Abstract Data-driven weather prediction (DWP) offers advantages in computational efficiency and demonstrates superior synoptic-scale performance compared with numerical weather prediction. However, global DWP models typically operate at coarser resolutions and remain limited in their ability to accurately predict tropical cyclone (TC) wind structure and rainfall. Therefore, the Lagrangian Limited-Area Transformer for typhoon (LLAT.ty) is developed for TC-following DWP; it is specifically designed to learn TC evolution with 3-hourly intervals and is trained using TC-centered ERA5 reanalysis. Notably, LLAT.ty explicitly predicts the TC center location for the next time step. Therefore, LLAT.ty can generate three-dimensional forecasts on continuous time steps, provided that boundary conditions from the global DWP are used via one-way boundary updating or two-way domain interactions. LLAT.ty also provides additional predicted variables essential for TC forecasting, including rainfall and vertical motion. This study subsequently uses LLAT.ty as a scientific testbed to examine whether a purely data-driven prediction system reproduces the established dynamical behavior of TCs. Simulations of all 2024 typhoons show that LLAT.ty improves TC track predictions by approximately 30% relative to the baseline FourCastNETv2 global DWP. Moreover, idealized experiments demonstrate that LLAT.ty produces realistic TC responses to variations in sea surface temperature, latitude-dependent Earth’s rotation, and vertical wind shear governing the convective asymmetry. Also, LLAT.ty successfully simulates the evolution of beta gyres, which exert a physically reasonable influence on TC motion. Overall, this study suggests that DWP models can better represent TC-specific dynamics by adjusting the learning framework to the scales and weather systems of interest.
Taylor's hypothesis (TH) converts temporal observations to spatial information of the flow while carrying out measurements on a micrometeorological tower. Other than TH, there exists a more general elliptic model, which converts time to space by focusing on the geometry of the space-time correlation function. In the elliptic model, TH is recovered when the space-time correlation functions are straight lines, and when TH is invalid, they are approximated as elliptic curves. To test whether TH or an elliptic model was appropriate for a highly heterogeneous forest clear-cut flow, we examined the geometry of the space-time correlation function of temperature by using an extensive distributed temperature sensing (DTS) dataset collected during daytime convective conditions at a height of 3.1 m above the clearing. This was complemented with an eddy covariance (EC) dataset that measured the turbulence characteristics. When the mean wind was parallel to a nearby forest edge, the DTS-derived space-time correlation function of temperature fluctuations resembled elliptic curves, rather than straight lines as predicted by TH. Due to large turbulence intensities, the curvatures in the space-time correlation contours were caused by the random sweeping events associated with large-scale eddies that invalidated the frozen turbulence assumption in TH. The velocity scale of these sweeping events correlated with the turbulence kinetic energy of the clear-cut flow, thereby lending support to the random sweeping hypothesis. Upon converting time to space through an elliptic and TH-based scaling, our results demonstrated that both temporal DTS and EC temperature measurements were impacted by the random sweeping events.
Abstract Rotating tank experiments have long been a cornerstone of geophysical and astrophysical fluid dynamics research. However, experimental studies often focus on conditions far removed from the large-scale aggregation of convection seen in Earth’s tropical and subtropical latitudes, such as tropical cyclones, mesoscale convective complexes, and heat lows. These atmospheric phenomena involve relatively slow rotation, asymmetric buoyancy sources between the surface and the atmosphere, and broad spatial scales. Our study investigates these dynamics using simple tank experiments where a shallow layer of hot water cools to the air above, bounded by insulating walls and a flat bottom. The experiments reveal distinct flow regimes depending on the convective Rossby number (Ro C ), a dimensionless ratio of rotational to convective time scales. Large, persistent cyclonic vortices emerge for Ro C greater than about 1, while weaker, short-lived cyclonic flows and anticyclonic flows occur for values below 1. These results, confirmed through analyses of flow persistence and spatial organization, highlight the role of slow rotation, asymmetric heat fluxes, and boundary conditions in generating large-scale circulations that couple with organized convection. These experiments illustrate how simple, single-phase setups can illuminate the basic physics of tropical-cyclone formation and convective aggregation, and motivate complementary laboratory and numerical work.
Abstract Tropical cyclones in environments with appreciable vertical wind shear commonly have tilts that hinder intensification. Such tilts may precess upshear and eventually diminish so that conditions for spinup improve. However, tilt behavior is variable and can be difficult to fully understand. To help elucidate the dynamics, this paper develops a novel method for analyzing temporal changes of the “tilt vector” representing the horizontal displacement of the upper vortex center from the lower center. The method rests on defining each vortex center to be where the origin of a polar coordinate system must be placed to obtain the strongest azimuthally averaged tangential velocity. Equations for the time derivatives of the center coordinates are derived and converted into equations for the growth rate Λ and angular velocity Ω of the tilt vector with readily interpretable and decomposable terms. The paper then illustrates how the converted equations can be used to diagnose the tilt dynamics of a simulated tropical cyclone during intervals of continuous change. The illustrative analysis—covering times before rapid intensification—proves revealing. Inertial contributions to Λ and Ω are seen to dominate the pressure-gradient and frictional terms. Contributions to Λ(Ω) from the actions of internal processes and environmental wind shear are more often than not (almost always) found in opposition. By certain measures, flow disturbances linked to regions of convective (stratiform) cloud processes are seen to promote cyclonic precession and the decay (growth) of tilt. After analyzing the continuous dynamics, a complementary technique to explain occasional discontinuous changes of the tilt vector is briefly demonstrated.
Publisher Note: By author request, the full PDF of the Early Online Release manuscript has been temporarily removed. Abstract Within the open- and closed- cell mesoscale cellular convection regime that characterizes the organization of marine boundary layer (MBL) clouds, a transitional period, referred to here as transition cellular convection, can occur between the two configurations. During this transition, cumulus-coupled stratocumulus organizes as mesoscale clusters known as MBL convective complexes (MBLCCs), which remain poorly understood. Using measurements from the ARM Eastern North Atlantic (ENA) site during the summers of 2016–2019, 439 MBLCCs were identified and classified by along-wind scale using a time–space conversion. Observed scales ranged from <20 km to >200 km, with most structures smaller than 50 km. Small MBLCCs (<20 km) exhibit shallow mixing depths (<200 m) in the sub-cloud layer indicative of weak surface coupling. Intermediate clusters (20–50 km) are well-mixed to the lifting condensation level connecting the cloud and sub-cloud layers. Larger MBLCCs (50–100 km) display layered moisture structures, and deep, shear-driven vertical coupling, indicative of frontal environments. Thermodynamic profiles show no statistically significant variation across MBLCC scale classes. Wind speed, reflectivity, and precipitation increase as scale sizes increase, highlighting dynamic mixing processes rather than thermodynamic variation as the key regulator of the scales in transition cellular convection.
