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.

The influence on the propagation of coastally trapped disturbances (CTD) of large gaps in the bounding coastal mountains is studied via application of the Colorado State University Regional Atmospheric Modeling System (RAMS). By large gap it is meant that the width is of order 25–50% of the Rossby radius. In order to isolate the effects of the gaps, idealised simulations are used. Thus, RAMS is configured with a straight north-south coastline with a ramp-shaped coastal mountain range in which a gap is inserted and a gravity current-like CTD generated through cooling the low level atmosphere at the southern end of the domain. Radiative, land surface and cloud parameterisations are turned off to avoid sea breeze generation and other thermal effects and to focus on the dynamical effect of the gaps. Four simulations are conducted: no gap in the coastal mountain barrier, an insertion of a narrow (80 km) gap, a wide (160 km) gap, and an idealised island in the barrier. It is found that the gaps influence CTD propagation by effectively stalling the propagation at their mouth for a period and subsequently weakening the gravity current-like features (vertical extent, strength and abruptness of the wind and stratification changes at the leading edge). The idealised island has a less obvious impact since it is bounded by relatively narrow straits and does not allow communication with the model interior like the gaps do. Although lack of data and the nature of the idealised simulation prevents a detailed assessment of the simulations against real cases, qualitative comparisons with observed events in western North America and south-eastern Australia are made. Application of these results to air quality and forecasting issues is discussed.

Long records of hydrological and hydrometeorological variables are of inestimable value for the planning, design and management of water resource systems. Unfortunately, such long series invariably exhibit inconsistencies and non-homogeneities arising from a wide variety of causes - for example, changes in instruments and observation practices, and alterations to the general environment of the instruments themselves. Both non-parametric and parametric statistical tests are available to detect the presence of long-term movements in recorded time series, but the interpretation of results from such testing has often to be carried out in the absence of sufficient station metadata. A case study of precipitation records for 20 stations in Scotland over the period from 1961-99 has demonstrated that the results from statistical testing for inconsistency and non-homogeneity should also be interpreted in the context of prevailing weather systems. In particular, the increases in both annual and winter (Dec-Feb) rainfall totals recorded during this period at sites in western Scotland appear to reflect the changes in the winter atmospheric circulation over the Northern Hemisphere as encapsulated in the North Atlantic Oscillation Index (NAOI). Sustained periods of positive values of the NAOI, albeit less severe than during those of the 1970s and 1980s, are evident in the historical record of this index. The trends in rainfall totals identified could therefore be interpreted as arising from natural variability or even greenhouse gas forcing rather than from any inconsistency and non-homogeneity.

Ground-based multi-parameter radar is used to validate and evaluate satellite passive microwave parameters related to rainfall over land. Light precipitation over the southern part of England is considered. The issues of diverse resolutions of radar and satellite data in space and time are investigated, as well as the satellite beam-filling problem, in relation to present passive microwave satellite algorithms related to rainfall over land, and their perceived behaviour. Several statistical analyses are applied and their sensitivities to data integration problems are quantified. Passive microwave parameters are evaluated and compared with each other. It is concluded that for radar passive microwave satellite data intercomparisons, calibrations and validations the time resolution seems to be more important than the spatial resolution, and high-resolution radar can be used operationally to tackle the satellite beam-filling problem. It is found that several passive microwave algorithms have performances very similar to each other.

A forecasting system for fungal infection of turfgrass using weather-based empirical indices (the ‘Fidanza’ and ‘Schumann’ models) was developed and evaluated for its ability to predict the occurrence of brown patch (Rhizoctonia blight) infection episodes at an experimental site in southeastern USA. Disease observations took place at the Turfgrass Field Laboratory in Raleigh, North Carolina between 8 June and 17 August 2003. Three meteorological data sources were used to generate disease risk indices using the empirical models: an on-site observing station, an observing station at a nearby airport, and the US National Weather Service's operational Eta weather forecast model. Visual observations of brown patch activity were conducted in the field and used to evaluate the accuracy of the disease prediction models. Results indicate that the Fidanza and Schumann models correctly predicted brown patch activity on 48% and 30% of the days on which disease occurred, respectively. A diagnosis of the model performance of these disease indices was undertaken. Results are dependent on occurrence of high temperatures and rainfall and independent of the source of the meteorological information (on-site, airport and the Eta model); therefore, regional meteorological information can be effectively applied to develop turfgrass disease forecasting systems. Ongoing efforts are directed towards developing new disease indices and modifying existing indices before an operational disease forecasting system can be implemented.

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.

This paper describes a new instrument designed to measure cloud or fog total water content mounted on a tethered balloon facility. The instrument is an evaporator type, which is inexpensive and relatively easy to construct. The device measures total water content with an uncertainty of 0.3 g kg–1, and a resolution of 0.03 g kg−1, at a frequency of 1 Hz. This typically gives a spatial resolution of 5–20 m and allows turbulent statistics to be calculated. Tethered balloons provide an ideal platform for the instrument to study low cloud, allowing very detailed measurement of cloud structure to be made. Some typical data are presented as an illustration.

This paper deals with the utility of Monin-Obukhov similarity theory for wind speed simulation in stable conditions over flat terrain in northern Croatia. Wind speed profiles observed through a 150-m deep layer are compared with those obtained from two simple wind speed models. For this purpose, the similarity functions for two stable classes based on Monin-Obukhov theory are locally determined. They are tested in wind speed simulations using a model based on the Monin-Obukhov theory (MO) and a model which combines the surface-layer model of Monin-Obukhov theory and the Ekman-Taylor type model (MOE). Under less stable conditions the combined model (MOE) produces better skill, whereas the model based on the Monin-Obukhov theory (MO) performed better under more stable conditions.

A triple-nested regional weather prediction model was used to investigate the effects of the model horizontal resolution and orography on southwest monsoon precipitation over India. Numerical experiments with different resolution topography and different horizontal resolution model domains were conducted. Simulation results indicate that both the distribution and intensity of simulated southwest monsoon precipitation over India is highly sensitive to model horizontal resolution and topography. The model with a finer resolution is able to predict mesoscale organization of rainfall over the land mass. Rainfall predicted over the coarse domain is much less than that observed owing to its unrealistic representation of orographic effects and mesoscale forcings. Simulated wind speed, surface pressure, and latent and sensible heat flux distributions are also sensitive to the model resolution. Larger values and more detailed structure of the distribution of the wind speed and latent and sensible heat fluxes are simulated in the finer domains.

Fruit growing in Slovenia has become one of the more important agricultural production branches over the last two decades. Due to climate variability over a relatively small area of 20,000 km2, irrigation practices are not only important but also indispensable agrotechnical measures for obtaining permanent, high quality crop yields in the northeastern and southwestern parts of the country. Hence, accurate estimation of water consumption by agricultural crops with the inclusion of metorological monitoring is essential in the field of water management. As a decision support tool, the Slovenian Agrometeorological Information System (SAgMIS) developed by Agrometeorological Department in the Environmental Agency of the Republic of Slovenia (EARS) and introduced 10 years ago has improved significally over the last two years. Transfer of actual and forecasted agrometeorological data to the end users has been quick and accurate, with the last version of mobile data dissemination in testing use. A case study of water use by irrigated peach trees in the plantation orchards of lower Vipava valley was undertaken from 1996 to 2004. A variety of irrigation systems with diverse irrigation water applications was introduced for the purposes of studying irrigation water benefits derived from accurate weather data and forecasts. The results showed that important savings in the amount of irrigation water used, on an annual average of 20%, could be achieved with accurate and timely irrigation forecasts during the vegetation periods.

The basic condition for using precipitation data from raingauges and radars is data quality control. This aspect is important for comparing and using rainfall data, for example in models. In the scope of the EU-project VOLTAIRE (Validation of multisensors precipitation fields and numerical modelling in Mediterranean test sites) rain data from Cyprus have been analysed. Different quality control methods have been applied to the rainfall data of 158 raingauges and the data of 11 events (in 2002 and 2003) of the C-Band radar in Kykkos. The first results of the use of ground clutter algorithms for radar data in Cyprus are presented in the paper.

In-situ methods for measuring upper tropospheric humidity are important for two reasons: (i) they can be used as accurate spot measurements with which to calibrate more extensive data from satellites and other sensors; (ii) they can provide high accuracy measurements from aircraft or balloon with which individual processes of transport, phase change or chemistry can be studied.

In either case the accuracy of the in-situ measurement is of paramount importance. This study compares the performance and accuracy of a resonance fluorescence type of sensor (the Fluorescence Water Vapour Sensor) with a standard frost-point hygrometer.

An intercomparison of these two hygrometers has confirmed a long-standing difference between these two types of sensors (the FWVS overestimates the water vapour volume mixing ratio by 10–20%, depending on pressure). Testing the FWVS experimentally in the laboratory, along with a modelling study of the sensor has revealed that a significant source of error is due to contamination of the FWVS source emission, and the subsequent underestimation of the oxygen absorption cross-section.

The aim of data-impact studies at the UK Met. Office is to investigate how observations affect the accuracy of model forecasts. Results from such experiments provide useful evidence on which to base the design of observational networks. This project, using a case study approach, investigated the relative benefit of different observation types within The Met. Office's Mesoscale Model domain on forecasts of three-hourly precipitation accumulation over the UK up to 12 hours ahead. The method used assesses the impact of assimilating single observation types, or a limited combination of types, where impact is measured against a control forecast obtained after a dummy assimilation using no observations. In experiments for 13 case studies, the observation types that most frequently provided a beneficial impact when presented alone to the assimilation were sonde data, surface data and data from the Moisture Observation Processing System (MOPS).

In order to test the current recommendation for reservoir safety that a snowmelt of 42 mm/day can be used throughout the UK, calculations of hourly snowmelt rates were made for hourly weather reporting stations in the UK. These data were analysed to give annual maximum melt totals for periods of 3, 6, 9, 12, 18, 24, 48, 72, 120 and 168 hours. Supplementary data from high altitude climate stations allowed further 24-hour melts to be calculated. The annual maxima were entered into an extreme value type one (Gumbel) analysis and estimates of the melt with return periods of 5, 20 and 50 years were made for the durations of 3, 6, etc. hours. An estimate of the return period of a 24-hour melt of 42 mm was made for the sites. These return periods were below 10 years in some high altitude Pennine and Scottish sites, but in excess of 1000 years at low altitude in England. The 24-hour melt with 5 year return period at the sites was related to altitude, northing, mean January temperature and windspeed in linear regressions which permit a calculation of snowmelt at any point in the UK.

The need for a continued reassessment of reservoir safety in relation to heavy rainfall and floods is of paramount importance. The latest advice given by the Institution of Civil Engineers states that for much of Somerset in southwest England, the Flood Studies Report underestimates the frequency of heavy rainfall and that local data should be adopted. However, this advice has not always been followed. Furthermore, the advice does not extend to other areas in southwest England. Therefore, it is essential to assess in detail the reliability of the four methods which can be used in order to estimate storm rarity at present in southwest England. These are the Bilham method, the Flood Studies Report (FSR) method, the FORGE method, and the Four Parameter Model. Both the Flood Studies Report and the FORGE method give higher values of storm rarity than either the Bilham or Four Parameter Model. The Bilham method is not sensitive to geographical variation in rainfall frequency. Comparison of all four methods with observed storm events and storm depths showed that the Four Parameter Model gave the most realistic results, followed by the Bilham method. For a given storm rarity the Four Parameter Model tends to give the highest storm depth, with the differences increasing with storm rarity. These new results suggest that in southwest England many existing dams and other drainage works have been underdesigned.

Agroclimatology represents the link between several agrometeorological fields and climatological applications. The German Weather Service (DWD) uses data from many meteorological stations for 40-year calculations by agrometeorological models. The topics extend from microclimatic elements over the wide field of soil conditions and water content, agricultural operations and product quality to forest fires and plant pests. Analyses of agroclimatic output allow for better planning, risk assessment, objective evaluation of the current situation and even for a test of the models used. Current applications concern crop microclimate, including soil, evapotranspiration and volatilisation, plant protection, phenology and product quality, with examples such as the frequency of extreme soil frost, optimum harvest conditions, plant water stress on different soils, and the frequency of high pest incidence. Not only singular places, but regions too can be evaluated. Results from combinations of elements, such as soil frozen with high water content, are considered valuable for recommendations to agricultural users. Agroclimatic model information concerning, for example, removal of plastic cover from spring crops, soil conditions for plant water use, tractability, herbicide effectiveness, germination, nutrient washout, and harvest, is directly usable by farmers. The information about forest fire index, extreme season assessment (for compensation payments), and trend analyses is of practical use for administration. The use of risk levels for plant pathogens is important both for farmers and extension services. The future importance of agroclimatic applications is considered high.

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.

Since the start of field station manufacturing approximately 25 years ago, the configuration of Road Weather Information System (RWIS) stations and the type of sensors used has changed very little. Little is known about the variation of climatic variables from the 2 m level, where instruments are normally placed, down to the road surface. The ‘Road Climate Room’ can be defined as the volume of air, road and surroundings influencing the conditions on the road. This study attempts to describe the Road Climate Room both theoretically and experimentally. Mobile measurements as well as a permanent station were used. At the permanent station detailed temperature measurements above and beside the road were made. These were related to other climatic variables such as wind, cloudiness, humidity and ground heat flux. The results show that the most important processes occur below the 10 cm level. The air column above this level is well represented by the 2 m level temperature sensor. For most situations the cooling of the air closest to the ground is much more intense in the vegetation than over the road. The temperature difference can be as large as 8 °C and can be represented statistically with high determination by wind and cloudiness. The heat storage in the road is a key factor for keeping the temperature of the road high throughout a full diurnal cycle. The cold air in the vegetation can be considered as a potential source for cold air drainage onto the road surface in terrain where that is a problem. No advection affecting the road surface was observed at the permanent station. This suggests that the Road Climate Room can be defined as being well within the internal boundary layer of the road. The mobile measurements, however, show that advection from the surroundings is likely to have taken place, which makes the definition of the Road Climate Room more difficult. Further studies are needed to fully understand the complicated processes.

During an Inter-Regional Workshop on Improving Agrometeorological Bulletins in Barbados in October 2001, participants recommended that a dedicated web server be developed for distributing agrometeorological products from WMO members. Subsequently, an Expert Group Meeting on Internet Applications for Agrometeorological Products was held in Washington, DC, during May 2002, to discuss the practical steps needed to develop this web server. Discussions from this meeting led to the development of the World AgroMeteorological Information Service (WAMIS). WAMIS is a dedicated web server on which countries and organisations can place their agrometeorological bulletins and advisories. Provision of such a central location for agrometeorological information enables users to quickly and easily evaluate various bulletins and gain insight into improving their own bulletins. Also, these bulletins represent the expert knowledge of the individual countries and provide the possibility to assess extreme events and disasters in a historical perspective, especially when an archive of bulletins is present. Placement of agrometeorological bulletins on WAMIS also increases the visibility of the National Meteorological/Hydrological Services (NMHS). In March 2005, a tools and resources section was added to WAMIS to provide users with additional papers, links to software tools, Internet links, and other resources to help improving their agrometeorological bulletins and advisories and services.

This paper presents a prediction system for regional crop growth in Sweden, recently set up at SMHI (Swedish Meteorological and Hydrological Institute). The system includes a state-of-the-art crop growth model, WOFOST (WOrld FOod STudies) and inputs from meteorological mesoscale analysis. The simulated crops are spring barley, spring rape, oats and winter wheat, and the period of investigation is 1985-98. The simulated water-limited grain yield is used as a predictor in the yield prediction procedure. The technological time trend describing the yearly increase of the production level is accounted for as well. Yield prediction based on crop growth modelling is justified since the ability to forecast the yield is higher compared to that using the technological time trend alone. The prediction errors are of the order of 8 to 16%, with the lowest errors for winter wheat and spring barley.