As a tropical cyclone approaches landfall, it progressively experiences asymmetric friction that directly modifies the boundary layer flow, since the land surface is rougher than the sea. An idealized model of the boundary layer flow within a stationary cyclone, located exactly on the coast, is presented. This model is linearized and utilizes simple representations of the turbulent fluxes. These simplifications enable analytical solutions, which represent the flow as the sum of three components: a symmetric component and two asymmetric components of azimuthal wavenumber 1, which rotate with height. The stronger asymmetric component rotates anticyclonically with height and the weaker asymmetric component rotates cyclonically. The solution is thereby similar to that for a moving cyclone over sea, except that (i) the symmetric component has larger amplitude because the azimuthal-mean surface roughness is greater and (ii) the amplitudes and phases of the asymmetric components are different because of the different surface boundary condition. The linear solutions are compared to simulations using a nonlinear model with more sophisticated representations of the turbulent fluxes, and it is shown how to extract the two asymmetric components from the flow in this latter model. This study complements the analysis of the observed wind asymmetry in Tropical Cyclone Veronica in a companion paper. SIGNIFICANCE STATEMENT: Landfall is the time at which tropical cyclones generally are most dangerous, so understanding the processes that cause structure change during landfall helps to mitigate impact. We derive a simple model of the near-surface flow in a tropical cyclone over a coastline and compare the results from this model to those from a more complete model, leading to an improved physical understanding of the effects of asymmetric friction on a tropical cyclone.

The turbulent transport of momentum, heat, and moisture can impact tropical cyclone intensity. However, representing subgrid-scale turbulence accurately in numerical weather prediction models is challenging due to a lack of observational data. To address this issue, a case study of Hurricane Maria was conducted to analyse the influence of different free tropospheric turbulence parametrisations on sheared tropical cyclones. The study used the current Met Office Unified Model (MetUM) parametrisation, as well as a parametrisation scheme with significantly reduced free tropospheric mixing length. Convection-permitting ensemble simulations were performed for both mixing schemes at two initialisation times (four 18-member ensembles in total), revealing an improvement in the intensity forecasts of Hurricane Maria when the mixing length was decreased in the free troposphere. By implementing this change, the less diffuse simulations presented a drier mid-level. The resolved downward transport of drier air from the mid-levels into the inflow layer (so-called "downdraft ventilation") was thus more effective in reducing the storm's intensity. In contrast to earlier studies, where decreasing the diffusivity in the boundary layer intensified the storm, we show that decreasing the free tropospheric diffusivity can weaken the storm by enhancing shear-related weakening processes. While this study was performed using the MetUM, the findings highlight the general importance of considering turbulence parametrisation, and show that changes in diffusivity can have different impacts on storm intensity depending on the environment and where the changes are applied. Tropical cyclone intensity forecasts can be significantly improved by implementing changes to the free tropospheric turbulence parametrisation via the mixing length (lambda$$ \lambda $$). The results show that decreasing the mixing length in the free troposphere can improve the representation of shear-related weakening processes by allowing the mid troposphere to become drier. In more diffuse parametrisations, the mid-level is moistened by the boundary layer and cloud layer, which reduces the impact of downdraft ventilation and has a negative effect on intensity prediction. image

Spotfires are a major problem in bushfire management, greatly complicate suppression efforts, and contribute to fires breaking control lines. Firebrands are often implicated in structure loss, and in extreme circumstances have been observed to ignite new fires over 30km ahead of the parent fire. Existing prediction techniques do not accommodate the problem of such long-range spotting, and the meteorological and fire conditions that lead to such events are not well understood. We present a computationally inexpensive, physically based model of ember transport within bushfire plumes, with four components: an integral plume model, a model of turbulence within the plume, a probabilistic model of ember transport by the plume, and a model of transport beneath the plume. The predicted ember landing distributions from this model compare satisfactorily to the explicit ember-transport calculations of Thurston et al. (2017) and to observations (Cruz et al., 2012). We examine the sensitivity of the simple model to its input parameters. The 90th percentile of spotting distance increases with increasing fire power and decreases with increasing ember terminal fall velocity and fire radius. Where there is a meteorological inversion or stable layer and the plume updraft is sufficiently strong to carry embers to that height, the stable layer substantially limits the transport distance, with increased height favoring longer-range transport. The effect of wind speed is complex, due to the competing factors of faster horizontal transport but suppressed vertical plume development with stronger winds.

Parametric models of tropical cyclone winds are widely used for risk assessment. Although tropical cyclones often present their worst wind risk to humanity during landfall, parametric models that represent land-sea differences are rare. This paper presents a parametric model with explicit representation of land-sea differences. Statistical models were developed over each surface of the frictional wind speed reduction from gradient level to 10 m, and of the surface inflow angle, based on about 1200 simulations with a three-dimensional dynamical boundary layer model. The wind profile of Willoughby et al. is used to represent the gradient flow, and a maximum likelihood scheme used to fit this profile to best track data. The mean RMS difference between the statistical and dynamical surface winds within 100 km of the storm center is 0.78 m s-1 and 4.26 & DEG; over sea, and 1.04 m s-1 and 4.59 & DEG; over land. During landfall, the use of a common gradient-level structure, but different surface roughnesses, provides dynamical consistency between the estimated winds over sea and land. A simple representation of internal boundary layers is applied near the coast. Analysis of the dynamical simula-tions revealed substantial consistency with observational studies of the tropical cyclone boundary layer, including that the azimuth of the surface wind maximum is on average 65 & DEG; from the front of the storm, in the left-forward quadrant in the Southern Hemisphere. There was, however, substantial variability around this figure, with the maximum occurring in the opposite forward quadrant in storms that were intense, and/or had a relatively rapid decrease in wind speed outside of the radius of maximum winds.

An analysis of the South Australian severe thunderstorm and tornado outbreak of 28 September 2016, which produced at least seven tornadoes and contributed to a state-wide power outage, is presented here. Although challenging, prediction and understanding of tornadoes and other hazards associated with severe thunderstorms is very important to forecasters and to community and emergency services preplanning and preparedness. High-resolution deterministic and ensemble simulations of the event are conducted using the Australian Community Climate and Earth-System Simulator (ACCESS) model and the simulations are compared to radar and satellite observations. The deterministic simulation and two of the ensemble members show that the overall structure, orientation, intensity and timing of simulated thunderstorms is in good agreement with the observations. In the deterministic simulation, a hook-echo feature in the simulated reflectivity, indicating the presence of a mesocyclone, appeared at the time and location of one of the observed tornadoes. Two diagnostics were found to have good value for identifying tornado-formation risk. Updraft helicity successfully identified the potential for mesocyclone development, and the Okubo–Weiss parameter identified model-resolved mesocyclone rotation. The ensemble simulations show a wide range of outcomes for intensity, timing and structure of the event, as well as differences in potential for tornado formation. This emphasises the importance of ensemble simulations in forecasting severe weather and associated hazards, as ensembles identify a range of possible scenarios and the uncertainty, leading to improved guidance for forecasters and emergency services.

The destructive Sir Ivan Dougherty fire burned 55,000 hectares around 250 km northwest of Sydney in New South Wales on 12 February 2017. Record hot temperatures were recorded in the area during the lead-in days and the fire conditions at the time were described as the ‘worst ever seen in NSW’. The observed weather conditions were hot, dry and very windy ahead of a synoptic frontal wind change during the afternoon. ‘Extreme’ to ‘catastrophic’ fire weather was predicted, and the potential for extreme fire behaviour was identified several days in advance. The Australian coupled fire–atmosphere model ACCESS-Fire has been run to explore the characteristics of the Sir Ivan fire. Several features resulting from fire–atmosphere interaction are produced in the simulations. Simulated heat flux along the fire perimeter shows increased intensity on the northern fire flank in response to gradual backing winds ahead of the main frontal wind change. Temporal and spatial variability in fire activity, seen as pulses in fire intensity and fireline wind speed, develop in response to boundary layer rolls in the wind fields. Deep moist convection consistent with the observed pyrocumulonimbus (pyroCb) cloud is simulated over the fire at around the time of the frontal wind change, and matches guidance from the ‘PyroCb Firepower Threshold’ tool, which showed transient favourable conditions. After the wind change, short-lived near-surface and elevated vortices suggest organised rotating features on the northern flank of the fire. The coupled model captures processes that cannot be produced in uncoupled fire predictions and that are not captured in current operational meteorological forecast products provided to Australian fire agencies. This paper links the features from coupled simulations to available observations and suggests pathways to embed the learnings in operational practice.

The meteorological conditions over the South Coast of New South Wales, Australia, are investigated on 18 March 2018, the day of the Tathra bushfire. We present an analysis of the event based on high-resolution (100- and 400-m grid-length) simulations with the Bureau of Meteorology’s ACCESS numerical weather prediction system and available observations. Through this analysis we find several mesoscale features that likely contributed to the extreme fire event. Key among these was the development of horizontal convective rolls, which emanated from inland and aided the fire’s spread toward Tathra. The rolls interacted with the terrain to produce complex regions of strongly ascending and descending air, likely accelerating the lofting of firebrands and potentially contributing to the significant lee-slope fire behavior observed. Mountain waves, specifically trapped lee waves, occurred on the day and are hypothesized to have contributed to the strong winds around the time the fire began. These waves may also have influenced conditions during the period of peak fire activity when the fire spotted across the Bega River and impacted Tathra. Finally, the passage of the cold front through the fireground was complex, with frontal regression observed at a nearby station and likely also through Tathra. We postulate that interactions between the strong prefrontal flow and the initially weak change resulted in highly variable and dangerous fire weather across the fireground for a significant period after the change initially occurred. Significance Statement The town of Tathra on the South Coast of New South Wales, Australia, was devastated on 18 March 2018, when a wildfire ignited in nearby bushland and quickly intensified to impact the town. Using high-resolution numerical weather simulations, we investigate the conditions that led to the extreme fire behavior. The simulations show that the fire ignited and intensified under highly variable conditions driven by complex interactions between the flow over nearby mountains and the passage of a strong cold front. This case study highlights the value of such models in understanding high-impact weather for the purpose of hazard preparedness and emergency response. Additionally, it contributes to a growing number of case studies that indicate the future direction of high-impact forecast services.

The Waroona fire burned 69000ha south of Perth in January 2016. There were two fatalities and 170 homes were lost. Two evening ember storms were reported and pyrocumulonimbus (pyroCb) cloud developed on consecutive days. The extreme fire behaviour did not reconcile with the near-surface conditions customarily used to assess fire danger. A case study of the fire (Peace et al. 2017) presented the hypothesis that the evening ember storms resulted from interactions between the above-surface wind fields, local topography and the fire plume. The coupled fire–atmosphere model ACCESS-Fire has been run in order to explore this hypothesis and other aspects of the fire activity, including the pyroCb development. ACCESS-Fire incorporates the numerical weather prediction model ACCESS (Australian Community Climate and Earth System Simulator, described by Puri et al. 2013) and a fire spread component. In these simulations, the Dry Eucalypt Forest Fire (Vesta) fire spread model is used. In this study we first show that the reconstruction of surface fire spread and simulated fire spread are a good match for the first day; second, we show that the model produces deep moist convection as an indicator of pyrocumulonimbus cloud and, third, we show the fire–atmosphere interactions surrounding the ember showers provided an environment conducive to the observed mass spotting. The simulation results demonstrate that ACCESS-Fire is a tool that may be used to further explore the complex processes and potential impacts surrounding pyroCb development and short-distance ember transport.

Pyrocumulonimbus (pyroCb) clouds are difficult to predict and can produce extreme and unexpected wildfire behavior that can be very hazardous to fire crews. Many forecasters modify conventional thunderstorm diagnostics to predict pyroCb potential, by adding temperature (Δ θ ) and moisture increments (Δ q ) to represent smoke plume thermodynamics near the expected plume condensation level. However, estimating these Δ θ and Δ q increments is a highly subjective process that requires expert knowledge of all factors that might influence future fire size and intensity. In this paper, instead of trying to anticipate these Δ θ and Δ q increments for a particular fire, the minimum firepower required to generate pyroCb for a given atmospheric environment is considered. This concept, termed the pyroCb firepower threshold (PFT) requires only atmospheric information, removing the need for subjective estimates of the fire contribution. A simple approach to calculating PFT is presented that incorporates only basic plume-rise physics, yielding an analytic solution that offers important insight into plume behavior and pyroCb formation. Minimum increments of Δ θ and Δ q required for deep, moist convection, plus a minimum cloud-base height ( z fc ), are diagnosed on a thermodynamic diagram. Briggs’s plume rise equations are used to convert Δ θ , z fc , and a mean horizontal wind speed U to a measure of the PFT: the minimum heat flux entering the base of the plume. This PFT is proportional to the product of U , Δ θ , and the square of z fc . Plume behavior insights provided by the Briggs’s equations are discussed, and a selection of PFT examples presented.

This paper describes a series of hindcast simulations of 17 tropical cyclones over the northwest shelf region of Australia. Tropical cyclone track and vortex details were obtained from the Bureau of Meteorology "Best Track" database. Wind fields were simulated using a dynamic boundary layer model referred to as the Kepert-Wang model. Surface wind and pressure fields were blended with background fields from the ERA-Interim dataset. These blended wind fields were then used as forcing for the WAVEWATCH III wave model to generate wave fields. Several different configurations of wave model source terms were trialled. Wind and wave models were validated against available observations from the Bureau of Meteorology and our industry partner. The mean absolute error for peak significant wave height (Hs) for all configurations was mostly less than 0.90 m, compared to a mean observed peak Hs of 4.8 m, and the bias was less than around 0.41 m. It was found that while in general the ST6 wave model source term physics package with NL3 non-linear interactions performs well overall, there is no single configuration that performs best for all 17 tropical cyclones.

Tropical Cyclone (TC) wind and wave models are used to quantify meteorological and oceanographic conditions in the application of offshore engineering design criteria. In regions such as the North West Shelf of Australia, a statistically sound 'risk of failure' design assessment can require historical records far longer than are typically available, even with meteorological datasets of several decades length. To address this mismatch between design requirements and observational history, synthetic tropical cyclone wind and wave datasets can be developed to mimic long records with the objective of estimating extreme event average recurrence intervals of 10,000 years. Modelling large numbers of TC storms in practice requires a trade-off between time (computational efficiency) and accuracy (model skill). The development of the synthetic dataset in this study draws the balance by combining computationally efficient parametric models, and computationally intensive fully dynamic models, with different model grid resolutions. This paper outlines performance differences between the various model approaches and make recommendations for engineering.

This study examines axisymmetric and asymmetric aspects of secondary eyewall formation (SEF) in tropical cyclones (TCs) by applying a nonlinear boundary layer model to tangential wind composites of observed TCs with and without SEF. SEF storms were further analyzed at times prior to and after SEF, as defined by the emergence of a secondary maximum in axisymmetric tangential wind. The model is used to investigate the steady‐state boundary layer response to the free‐tropospheric pressure forcing derived from observed tangential wind fields. The axisymmetric response to the Post‐SEF wind field displayed a secondary updraft maximum associated with a mature secondary eyewall; the model correctly produced no secondary updraft for non‐SEF storms. The Pre‐SEF response also exhibited a secondary updraft associated with an incipient secondary eyewall largely due to the broadened outer tangential wind field that commonly precedes SEF events. The asymmetric wind fields and model response were analyzed relative to the 850–200 hPa environmental wind shear vector. In Pre‐SEF storms, the tangential wind field displayed a broadened tangential wind structure in the downshear quadrants. The boundary layer response shows a downwind shift toward the left‐of‐shear quadrants, exhibiting the clearest secondary maxima in updrafts, tangential wind, and radial inflow. This left‐of‐shear response was the leading contributor to the secondary eyewall signals in the Pre‐SEF axisymmetric response. Sensitivity analyses confirmed the robustness of these asymmetric signals. These findings suggest that enhanced tangential wind and boundary layer updrafts in the left‐of‐shear sectors may be early indicators and critical features of SEF in sheared TCs.

In tropical cyclones (TCs), the peak wind speed is typically found near the top of the boundary layer (approximately 0.5-1 km). Recently, it was shown that in a few observed TCs, the wind speed within the eyewall can increase with height within the midtroposphere, resulting in a secondary local maximum at 4-5 km. This study presents additional evidence of such an atypical structure, using dropsonde and Doppler radar observations from Hurricane Patricia (2015). Near peak intensity, Patricia exhibited an absolute wind speed maximum at 5-6-km height, along with a weaker boundary layer maximum. Idealized simulations and a diagnostic boundary layer model are used to investigate the dynamics that result in these atypical wind profiles, which only occur in TCs that are very intense (surface wind speed > 50 m s(-1)) and/or very small (radius of maximum winds < 20 km). The existence of multiple maxima in wind speed is a consequence of an inertial oscillation that is driven ultimately by surface friction. The vertical oscillation in the radial velocity results in a series of unbalanced tangential wind jets, whose magnitude and structure can manifest as a midlevel wind speed maximum. The wavelength of the inertial oscillation increases with vertical mixing length l(infinity) in a turbulence parameterization, and no midlevel wind speed maximum occurs when l(infinity) is large. Consistent with theory, the wavelength in the simulations scales with (2K/I)(1/2), where K is the (vertical) turbulent diffusivity, and I-2 is the inertial stability. This scaling is used to explain why only small and/or strong TCs exhibit midlevel wind speed maxima.

89 GHz passive microwave satellite data are used to develop a five year climatology of the incidence and morphology of the stationary banding complex in tropical cyclones and quantify changes in convective morphology prior to secondary eyewall formation. The stationary banding complex is shown to be present in 39% of passive microwave overpasses. Morphology varies substantially between tropical cyclones, with crossing angles ranging from 0.19 degrees to 61.78 degrees and azimuthal extents from 0.29 to 4.02 radians. Variations in the incidence and geometry of the stationary banding complex are observed in different environmental conditions and geographic locations. For 84 secondary eyewall formation events included in the sample, a stationary banding complex is observed within 6 hr of the secondary eyewall developing in 79% of cases. Within 12 hr prior to secondary eyewall formation, the crossing angle is significantly lower than its sample median, while the azimuthal extent is higher than its sample median. These results demonstrate that secondary eyewall formation is (most) often preceded by the formation and axisymmetrization of a stationary banding complex.

The Australian tropical storm surge forecasting system is described, including the development of a tropical cyclone atmospheric forcing model and the configuration of the ocean hydrodynamic model. The atmospheric model is developed as an asymmetric modified Rankine vortex and the resulting time dependent stress and pressure fields are applied to a shallow water hydrodynamic model. The system was benchmarked against seven contemporary tropical cyclones occurring within the northern Australian region between 2011and 2017. The model storm surge response to the synthetic forcing was compared against tide gauge observations. For the seven test cases, the root mean square error for maximum sea level was 0.30 m, the mean absolute error was 0.21 m and the mean bias error was 0.11 m. For peak timings, the root mean square error of the model was 62 min, the mean absolute error was 48 min and the mean bias error was 8 min. Surface forcing fields were compared against observations for TC Yasi and found to be in general agreement.

Global ensemble prediction systems have considerable ability to predict tropical cyclone (TC) formation and subsequent evolution. However, because of their relatively coarse resolution, their predictions of intensity and structure are biased. The biases arise mainly from underestimated intensities and enlarged radii, in particular the radius of maximum winds. This paper describes a method to reduce this limitation by bias correcting TCs in the ECMWF Ensemble Prediction System (ECMWF-EPS) for a region northwest of Australia. A bias-corrected TC system will provide more accurate forecasts of TC-generated wind and waves to the oil and gas industry, which operates a large number of offshore facilities in the region. It will also enable improvements in response decisions for weather sensitive operations that affect downtime and safety risks. The bias-correction technique uses a multivariate linear regression method to bias correct storm intensity and structure. Special strategies are used to maintain ensemble spread after bias correction and to predict the radius of maximum winds using a climatological relationship based on wind intensity and storm latitude. The system was trained on the Australian best track TC data and the ECMWF-EPS TC data from two cyclone seasons. The system inserts corrected vortices into the original surface wind and pressure fields, which are then used to estimate wind exceedance probabilities, and to drive a wave model. The bias-corrected system has shown an overall skill improvement over the uncorrected ECMWF-EPS for all TC intensity and structure parameters with the most significant gains for the maximum wind speed prediction. The system has been operational at the Australian Bureau of Meteorology since November 2016.

Forecasting of waves under extreme conditions such as tropical cyclones is vitally important for many offshore industries, but there remain many challenges. For Northwest Western Australia (NW WA), wave forecasts issued by the Australian Bureau of Meteorology have previously been limited to products from deterministic operational wave models forced by deterministic atmospheric models. The wave models are run over global (resolution 1/4∘) and regional (resolution 1/10∘) domains with forecast ranges of + 7 and + 3 day respectively. Because of this relatively coarse resolution (both in the wave models and in the forcing fields), the accuracy of these products is limited under tropical cyclone conditions. Given this limited accuracy, a new ensemble-based wave forecasting system for the NW WA region has been developed. To achieve this, a new dedicated 8-km resolution grid was nested in the global wave model. Over this grid, the wave model is forced with winds from a bias-corrected European Centre for Medium Range Weather Forecast atmospheric ensemble that comprises 51 ensemble members to take into account the uncertainties in location, intensity and structure of a tropical cyclone system. A unique technique is used to select restart files for each wave ensemble member. The system is designed to operate in real time during the cyclone season providing + 10-day forecasts. This paper will describe the wave forecast components of this system and present the verification metrics and skill for specific events.