Wind farming has grown rapidly in Europe over the last decade. All European countries with shallow coastal waters and strong mean coastal wind speeds are planning or already constructing offshore wind farms. Large parts of the North Sea and Baltic Sea are being investigated to see whether they are suitable for offshore wind parks. In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High-resolution synthetic aperture radar (SAR) images acquired by the European remote sensing satellite ERS-2 showing single wind turbines are investigated. The methods for retrieving high-resolution wind fields from SAR images are explained and statistical comparisons of wind speed and wind direction at the two offshore wind park sites in the North Sea, Horns Rev and Butendiek, are given.

In Part II of this study the ECMWF Ensemble Prediction System (EPS) is used to study the probabilistic predictability of three major European storms of the twentieth century. The storms considered are the Dutch storm of 1 February 1953, the Hamburg storm of 17 February 1962, and the British/French storm of October 1987 (Great October storm). Common to all these storms is their severity that caused large loss of life and widespread damage.

In Part I of this study it has been found that deterministic predictability of the Dutch and Hamburg storms amount to 48 and 84 hours, respectively. Here, it is shown that the ensemble forecasts supplement the deterministic forecasts. The large number of members in the 48 and 84 hour ensemble forecasts of the Dutch and Hamburg storms, respectively, suggest that at this forecast range and for these storms the sensitivity of the forecasts to analysis and model uncertainties is rather small. From these results, therefore, it is argued that reliable warnings (i.e. low probability for the occurrence of a forecast failure) for the Dutch and Hamburg storms could have been issued 48 and 84 hours, respectively, in advance, had the current ECMWF EPS been available.

For the Great October storm it has been found in Part I of this study that short-range and medium-range forecasts of the intensity and track of the storm were very skilful with a high-resolution model of the ECWMF model. The actual timing of the storm, however, was difficult to predict. Here, it is shown that the EPS is capable of predicting large forecast uncertainties associated with the timing of the Great October storm up to 4 days in advance. It is argued that reliable warnings could have been issued at least 96 hours in advance had the ECMWF EPS been available.

From the results presented in this study it is concluded that an Ensemble Prediction System is an important component of every early warning system for it allows an a priori quantification of the probability of the occurrence of severe wind storms.

This study aims to describe the synoptic features that caused the water level in the Río de la Plata estuary to rise above critical levels between December 1989 and December 1998. Floods in the estuary can seriously affect the land beside the river from Punta Indio (35.22°S, 57.17°W) to the Paraná delta, including the lowlands of Buenos Aires City.

Surface pressure patterns associated with floods in the Río de la Plata estuary were obtained by using Quartimax rotated T-mode Principal Component Analysis (PCA) of 1000 hPa geopotential heights. The PCA patterns and 1000 hPa composite and anomaly fields show two main causes for overflows in the Río de la Plata estuary. First, the presence of a surface anticyclone, located south of Buenos Aires province and over northern Patagonia; and, second, cyclogenesis over northeastern Argentina or over Uruguay. The two synoptic features are often present simultaneously.

Two representative points were selected in the area under study: one over the continent at the Aeroparque meteorological station (34.34°S, 58.25°W) and another over the ocean between 36°S, 56°W and 36°S, 50°W. Predominant 1000 hPa wind directions associated with overflows were SE at the former location and SSW at the latter.

Based on the analysis of the obtained fields, the relationship between the estuary overflow and blocking situations and/or positive pressure anomalies over southern South America and adjacent seas was studied. The zonal circulation index (I), used to detect blocking actions, was found to be useful for identifying synoptic situations related to the estuary swelling. The probability of water level rises in the Río de la Plata with a blocking or I>0 at 70°W is 0.48, 0.72, 0.78 and 0.73, for summer, autumn, winter and spring, respectively. When I>0 is observed over the Atlantic at 40°W the probability of flooding is 0.16 for the whole year, but it decreases to 0.028 in autumn, winter and spring.

These results and weather charts from different numerical prediction models show that alerts of possible Río de la Plata estuary overflow can be released five days in advance.

The story of numerical weather prediction (NWP) is a great story. It deals with the first successful attempts to see into the chaotic future, to predict non-period events. It is to a large extent a story of computers, mathematics and numerical schemes. But the development cannot be fully understood unless non-mathematical and non-technological facts are also included. Meteorological understanding, political considerations and human emotions are difficult to quantify, but they make the picture complete and the narrative more interesting for readers outside the ‘NWP community’.

Daily rainfall records at 50 sites across southern Ontario are used to investigate the association of summer regional rainfall with outgoing longwave radiation (OLR) and moisture convergence, from 1991 to 2000. The results suggest that OLR values correspond well to heavy rainfall amounts when rain occurs over more than 90% of the study region. The average regional daily precipitation of 12.1 mm/day corresponds to 213.0 W/m2 of OLR values in the study region. Also, OLR is more significantly associated with the regional daily rainfall amount than moisture convergence in the atmospheric layers between 1000 hPa and 300 hPa although both are associated with precipitation. The study suggests that when a low OLR departure centres over Ontario, the region tends to have extremely heavy rainfall and flooding. The results of this study indicate that OLR is a useful tool for satellite detection of extremely heavy rainfall and possible flash flooding during the summer season over southern Ontario.

Using a variety of trend extraction techniques applied to monthly observations from 1766 to 2002 on the EWP dataset, this study confirms that there is evidence of a trend towards wetter winters (November to March), particularly in December and January, and drier summers, although this feature appears to be concentrated in June and July. Trend precipitation in autumn (August to November) is more difficult to pin down, with alternative methods producing quite different trend patterns, thus highlighting how difficult it can be to extract trends from noisy data. In general, the results appear to be reasonably consistent with those of Alexander & Jones (2001) using rather different techniques, thus lending weight to the views expressed by them.

A superensemble forecast that consists of six operational general circulation models is tested to simulate weather parameters over the equatorial South-East Asian region. The forecast technique, developed at Florida State University, is a unique ensemble that has proved to be one of the better prognosticators for weather forecasting. In this paper, the root mean square errors of the superensemble precipitation for a case of a severe tropical rainfall event during the winter monsoon of 2001 were smaller than the other global operational member or ensemble models used, indicating a skilled forecast. This trait is also reflected in the equitable threat score which indicates the association of the common rainfall threshold distribution between the forecast and observed best rainfall analysis from the Tropical Rainfall Measurement Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) dataset, where although it is slightly underpredicted for light rain thresholds, its results are still superior to other individual member or even the ensemble mean forecasts. Higher correlation between the superensemble forecast and the observed is maintained for up to 3-day forecasts, which indicates its potential as a reliable and good forecast tool for predicting equatorial precipitation.