Capturing the spatial and temporal correlation of multiple variables in a weather generator is challenging. A new massively multi-site, multivariate daily stochastic weather generator called IMAGE is presented here. It models temperature and precipitation variables as latent Gaussian variables with temporal behaviour governed by an auto-regressive model whose residuals and parameters are correlated through resampling of principle component time series of empirical orthogonal function modes. A case study using European climate data demonstrates the model's ability to reproduce extreme events of temperature and precipitation. The ability to capture the spatial and temporal extent of extremes using a modified Climate Extremes Index is demonstrated. Importantly, the model generates events covering not observed temporal and spatial scales giving new insights for risk management purposes.

No abstract

No abstract

There have been no high-frequency aircraft observations of tropical cyclone (TC) eyewall boundary layer turbulence since two flights into Atlantic hurricanes in the 1980s. We present an analysis of the first TC boundary layer flight observations in the South China Sea by the Hong Kong Observatory comprising four eyewall penetrations. We derive the vertical flux of momentum and vertical momentum diffusivity from observed turbulence parameters. We observe negative (upward) vertical fluxes of tangential momentum near the eyewall consistent with a jet below the flight level near the radius of maximum wind. Our observations of vertical momentum diffusivity support a superlinear relationship between diffusivity and wind speed at the high wind speeds in the inner-core of TCs (power-law exponent of 1.73 ± 0.20) while the few existing boundary layer hurricane observations in the North Atlantic suggest a more linear relationship.

We derive a simple physically based analytic model which describes the pressure filling of a tropical cyclone (TC) over land. Starting from the axisymmetric mass continuity equation in cylindrical coordinates we derive that the half-life decay of the pressure deficit between the environment and TC centre is proportional to the initial radius of maximum surface wind speed. The initial pressure deficit and column-mean radial inflow speed into the core are the other key variables. The assumptions made in deriving the model are validated against idealised numerical simulations of TC decay over land. Decay half-lives predicted from a range of initial TC states are tested against the idealized simulations and are in good agreement. Dry idealised TC decay simulations show that without latent convective heating, the boundary layer decouples from the vortex above leading to a fast decay of surface winds while a mid-level vortex persists.

No abstract

Current theories of tropical cyclone (TC) intensification give little direct indication of the role of the TC size in intensity changes, although there are observations showing a relationship. We develop a new model of TC central pressure tendency where the pressure change can be expressed as exponential with a time constant determined by the ratio of radius maximum wind (Rmax) and the column inflow or outflow speed. An analysis of observations confirms the relationship which becomes more important for a larger pressure tendency and suggests an upper bound on pressure tendency for a given Rmax. The dependence of the pressure tendency on size poses a challenging constraint on the accurate forecasting of TCs in numerical weather prediction and climate models.

Seasonal forecasts of the tropical cyclones which frequently make landfall along the densely populated South China coast are highly desirable. Here, we analyse observations of landfalling tropical cyclones in South China and of subsurface ocean temperatures in the Pacific warm pool region, and identify the possibility of forecasts of South China tropical cyclone landfall a year ahead. Specifically, we define a subsurface temperature index, subNiño4, and build a predictive model based on subNiño4 anomalies with a robust double cross-validated forecast skill against climatology of 23%, similar in skill to existing forecasts issued much later in the spring. We suggest that subNiño4 ocean temperatures precede the surface El Niño/Southern Oscillation state by about 12 months, and that the zonal shifts in atmospheric heating then change mid-level winds to steer tropical cyclones towards landfall in South China. We note that regional subsurface ocean temperature anomalies may permit atmospheric predictions in other locations at a longer range than is currently thought possible.