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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. KEYWORDS: Extreme events; Hurricanes/ typhoons; Tropical cyclones; Short-range prediction; Model evaluation/ performance; Numerical weather prediction/ forecasting, 1. Introduction (the rise of dynamical hurricane models at NOAA) Tropical cyclone (TC) forecast errors have markedly decreased over the past two decades, largely due to improved numerical weather prediction [...]

While recent observational studies of intensifying (IN) versus steady-state (SS) hurricanes have noted several differences in their axisymmetric and asymmetric structures, there remain gaps in the characterization of these differences in a fully three-dimensional framework. To address these limitations, this study investigates differences in the shear-relative asymmetric structure between IN and SS hurricanes using airborne Doppler radar data from a dataset covering an extended period of time. Statistics from individual cases show that IN cases are characterized by peak wavenumber-1 ascent concentrated in the upshear-left (USL) quadrant at ∼12-km height, consistent with previous studies. Moderate updrafts (2–6 m s−1) occur more frequently in the downshear eyewall for IN cases than for SS cases, likely leading to a higher frequency of moderate to strong updrafts USL above 9-km height. Composites of IN cases show that low-level outflow from the eye region associated with maximum wavenumber-1 vorticity inside the radius of maximum wind (RMW) in the downshear-left quadrant converges with low-level inflow outside the RMW, forming a stronger local secondary circulation in the downshear eyewall than SS cases. The vigorous eyewall convection of IN cases produces a net vertical mass flux increasing with height up to ∼5 km and then is almost constant up to 10 km, whereas the net vertical mass flux of SS cases decreases with height above 4 km. Strong USL upper-level ascent provides greater potential for the vertical development of the hurricane vortex, which is argued to be favorable for continued intensification in shear environments. [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]

Taking the examples of Hurricane Florence (2018) over the Carolinas and Hurricane Harvey (2017) over the Texas Gulf Coast, the study attempts to understand the performance of slab, single‐layer Urban Canopy Model (UCM), and Building Environment Parameterization (BEP) in simulating hurricane rainfall using the Weather Research and Forecasting (WRF) model. The WRF model simulations showed that for an intense, large‐scale event such as a hurricane, the model quantitative precipitation forecast over the urban domain was sensitive to the model urban physics. The spatial and temporal verification using the modified Kling‐Gupta efficiency and Method for Object based Diagnostic and Evaluation in Time Domain suggests that UCM performance is superior to the BEP scheme. Additionally, using the BEP urban physics scheme over UCM for landfalling hurricane rainfall simulations has helped simulate heavy rainfall hotspots. Plain Language Summary: In the wake of the continuing threat of urban flooding following landfalling hurricanes, understanding the possible interplay between the urban landscape and hurricane rainfall is an emerging research area. Prior studies have shown that the micro‐climate of the urban regions can modify rain over the city centers and periphery. However, most urban rainfall modification studies have considered thunderstorms and local convective storms in developing this understanding. However, an intriguing question is whether the urban land surface has any feedback on rainfall due to large systems such as hurricanes. This question was addressed here using a state‐of‐the‐art weather model considering three different representations of urban surfaces. The analysis showed that the simulated hurricane rainfall corresponding to Florence (2018) and Harvey (2017) is sensitive to the choice of the urban model physics used. The results suggest that the model better simulates the environmental conditions and spatial distribution of rainfall using single‐layer urban physics. Key Points: Quantitative Precipitation Forecasts over urban areas from landfalling hurricanes are sensitive to urban representation in Weather Research and Forecasting (WRF) simulationsThe consideration of urban physics in the WRF model simulation helped improve the urban rainfall simulationsRepresenting urban morphology helped simulated heavy rain hotpots and simpler physics better simulated regional rains [ABSTRACT FROM AUTHOR]

Hurricane Florence made landfall over the Carolinas 14 September 2018, bringing over 30 inches of rainfall. What remains understudied is the possible storm re‐intensification by wet and warm antecedent soil moisture (ASM), known as the Brown Ocean Effect (BOE). This study investigates this effect with two approaches: (a) two satellite‐based soil moisture (SM) data and (b) model simulation. The averaged Cyclone Global Navigation System and Soil Moisture Active Passive SM enables examination of land‐atmosphere interaction at a sub‐daily scale. Both observations and simulation results manifest positive feedback between ASM and rainfall intensity, with 3 days prior to landfall being the typical antecedent time scale. Wet (dry) ASM lead to intense (light) and concentrated (widespread) rains. We also found that soil temperature can modulate the BOE. This study aims to advance our understanding of land‐atmosphere feedback and calls to acquire accurate antecedent land states to enhance forecast skills. Plain Language Summary: Antecedent wet and warm soil conditions can maintain or re‐intensify storms via vertical mixing of water vapor, a phenomenon called the Brown Ocean Effect (BOE). Previous studies investigating the existence of BOE have considered model simulations by perturbing antecedent soil moisture. Given the uncertainties in weather models, it is important to cross‐validate the soil‐rainfall feedback by both observations and simulations. It is also critical to understand the time scale of such feedback. The growing number of remote sensing soil moisture (SM) and weather radar rainfall products at various resolutions and spatial‐temporal sampling offer unprecedented opportunities to examine this effect. Our results show consistent positive soil‐rainfall feedback from both observations and simulations. Wet antecedent soils promote intense yet concentrated rains, while dry antecedent soils cause light and widespread rains. Meanwhile, soil temperature was also found to play an important role in mediating the feedback, with colder soils even leading to a negative correlation between wet antecedent soils and extreme rainfall rates. We advocate accurate representation of antecedent land surface states combined with assimilation of remote sensing SM products into models to enhance tropical cyclone forecasts. Key Points: We hypothesize the wet antecedent soil moisture re‐intensified Hurricane FlorenceWe found that Hurricane Florence was re‐intensified by wet antecedent soils, leading to intense and concentrated rainfallWe found that cold antecedent soils impair the Brown Ocean effect in Hurricane Florence [ABSTRACT FROM AUTHOR]

Entrainment of dry moat air with low equivalent potential temperature laterally into the eyewall and rainbands is a unique turbulent process in the inner‐core region of a tropical cyclone (TC). By analyzing in‐situ aircraft measurements collected by the reconnaissance flights that penetrated the eyewalls and rainbands of Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018), as well as numerical simulations of Hurricanes Patricia (2015), and Michael (2018), we show that the moat air entrained into the eyewall and rainbands meets the instability criterion, and therefore, sinks unstably as a convective downdraft. The resultant positive buoyancy fluxes are an important source for the turbulent kinetic energy (TKE) in the eyewall and rainband clouds. This mechanism of TKE generation via lateral entrainment instability should be included in the TKE‐type turbulent mixing schemes for a better representation of turbulent transport processes in numerical forecasts of TCs. Plain Language Summary: Turbulence is commonly regarded as a chaotic flow feature pertaining to the planetary boundary layer (PBL). In the inner core of a tropical cyclone (TC), however, turbulence can also be generated in the eyewall and rainbands above the PBL by cloud processes. The turbulence at the edge of the eyewall/rainbands not only experiences the large lateral thermodynamic contrasts across the interface between clouds and moat but also entrains moat air into clouds. Previous studies suggest that under certain conditions the entrained air into the clouds can sink unstably as convective downdrafts, leading to the generation of turbulent kinetic energy (TKE) in the clouds. By analyzing in‐situ aircraft measurements collected during the reconnaissance flights that penetrated the eyewalls and rainbands of Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018), as well as numerical simulations of Patricia (2015) and Michael (2018), this study shows that the moat air entrained into the eyewall and rainbands meets the instability criterion. An estimate of the entrainment buoyancy fluxes suggests that the lateral entrainment instability is an important source of TKE in the eyewall and rainbands, and thus, it needs to be included in the TKE‐type turbulence schemes used in numerical forecasts of TCs. Key Points: Lateral entrainment of air from the moat region into eyewall and rainbands of a tropical cyclone (TC) satisfies the instability criterionPositive buoyancy flux induced by the entrainment is an important source of turbulent kinetic energy for the eyewall and rainband cloudsLateral entrainment instability should be included in turbulent mixing parameterizations in TC forecast models [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]

Raindrop size distributions collected by the DROPLET MEASUREMENT TECHNOLogies Precipitation imaging probe from 17 flights through 6 hurricanes during National Oceanic and Atmospheric Administration's hurricane field program in 2020 are used to study reflectivity (Z) and rainfall rate (RR) (R) relationship (i.e., Z‐R relationship). The results show that the Z‐R distribution is highly scattered and the scatter increases with RR and reflectivity up to 48 dBZ or 25 mm hr−1, after which it decreases rapidly. The range of the estimated RR from a power‐law Z‐R relationship can be as large as 50 mm hr−1 at reflectivity of 40 dBZ. The result from random forest regression model demonstrates that including the information of mass‐weighted‐diameter (Dm) along with radar reflectivity improves the estimated RR significantly. Plain Language Summary: One of the main applications of radar measurements is to estimate rainfall rate (RR) based on its power‐law relationships with radar reflectivity. Different relationships have been obtained for different weather scenarios. Hurricanes, in comparison with other severe weather systems, have a much longer life cycle and travel across much greater zonal and meridional extent. Therefore, in order to accurately estimate the RR for a specific time at a specific location in a hurricane, the power‐law relationship with constant coefficients needs to be improved. The uncertainties of the estimated RR using power‐law relationship are related to the raindrop sizes. The usage of a machine learning model (random forest regression) demonstrates that the uncertainties in the estimated rainfall are reduced significantly when both radar reflectivity and the drop sizes are taken into account. Key Points: The scatter in reflectivity (Z) ‐rainfall rate (R) distribution increases up to 48 dBZ or 25 mm hr−1, after which it decreases rapidlyThere are significant uncertainties associated with using a power law Z‐R relationship to estimate rainfall rate from radar reflectivityThe result from a machine learning model shows that rainfall estimation is improved if drop size information and reflectivity are both used [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]

Simultaneous observations by the lower fuselage (LF) radar, the tail (TA) radar, and the Stepped Frequency Microwave Radiometer (SFMR) on board the NOAA WP-3D aircraft are used to validate the rainfall rate estimates from microwave emission measurements of SFMR in tropical cyclones. Data collected in Hurricane Bonnie (1998) and Hurricane Humberto (2001) with a total of 820 paired samples are used in the comparisons. The SFMR 10-s path-integrated rain rates are found to have an overestimate in light rain and an underestimate in heavy rain relative to radar rainfall estimates. Examination of the existing SFMR algorithm shows that the coefficient should be changed in the attenuation--rain-rate relationship used in the inversion algorithm. After this correction, a linear regression result with a correlation coefficient of 0.8 and a slope close to 1 is obtained. But an overall high bias of 5 mm [h.sup.-1] of the SFMR rainfall estimate relative to radar is also found. The error analysis shows that the bias is nearly independent of rain type, a result confirming Jorgensen and Willis's conclusion that the drop size distributions between convective and stratiform rain in hurricanes are similar. It is also shown that the bias is a weak function of wind speed, as well as a weak inverse function of radial distance to the hurricane center. Temperature dependence has been ruled out as the main explanation. After doing sensitivity tests, the authors conclude that the bias results from a combination of two factors: an underestimate of the freezing-level height, and a downward increase of radar reflectivity in the high wind regions. If the true downward increase is 1-2 dBZ [km.sup.-1], a 0.5-km underestimate of the freezing-level height could account for up to a 3-5 mm [h.sup.-1] bias.

The downshear reformation of Tropical Storm Gabrielle (2001) was investigated using radar reflectivity and lightning data that were nearly continuous in time, as well as frequent aircraft reconnaissance flights. Initially the storm was a marginal tropical storm in an environment with strong 850-200-hPa vertical wind shear of 12-13 m [s.sup.-1] and an approaching upper tropospheric trough. Both the observed outflow and an adiabatic balance model calculation showed that the radial-vertical circulation increased with time as the trough approached. Convection was highly asymmetric, with almost all radar return located in one quadrant left of downshear in the storm. Reconnaissance data show that an intense mesovortex formed downshear of the original center. This vortex was located just south of, rather than within, a strong downshear-left lightning outbreak, consistent with tilting of the horizontal vorticity associated with the vertical wind shear. The downshear mesovortex contained a 972-hPa minimum central pressure, 20 hPa lower than minimum pressure in the original vortex just 3 h earlier. The mesovortex became the new center of the storm, but weakened somewhat prior to landfall. It is argued that dry air carried around the storm from the region of upshear subsidence, as well as the direct effects of the shear, prevented the reformed vortex from continuing to intensify. Despite the subsequent weakening of the reformed center, it reached land with greater intensity than the original center. It is argued that this intensification process was set into motion by the vertical wind shear in the presence of an environment with upward motion forced by the upper tropospheric trough. In addition, the new center formed much closer to the coast and made landfall much earlier than predicted. Such vertical-shear-induced intensity and track fluctuations are important to understand, especially in storms approaching the coast.

During the 1998 and 2001 hurricane seasons of the western Atlantic Ocean and Gulf of Mexico, the Advanced Microwave Precipitation Radiometer (AMPR), the ER-2 Doppler (EDOP) radar, and the Lightning Instrument Package (LIP) were flown aboard the NASA ER-2 high-altitude aircraft as part of the Third Convection and Moisture Experiment (CAMEX-3) and the Fourth Convection and Moisture Experiment (CAMEX-4). Several hurricanes, tropical storms, and other precipitation systems were sampled during these experiments. An oceanic rainfall screening technique has been developed using AMPR passive microwave observations of these systems collected at frequencies of 10.7, 19.35, 37.1, and 85.5 GHz. This technique combines the information content of the four AMPR frequencies regarding the gross vertical structure of hydrometeors into an intuitive and easily executable precipitation mapping format. The results have been verified using vertical profiles of EDOP reflectivity and lower-altitude horizontal reflectivity scans collected by the NOAA WP-3D Orion radar. Matching the rainfall classification results with coincident electric field information collected by the LIP readily identifies convective rain regions within the precipitation fields. This technique shows promise as a real-time research and analysis tool for monitoring vertical updraft strength and convective intensity from airborne platforms such as remotely operated or uninhabited aerial vehicles. The technique is analyzed and discussed for a wide variety of precipitation types using the 26 August 1998 observations of Hurricane Bonnie near landfall.

A photograph of a wavenumber-2 asymmetry in the eye of Hurricane Erin taken during a NOAA WP-3D research flight during the Fourth Convection and Moisture Experiment (CAMEX-4) field program on 10 September 2001 is described. The photograph of the cloud structure within the eye is evaluated using airborne and satellite remote sensing observations, and a possible explanation for the asymmetry is presented.

Fine-resolution simulations of Hurricane Erin are conducted using the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) to investigate roles of thermodynamic, boundary layer, and microphysical processes on Erin's structure and evolution. Choice of boundary layer scheme has the biggest impact on simulations, with the minimum surface pressure ([P.sub.min]) averaged over the last 18 h (when Erin is relatively mature) varying by over 20 hPa. Over the same period, coefficients used to describe graupel fall speeds ([V.sub.g]) affect [P.sub.min] by up to 7 hPa, almost equivalent to the maximum 9-hPa difference between microphysical parameterization schemes; faster [V.sub.g] and schemes with more hydrometeor categories generally give lower [P.sub.min]. Compared to radar reflectivity factor (Z) observed by the NOAA P-3 lower fuselage radar and the NASA ER-2 Doppler radar (EDOP) in Erin, all simulations overpredict the normalized frequency of occurrence of Z larger than 40 dBZ and underpredict that between 20 and 40 dBZ near the surface; simulations overpredict Z larger than 25 to 30 dBZ and underpredict that between 15 and 25 or 30 dBZ near the melting layer, the upper limit depending on altitude. Brightness temperatures ([T.sub.b]) computed from modeled fields at 37.1- and 85.5-GHz channels that respond to scattering by graupel-size ice show enhanced scattering, mainly due to graupel, compared to observations. Simulated graupel mixing ratios are about 10 times larger than values observed in other hurricanes. For the control run at 6.5 km averaged over the last 18 simulated hours, Doppler velocities computed from modeled fields ([V.sub.dop]) greater than 5 m [s.sup.-1] make up 12% of Erin's simulated area for the base simulation but less than 2% of the observed area. In the eyewall, 5% of model updrafts above 9 km are stronger than 10 m [s.sup.-1], whereas statistics from other hurricanes show that 5% of updrafts are stronger than only 5 m [s.sup.-1]. Variations in distributions of Z, vertical motion, and graupel mixing ratios between schemes are not sufficient to explain systematic offsets between observations and models. A new iterative condensation scheme, used with the Reisner mixed-phase microphysics scheme, limits unphysical increases of equivalent potential temperature associated with many condensation schemes and reduces the frequency of Z larger than 50 dBZ, but has minimal effect on Z below 50 dBZ, which represent 95% of the modeled hurricane rain area. However, the new scheme changes the Erin simulations in that 95% of the updrafts are weaker than 5 m [s.sup.-1] and [P.sub.min] is up to 12 hPa higher over the last 18 simulated hours.

Doppler velocity data from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars during four hurricane landfalls are analyzed to investigate the presence of organized vortices in the hurricane boundary layer (HBL). The wavelength, depth, magnitude, and track of velocity anomalies were compiled through analysis of Doppler velocity data. The analysis reveals alternating bands of enhanced and reduced azimuthal winds closely aligned with the mean wind direction. Resulting statistics provide compelling evidence for the presence of organized secondary circulations or boundary layer rolls across significant areas during four hurricane landfalls. The results confirm previous observations of the presence of rolls in the HBL. A potential limitation of the study presented here is the resolution of the WSR-88D data. In particular, analysis of higher-resolution data (e.g., from the Doppler on Wheels) is needed to confirm that data aliasing has not unduly impacted the statistics reported here. Momentum fluxes associated with the secondary circulations are estimated using the covariance between the horizontal and vertical components of the wind fluctuations in roils, with resulting fluxes 2-3 times greater than estimated by parameterizations in numerical weather prediction models. The observational analysis presented here, showing a prevalence of roll vortices in the HBL, has significant implications for the vertical transport of energy in hurricanes, for the character of wind damage, and for improvements in numerical simulations of hurricanes.

The Imaging Wind and Rain Airborne Profiler (IWRAP) is the first high-resolution dual-band airborne Doppler radar designed to study the inner core of teyclones (TCs). IWRAP is operated from a National Oceanic and Atmospheric Administration WP-3D aircraft during missions through TCs and severe ocean storms. The system is designed to provide high-resolution dual-polarized C- and Ku-band reflectivity and Doppler velocity profiles of the atmospheric boundary layer (ABL) within the inner core precipitation bands of TCs and to study the effects precipitation has on ocean wind scatterometry as it applies to TCs. IWRAP implements a very unique measurement strategy; it profiles simultaneously at four separate incidence angles (approximately 30[degrees], 35[degrees], 40[degrees], and 50[degrees]) while conically scanning at 60 rpm. A summary of the principles of operation and the design of the instrument is given, followed by examples of IWRAP's unique imaging capability. To our knowledge, these examples include the highest resolution measurements of the ABL winds in a hurricane ever obtained. Index Terms--Atmospheric boundary layer (ABL), cyclone, ocean remote sensing, precipitation, scatterometry.

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]

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. Plain Language Summary: Turbulence is commonly regarded as a flow feature pertaining to the planetary boundary layer (PBL), the lowest layer of the atmosphere with a typical depth of 1 km. In fair‐weather conditions, the turbulent PBL is cleanly separated from the free atmosphere above by an inversion. In tropical cyclones (TCs), however, intense turbulence can be generated by the cloud‐induced buoyancy and extends all the way up to the tropopause in the eyewall and rainbands. In this study, we found that the Hurricane Analysis and Forecast System (HAFS), a new multi‐scale operational model for TC prediction expected to be in full operational implementation likely in 2023, is unable to capture the vertical turbulent transport above the PBL in eyewall and rainbands due to a poor estimation of static stability that neglects the buoyancy induced by clouds. This problem is fixed by including the effects of multi‐phase water (vapor, liquid and solid hydrometeors) in the stability calculation. The stability correction substantially improves HAFS's skill in predicting storm track and intensity. It is found that the sub‐grid‐scale turbulent transport above the PBL in the eyewall plays a pivotal role in initiating a positive feedback underlying the rapid intensification of a TC. Key Points: A stability correction that considers cloud effect is added in the turbulence scheme used in the Hurricane Analysis and Forecast SystemThe stability correction substantially improves the model's skill in predicting track and intensity of tropical cyclonesThe turbulent transport in the eyewall plays a pivotal role in initiating a positive feedback underlying the storm rapid intensification [ABSTRACT FROM AUTHOR]

As part of the NASA Earth Venture-Instrument program, the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, to be launched in January 2022, will deliver unprecedented rapid-update microwave measurements over the tropics that can be used to observe the evolution of the precipitation and thermodynamic structure of tropical cyclones (TCs) at meso- and synoptic scales. TROPICS consists of six CubeSats, each hosting a passive microwave radiometer that provides radiance observations sensitive to atmospheric temperature, water vapor, precipitation, and precipitation-sized ice particles. In this study, the impact of TROPICS all-sky radiances on TC analyses and forecasts is explored through a regional mesoscale observing system simulation experiment (OSSE). The results indicate that the TROPICS all-sky radiances can have positive impacts on TC track and intensity forecasts, particularly when some hydrometeor state variables and other state variables of the data assimilation system that are relevant to cloudy radiance assimilation are updated. The largest impact on the model analyses is seen in the humidity fields, regardless of whether or not there are radiances assimilated from other satellites. TROPICS radiances demonstrate large impact on TC analyses and forecasts when other satellite radiances are absent. The assimilation of the all-sky TROPICS radiances without default radiances leads to a consistent improvement in the low- and midtropospheric temperature and wind forecasts throughout the 5-day forecasts, but only up to 36-h lead time in the humidity forecasts at all pressure levels. This study illustrates the potential benefits of TROPICS data assimilation for TC forecasts and provides a potentially streamlined pathway for transitioning TROPICS data from research to operations postlaunch. Significance Statement: As the Global Observing System evolves, smaller satellites such as CubeSats are emerging as inexpensive alternatives for providing important observations of Earth as compared to traditional satellites. TROPICS, to be launched in January 2022, is one of the NASA CubeSats missions that will deliver unprecedented rapid-update microwave measurements over the tropics. This study examines the impacts of simulated radiances from the TROPICS constellation of satellites for tropical cyclone analyses and forecasts in a regional mesoscale model and demonstrates the potential benefits of TROPICS data assimilation on TC forecasts. The infrastructure to incorporate the new TROPICS datasets into the operational model that was developed for this study will facilitate a transition from research to operations once the TROPICS data becomes available after the mission launch. [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]

This study investigates the precipitation symmetrization preceding rapid intensification (RI) of tropical cyclones (TCs) experiencing vertical wind shear by analyzing numerical simulations of Typhoon Mujigae (2015) with warm (CTL) and relatively cool (S1) sea surface temperatures (SSTs). A novel finding is that precipitation symmetrization is maintained by the continuous development of deep convection along the inward flank of a convective precipitation shield (CPS), especially in the downwind part. Beneath the CPS, downdrafts flush the boundary layer with low-entropy parcels. These low-entropy parcels do not necessarily weaken the TCs; instead, they are ''recycled'' in the TC circulation, gradually recovered by positive enthalpy fluxes, and develop into convection during their propagation toward a downshear convergence zone. Along-trajectory vertical momentum budget analyses reveal the predominant role of buoyancy acceleration in the convective development in both experiments. The boundary layer recovery is more efficient for warmer SST, and the stronger buoyancy acceleration accounts for the higher probability of these parcels developing into deep convection in the downwind part of the CPS, which helps maintain the precipitation symmetrization in CTL. In contrast, less efficient boundary layer recovery and less upshear deep convection hinder the precipitation symmetrization in S1. These findings highlight the key role of boundary layer recovery in regulating the precipitation symmetrization and upshear deep convection, which further accounts for an earlier RI onset timing of the CTL TC. The inward-rebuilding pathway also illuminates why deep convection is preferentially located inside the radius of maximum wind of sheared TCs undergoing RI. [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]