Patterns often sought in meteorological fields are ridge lines or narrow zones of relatively high or low values (e.g. stripes or bands in satellite imagery). A method for the automatic detection of such features is presented, using input fields given on regular grids. The fundamental idea is that a grid point is a plausible position for a significant line where not more than two (out of eight) neighbours exhibit better suitability to lie on that very line. Locations with three or more superior neighbours are considered unsuitable, or at least less qualified, for representing positions of the line. This criterion derives from the concept that a significant line passing through a point normally enters the latter from one of the adjacent points and leaves through another neighbour, with these two special neighbours permissibly having superior values of the appropriate test variable. It is empirically demonstrated for selected applications within the field of air mass analysis (including objective front positioning on the basis of numerical model output) that the identification of points satisfying the formulated ‘2-out-of-8’ criterion is, when linked with simple post-processing steps, sufficient to accomplish a good recognition of the sought patterns.

Contrail forecasting techniques used within the UK Meteorological Office have changed little since the early 1940s and there has been no formal verification of the results. Recent research has shown that old forecasting techniques may not be wholly applicable to modern aircraft that now use more efficient engines. In order to compare the performance of both the old and new forecasting techniques a validation trial was carried out over a nine-month period in which RAF pilots reported when and where contrails did and did not occur. These observations were compared with the predicted contrail levels from both the old and newer forecasting techniques. The results indicate that both techniques give a similar performance and that neither significantly out-perform a simple persistence prediction.

The Levanter is an easterly wind which frequently blows for several hours through the Strait of Gibraltar in summer. In the presence of a strong capping inversion, a synoptic or local scale pressure gradient forces the air through the gap between the orography on either side of the Strait. This flow cannot be resolved with either a global NWP model or a simplified linear model. Results from two Levanter cases, run using the Met Office Unified Model Version 5.3 at 1 km horizontal resolution over a 300 × 250 km limited area domain covering the Strait of Gibraltar, are presented, together with an unexpected source of verification.

There are several extant techniques for diagnosing the dynamics and structure of synoptic-scale flow. The essence of three of these approaches (the Q-field diagnosis, Lagrangian airstreams and the PV-perspective) is outlined, and their relative characteristics illustrated by examining two synoptic cases. It is shown that the three approaches can independently reveal key features of the events, and that the views they offer are complementary.

Accurate forecasts of minimum surface temperature during winter help in the prediction of cold-wave conditions over northwest India. Statistical models for forecasting the minimum surface temperature at Delhi during winter (December, January and February) are developed by using the classical method and the perfect prognostic method (PPM), and the results are compared. Surface and upper air data are used for the classical method, whereas for PPM additional reanalysis data from the National Center of Environmental Prediction (NCEP) US are incorporated in the model development. Minimum surface temperature forecast models are developed by using data for the winter period 1985–89. The models are validated using an independent dataset (winter 1994–96). It is seen that by applying PPM, rather than the classical method, the model's forecast accuracy is improved by about 10% (correct to within ±2 °C).

In this paper the position and intensity of the long waves around South America are related to the precipitation in Argentina. For this purpose indices of zonal and meridional circulation as well as of the curvature of geopotential height at 1000 and 500 hPa were selected. The daily 12 UTC analyses from the European Centre for Medium Range Forecast for 1980 to 1988 were used, averaged over at least five days. A strong positive (negative) anomaly of the meridional index at 1000 and 500 hPa is associated with a negative (positive) anomaly of precipitation. Positive (negative) anomalies of the zonal index at both levels are related to negative (positive) deviations of rainfall. Positive (cyclonic) anomalies of the curvature at 500 and 1000 hPa correspond to enhanced precipitation over the central-eastern part of the country, while over the central-western part the correspondence is of opposite sign. Once methods for forecasting long wave behaviour are available, including for the region around South America, the results may be used to produce medium-range and long-range forecasts of precipitation anomalies over Argentina.

With growing international collaboration (e.g. the European Composite Observing System programme – EUCOS), changing demands of data users, technical progress with new measuring systems and national budget cuts, the design of meteorological networks has become increasingly important. By analysing future user requirements and taking into account cost-benefit considerations, MeteoSwiss has elaborated a network configuration for ground-based and upper air stations. It is evident that for ground-based stations no separate networks should be distinguished – instead, the needs of climatological modellers and forecasters should all be integrated into one network. The future upper air network will be complemented with additional windprofilers, a mini radar and additional radar information supplied by neighbouring countries.

The United States Defense Threat Reduction Agency (DTRA) DIPOLE EAST 169 experiment took place at White Sands Missile Range (WSMR), New Mexico on 23 September 1999. The objective of the experiment was to validate the DTRA Hazard Prediction and Assessment Capability (HPAC) suite of models in a weakly forced, light wind environment. Specifically, DTRA diagnostic and prognostic models were used to produce wind fields that were passed to DTRA's transport model. The resultant transport calculations were compared with the ground truth data. A release of SF6 was tracked by remote sensors to provide ground truth data. Test day weather conditions were gathered. Data from the WSMR Surface Automated Meteorological Site (SAMS) sites, a mobile profiling system, and from rawinsonde were collected and fed into the models.

A presentation of the general weather conditions that existed on the test day is first reviewed, followed by a discussion of the forecast profiles for the test site as well as a discussion of the weather condition that existed in the calculation domain as evidenced by the surface data. This provides the background conditions for the test such as the cloudy conditions that were experienced and the light winds throughout the domain. Included in this discussion is the presentation of the ground truth data collected by the Fourier Transfer Infrared Spectrometers (FTIRs) used to determine the location of the SF6 cloud centroid. The results of the transport model output based on input from the diagnostic and prognostic models are presented. Finally, the results of the actual SF6 cloud centroid are compared with the modelled results. The differences are discussed and potential causes for the differences considered. However, the overall model performance produced results that show that cloud tracking and calculations were within one grid unit of ground truth. Overall, the models produced reliable results for this limited study on a light wind case.

A mesoscale diagnostic wind model, based on mass conservation, is utilised to develop a wind climatology for the southern Appennines in Italy, with the aim of identifying areas suitable for wind energy production plants. The model includes the kinematic effects of the high ground, anabatic and katabatic flows along mountain slopes as well as blocking effects. The climatological analysis carried out appears quite effective in selecting favourable areas where a more detailed investigation based on boundary layer models and observational field studies may lead to the final specification of locations suitable for mountain wind farms.

A multiscale study of a cold-air comma cloud that produced an area of heavy rain and locally severe weather has been undertaken by synthesising data from a research microwave Doppler radar and VHF and UHF Doppler wind profilers, along with routinely available radar-network, satellite, in situ and mesoscale-model data. The rain area was generated in the exit region of an upper-level jet characterised by laminated velocity perturbations. Some of the perturbations were attributable to inertia-gravity wave activity. The rain area itself is shown to have been composed of a well-organised set of mesoscale rainbands each being due to a mixture of upright and slantwise convection. The existence of the multiple rainbands may have been related to the multi-layered atmospheric structure upwind. Each of the rainbands had cold-frontal and warm-frontal portions, so as to form a series of mini warm sectors stacked along the axis of the comma cloud at roughly 70 km intervals. The multiple rainbands were accompanied by multiple fingers of overrunning low-θw air from part of a dry intrusion originating from just below a major tropopause fold. The fold contained an intense potential-vorticity maximum which appeared to be the focus of the overall system. The operational mesoscale version of the Met. Office's Unified Model, with its 12 km grid, is shown to have resolved many but not all of the key features of the rainbands. It is suggested that further improvements in very-short-range forecasting of important local detail could be achieved by further increasing its resolution and assimilating more mesoscale observational data.

The role of thermal advection in development is examined in its different guises, from the frontal cyclone model of the Bergen School, through the ideas of Sutcliffe and Petterssen, to the quasi-geostrophic omega equation, system-relative isentropic analysis and the potential vorticity (PV) perspective. The PV formulation of the omega equation introduced by Hoskins et al. (1985) is used, together with a simple quasi-geostrophic numerical model, to compare system relative isentropic upgliding with full vertical velocity. The PV approach is compared with the application of the traditional omega equation, particularly with regard to cancellation between vorticity/potential vorticity and thermal advection terms. An equivalence is proved between the traditional form of the omega equation and the diagnosis of vertical velocity via ageostrophic motion, with the contribution from thermal advection being identified with the vertical motion that arises from isallobaric ageostrophic motion.

This paper deals with ‘mushroom-shaped’ patterns that may be observed in water vapour (WV) imagery. Its associated conceptual model has been adapted from the ‘T’ configuration. For this model some remarkable properties of WV imagery have been used: the spatial and temporal continuity of atmospheric structures, the more detailed upper-level circulation features and the possibility of observing and monitoring relationships between them. Using this model, and from the kinematic viewpoint, it is possible to infer some features such as deformation zones, rotation centres (vorticity centres) and relative maxima of wind in the upper-middle-level flows. Some examples are presented to show the usefulness of this conceptual model for the interpretation of WV imagery, the diagnosis of upper-middle-level flow and the evaluation of the numerical model.

The aim of this work is to present a methodology to downscale weather forecasts (i.e. to give regional-scale forecasts based on synoptic-scale forecasts from a numerical model). This methodology consists of the regionalisation of a large zone into thermally homogeneous meteorological regions followed by a study of how different types of weather affect them. Once the meteorological behaviour of each region is determined, cokriging is used to predict its temperature knowing the current temperature and type of weather expected (i.e. based on forecasts from a numerical model). Thus, from a methodological point of view, it is shown that geostatistical prediction techniques can be used in the meteorological sciences by combining classical multivariate statistics and space-time prediction techniques. To illustrate this methodology, the maximum and minimum temperatures at 54 observatories in Catalonia in winter and synoptic data from Barcelona's airport have been used. The method proposed in this paper, which represents an improvement in temperature prediction compared to that given by classical statistical methods, allows the forecasting of temperature. This case study shows that forecasts can be easily downscaled and that, to produce daily forecasts, just a pocket calculator is needed. The results are presented for a one-day forecast, but this technique can be applied to forecasts over a four-day period.

There are many challenges facing today's farmers and the use of weather and climate can help farmers in meeting and overcoming these challenges. Additionally, government decision-makers use information on actual and potential crop production impacts, a large percentage of which is based on weather and climate information such as drought, heavy rain events, and hurricanes. The Joint Agricultural Weather Facility (JAWF) is an example of one U.S. Government organization successfully using weather and climate information in many of its operational applications that are disseminated to users. These agricultural weather applications or products are grouped into tactical (short-term) and strategic (long-term) products. Examples of tactical products discussed include the Weekly Weather and Crop Bulletin (WWCB); routine and special crop-weather assessments, and a Regional Weather Network in Mississippi. Strategic products discussed include the U.S. Drought Monitor and the use of weather information in the monthly World Agricultural Supply and Demand Estimates (WASDE) process. The purpose of this paper is to provide some successful applications of climate and weather information and how this information is communicated between this agrometeorological service and farmers. Also, the goal is to provide lessons learned for other agrometeorological services around the world.

The performance of the European Centre for Medium-Range Forecasts model in forecasting the tracks of tropical cyclones in the South China Sea and parts of the western North Pacific for the years 1991-8 was assessed using 2.5° resolution data transmitted operationally over the WMO Global Telecommunication System. Minimum mean sea level pressure centres were used to identify and track the positions of tropical cyclones, and in 1998 the positions of the centre of maximum 850 hPa relative vorticity were also used. The model's performance was compared with that of subjective forecasts made by the Hong Kong Observatory and with no-skill forecasts as represented by a climatology-persistence method in the 1990s. Significant improvements in the model forecasting of tropical cyclone tracks were identified towards the end of that period. The model mean forecast errors for 24-hour, 48-hour and 72-hour positions were 215 km, 340 km and 453 km in the early 1990s (1991-3) respectively, compared with 155 km, 244 km and 292 km in the late 1990s (1996-8).

River flow forecasting using rainfall predictions from a mesoscale weather prediction model in combination with a physically-based rainfall disaggregation model incorporating small-scale topographic variability is demonstrated. Rainfall predicted by the UK Met Office Mesoscale Model on a 16.8 km grid is disaggregated onto a 2 km grid using a rainfall model which adds the effect of small-scale topography. River flow is calculated by a distributed rainfall-runoff model using the output from the rainfall model. A thunderstorm event on 7 June 1996 over the Brue catchment in Somerset, England is used to evaluate the models. The rainfall model successfully forecasts the band-shaped rainfall field within the catchment and the error in the total amount of flow during the storm is only -12%. An error of -40% in the peak flow is attributed to the treatment of convective clouds in the model.

In partnership with the Environment Agency, the Met Office has developed a short-period thunderstorm forecasting system based on a conceptual life-cycle model of convective cells. Although originally intended to provide forecasts of intense precipitation, the model provides a mechanism for predicting other forms of severe weather phenomena associated with thunderstorms. This paper investigates the possibility of using GANDOLF to generate a forecast of lightning risk. Model life-cycle stages are compared against observed lightning locations in order to derive a basis for forecasting risk, and this was then tested on data for three different events. The results from this initial investigation seem promising and suggest this type of approach can be effective.

The qualitative parameters describing present weather are particularly difficult to automate. The weather types which create most of these difficulties are known, but little attention has been given to investigating the reasons for disagreements between the primary reference, the professional observer and an automated instrument. This paper provides a method - multiple logistic regression - to compare the WMO present weather codes detected by a professional observer and an automated system. A new approach is introduced to explain the errors relative to the official weather variables. Many weather periods have been analysed, but here results are presented for a snow period with slight and very slight precipitation. The best predictive variables were the dew point temperature, wind direction, relative humidity and visibility. The catalyst for this study was the need for better quality control and for tools to enable the development and the manufacture of better instruments and systems to detect present weather.

Currently the South African Weather Service (SAWS) compiles seasonal rainfall and temperature outlooks by combining output from various models in a subjective manner. A group of scientists discusses the forecasts from a variety of models and then decides, from these discussions, what the strongest climate signal is. A map is drawn to represent the ‘gut feeling’ from the specialists based on the results from the various models. Although the models used are all scientifically sound, the compilation of the outlook remains subjective. In order to compile a single probability forecast out of the many different model outputs an objective method has to be implemented. This paper proposes such a method. The results were tested during the December–January–February season over a retroactive period from 1991/92 to 1999/2000. Results show that a combination of different models consistently delivers a more skilful forecast than any individual model on its own.

Radar reflectivity information is often displayed in two dimensions, making it difficult to extract the structural characteristics of convective storms. The maximum radar reflectivity and the vertical profile of liquid water distribution in a vertical column of a convective cell is used to determine a structural and intensity classification of the cell. The application of this Storm-Structure-Severity classification is demonstrated by investigating a tornado event on 15 November 1998 in Harrismith, South Africa, by using volume-scanned reflectivity data from the S-band MRL-5 radar. The regions of convective development, decay and mesocyclone evolution are identified with this classification. The method is able to extract the three-dimensional structural information of convective storms embedded in volume-scanned reflectivity data and present it in a simple display format.