Over the last decade, research has greatly increased into the use of Geographical Information Systems (GIS) in a variety of applications that involve the processing of climatological and meteorological data. This upsurge of interest is related directly to the fall in price of ‘commercial off-the-shelf’ GIS products together with large advances in computer processing ability. Add to this the proliferation of the Internet and the result is a set of fast real-time bespoke solutions and visualisations for many national meterological services and end-users.

The COST Action 719 started in 2001 and presently 20 European countries are participating. The main objectives of the Action are to establish interfaces between GIS and meteorological data, assess the availability, contents and accessibility of meteorological and climatological data sets and encourage and foster European co-operation.

The tasks are carried out within three working groups concentrated on issues such as data access and availability, methods of spatial interpolation and developing recommendations for standardised GIS applications.

The applications that have been adopted mainly focus on three parameters, i.e. precipitation, temperature and energy balance for which three demonstration projects have been formulated.

It is expected that the Action will result in recommendations for better and more cost-effective production of state-of-the-art meteorological and climatological information. Also an improvement of the co-operation between European countries in the application of GIS in the field of meteorology, climatology and environmental sciences should be achieved together with better-trained personnel within the operational and scientific divisions of national meteorological services.

Additionally, the development of a visualisation system for climate data sets for internet applications is under preparation. This paper provides information concerning the work in progress on the demonstration projects made within COST 719.

The Internet is increasingly used as a means for exchanging large amounts of spatial data. Professional data centres have found secure ways to share their data resources with peers and third-party users, either as a free service or as a commercial activity. Ranging from a simple download of tables to online queries of distributed SQL databases, the role of the Internet is undeniable. It is obvious that extended security measurements are needed in order to share data over the Internet, such as a DMZ or ‘demilitarized zone’ and firewalls. Increasingly, dedicated server-side applications contribute to a straightforward data retrieval procedure.

Emerging developments in geographic information systems and distributed computing offer a roadmap towards an unprecedented spatial data infrastructure in the climate sciences. Key to this are the standards developments for digital geographic information being led by the International Organisation for Standardisation (ISO) technical committee on geographic information/geomatics (TC211) and the Open Geospatial Consortium (OGC). These, coupled with the evolution of standardised web services for applications on the internet by the World Wide Web Consortium (W3C), mean that opportunities for both new applications and increased interoperability exist. These are exemplified by the ability to construct ISO-compliant data models that expose legacy data sources through OGC web services. This paper concentrates on the applicability of these standards to climate data by introducing some examples and outlining the challenges ahead. An abstract data model is developed, based on ISO standards, and applied to a range of climate data–both observational and modelled. An OGC Web Map Server interface is constructed for numerical weather prediction (NWP) data stored in legacy data files. A W3C web service for remotely accessing gridded climate data is illustrated. Challenges identified include the following: first, both the ISO and OGC specifications require extensions to support climate data. Secondly, OGC services need to fully comply with W3C web services, and support complex access control. Finally, to achieve real interoperability, broadly accepted community-based semantic data models are required across the range of climate data types. These challenges are being actively pursued, and broad data interoperability for the climate sciences appears within reach.

The Institute of Meteorology and Water Management (IMWM) manages the national hydrological-meteorological service, which maintains the measurement network, processes data, and issues warnings, reports and announcements. There are five divisions of IMWM located around Poland. Each division includes numerous stations and scientific-research departments. The data gathered, processed and analysed by IMWM are space-related; therefore spatial information systems are indispensable for data processing and visualisation. In this paper we discuss the development of the model for GIS applications in the national hydro-meteorological service in Poland (IMWM).

Soil/vegetation–atmosphere transfer schemes (SVATS) require only a few primary parameters as inputs (leaf area index, vegetation fraction and albedo). The object of this paper is to describe methods used to derive these parameters from surface cover maps, climate maps and NDVI datasets. The resolution of these new surface parameters is 1 km at the global scale. The ECOCLIMAP database is available online to the research community at http://www.cnrm.meteo.fr/gmme/PROJETS/ECOCLIMAP/page_ecoclimap.htm. An application of this strategy for urban use at a finer scale (30 m resolution) is presented here for the city of Marseille.

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.

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.

The Champagne vineyards, famous worldwide, are located at the northern limit of viticulture. Consequently, they are very sensitive to spring frosts that can occur after bud burst. These spring frosts occur mainly in radiative atmospheric situations (low speed wind, clear sky) where spatial variations in minimum temperatures are very important. The latter depend on several factors at different scales: from the macroclimatic scale, where the geographical location (latitude/longitude) has a strong influence, to the topoclimatic scale, where environmental and topographical factors play an important role. After a brief recall of the definition of these different factors extracted from a Digital Elevation Model and a land-use database, we propose a spatial interpolation of minimum temperatures in the Champagne vineyards based on multiple regression. From this interpolation, we can map the frost hazard for the whole vineyard from data measured over five spring seasons (1998–2003) and for about 20 weather stations. In this paper, we present this mapping technique and compare it with the data for spring 2003 when particularly strong frosts occurred.

The introduction of GIS has opened up new possibilities in combining different sources of geographical information. In Norway, an agro-meteorological decision system is under development which combines gridded weather information with soil and crop development data. The system is based on a daily scale soil moisture model driven by meteorological inputs. Weather information is based on in-situ observations, and spatial interpolation schemes are used to establish fine-mesh grids of these variables over the model domain. These interpolation schemes take advantage of geographical co-variables such as terrain information. The soil moisture model is used to estimate the soil water content, which is the determinant of soil suitability for tillage and sowing. The system also includes a phenological model for identification of suitable days when combine-harvesting of cereals can be satisfactorily undertaken.

Spatial interpolation of the meteorological elements is based upon all available in-situ observations. The different elements are interpolated by different interpolation techniques. Snow depth, cloud cover, relative humidity and wind are in this first version, interpolated by using inverse distance weighting. Precipitation is determined by triangulation with elevation adjustment. Temperature is interpolated by using a residual kriging approach that includes five independent predictors in the trend equation. Evaporation is estimated by using the Penman2 formula based on the estimates of the meteorological elements.

This approach is a good demonstration of the benefits of applying GIS and distributed geo-data in cross-disciplinary situations. The application is a valuable contribution to soil capability assessments.

Precipitation is one of the most variable meteorological parameters in time and space. The standard surface measurement network provides very localised information about the precipitation. The satellite and radar observations and Numerical Weather Prediction (NWP) models provide continuous information on the state of the atmosphere, but at much lower resolution.

This paper presents work undertaken in central Europe on stratiform and convective precipitation estimated from satellite microwave data. The results of analysis are prepared in the form of precipitation intensity and range maps. The data available from an Advanced Microwave Sounding Unit (AMSU) on board NOAA-15, 16 and 17 satellites enhanced the scope of the work by providing access to new meteorological precipitation-related products. These products, such as Rain Rate (RR), Scattering Index (SI), Total Precipitation Water (TPW), Precipitation Probability (PP) and Liquid Water Path (LWP), were prepared using the regression algorithms. The data from spring and summer seasons in 2001 and 2002 were used for analysis.

The temperature and precipitation thematic layers are created from the NWP model grid data. Also SYNOP (Surface Synoptic Observations) and TEMP (Sonde air temperature) data are converted into thematic coverages. Progress in GIS technology application for NOAA/AMSU microwave-derived products preparation and visualisation in the Satellite Research Department in Poland was achieved. The developed system allows the display of the rain field forecast by the NWP model Aladin and the precipitation observed with the satellite data and other ancillary information. The maps of precipitation with additional geographical data and administrative boundaries are available for weather forecasting units via the Intranet. It is also planned to make images available on the web for external customers.

Astronomical research at present requires that a telescope with an aperture diameter of between 50 and 100 metres be constructed within the next 10 years or so. This new generation of telescopes will be called OWL (Overwhelmingly Large), and it represents one order of magnitude increase in size over today's telescopes. Selection of an ideal site for this giant telescope is dependent on many climatological, meteorological and geomorphological parameters (Grenon 1990). Among these are cloud cover, atmospheric humidity, aerosol content, airflow direction and strength, air temperature, topography, and seismicity. Even relatively minor changes in weather patterns can have a significant effect on seeing conditions (Beniston et al. 2002).

A new method (XRWIS) to predict the minimum road surface temperature for the winter maintenance of roads, using geomatics, has been tested in Poland. A geographical database was constructed for a 200 km test route from Krakow to the Slovakian border. A GPS survey to measure sky-view factor was carried out as part of the COST 719 project. A computer energy balance model ‘IceMiser’ was run retrospectively to predict road surface temperature every 20 minutes for every 20 m along the road using hourly weather data recorded at two adjacent climate stations: at low elevation in Krakow and at high elevation in Zakopane, in March 2003. A GIS was used to visualise the predicted road surface temperatures. The IceMiser model was verified by comparing the predicted road surface temperatures with measured road surface temperatures at a number of road weather outstations along the route. The results for four road weather outstations are discussed. The best results are for Libertow (264 m) and Myslenice (304 m) close to Krakow, whereas the results for Skawa (518 m) and Piatkowa Gora (649 m) at high elevation are not as good, probably due to their distance from the Zakopane climate station.

Correlation between weather radar reflectivity and precipitation data collected by rain gauges allows empirical formulae to be obtained that can be used to create continuous rainfall surfaces from discrete data. Such surfaces are useful in distributed hydrologic modelling and early warning systems in flood management. Because of the spatial relationship between rain gauge locations and radar coverage area, GIS provides the basis for data analysis and manipulation. A database of 82 radar stations and more than 1500 rain gauges in continental USA was compiled and used for the continuous downloading of radar images and rain data. Image sequences corresponding to rain events were extracted for two randomly selected radar stations in South and North Carolina. Rainfall data from multiple gauges within the radar zone of 124 nautical miles (nm) (∼230 km) were extracted and combined with corresponding reflectivity values for each time interval of the selected rain event. Data were normalised to one-hour intervals and then statistical analysis was applied to study the potential correlation. Results of regression analysis showed a significant correlation between rain gauge data and radar reflectivity values and allowed derivation of empirical formulae.