How to save a bad element with weak boundary conditions

The P-1-P-1 finite element pair is known to allow the existence of spurious pressure (surface elevation) modes for the shallow water equations and to be unstable for mixed formulations. We show that this behavior is strongly influenced by the strong or the weak enforcement of the impermeability boundary conditions. A numerical analysis of the Stommel model is performed for both P-1-P-1 and P-1(NC)-P-1 mixed formulations. Steady and transient test cases are considered. We observe that the P-1-P-1 element exhibits stable discrete solutions with weak boundary conditions or with fully unstructured meshes. (c) 2005 Elsevier Ltd. All rights reserved.

The zonal asymmetry of the Southern Hemisphere storm-track

Atmospheric general circulation model experiments have been performed to investigate how the significant zonal asymmetry in the Southern Hemisphere (SH) winter storm track is forced by sea surface temperature (SST) and orography. An experiment with zonally symmetric tropical SSTs expands the SH upper-tropospheric storm track poleward and eastward and destroys its spiral structure. Diagnosis suggests that these aspects of the observed storm track result from Rossby wave propagation from a wave source in the Indian Ocean region associated with the monsoon there. The lower-tropospheric storm track is not sensitive to this forcing. However, an experiment with zonally symmetric midlatitude SSTs exhibits a marked reduction in the magnitude of the maximum intensity of the lower-tropospheric storm track associated with reduced SST gradients in the western Indian Ocean. Experiments without the elevation of the South African Plateau or the Andes show reductions in the intensity of the major storm track downstream of them due to reduced cyclogenesis associated with the topography. These results suggest that the zonal asymmetry of the SH winter storm track is mainly established by stationary waves excited by zonal asymmetry in tropical SST in the upper troposphere and by local SST gradients in the lower troposphere, and that it is modified through cyclogenesis associated with the topography of South Africa and South America.

The interaction of the Madden-Julian Oscillation with the Maritime Continent in a GCM

Previous studies using the Hadley Centre coupled model (HadCM3) have shown that the islands of the Maritime Continent act as an unrealistic block to the eastward propagation of the Madden-Julian Oscillation (MJO). This blocking effect is investigated using a simplified, aqua-planet version of this GCM, with various idealized configurations of the Maritime Continent islands placed on the equator, and an MJO-like convective signal forced by a propagating sea-surface temperature anomaly dipole. Results suggest that it is the orography of the islands, rather than the presence of the islands themselves, which results in the blocking of the MJO. Although the peak elevation of the orography in the GCM is very much lower than in reality, it appears to act as effective block to the eastward propagation of the low-level Kelvin wave signal which accompanies the MJO. In particular, the representation of Sumatra in the GCM, as a north-south oriented ridge straddling the equator, seems to be particularly effective at blocking the Kelvin wave signal, which in a full GCM would result in the weakening or complete extinction of the MJO signal to the east of the Maritime Continent.

Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents

Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.