تحميل كتاب الاستكمال المكاني للبيانات المناخية باستخدام نظم المعلومات الجغرافية Spatial Interpolation for Climate Data The Use of GIS

استكمالا لسلسلة تعلم GIS نقدم لكم في هذه المقالة تحميل كتاب الاستكمال المكاني للبيانات المناخية باستخدام نظم المعلومات الجغرافية GIS في علم المناخ والأرصاد الجوية Spatial Interpolation for Climate Data The Use of GIS in Climatology and Meteorology ، من تأليف Hartwig Dobesch , Pierre Dumolard , Izabela Dyras .

Introduction book Spatial Interpolation for Climate Data The Use of GIS in Climatology and Meteorology Pdf

The Internet can be used in an effective manner to visualize as well as provide access to information for a wide range of users. This also applies to presentation and provision of access to numerical maps (Web mapping). This latter task is often performed on the basis of GIS technology, since the GIS packages available on the market offer Internet map servers as a standard software element. Open-source solutions can also be used. In both cases, we have at our disposal solutions which provide unified access to spatial information based on OGC standards1 and fulfill modern interoperability requirements.

Aside from the direct usage of GIS for Web mapping, the usage in offline mode is also possible. In this case, GIS tools are used to prepare a Web map service which will later be made available to the user without the involvement of GIS tools. Here as well, we can use inexpensive or free tools, which are normally compatible with desktop GIS packages, in order to prepare dedicated solutions which do not require the aforementioned spatial information access standards to be fulfilled.

Below, we present our experiences concerning the building and usage of Internet services providing access to spatial information from areas of meteorology and climatology. We shall present several examples which use GIS tools in both offline and online mode.

Firstly let us consider the abstract diagram of meteorological examinations. The initial stage is meteorology that means the qualitative formulation of the given problem. The next stage is mathematical calculation in order to formulate the problem quantitatively and the third stage is to develop a software on the basis of the mathematical calculations. Finally, the last stage is again meteorology, that is, the application of the developed software and the evaluation of the obtained results. In practice, however, the mathematical calculations are sometimes neglected. Instead of an adequate mathematical formulation of the meteorological problem, readymade software is applied to solve the problem. Of course in this case the results are not authentic either. Let us quote John von Neumann: “without quantitative formulation of the meteorological questions we are not able to answer the simplest qualitative questions either”.

Concerning our topic, we have the following question: what kind of spatial interpolation mathematics is adequate for meteorology? Nowadays geostatistical interpolation methods built in GIS software are applied in meteorology. The mathematical basis of these methods is geostatistics, which is an exact but special art of mathematical statistics. The specialty is connected with the assumption that the data is purely spatial. Consequently, the geostatistical methods cannot efficiently use the meteorological data series whereas the data series make it possible to obtain the necessary climate information for the interpolation in meteorology.

The Developments in Spatialization of Meteorological and Climatological Elements 

An important but difficult task for a climatologist or a meteorologist is to provide information about weather and climate for any place at any time, even for places where observations of the meteorological elements do not exist. In such cases they have to use their skill and knowledge to give the most reliable value for the desired information. Traditionally this is done by using observed values at neighboring stations which are then adjusted for representativity, terrain and other effects affecting the local climatology. Such estimates have usually been carried out as single point calculations, often including subjective considerations based on local knowledge and experience. Most of these estimates will not be consistently derived and they are thereby not reproducible and cannot be regarded as homogenous. They are therefore of limited value, for example, for advanced climate analysis.

Geographical Information Systems (GIS) give possibilities to combine different georeferenced variables and parameters in such a way that it should be also possible to give consistently derived estimates of meteorological and climatological variables at any location at any time. This potential was realized by the European Meteorological Services in the mid-1990s, which meant an increasing activity within this field over the last 5-10 years. In the beginning, GIS was primarily used as a tool to establish continuous maps of climate reference values of several elements. Many of the attempts were carried out by using the built-in, though verylimited, possibilities for spatial interpolation.