cost 719: interoperability and integration issues of ... - EC GI & GIS Portal

10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

COST 719: INTEROPERABILITY AND INTEGRATION ISSUES OF GIS DATA IN CLIMATOLOGY AND METEOROLOGY Frans van der Wel1, António Perdigão2, Pawel Madej3, Malgorzata Barszczynska3 and Danuta Kubacka3 1

Royal Netherlands Meteorological Institute (KNMI) , De Bilt (NL) 2 Instituto de Desenvolvimento Rural e Hidráulica (IDRHa), Lisbon (P), 3 Institute of Meteorology and Water Management (IMGW), Kraków (PL)

ABSTRACT Geographical Information Systems (GIS) are still not common within National Meteorological Institutes (NMS). COST-719 is a cooperation of 20 countries investigating the extra value of GIS for meteorology and climatology. An interesting role of GIS is related to the standardization of spatial (meta)data. Users outside NMS’s benefit from atmospheric data for numerous applications while NMS’s need geographical base data for analyses and visualization. The meteorological and climatological field is working on new ways to exchange these data through the development of spatial data infrastructures. KEYWORDS: COST-719, infrastructure, interoperability, metadata, meteorology INTRODUCTION In the framework of the COST Programme, COST-719 is aiming at the spread of knowledge and skills concerning Geographical Information Systems (GIS) within the climatological and meteorological community. As weather data are spatially distributed, a GIS could offer a practical and relevant working environment for the integration, analysis and visualization of these data together with other spatial data sources. Within most National Meteorological Services (NMS) the acceptance of commercial GIS tools beyond climatology is still a cumbersome process, partly caused by the shortcomings underlying the datamodel (temporal aspects!). Another reason is that atmospheric science is “more concerned with the question why phenomena happen and less with the region where they happen” (Petrosyan, 2001). The current generation of COTS GIS systems can by far not be referred to as atmospheric information systems, though there are sufficient reasons to use these GIS systems in meteorological practice. As an example, consider visualization, (pre)processing of geographical data layers (also used outside GIS) and dissemination of results by means of map servers. Geographical data can further improve atmospheric applications. Nowadays, it appears to be quite difficult to collect uniform geographical data such as Digital Terrain Models and land cover at a European level with sufficient quality and against low costs. Recent developments, such as the GMES initiative of the EC and ESA, the publication of the European Directive on public access to environmental information (28 January 2003) and the Water Framework Directive are therefore of the utmost importance for the user community that could benefit from the information that results from accessible data sources. From a technical point of view, integration of data from different

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

sources has become easier with the advent of GIS tools. As regards policy and methodology there are still a lot of open issues. COST-719 aims to gather and disseminate know-how and technical skills among the different member states in order to increase the use of GIS tools for management and integration of climatological, meteorological and other environmental data obtained from different sources. This is organized and developed according to the contents of the memorandum of understanding, inciting the establishment of projects in which different countries cooperate and make use of panEuropean data bases that are not always usable or accessible, affecting directly the final results of the action. The action is structured in working groups, one dealing with the so-called watchdog function, searching for publicly accessible European spatial databases and the inventory and dissemination of knowledge about relevant software developments. Initiatives like GMES, GINIE, INSPIRE and the Water Framework Directive are intensively monitored. WEATHER AND GIS It is true that GIS technology is rather new for the meteorological community. This may sound somewhat strange as the history of GIS goes back to the 1960’s! However, in meteorology the tools have long gone un-noted, although climatologists started to visualize their data somewhat earlier with commercial GIS packages. One conclusion that can be derived from the above is that we, the NMS’s, do not really need such applications. Another could be that the applications are maybe not fully suited to the needs of people working at a NMS. From the number of “GIS-like” tools present at most weather services it is stated that the first conclusion is wrong. The data used to study weather and climate are spatial and are therefore typically processed in some kind of spatial information system. The major problem consists in the time dimension of the data used in meteorology. Commercial GIS packages are only starting to deal with spatio-temporal data models that are relevant for atmospheric data. Christakos et al. (2002) state in the very first beginning of their book that “…commonly used atemporal GIS neglect essential dynamics of the natural processes in time and do not take into account important cross-correlations and causal dependendies in the composite space/time domain...”. As this development will take some time to mature, a more pragmatic approach could help to interface GIS and Atmospheric Science Information Systems (ASIS). Nativi et al. (2004) describe the differences between both underlying data models and advocate models that are supported by so-called interoperability services. This is extremely important as traditional GIS users are for example willing to incorporate weather information in their applications (radar data for hydrologists) while meteorological researchers are interested in local topography for their high-resolution models (downscaling). Even without the support of the time dimension, the current generation of GIS tools is valuable for approaching weather-related issues. Shipley et al. (1996) already noted that “...GIS does the weather...”, meaning that COTS-GIS packages are able to deal with basic functionality that is also available in expensive, dedicated weather processing systems. With more open and standardized packages, this is even truer (e.g. ArcGISEngine from ESRI and ENVI from RSI). These developments notwithstanding, GIS is still playing a modest role at the atmospheric research stage on which researchers tend to develop their own tools. GEOGRAPHICAL DATA AND WEATHER DATA In meteorology and climatology, geographical data play a key role. The demand for that kind of data can be considered in view of two aspects:

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Their use in analyses, that is for various kinds of spatial interpolation and modelling – in which case the data are a factor that determines the spatial distribution of the analyzed meteorological phenomena or climatological elements. The derivation of parameters for traffic safety applications (fog, glazed frost, heavy rainfall, storm), NWP modelling (description of physiographic features that influence surface fluxes), impact studies based on air pollution dispersion models, etcetera. Their use for visualization of the results of measurements or calculations – in which case they are used mainly as a background image for other data.

Modelling requires geographical data Meteorological modelling takes advantage of climatic data while climatic analyses are based on meteorological data, and in both fields geographical data constitute vital input information. In this case, geographical data concern mainly elevation (with slope and exposure of the area), land cover (with parameters dependent and independent of the season of the year), hydrography and soils. Consider the preparation of climatological maps. This requires not only measurement data about weather elements from many years, but also data about geographical environment. These data significantly influence spatial distribution of meteorological elements that are shaped and influenced by geographical factors. Mainly, but not solely, the applied data pertain to topographic profile. For instance, air temperature is clearly correlated with the height above sea level, distance from water reservoirs, slope, longitude and latitude. Geographical data change very slowly in time, as compared to meteorological data. Therefore, in operational models, e.g. of weather forecasting, they are treated differently than current measurement information. Once prepared and processed, geographical data can be used even for a few years. It is important though, to allow for changeability of certain geographical elements in respective seasons of the year, or even months (e.g. leaf area index, vegetation dependent on the season of the year). Presentation of information is based on geographical data Another aspect of the application of geographical data in meteorology and climatology is the presentation of measurement data or the results of models and analyses to a range of end users. This is well exemplified by weather forecast maps and satellite or radar images, presented on e.g. web pages of meteorological services. In that case, geographical data are mainly used as land-sea mask, reference map or simply as background images making an appeal to our sense of aesthetics. Data about administrative division, location of places, elevation or hydrography are very helpful for advanced users of operational meteorological products to understand the nature of a phenomenon. Scales, formats and availability of data Concerning meteorological and climatological analyses, the need for the accuracy of data depends to a large extent on the analyzed issue. In case of meteorological forecast maps, the area of interest is large (the whole country or region) and geographical data do not have to be very precise. Mesoscale numerical weather prediction models are usually based on a grid at a resolution of a few to a dozen kilometres. Therefore we can use map scales of 1 : 1 000 000 or smaller. Local operational models require much more detailed material. For instance, a local model of road icing may require a digital elevation model at a resolution of a few or several dozen meters while other geographical data has to be gathered at corresponding scales (e.g. road topography, type of

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

surface, road surroundings). The positional accuracy should then conform to a scale of 1:10 000. The same is true for climatological issues. The smaller the area in question, the more detailed the data should be, including the geographical layers. One of the prerequisites to successfully embed GIS in a NMS is the availability of geographical data crossing national borders. While the access to weather data has always been clearly defined for third parties, i.e. non-NMS’s using data in XML or GIS formats, finding accurate, costefficient and up-to-date geographical data is much harder. Especially pan-European data sets are difficult to obtain, certainly if a particular fitness-for-use is required. Recently, such data are becoming available, for example: • Height data – Some countries have mapped topography at a high resolution resulting in very good height maps. As an example consider the Dutch data set retrieved by means of laser altimetry (at least one data point every 16 m2). A European alternative is the dataset gathered in the framework of the Shuttle Radar Topography Mission (SRTM), with data points approximately every 30 meters (see figure 1). • Land cover data - At national scales good data sets are available although not for free. The CLC2000 project pursues a European Land Cover map based on satellite image classification and will be available at no cost for registered users.

Figuur 1: Differences between GTOPO30 and SRTM data In most cases, only small scale data are available free of charge (e.g. GTOPO30, Vmap level0, low resolution satellite images). In addition, there are differences in geographical data policies among different countries. Directive 2003/98/EC (2003) of the European Parliament and of the Council on the re-use of public sector information could be beneficial in this matter as it states that “...It is necessary to ensure that any natural and legal person has a right of access to environmental information held by or for public authorities without his having to state an interest..” Later on one can read what environmental information exactly means: “Environmental information” shall mean any information in written, visual, aural, electronic or any other material form on: the state of the elements of the environment, such as air and atmosphere, water, soil, land, landscape and natural sites including wetlands, coastal and marine areas, biological diversity and its components, including genetically modified organisms, and the

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

interaction among these elements..” The impact of such a directive is tremendous, even more because it should become effective in February 2005! The INSPIRE initiative related to the European spatial data infrastructure is very important for the future. Taking into consideration the classification used under the INSPIRE initiative, geographical data used in the meteorological and climatological realm are to be mainly considered basic (reference) data and its availability at European level should increase. On the other side, atmospheric conditions and meteorological spatial features are classified as thematic data and are also in the focus of interest of INSPIRE and related initiatives (like GMES) which will hopefully support to solve interoperability problems. METADATA Exchanging and applying geographical data has to be attended by a set of meaningful metadata. Metadata provide information about the data. Both intrinsic and extrinsic metadata are relevant as the former refers to the qualities of the data set, e.g. accuracy and lineage, while the latter points to the context of the data set, e.g. access rules, costs, etcetera. Within the World Meteorological Organization of the United Nations (WMO), the role of ISO 19115 is stressed as the metadata standard for describing meteorological and climatological data. Originally, this standard has been developed for geographical metadata but of course it could be extended for atmospheric data as well. Not officically accepted by WMO, this standard is already used when possible in order to gain experience. In a data infrastructure metadata databases are required to find and evaluate data on a network such as the internet. One can imagine that for dynamic data such as atmospheric data this requires some smart classification system. Current developments are mainly focusing on station data, but other data such as model and satellite data will follow without doubt. If the ISO standard becomes the de jure standard, it will improve the interoperability of different databases. Spatial data infrastructures can benefit from standardized queries because the metadata catalogues are similarly structured. This is something that will be addressed in the INSPIRE initiative as well. A GIS APPROACH TO ACCESS WEATHER DATA Meteorology has its own data infrastructure based on the Global Telecommunication System (GTS) which is operating according to a so-called push mechanism. Station observations for example are shared worldwide within the hour in order to obtain a synoptic view of the current weather conditions. For operational purposes, i.e. forecasting, such a mechanism is efficient and secure. A more on-demand retrieval of weather-related data should prove very helpful to an increasing number of users within and outside NMS’s. Therefore, projects such as UNIDART (http://www.dwd.de/UNIDART ) are established within the framework of Eumetnet, the network of European NMS’s. UNIDART UNIDART aims at the development of a technical infrastructure based on GRID technology to transparently access climatological and meteorological data from numerous distributed and heterogeneous databases. In addition to weather data, geographical data could be added to this service as well. Although the project itself is not using GIS technology, it creates the prerequisite for an effective use of GIS within NMS’s as suitable, standardized (XML?) data are the fuel for such systems. Will UNIDART be just another alternative to disseminate data? Earth Science Portals (ESP), Live Access Servers (LAS), internet map servers, dataGrids and numerous portal initiatives are

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

being discussed and demonstrated throughout the internet. It is foreseen that some of these activities will converge towards a more standaardized solution, eventually. Nonetheless, UNIDART is supported by the official European meteorological framework and will be based on open source technology. This means that the approach is very generic and extensible. Of course, lessons will be learned from other areas such as geoinformatics. GIS application servers could play a role in preparing climate maps based on data from different databases. Metadata standards can be used in parallel with the GIS community as shown above. A lot of work that will be done within the framework of UNIDART can be considered a preparation for research into a Future WMO Information System (FWIS). This will be a new data infrastructure for both realtime (meteorological) and non-realtime (climatological) data and products according to a push as well as pull mechanism (ad hoc requests). It will be extremely important for the way in which NMS’s will disseminate their data and products in the future, i.e. as from 2008 onwards. Industry solutions Meanwhile, the industry offers increasingly promising solutions as well. A questionnaire performed among the participating countries of COST-719 has shown that the majority of NMS’s and climatological research institutes make use of ESRI software products, i.e. ArcGIS and the former Arcview and Arc/Info software. A specifically interesting development of ESRI is the establishment of ArcWeb products. In this case, spatial data and GIS functionality are hosted on servers outside the organization. All that is needed is a web browser and an Internet connection! The data can be used in ArcGIS or some custom-made application. A nice example comes from Meteorlogix, a US enterprise that offers different meteorological services to the public, containing information about cloud cover, NEXRAD (weather radar) base reflectivity and precipitation type (rain, mix, snow), and surface observations (see figure 2). The weather information is updated on a continuous basis, from every fifteen minutes to every hour and can be accessed through ArcGIS or ArcExplorer Java Edition. Unfortunately, the services are not for free and concern US data only. ArcIMS is dedicated to the development of web applications and the dissemination of spatial data on the Internet. As opposed to the ArcGIS desktop software, ArcIMS runs also on Linux machines, a great advantage for the meteorological community. Conceptually, three servers are required: a web server, a data server and an application server but these can be installed on the same machine, e.g. for test purposes. Now that this product complies with the standards of the Open GIS Consortium (OGC) regarding map servers, communication with other, non-commercial although OGC-compliant software is guaranteed. If a NMS has to open up part of its data collection, for example as a result of national or European policy, it should preferably link up to an European infrastructure initiative. But due to the status of construction of the projects, a more pragmatic approach is often followed, meaning that a lot of effort is put in temporary solutions (dedicated databases or map servers). Is is advocated that once such approach is followed, compliance to standards and extensible sources is kept in mind.

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

Figure 2: Example of a service offered by Meteorlogix (Source: ESRI, 2003) OUTLOOK FOR THE FUTURE Data flows are increasing with satellite instruments operating at even higher resolutions in time, space, spectrum or radiometry. Network technology improves and bandwidths offer new posibilities for the transfer of huge amounts of data in a cost-efficient way. Better models and forecasts contribute to better warning systems for floods, dangerous road conditions or other environmental disasters. Intelligent data infrastructures, interoperable databases and standardized data and metadata further improve this situation. The role of environmental data, delivered timely, at the correct place with a suitable quality and against low costs is essential in this context. This is partly a matter of finding the data (data discovery), but policy should not be ignored! Hopefully, European agreements and cooperations make the availability of, at least, base data easier. Notwithstanding the differences among the meteorological institutes in Europe, cooperation in the areas of GIS (COST-719) and infrastructure (UNIDART) are promising. Components of both projects, GIS and Grid technology, could prove to be a fruitful mixture - beneficial for the European Data Infrastructure.

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10th EC GI & GIS Workshop, ESDI State of the Art, Warsaw, Poland, 23-25 June 2004

BIBLIOGRAPHY Christakos, G., Bogaert, P. and Serre, M. (2002). Temporal GIS. Advanced functions for fieldbased applications, Springer-Verlag. Directive 2003/98/EC (2003). http://europa.eu.int/eur-lex/en/search/search_oj.html, search for L series, OJ, number 41 and page 26. Nativi, S., Blumenthal, M.B., Caron, J., Domenico, B., Habermann, T., Hertzmann, D., Ho, Y., Raskin, R. and Weber, J. (2004). Differences among the data models used by the Geographic Information Systems and Atmospheric Science communities. Proceedings of the 84th AMS Annual Meeting, January 11-15 2004, Seattle,USA. Petrosyan, A.S. (2001): GIS in meteorology and climatology. The needs and the challenges. Proceedings of the European Geophysical Society, XXVI General Assembly, March 25-30 2001, Nice, France. Shipley, S.T , Graffman, I.A. and Beddoe, D.P (1996): GIS does the weather, Proceedings, ESRI User Conference, May 20-24 1996, Palm Springs,USA.

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