 2011–14 Atlantic hurricane seasons, strengths of HWRF-B are identified and linked to its configuration differences. HWRF-B track forecasts were generally more accurate compared with the operational HWRF when at least one additional TC was simultaneously active in the Atlantic or east Pacific basins and, in particular, when additional TCs were greater than 3500 km away. In addition, at long lead times, HWRF-B average track errors were lower than for the operational HWRF for TCs initialized north of 25°N or west of 60°W, highlighting the sensitivity of TC track forecasts to the location of the operational HWRF’s outermost domain. A case study, performed on Hurricane Michael, corroborated these HWRF-B strengths. HWRF-B shows the potential to serve as an effective bridge between regional modeling systems and next-generational global efforts. [ABSTRACT FROM AUTHOR]

This study examines the effects of horizontal diffusion on tropical cyclone (TC) intensity change and structure using idealized simulations of the Hurricane Weather Research and Forecasting Model (HWRF). A series of sensitivity experiments were conducted with varying horizontal mixing lengths ( L h), but kept the vertical diffusion coefficient and other physical parameterizations unchanged. The results show that both simulated maximum intensity and intensity change are sensitive to the L h used in the parameterization of the horizontal turbulent flux, in particular, for L h less than the model's horizontal resolution. The results also show that simulated storm structures such as storm size, kinematic boundary layer height, and eyewall slope are sensitive to L h as well. However, L h has little impact on the magnitude of the surface inflow angle and thermodynamic mixed layer height. Angular momentum budget analyses indicate that the effect of L h is to mainly spin down a TC vortex. Both mean and eddy advection terms in the angular momentum budget are affected by the magnitude of L h. For smaller L h, the convergence of angular momentum is larger in the boundary layer, which leads to a faster spinup of the vortex. The resolved eddy advection of angular momentum plays an important role in the spinup of the low-level vortex inward from the radius of the maximum wind speed when L h is small. [ABSTRACT FROM AUTHOR]

The Hurricane Weather Research and Forecasting Model (HWRF) was operationally implemented with a 27-km outer domain and a 9-km moving nest in 2007 (H007) as a tropical cyclone forecast model for the North Atlantic and eastern Pacific hurricane basins. During the 2012 hurricane season, a modified version of HWRF (H212), which increased horizontal resolution by adding a third (3 km) nest within the 9-km nest, replaced H007. H212 thus became the first operational model running at convection-permitting resolution. In addition, there were modifications to the initialization, model physics, tracking algorithm, etc. This paper compares H212 hindcast forecasts for the 2010-11 Atlantic hurricane seasons with forecasts from H007 and H3GP, a triply nested research version of HWRF. H212 reduced track forecast errors for almost all forecast times versus H007 and H3GP. H3GP was superior for intensity forecasts, although H212 showed some improvement over H007. Stratifying the cases by initial vertical wind shear revealed that the main weakness for H212 intensity forecasts was for cases with initially high shear. In these cases, H212 over- and under-intensified storms that were initially stronger and weaker, respectively. These results suggest the primary deficiency negatively impacting H212 intensity forecasts, especially in cases of rapid intensification, was that physics calls were too infrequent for the 3-km inner mesh. Correcting this deficiency along with additional modifications in the 2013 operational version yielded improved track and intensity forecasts. These intensity forecasts were comparable to statistical-dynamical models, showing that dynamical models can contribute to a decrease in operational forecast errors. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Symmetrical and Asymmetric Structures of Hurricane Boundary Layer in Coupled Atmosphere-Wave-Ocean Models and Observations," which appeared in the 2012 issue.

This study investigates the asymmetric structure of the hurricane boundary layer in relation to the environmental vertical wind shear in the inner core region. Data from 1878 GPS dropsondes deployed by research aircraft in 19 hurricanes are analyzed in a composite framework. Kinematic structure analyses based on Doppler radar data from 75 flights are compared with the dropsonde composites. Shear-relative quadrant-mean composite analyses show that both the kinematic and thermodynamic boundary layer height scales tend to decrease with decreasing radius, consistent with previous axisymmetric analyses. There is still a clear separation between the kinematic and thermodynamic boundary layer heights. Both the thermodynamic mixed layer and height of maximum tangential wind speed are within the inflow layer. The inflow layer depth is found to be deeper in quadrants downshear, with the downshear right (DR) quadrant being the deepest. The mixed layer depth and height of maximum tangential wind speed are alike at the eyewall, but are deeper outside in quadrants left of the shear. The results also suggest that air parcels acquire equivalent potential temperature θe from surface fluxes as they rotate through the upshear right (UR) quadrant from the upshear left (UL) quadrant. Convection is triggered in the DR quadrant in the presence of asymmetric mesoscale lifting coincident with a maximum in θe. Energy is then released by latent heating in the downshear left (DL) quadrant. Convective downdrafts bring down cool and dry air to the surface and lower θe again in the DL and UL quadrants. This cycling process may be directly tied to shear-induced asymmetry of convection in hurricanes. [ABSTRACT FROM AUTHOR]