In tropical-equatorial environments, where weather has a high degree of variability, a reliable weather forecast is an essential decision-making tool. To achieve reliability and accuracy it is important to study both the climatological trends and the elements affecting the meteorological variables of the areas under analysis. A precise weather forecast is not enough, however. The way in which the information is presented to users in weather bulletins is also important. The users need to comprehend the forecasted meteorological synopsis and to draw relevant conclusions. In this case study a Medium Range Forecast model was used (NOAA Air Resources Laboratory MRF) to predict, in statistical form, the likely weather conditions. The verification of the weather forecast scored good results, especially in the shorter period (7 days), showing that this specifically designed weather bulletin was a reliable decision tool. In order to demonstrate the key role of the meteorological information to the decision-maker, an economic estimation of the weather forecasts was carried out.

Data from a VHF wind-profiling radar are being used as a teaching aid in the Department of Meteorology at the University of Reading. An example is given of data obtained during the passage of a train of baroclinic waves which shows how the radar, together with output from weather-forecast models, can vividly illustrate processes occurring over a range of scales.

Hong Kong International Airport (HKIA) is located in a coastal environment and is occasionally affected by sea breezes. High air temperatures relative to sea surface temperature, coupled with light winds or moderate east to northeasterly winds are favourable conditions for the development of a sea breeze at the airport. In the afternoon of 27 April 2000, sea breezes affected the airport and a sea breeze front was formed by convergence between the westerly sea breeze and strengthening easterlies. An aircraft landing at HKIA encountered the sea breeze front and reported wind shear with airspeed gain of up to 15 kt at a height of 30 m (100 feet) above ground. Surface wind observations and Doppler velocity data of a Terminal Doppler Weather Radar (TDWR) allow quantitative analysis of the wind shear event. Shortly after the wind shear event, the TDWR also captured interesting interactions between the sea breeze front and an area of passing showers. This paper presents a quantitative analysis of the wind shear event and observations of the sea breeze interactions by the TDWR.

The impact of vegetation on the microclimate has not been adequately considered in the analysis of temperature forecasting and modelling. To fill part of this gap, the following study was undertaken.

A daily 850-700 mb layer mean temperature, computed from the National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis, and satellite-derived greenness values, as defined by NDVI (Normalised Difference Vegetation Index), were correlated with surface maximum and minimum temperatures at six sites in northeast Colorado for the years 1989-98. The NDVI values, representing landscape greenness, act as a proxy for latent heat partitioning via transpiration. These sites encompass a wide array of environments, from irrigated-urban to short-grass prairie. The explained variance (r2 value) of surface maximum and minimum temperature by only the 850-700 mb layer mean temperature was subtracted from the corresponding explained variance by the 850-700 mb layer mean temperature and NDVI values. The subtraction shows that by including NDVI values in the analysis, the r2 values, and thus the degree of explanation of the surface temperatures, increase by a mean of 6% for the maxima and 8% for the minima over the period March-October. At most sites, there is a seasonal dependence in the explained variance of the maximum temperatures because of the seasonal cycle of plant growth and senescence. Between individual sites, the highest increase in explained variance occurred at the site with the least amount of anthropogenic influence. This work suggests the vegetation state needs to be included as a factor in surface temperature forecasting, numerical modeling, and climate change assessments.

A volcanic ash detection product using AVHRR data has been developed for use in the London Volcanic Ash Advisory Centre, operated by forecasters at the Met Office. The product is an image that shows the brightness temperature difference between two infrared channels, which can be used to discriminate between clouds containing volcanic ash particles and those containing water droplets or ice crystals. Factors such as water vapour, water droplet and ice crystal content, opacity, cloud top temperature, ash particle size, surface emissivity properties and instrumental effects all have an effect on the spectral signal represented in the image. AVHRR imagery has been used to study the volcanic clouds ejected from eruptions of Mount Etna (Italy) in July 2001, Hekla (Iceland) in February 2000 and Mount Spurr (USA) in September 1992 to demonstrate the application of this product during volcanic events. The volcanic ash detection product provides essential information that can help forecasters locate volcanic ash and give appropriate guidance through advisory statements to the aviation industry and thus help avoid dangerous and expensive encounters between aircraft and volcanic ash.

Over recent years most European countries have experienced destructive precipitation events, many of which have generated floods resulting in the loss of lives and economic damage. Rather surprisingly, Europe has no common database for flood events, which continue to be monitored by different national and/or local authorities, with different criteria. In the light of this situation, the main aim of the present work is to propose a classification scheme for a European-level flood database, in which severe flood episodes are related to meteorological conditions and mesoscale settings.

The meteorological systems relating to the most severe events (22 events) over a five-year period (1992-1996) were analysed using Meteosat imagery and conventional meteorological data. Most of the observed events were related to extra tropical cyclone development. The results are discussed in terms of conceptual models currently used for extra tropical cyclones: the structure and dynamics of Atlantic cyclones can very often be interpreted in terms of well- known conceptual models, while characteristics of Mediterranean systems are not fully rendered by current descriptions. Our study underpins the need to improve the knowledge of Mediterranean systems, possibly introducing new conceptual models and/or refining the current ones.

A new index to estimate aircraft icing in clouds from operational meteorological models has been developed by Swedish meteorologists. Although rather simple it takes into account, directly or indirectly, all the principal meteorological variables for icing. The index has been evaluated during three winter seasons and is now operational in the Swedish HIRLAM model. A graphical representation of the index is presented.

The prediction of severe convection is a major forecasting problem in Australia during the summer months. In particular, severe convection in the Sydney basin frequently produces heavy rain or hail, flash flooding, and destructive winds. Convective activity is a forecasting challenge for the Sydney basin, mainly from October to April. Currently, there is a need for improved numerical model guidance to supplement the official probabilistic convective outlooks, issued by the operational forecasters. In this study we assess the performance of a very high resolution (2 km) numerical weather prediction (NWP) model in terms of how well it performed in providing guidance on heavy rainfall and hail, as well as other mesoscale features such as low level convergence lines. Two cases are described in which the operational forecasts were incorrect on both occasions. Non-severe thunderstorms were predicted on 1 December 2000 but severe convection occurred. Severe convection was predicted on 8 December 2000, but no convection was reported. In contrast, the numerical model performed well, accurately predicting severe convection on 1 December and no convection on 8 December. These results have encouraged a program aimed at providing an enhanced numerical modelling capability to the operational forecasters for the Sydney basin.

It is part of British sailing and forecasting folklore that the wind speed increases in the Dover Straits when there is an established wind-flow - westerly/south-westerly or easterly/north-easterly - along the English Channel. However the underlying mechanism of the phenomenon is unclear. We have used the Met Office ‘New Dynamics’ mesoscale model to perform a case study on an occasion when this phenomenon was observed in the Channel but not forecast well by the operational model, UM 4.5. Results are presented showing the sensitivity of forecasts to horizontal resolution (down to 2km) and to vertical resolution. We probe the physical mechanism of the Channel jet by altering the surrounding orography and the land or sea surface roughness. Both the orography and the surface roughness are shown to influence the jet formation.

The solar ultraviolet radiation (UV) flux density at the earth's surface depends on the incoming solar energy and the transmission properties of the atmosphere. UV radiation is strongly absorbed by ozone in the spectral range 200-310 nm, while the attenuation is increasingly weaker at longer wavelengths. Following the discovery of the Antarctic ozone hole in 1985, the risk of a possible UV increase at ground level, due to the observed stratospheric ozone depletion, has heightened the interest within the scientific community given the potentially harmful effects on terrestrial and aquatic ecosystems. Spectroradiometers, broad-band meters and dosimeters may be used for measurements of solar UV. In addition, radiation transfer models can be used to quantify UV irradiances at various times and locations, provided that the extraterrestrial solar radiation and the state of the atmosphere are known. Information about UV radiation at the earth's surface is given by the ultraviolet index ‘UVI’, which is defined as the effective integrated irradiance (280-400 nm) weighted by the erythemal action spectrum. The UV Index is widely used by many international weather services as an indicator of UV levels at the earth's surface providing public awareness of the effects of prolonged exposure to the sun's rays.

The aim of this paper is to present a device capable of estimating the UV Index. This device is a compact disc, used as a sundial, and is based on modelled UV irradiances derived from the STAR radiative transfer model (System for Transfer of Atmospheric Radiation). The device was tested in an urban setting under clear sky conditions.

It is a well-known fact that adverse weather significantly influences the safety and operating efficiency of air traffic, particularly in the terminal area. The unavoidable consequences of reduced operating efficiency are delays, diversions and cancellations of flights. In this paper the impact of thunderstorms on landing aircraft at Frankfurt Airport (Germany) during 1997 and 1998 is analysed. Thunderstorms are among the major weather phenomena affecting airport operations. Weather and operating conditions permitting, Frankfurt Airport is operated at more than 100% of its nominal capacity, which in turn lowers the actual capacity during periods of adverse weather. To the authors' knowledge this is the first quantitative study of weather impact on aviation in Germany. To identify thunderstorms as the unambiguous cause of delays, days without thunderstorms were used for reference and the difference in delay time was determined. The study shows that in 1997 thunderstorms increased the accumulated regular delay time by a factor of 6.3 and in 1998 by a factor of 1.1. On average, a thunderstorm typically caused about 740 delay minutes in addition to the 280 regular delay minutes for a sum of 100 arriving aircraft within four hours of average impact time.

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.

Ice accumulation on overhead railway wires can damage railway devices and disrupt railway services. In order to provide timely short-period forecasts of ice on the wires, an automated wire ice-prediction model is developed in this study. It is a statistical model with much simplified mechanisms of icing, and provides forecasts of wire surface temperature and wire surface state (icy or not), along with the forecasts of air temperature, dew point and wind speed, for three hours ahead. The model was validated against actual sensor measurements at the Dalton test site in north-east England during the winter of 1998-99. The results of the validation show that the model forecasts of wire surface temperature, air temperature, dew point and wind speed are slightly biased. The standard deviation of wire surface temperature forecast is 1.43°C. The accuracy of ice prediction when ice was reported is 81.8% and the accuracy of no-ice forecast when ice was not observed is 97.5%.

A Cloud Resolving Model (CRM) is used to simulate the showery convective activity that occurred over the United Kingdom on 13 April 1999, which was notable for observations of strong gusts. Simulations based on radiosonde profiles from both Herstmonceux and Hemsby are shown to give good agreement with available observations for this case. In particular, there is good agreement with the observed cloud top heights, precipitation amount and type, and strength of convective gusts. An algorithm to predict the maximum convective gust strength is shown to be consistent with values measured from the model. Further analysis of the model gust strengths shows that they could be approximated to a Gaussian distribution and that the mean and standard deviation of the Gaussian can be related to the maximum gust strength and the mean wind. A simple algorithm for predicting the probability distribution of the gust strengths measured in the model gives reasonable qualitative agreement with the measured probabilities and it is suggested that this demonstrates the utility of the CRM in developing and evaluating probabilistic forecasting tools for convective weather.

This paper uses an alternative to the usual cost-avoidance approach to estimating the value of weather forecast products. Value is estimated via a demand-based approach based on the willingness to pay of those who use weather forecast services. Contingent valuation is used to estimate the benefits generated by an automated telephone-answering device that provides weather forecast information to commercial users in the Toronto area of Ontario, Canada. Commercial sectors included in the study are construction, landscaping/snow-removal businesses, TV and film, recreation and sports, agriculture, hotel and catering, and institutions such as schools and hospitals. Average value per call varied by commercial sector, from $2.17 for agricultural users to $0.60 per call for institutional users, with an overall mean of $1.20 per call. At roughly 13,750,000 commercial calls annually, this would result in an estimate of benefits generated by the service to commercial users of $16,500,000 per year.

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.

Extensive studies of extra-tropical cyclones over the past sixty years have led to a plethora of conceptual models that describe the structure and evolution of storms. These conceptual (or structural) models blend observational, experimental and mathematical studies so as to represent the physical phenomena within a simple, yet flexible framework. The first three sections of this report review these conceptual models by stepping through the evolution of a mid-latitude cyclone and aim to illustrate how at each stage, conceptual models give a description of the physical processes occurring within the system. The fourth section reviews a recent cyclone classification scheme in the context of these conceptual models and attempts to group the cyclone classes into those arising through similar mechanisms. Conceptual models are then combined with this classification scheme so as to offer a unified perspective of cyclogenesis out of which a cyclone continuum develops.

This paper reports the results of the aerosol lidar experiments that have been performed at the Indian Institute of Tropical Meteorology (IITM), Pune (18.54°N, 73.85°E, 559 m amsl), a tropical station in India. The lidar-observed cloud macro-physical parameters (cloud-base and cloud-ceiling heights, vertical thickness, etc.) and polarisation characteristics and their association with surface-generated aerosols at the experimental site are presented and discussed. The correspondence among the lidar-derived aerosol distributions, meteorological parameters and south-west (SW) monsoon (June-September) activity over Pune during 12 successive SW monsoon seasons (1987-98) including two pairs of contrasting seasons of 1987-8 and 1993-4 is also examined. The results indicate an association between variations in aerosol loading in the boundary layer during the pre-monsoon season (March-May) and precipitation intensity during the ensuing monsoon season. Moreover, the decrease in aerosol content from pre-monsoon to monsoon season is found to follow the SW monsoon season total precipitation. Thus the results suggest that (i) the IITM lidar can also be a useful remote sensor for aerosol characterisation studies from polarisation measurements, and some important physical properties of clouds in the lower atmosphere over the station, and (ii) there exists a correspondence between boundary-layer aerosol content and SW monsoon precipitation over Pune, which is explained in terms of the type of aerosols and the environmental and meteorological processes, particularly during pre-monsoon and monsoon months prevailing over the experimental station.

Artificial Neural Networks (ANNs) that were originally proposed to model brain functions mathematically are now being used in many branches of research, including the atmospheric sciences. The main contribution of this paper is the development of ANN to identify the presence of thunderstorms (and their location) based on microwave measurements from all five AMSU-B frequencies and on surface observations over Iran (45–65°E, 25–45°N). From the surface observations, the position of each of the different meteorological events (thunderstorm, heavy rain, rain, light rain, snowfall and clear sky) is located in AMSU-B images. An area around this position with roughly the same brightness (visually) is selected. Then the brightness temperatures (TBs) of a few randomly selected pixels from this area are noted. In all, there were 560 pixel-points, over 20 passes of AMSU-B, in these selected areas. It is found that the thunderstorms are related to image features that are bright in all of the five-frequency images (i.e. have low TB), as expected.

The architecture of the neural network that was finally selected for identifying thunderstorm events (as against other reported events), after a series of trial and error for the best accuracy, was achieved using the four-layered Feed-Forward Artificial Neural Network (FFANN) with five nodes in input, two hidden layers with four nodes each, and one node in the output layer. In the ANN output, the thunderstorms clustered clearly away from other phenomena. ANN gave more correct thunderstorm recognition (96.7%), whereas the discriminant analysis gave 95.3% correct recognition without clear separation between the two classes.

Using a statistical approach this paper focuses on an analysis of spatial air temperature variations and their relation to urban land use. The work is based on data collected during an 18-month period at 30 sites in Göteborg, Sweden. Measurements show intra-urban air temperature differences of up to 9 °C in the urban district, and the main purpose of this study is to determine if these variations are statistically significant. A stepwise multiple regression analysis confirmed that surface cover is important for governing air temperature differences in the area. Information on land use and surface cover was gathered from a continuously updated land use database, the Master Plan of Göteborg, and a separate site description analysis. The site description analysis includes a test of three methods using aerial or fish-eye photos for characterisation of surface cover in the urban district. The results show statistically significant temperature variations between different land use/land cover categories on a diurnal basis and for all weather conditions. The importance of the results for urban planning application is discussed.