During December 1993 a microwave radiometer belonging to the Central Aerological Observatory (CAO) Moscow was operated at the Meteorological Research Unit, Cardington, UK. The radiometer has a single channel with a central frequency of 61.0 GHz, bandwidth of 2 GHz and sensitivity 0.04 K for a 1 s integration time. The antenna (beam-width 6°) was scanned from nadir to horizontal in 9° steps. Calibration was done every scan cycle using an electrically switched load. The information potentially available from such a radiometer is discussed. The measurements made at Cardington are compared with in situ observations made by radiosondes and by the Meteorological Office's tethered balloon system. Microwave brightness temperatures calculated from the radiosonde ascents are compared with observations. These were found to agree with a mean difference of 0.1 K and with a standard deviation of < 0.3 K. Similarly retrieved temperature profiles up to 500 m were found to agree with the radiosonde profiles within 1 K rms. During the comparison period there were no strong low-level inversions to test fully the radiometer's retrieval capability.

Satellite images occasionally show the existence of mesocyclones (MCs) close to the eastern coast of Greenland, especially in the region of Angmagssalik/Tasiilaq. The forcing mechanisms of such MCs are investigated by means of numerical simulations with a three-dimensional mesoscale model. The special characteristics of the East Greenland topography are shown to be a key factor for the development of the MCs. The channeling of the flow in large valleys along the East Greenland coast leads to a convergence, implying a vertical stretching of the flow through the valleys and the generation of cyclonic vorticity. This convergence can be strong during intense katabatic storms, so-called Piteraqs, which are a much-feared phenomenon in that area of Greenland. During these situations the synoptic environment enforces the katabatic flow. The results of the simulations suggest a close relationship between the occurrence of Piteraqs and the generation of mesoscale vortices close to the East Greenland coast. An improved understanding of these processes will help forecasters to advise aircraft and ship operations near the coast of East Greenland.

A climatological study of the occurrence of freezing precipitation at ground level is presented. It is based on reports of freezing precipitation in SYNOP messages from the three winters covering the years 1995-1998. The geographical domain covered is Western and Central Europe, extending northwards to Scandinavia and southwards to North Africa. The types of freezing precipitation selected are freezing rain, freezing drizzle and ice pellets. The frequency of occurrence of each of these types of freezing precipitation was computed. The results show that freezing precipitation is not an uncommon phenomenon in Europe, with the combined frequency of the various types of freezing precipitation (either drizzle, rain or ice pellets) being 0.5 to 1% of all SYNOP messages that include an observation of the current weather in Central Europe. The surface air temperature intervals associated with freezing precipitation have been studied. An attempt was then made to determine the mode of formation of freezing precipitation (either by melting of snow crystals in a layer of positive temperatures or by a process of coalescence or diffusional growth) by studying the thermodynamic soundings associated with freezing precipitation events.

Locally applicable information about climate and soil properties can help farmers identify opportunities and reduce risks associated with changing to new land uses. This article describes techniques for preparing high-resolution regional maps and GIS surfaces of agriculturally relevant climate parameters. Ways of combining these climate surfaces with soil data and information about the physical requirements of crops to identify areas likely to be the most suitable for new high-value crops are then outlined. Innovative features include methods for merging observations from temporary climate stations installed for one to two years in conjunction with longer-term climate station observations to improve input data for the maps, and techniques for mapping quantiles of climatic factors that may constrain agricultural operations. Examples are the expected ‘one-in-five year’ first and last frost dates, and the ‘one-in-five year’ lowest and highest seasonal rainfalls. The use of night-time satellite infrared observations to improve spatial resolution of frost hazard maps is also described. Typical standard errors of these climate mapping techniques are summarised. The benefits of ongoing consultation with local farmers and local government staff during the design and implementation of climate/soil/crop potential studies are described. These include optimising products to meet local needs, quality control of the resulting maps and GIS surfaces through local knowledge, and improved uptake of information by users. Further applications of techniques described in this paper include products useful to the energy sector, preparation of daily gridded climate data estimates for use in water quality and plant growth modelling, and development of regional climate change scenarios.

The World Health Organisation (WHO) and the World Meteorological Organisation (WMO) have jointly recommended that the UV Index (UVI) should be used to inform the public about possible health risks due to overexposure to solar radiation, especially skin damage. To test the current operational status of measuring and modelling techniques used in providing the public with UVI information, this article compares cloudless sky UVIs (measured using five instruments at four locations with different latitudes and climate) with the results of 13 models used in UVI forecasting schemes. For the models, only location, total ozone and solar zenith angle were provided as input parameters. In many cases the agreement is acceptable, i.e. less than 0.5 UVI. Larger differences may originate from instrumental errors and shortcomings in the models and their input parameters. A possible explanation for the differences between models is the treatment of the unknown input parameters, especially aerosols.

Most operational hail detection algorithms for single-polarisation radars are based on the analysis of the vertical profiles of radar reflectivity. At KNMI (Royal Netherlands Meteorological Institute) and RMI (Royal Meteorological Institute of Belgium) the probability of hail is derived from the height of the freezing level and the 45-dBZ radar echo top height (maximum height of the 45-dBZ echo). Echo tops are affected by errors in the measured reflectivity itself and by errors in the height assigned to these reflectivities. This study investigates the quality of radar echo top heights as a function of range and explores the implications for hail detection.

The method is based on the comparison between reflectivity measurements from two radars on the vertical cross-section extending between these radars. In a first step, sampling errors related to the radar Volume Coverage Patterns are analysed using idealised storm profiles. Subsequently, real reflectivity data for 25 thunderstorm episodes are compared. It is found that the quality of the maximum reflectivity measurements strongly deteriorates with range and that about half of this degradation can be attributed to overshooting effects. Height assignment differences between the two radars are limited to about 0.5 km. Errors on the reflectivity measurements strongly affect the frequency of 45-dBZ threshold exceedances. However, once the threshold is exceeded, errors in measuring the 45-dBZ echo top heights generally affect the derived probability of hail by less than 20%.

The two latest changes introduced during 1998 into the Ensemble Prediction System (EPS) operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) are described. The first change, the inclusion of instabilities growing during the data assimilation period in the generation of the EPS initial perturbations, increased the probability that the analysis lies inside the ensemble forecast range. The second change, the introduction of a simulation of random model errors due to parametrized physical processes, improved in particular the prediction of precipitation. The performance of the ECMWF Ensemble Prediction System from 1 May 1994 to 2 March 1999 is assessed using different statistical measures. Results indicate that the general performance of the EPS has been improving over the years. Finally, ongoing research projects on predictability issues developed either at ECMWF or at European research institutes in collaboration with ECMWF are discussed

It is known that topography is an important factor controlling the variation of road surface temperature (RST). In order to explore possible relationships between RST and topography, the authors used Thermal Mapping data obtained by a vehicle-mounted thermometer in a mountainous area in Nevada, USA, under different weather conditions in December 1994. The data were validated against the measurements of road surface sensors. After that, a step-wise regression technique is employed to find out possible statistic relationships between RST and altitude at different surveying routes. It was found that the relationships exhibited different characteristics in different climate domains and under different weather types. In most cases, the relationships were non-linear. In order to obtain more information about the cause of the residuals and the variation, the error of regression fitting is related to near-ground meteorological parameters (air temperature, dew point and wind, etc.). This study proved that Thermal Mapping is a reliable and effective method to display spatial variation of road surface temperature.

Challenges in linking meteorological and climatological information with a wide range of farming decisions are addressed in this paper. In particular, while a considerable amount of weather and climate information is now available for farmers, some types of information under development or already operational, particularly climate forecasting, formation, may be ill-suited for use by farmers for their decision-making. Case studies show it is particularly important for those key farm decisions that are amenable to weather and climate information to be identified clearly so that weather and climate information can be better tailored to suit farming decisions. A participatory approach provides farmers with ownership of the processes associated with development of weather and climate information and facilitates advances in linking climate and weather information and forecasts to farm decisions. Decision-support systems provide useful output when used with farmer discussion groups. Developing appropriate interdisciplinary systems to connect climate, weather, and agronomic information, especially including forecasting systems, with farm management is needed if uptake of weather and climate information by farmers is to be successful. Provision of output of climate change scenario and trend information to aid long-term strategic farm management decisions needs to be considered, especially in regions where more vulnerable farming zones exist.

If mean temperature increases, in accordance with Intergovernmental Panel on Climate Change (IPCC) projections and adaptations and/or genetic modifications are not considered, suitable areas for farming corn (Zea mays) and coffee (Coffea arabica) will decrease in the state of Sao Paulo (Brazil). Further, increases in precipitation will not be enough to ameliorate the impacts associated with increases in mean temperatures. Suitability for grain production will decrease more rapidly in regions with sandy soils than in regions with clay or medium soils, as the temperature increases. The projected increase in mean temperature of up to 5.8°C would decrease the suitability for grain production drastically in spite of soil texture. Besides the reduction of suitable areas for coffee production, the projections suggest that changes will be more enhanced in the southeast of the state, especially in higher elevation regions, where farming practice, soils, and infrastructure are unsuitable for the economic production of coffee. In both cases, no compensatory increase in suitable areas for production is likely under current IPCC scenarios.

Used to predict icy stretches of road during winter nights, thermal mapping is the measurement and visualisation of road surface temperatures for road ice prediction. From its development in the 1970s, the accuracy of thermal mapping has been subject to numerous systematic and random errors. One source of error is the effect of traffic, which is known to have a considerable influence on road surface temperatures. However, as the effects have never been fully quantified, the full implications for thermal mapping are unknown. In this study, consistent temperature differences of around 1.5 °C were found across the different lanes and carriageways of a multi-laned road. The thermal differences are significant and can be directly attributed to traffic heat fluxes.

A short review paper is presented for the subject area of air quality modelling. The paper is geared towards equipping new researchers and workers with a basic appreciation for the technical aspects of their field, providing a staging point for further investigation, and highlighting useful source materials. The paper is introduced through a discussion of the philosophical and practical implications regarding mathematical air quality modelling. A critique of relevant mathematical modelling techniques is presented and includes a treatment of Box, Gaussian, Eulerian, Lagrangian and Particle modelling approaches. Conclusions on the future of mathematical air quality modelling are drawn.

Two models were used to assess the effects of coastal characteristics on radar propagation in ducting conditions in the Persian Gulf. The NCAR/Penn State MM5 model simulated atmospheric conditions at a 5-km horizontal spatial and hourly temporal resolution on a day on which observations of ducts existed. The output from this model was input to the AREPS propagation model to produce radar coverage over coastal areas. Four factors influenced radar propagation: the sea breeze; coastal configuration; orography; and ambient wind. The sea breeze alone allowed propagation to extend about 100 km inland in a layer 200 m deep. When the breeze was aided by a following ambient wind the propagation layer extended for 150 km and was 400 m deep. A coastal indentation caused differences in depth and intensity of propagation over a distance of about 30 km parallel to the coast in which the indentation occurred. Steep near-coastal orography blocked radar propagation.

The comparative performance of the WASP and MS-Micro/3 airflow models and of the DAMS scoring system in calculating the wind climate in complex forested terrain has been examined. An analysis was carried out of predicted and observed wind speeds collected over 18 months at six monitoring sites in mountainous country in the Cowal Peninsula, western Scotland. Both airflow models and the DAMS system produced variable results: the airflow models were most accurate on exposed hill tops whereas DAMS tended to be more accurate in valleys and lower slopes. Taken as a whole this study showed that the DAMS scoring system performed as well as the other airflow models considered.

In low mountain-range areas with complex topography, climate elements show a high variability caused by manifold interactions between relief and land use. The lack of continuous measurements demands concepts for the transfer of regional climatic information to smaller scales. In this study, a radiation model and a coupled vegetation atmosphere model using GIS were combined to estimate radiation balances, temperature and evapotranspiration as well as coupling and feedback mechanisms between vegetation and atmosphere of small-scale heterogeneous areas.

In the system HIRGIS, these approaches were parameterised with the output of the vegetation-boundary layer model HIRVAC and transferred in a GIS (ArcView) environment to consider topographic influences including sky view factors as well as the influence of different land uses (e.g. pasture and forest) especially on net radiation. Depending on the horizontal resolution of the digital elevation data, it is feasible to model area-related meteorological surface data without any interpolation methods and associated loss of precision. The results are applicable to water budget modelling, forest management, alternative energy supply or downscaling of satellite information.

To illustrate the results, the area of the Tharandter Wald near Dresden as well as the Sperrgraben watershed in the Bavarian Alps were selected. The results clearly show the combined effects of topography and land use. The differences of solar irradiance on a clear spring morning between slopes oriented east–west and south–east in the Tharandter Wald reach up to 800 W/m2. The daily sum of evapotranspiration on a steep, south-facing spruce-covered surface in the Sperrgraben watershed is two times higher than the evapotranspiration on a north-facing grass surface.

Model results match data collected at the ‘Anchor Station Tharandter Wald’ and from the Sperrgraben watershed for the periods under investigation.

Trends and periodicities of annual rainfall for 29 sub-divisions of India and all India (area-weighted average of the sub-divisions) are studied by using the rainfall series for a period of 124 years (1871–1994). The trends are evaluated by using a linear regression technique. To identify the climatic changes, the rainfall series are subjected to 11-year moving averages. These averages show some epochs. From this, it is found that in some sub-divisions the trend in one direction reverses its direction after some years. The years pertaining to these changes are identified and the trends are calculated for the segments of the series. The significance of the trend values are tested. Power spectra are obtained using the maximum-entropy method. The periods in the range 2.0–2.5 years are present in the rainfall series of the sub-divisions to the north of 20 °N, on the west coast, and in Tamilnadu and for all India. This periodicity may be attributed to the quasi-biennial oscillation. Rainfall series of the most of the sub-divisions and all India indicate a triennial cycle. Significant periods in the range from 3.0 to 8.0 years and 8.0 to 12.0 years are also identified.

Neural networks (NNs) have been successfully used in the environmental sciences over the last two decades. However, only a few review papers have been published, most of which cover image processing, classification, prediction and geophysical retrieval in general, while neglecting rainfall estimation issues. This paper reviews, without aiming to be exhaustive, NN approaches to satellite rainfall estimation (SRE) by providing an overview of some of the methodologies proposed. A basic introduction to NNs is provided and the advantages of using NNs in SRE are explained, illustrating how NNs can be used to complement more computational-expensive methods to generate quick and accurate results in near real time. The role of the NNs in statistical-empirical algorithms is also reviewed. The last section aims to generate some discussion through comparing the empirical and deterministic algorithmic approaches and contrasting some of the apparent drawbacks of using NNs with a statistically based view of the satellite geophysical parameter estimation.

The present study deals with the thermal mapping technique in a road climatological perspective. The temperature mapping technique is analysed in relation to instrument set-ups, data collecting and possible sources of errors in converting measured radiation to surface temperature values. Furthermore, analyses of thermal mapping recordings are discussed. Factors that give rise to a varying temperature pattern are presented (i.e. road-bed material, radiation and advection), and also how the thermal mapping technique can be used to determine the relative importance of these factors. The conclusion of the study is that the technique is very useful but it is very important to be aware of the limits and different source of errors involved.

The main objective of the present study is the construction of air temperature maps for the territory of Poland through the application of contemporary GIS techniques. First a review of currently used spatial interpolation methods is presented. Several spatial interpolation methods have been tested: ordinary kriging, cokriging, universal kriging and residual kriging. The last of these–residual kriging–was chosen for the map constructions. The dataset contains mean monthly temperatures from 168 stations (synoptic and climatological) located across the entire territory of Poland as well as from 55 stations located in bordering zones. Additionally, mean daily temperature data from all synoptic stations have been collected for the 50-year period 1951–2000. Several geographic parameters, including elevation, latitude, longitude, and distance to the Baltic coast (for stations located within 100 km) were used as predictor variables for air temperature interpolation. The first set of maps display the mean annual, seasonal and monthly temperatures for Central Europe and other selected regions. Special attention was paid to temperature parameters which have practical value (e.g. the length of the growing season, duration of thermal summer and winter, and degree day accumulations). GIS tools also enable the easy calculation and display of the area under specified thermal conditions and the display of maps for climate monitoring purposes. An example of the synoptic–climatic analysis with the application of mean daily temperatures and circulation using Grosswetterlagen circulation types is also presented.

This brief paper further develops the objective front-plotting methodology described in Hewson (1996), to enable the tips of frontal wave cyclones to also be objectively identified. The method embraces a new definition of frontal waves, but is analogous to operational practice in that these waves are located where cold and warm fronts join. It is suggested that for the early stages of cyclonic development the new methodology will perform better than those previously published.