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.

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.

Limited meteorological monitoring networks provide insufficient information for determining the suitability of a specific location for an airport runway. These data limitations are compounded by the constraints imposed by the terrain itself. Clusters of small islands (archipelagos) generally lack dense meteorological monitoring networks, while the land–water distribution induces different meteorological regimes on neighbouring islands.

In this paper we present an integrated methodology to study the meteorological characteristics of potential runway sites on a medium-size island in the Aegean Sea in Greece. The methodology is based on studying the three scales of motion: (i) the synoptic scale, through a synoptic classification scheme, (ii) the mesoscale circulations with the aid of a Computational Fluid Dynamics (CFD) model, and (iii) micro-scale characteristics of each potential runway site through in-situ inspections.

Using a variety of trend extraction techniques applied to monthly observations from 1766 to 2002 on the EWP dataset, this study confirms that there is evidence of a trend towards wetter winters (November to March), particularly in December and January, and drier summers, although this feature appears to be concentrated in June and July. Trend precipitation in autumn (August to November) is more difficult to pin down, with alternative methods producing quite different trend patterns, thus highlighting how difficult it can be to extract trends from noisy data. In general, the results appear to be reasonably consistent with those of Alexander & Jones (2001) using rather different techniques, thus lending weight to the views expressed by them.

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.

A superensemble forecast that consists of six operational general circulation models is tested to simulate weather parameters over the equatorial South-East Asian region. The forecast technique, developed at Florida State University, is a unique ensemble that has proved to be one of the better prognosticators for weather forecasting. In this paper, the root mean square errors of the superensemble precipitation for a case of a severe tropical rainfall event during the winter monsoon of 2001 were smaller than the other global operational member or ensemble models used, indicating a skilled forecast. This trait is also reflected in the equitable threat score which indicates the association of the common rainfall threshold distribution between the forecast and observed best rainfall analysis from the Tropical Rainfall Measurement Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) dataset, where although it is slightly underpredicted for light rain thresholds, its results are still superior to other individual member or even the ensemble mean forecasts. Higher correlation between the superensemble forecast and the observed is maintained for up to 3-day forecasts, which indicates its potential as a reliable and good forecast tool for predicting equatorial precipitation.

The motivation for this study stems from the fact that there are no uniform criteria to identify the onset of the summer monsoon at a particular location. Furthermore, proper understanding of the events that culminate in the onset of the monsoon is crucial to allow its prediction over various time scales. An attempt is made to elucidate the characteristics of the onset and retreat of the monsoon using a global data assimilation and forecast system. For this purpose, the time series of net tropospheric large-scale budgets of kinetic energy, heat and moisture are examined over the Arabian Sea, Bay of Bengal and some land locations in India. The study makes use of daily data comprising operational analysis (0000 UTC) and forecasts (day1 through day5) produced by the National Centre for Medium Range Weather Forecasting, India, for the summer season of 1994.

The sequence of events associated with the advent of the monsoon is noticeably different at various locations. The horizontal fluxes of heat and moisture produce a divergence regime prior to the evolution and change to convergence during the onset of monsoon over the Arabian Sea. Similarly, intense diabatic cooling is noticed prior to the onset of mansoon and changes to heating subsequently. On the other hand, heat and moisture fluxes remain in the convergence regime well before the arrival of the monsoon over the Bay of Bengal. In turn, diabatic heating is noticed prior to the onset here. Onset characteristics at Bombay and Nagpur are similar to those of the Arabian Sea. However, features at Calcutta are identical to those over the Bay of Bengal. Further, the budgets of kinetic energy, heat and moisture depict monotonic decrease at various land locations corresponding to the retreat. Interestingly, the signature of retreat is very similar at the various locations considered here. These changes are observed in the analysis and further corroborated by the model forecasts. Despite the systematic biases, the model captures the essential signature of the onset at various forecast ranges.

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.

The Meteorological Office of the United Kingdom (UKMO) began its operational NWP in November 1965. This marked the start of very successful activity that would gradually bring it to the forefront of NWP development, where it stands today.

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.

Precipitation forecasts from mesoscale numerical weather prediction (NWP) models often contain features that are not deterministically predictable and require a probabilistic forecast approach. However, some forecast providers still refrain from a probabilistic approach in operational forecasting because existing methods are associated with substantial costs. Therefore, a pragmatic, low-budget postprocessing procedure is presented that derives probabilistic precipitation forecasts from deterministic NWP model output. The methodology looks in the spatio-temporal neighbourhood of a point to get a set of forecasts and uses this set to derive a probabilistic forecast at the central point of the neighbourhood. For the sake of low implementation costs and low running costs, the procedure does without ensemble simulations, historical error statistics on the operational interaction of a forecaster. The procedure is applied to the output of the mesoscale model LM, the regional part of the operational modelling system of the German Weather Service (DWD). The probabilistic postprocessed forecast (PPPF) outperforms the deterministic direct model output in terms of forecast consistency, forecast quality and forecast value.

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.

When computers became available in the 1950s meteorologists were among the first to display a keen interest in their use. They also placed the highest demands on their capacity. The earliest NWP initiatives came both from the universities and from the meteorological institutes, especially when the development of computers allowed operational runs.

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.