An attempt is made to establish a probable link between mean September upper-air temperatures at Indian stations and the ensuing winter monsoon rainfall over eight individual meteorological subdivisions of southern India where the winter monsoon accounts for a large percentage of mean annual rainfall. For this purpose, linear correlations between the winter monsoon rainfall of the subdivisions and the mean September upper-air temperatures and vertical temperature differences at the Indian stations have been evaluated using the data set for the period 1959 to 1988. The inter-correlations between the significant parameters were calculated and then tested to derive multiple linear regression equations containing the best combination of predictor variables. There is a significant positive relationship between the winter monsoon rainfall over Tamilnadu and the mean temperature difference at 500–300 hPa levels at Nagpur in September. Secondly, the winter monsoon rainfall over Coastal Andhra Pradesh is significantly negatively correlated with the mean September temperature over Visakhapatnam at 700 hPa. The most significant inverse relationship exists between the winter monsoon rainfall over Rayalaseema and the mean September temperature over Visakhapatnam at 850 hPa. By using significant parameters, algorithms have been formulated and tested for each subdivision for six succeeding years, 1989–94. These results assisted to some extent in the prediction of winter monsoon rainfall over subdivisions of South India. Finally, stationarity is tested by evaluating another set of multiple linear regression equations using the data set for the period 1965–94 and then testing the algorithms on the preceding six years.

This study identifies the use of the sky view factor (SVF) in urban climate studies. In addition, it relates air temperature differences to the SVF and examines these differences with respect to the height at which fish-eye photographs are taken for the calculation of the SVF. The study focuses on night-time air temperature patterns within the urban canopy using data collected during clear, calm nights from sixteen permanent stations and from car measurements. Fish-eye photographs taken at two levels (2 m above ground and at ground level) are compared and shown to be statistically different. The results of the study performed in Göteborg, Sweden, indicate a fairly strong relationship between air temperature and SVF. The permanent stations used indicate that it is better to use fish-eye photographs taken at ground level. The relationship is determined by means of regression analysis. The SVF variation in urban areas and the importance of SVF in relation to other central parameters such as thermal admittance are also discussed.

The observation and analysis of the difficulties and differences, as well as possible errors, in the information output by automated stations is a complicated process. In observing the present weather the human observer is, for example, able to code many different codes at the same time. A period of mixed winter precipitation events is recognised as a significant challenge in assessing the reliability of automated Present Weather Sensors (PWS). The period of difficult winter conditions presented in this paper was unique in the whole two-year test period. Earlier studies have mostly been based only on liquid precipitation.

This paper presents two basic ideas: the first is to compare many simultaneous human-observed codes with one PWS code; the second is to use logistic regression to compare the observations. A wide variety of weather variables are used as candidates for ‘methodical error’.

This paper describes a new model developed by the Met Office to predict night-time light levels. The Met Office Night Illumination Model (MONIM) predicts light levels both in the visible (photopic) range and in the waveband to which night vision goggles (NVGs) are sensitive. The model will be used operationally for support of night-time flying operations. The model is described in detail and its light-level forecasts are compared with observations.

A three-day mesoscale numerical simulation has been performed over the narrow Salento peninsula (south-eastern Italy) during summer conditions characterised by weak synoptic forcing. These atmospheric conditions favour the development of complex sea-breeze systems and convergence zones on the peninsula. The aim of this work is to investigate the ability of an atmospheric mesoscale model to reproduce the surface fields of meteorological variables in the presence of local-scale forcing and breeze circulations, which are fundamental in applications such as air pollution modelling and nowcasting.

The modelled fields have been compared with available surface measurements and sodar data. Results indicate that the model can simulate the general mean wind field in a realistic way. The diurnal evolution of the wind is well reproduced and the maximum deviations mostly occur during the night, being associated with calm conditions.

Statistical analysis indicates that the typical mean bias is found to be about 1 m s-1 for hourly averaged wind speed, less than 20° for wind direction and about 1°C for temperature. The root mean square error (rmse) varies from 1 to 3 m s-1 for wind speed, from 50° to 70° for wind direction, and is about 2.4°C for temperature. All the values of the numerical indexes are within ranges which are characteristic of those found for other state-of-the-art models applied to similar cases studies.

Despite a good overall agreement between predictions and observations, some discrepancies were found in the individual profiles due both to the limited spatial representation of the local details and to the complex wind field which makes the space–time matching between the model and the observations quite critical.

The structures of the thermal mixed layer and the breeze convergence zone are similar to numerical studies relative to more idealised conditions.

A recursive statistical method is given to post-process the 2-metre temperature ECMWF General Circulation Model by using the SAR network of surface stations in Sardinia. The method calculates daily maximum and minimum temperature forecasts up to 5 days ahead for 55 stations. Forecasts over one year for 55 ground stations have been analysed. A comparison with Direct Model Output (DMO) and persistence is then made, giving special attention to the winter season and to freezing conditions. The error analysis shows a BIAS very close to zero (between 0°C and 0.5°C) on all the stations and a marked reduction of mean absolute error compared to the DMO forecast. The error reduction is more marked in the case of freezing conditions than with the DMO forecast. Such situations are difficult to forecast and the very high BIAS of DMO has not been eliminated completely. The advantages of the procedure are: (a) there is no need to store large numbers of measurements and large amounts of model forecast data; (b) the estimated correction is easily adapted to new meteorological conditions; (c) the procedure is transparent to the updating of the model; and (d) the procedure is very easy to implement operationally.

Operational forecasting of mesoscale weather systems in Hong Kong is supported by an automated nowcasting system called SWIRLS (Short-range Warning of Intense Rainstorms in Localised Systems). SWIRLS is based on the extrapolation of radar echoes using the TREC (Tracking Radar Echoes by Correlation) technique. With a suitable choice of pixel array size on the radar reflectivity maps, the TREC vectors derived can be used to monitor and extrapolate echo motion right across the mesoscale spectrum, from individual convective cells, to supercells and clusters, and to groups of rainbands or squall lines.

On the basis of TREC, quantitative precipitation forecast (QPF) algorithms have been developed to produce high resolution forecast rainfall distribution maps over the local area. These maps provide useful objective guidance for forecasters to assess the likely rain scenario in the next few hours and to facilitate decision-making in operating the Rainstorm Warning System. This review, however, will focus on other aspects of TREC applications and some side benefits for operational mesoscale forecasting in Hong Kong. First, extension of the TREC technique to group tracking of echoes (GTrack) have enabled forecasters to make qualitative educated guesses of the likelihood of prolonged heavy rain or the potential of enhanced storm development. Secondly, extension of the QPF algorithms to a forecast range of 3 hours, supplemented by real-time accumulated rainfall data from a high density raingauge network, has enabled forecasters to provide reliable advice and guidance to geotechnical engineers for landslip risk assessment. Thirdly, rain-related applications aside, TREC vectors are also ingested into a data analysis system LAPS (Local Analysis and Prediction System) adapted from Forecast Systems Laboratory (FSL) of NOAA. Through the assimilation of TREC vectors and other wind observations, a three-dimensional wind structure of tropical cyclones can be generated in near real-time for forecasters' reference in assessing landfall impact.

Regional air pollution models are usually off-line coupled with numerical weather prediction models. The present study, however, focuses on on-line coupled modelling, for which the air pollution model is an integral part of the meteorological model. To this purpose, simulations of the first European Tracer Experiment (ETEX), which supplies the best suited verification data for dispersion modelling of a passive tracer, have been performed using versions of the Danish Meteorological Institute High Resolution Limited-Area Model (DMI-HIRLAM). Simulation results have been compared with observed values as well as with results from other models.

The operational version of DMI-HIRLAM using well-known basic advection schemes has been tested, showing the need for improvements for air pollution purposes. The fourth-order Bott algorithm for advection has thus been implemented in the semi-Lagrangian version of DMI-HIRLAM. Due to its practically perfect mass conservation properties and its low computational cost, this method turns out to be efficient for simulations of transport of pollutants in the atmosphere. This represents a first effort towards a fully integrated air pollution model, e.g. for forecasting purposes.