The dependence of precipitation and its footprint on atmospheric temperature in idealized extratropical cyclones

Flood hazard is a function of the magnitude and spatial pattern of precipitation accumulation. The sensitivity of precipitation to atmospheric temperature is investigated for idealized extratropical cyclones, enabling us to examine the footprint of extreme precipitation (surface area where accumulated precipitation exceeds high thresholds) and the accumulation in different-sized catchment areas. The mean precipitation increases with temperature, with the mean increase at 5.40%/∘C. The 99.9th percentile of accumulated precipitation increases at 12.7%/∘C for 1 h and 9.38%/∘C for 24 h, both greater than Clausius-Clapeyron scaling. The footprint of extreme precipitation grows considerably with temperature, with the relative increase generally greater for longer durations. The sensitivity of the footprint of extreme precipitation is generally super Clausius-Clapeyron. The surface area of all precipitation shrinks with increasing temperature. Greater relative changes in the number of catchment areas exceeding extreme total precipitation are found when the domain is divided into larger rather than smaller catchment areas. This indicates that fluvial flooding may increase faster than pluvial flooding from extratropical cyclones in a warming world. When the catchment areas are ranked in order of total precipitation, the 99.9th percentile is found to increase slightly above Clausius-Clapeyron expectations for all of the catchment sizes, from 9 km2 to 22,500 km2. This is surprising for larger catchment areas given the change in mean precipitation. We propose that this is due to spatially concentrated changes in extreme precipitation in the occluded fron

On the relationship between hurricane cost and the integrated wind profile

It is challenging to identify metrics that best capture hurricane destructive potential and costs. Although it has been found that the sea surface temperature and vertical wind shear can both make considerable changes to the hurricane destructive potential metrics, it is still unknown which plays a more important role. Here we present a new method to reconstruct the historical wind structure of hurricanes that allows us, for the first time, to calculate the correlation of damage with integrated power dissipation and integrated kinetic energy of all hurricanes at landfall since 1988. We find that those metrics, which include the horizontal wind structure, rather than just maximum intensity, are much better correlated with the hurricane cost. The vertical wind shear over the main development region of hurricanes plays a more dominant role than the sea surface temperature in controlling these metrics and therefore also ultimately the cost of hurricanes

A time delay controller for magnetic bearings

The control of systems with unknown dynamics and unpredictable disturbances has raised some challenging problems. This is particularly important when high system performance needs to be guaranteed at all times. Recently, the Time Delay Control has been suggested as an alternative control scheme. The proposed control system does not require an explicit plant model nor does it depend on the estimation of specific plant parameters. Rather, it combines adaptation with past observations to directly estimate the effect of the plant dynamics. A control law is formulated for a class of dynamic systems and a sufficient condition is presented for control systems stability. The derivation is based on the bounded input-bounded output stability approach using L sub infinity function norms. The control scheme is implemented on a five degrees of freedom high speed and high precision magnetic bearing. The control performance is evaluated using step responses, frequency responses, and disturbance rejection properties. The experimental data show an excellent control performance despite the system complexity

An analytic model of the tropical cyclone outer size

There are simple conceptual models of tropical cyclone intensification and potential intensity. However, such a framework has been lacking to describe the evolution of the outer circulation. An analytic growth model of the tropical cyclone outer size is derived from the angular momentum equation. The growth model fits a full-physics idealized tropical cyclone simulation. The lifecycle composite of the best-track outer size growth shows a strong super-linear nature, which supports an exponential growth as predicted by the growth model. The climatology of outer size growth measured by the radius of gale-force wind in the North Atlantic and Eastern Pacific during the period 2004–2017, can be understood in terms of four growth factors of the model: the initial size, the growth duration, the mean growth latitude, and the mean top-of-boundary-layer effective local inflow angle. All four variables are significantly different between the two basins. The observed lifetime maximum size follows a lognormal distribution, which is in line with the law of the proportionate effect of this exponential growth model. The growth model fits the observed outer size well in global basins. The time constant of the exponential size growth is approximately equal to the product of the Coriolis parameter and the mean effective inflow angle above the boundary layer. Further sensitivity experiments with the growth model suggest that the interannual variability of the global lifetime maximum size is largely driven by the variation of growth duration

Author Correction: On the intensity decay of tropical cyclones before landfall.

It remains unclear how tropical cyclones (TCs) decay from their ocean lifetime maximum intensity (LMI) to landfall intensity (LI), yet this stage is of fundamental importance governing the socio-economic impact of TCs. Here we show that TCs decay on average by 25% from LMI to LI. A logistic decay model of energy production by ocean enthalpy input and surface dissipation by frictional drag, can physically connect the LMI to LI. The logistic model fits the observed intensity decay as well as an empirically exponential decay does, but with a clear physical foundation. The distance between locations of LMI and TC landfall is found to dominate the variability of the decay from the LMI to LI, whereas environmental conditions are generally less important. A major TC at landfall typically has a very large LMI close to land. The LMI depends on the heating by ocean warming, but the LMI location is also important to future landfall TC intensity changes which are of socio-economic importance

Reduced sensitivity of tropical cyclone intensity and size to sea surface temperature in a radiative-convective equilibrium environment

It has been challenging to project the tropical cyclone (TC) intensity, structure and destructive potential changes in a warming climate. Here, we compare the sensitivities of TC intensity, size and destructive potential to sea surface warming with and without a pre-storm atmospheric adjustment to an idealized state of Radiative-Convective Equilibrium (RCE). Without RCE, we find large responses of TC intensity, size and destructive potential to sea surface temperature (SST) changes, which is in line with some previous studies. However, in an environment under RCE, the TC size is almost insensitive to SST changes, and the sensitivity of intensity is also much reduced to 3% °C−1–4% °C−1. Without the pre-storm RCE adjustment, the mean destructive potential measured by the integrated power dissipation increases by about 25% °C−1 during the mature stage. However, in an environment under RCE, the sensitivity of destructive potential to sea surface warming does not change significantly. Further analyses show that the reduced response of TC intensity and size to sea surface warming under RCE can be explained by the reduced thermodynamic disequilibrium between the air boundary layer and the sea surface due to the RCE adjustment. When conducting regional-scale sea surface warming experiments for TC case studies, without any RCE adjustment the TC response is likely to be unrealistically exaggerated. The TC intensity–temperature sensitivity under RCE is very similar to those found in coupled climate model simulations. This suggests global mean intensity projections under climate change can be understood in terms of a thermodynamic response to temperature with only a minor contribution from any changes in large-scale dynamics

Long memory impact of ocean mesoscale temperature anomalies on tropical cyclone size

Mesoscale ocean temperature anomalies modify a tropical cyclone (TC). Through a modeling study we show that, while the maximum wind speed is rapidly restored after the TC passes a warm‐ or cold‐ (eddy size) sea surface temperature (SST) anomaly, the storm size changes are more significant and persistent. The radius of gale force winds and integrated kinetic energy (IKE) can change by more than 10% per degree and this endures several days after crossing an SST anomaly. These properties have a long memory of the impact from the ocean fluxes and depend on the integrated history of SST exposure. They are found to be directly proportional to the storm total precipitation. Accurate continuous forecast of the SST along the track may therefore be of central importance to improving predictions of size and IKE, while instantaneous local SST near the TC core is more important for the forecast of maximum wind speed

Toward the S3DVAR data assimilation software for the Caspian Sea

Data Assimilation (DA) is an uncertainty quantification technique used to incorporate observed data into a prediction model in order to improve numerical forecasted results. The forecasting model used for producing oceanographic prediction into the Caspian Sea is the Regional Ocean Modeling System (ROMS). Here we propose the computational issues we are facing in a DA software we are developing (we named S3DVAR) which implements a Scalable Three Dimensional Variational Data Assimilation model for assimilating sea surface temperature (SST) values collected into the Caspian Sea with observations provided by the Group of High resolution sea surface temperature (GHRSST). We present the algorithmic strategies we employ and the numerical issues on data collected in two of the months which present the most significant variability in water temperature: August and March