GAP · Geostatistical Analysis of Precipitation data
6РП — Действия „Мария Кюри“
- Период
- 2004-05-01 → 2006-04-30
- Финансиране от ЕС
- 168 799 €
- Участници
- 1
- Схема
- EIF
Линиите свързват координатора с партньорите.
Накратко на български
Геостатистическите инструменти се използват за определяне на количеството валежи в райони, където няма измервателни станции. Това помага за по-точното моделиране на екосистемите и проверка на климатичните модели.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Final Activity Report Summary - GAP (Geostatistical analysis of precipitation data)
Spatial regionalisation of rainfall serves an important role in climate science, particularly in terms of visualising spatial patterns and providing rainfall estimates at locations where there currently are no observations. Furthermore, regular estimates of rainfall in space and time are often required in ecosystem and hydrological modelling or used for validation exercises of numerical weather or climate models or climate models. Commonly, point measurements of rainfall are regionalised in space using some form of spatial interpolation. Various techniques are available and depending on the purpose of the interpolated product, different methods may be more or less suitable. The purpose of GAP (Geostatistical Analysis of Precipitation data) was to investigate and implement geostatistical tools for long term analysis of rainfall for the United Kingdom and the Iberian Peninsula. Geostatistics is an applied branch of spatial statistics, developed within the earth science community but now widely used within other environmental sciences. However, many of the tools developed within the framework of geostatistics are yet not commonly used within climate science despite the regular need for spatial regionalisation of meteorological variables. GAP provided an opportunity to explore the use of geostatistics to estimate rainfall for unsampled locations in space and time. The method chosen to regionalise rainfall for the study areas builds on the concept of stochastic simulation. This methodology represents a development within geostatistics that has become increasingly popular in earth sciences during the previous decade. The way in which is was implemented in GAP, presented two important qualities for spatial regionalisation of rainfall data, namely: (i) the possibility to make an assessment of uncertainty in each rainfall estimate due to the estimation process and (ii) the potential to draw upon information in the time domain in addition to the more commonly used space domain. These aspects of regionalisation are particularly important in regions were data are sparse and estimates can be very uncertain. Furthermore, the use of information in time showed to be important when analysing daily rainfall from the Iberian Peninsula, where spatial dependence in rainfall is very low.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
The spatial interpolation of precipitation is increasingly important in the development of agricultural, hydrological and ecological models. Such models are becoming an integral part of our ability to understand global climate change and both natural and anthropogenic impacts on the environment. For example, spatially explicit modelling of global climate change requires estimates of climate variables at unstapled locations, usually on a regularly spaced grid. In GAP, the fellow will develop a methodology to combine methods of multivariate geostatistics with rationalised climatologies in order to map the long-term (1960-2002) spatial variability in rainfall. Rainfall in two regions in Europe will be analysed for its long-term variation in the spatial distribution of rainfall and to consider the effect of sample network on these long-term patterns. Firstly, rainfall sample networks and patterns in the United Kingdom will be analysed because of the relatively dense, long-term and relatively static network of rainfall stations. A similar investigation will be conducted using rainfall data from the Iberian Peninsula. These regions have different climatologically characteristics that will also be compared as part of the investigation. This investigation is expected to improve the robustness in the representation of rainfall due to inclusion of more data sources and the possibility of identifying trends and shifts in spatial variation using the variables derived from the analysis.
Оригинален текст от CORDIS (на английски).
Участници
- UNIVERSITY OF EAST ANGLIA · NORWICHКоординаторОбединеното кралство
Връзки
Данни: CORDIS, © Европейски съюз