Mashing-Up Weather Networks Data to Support Hydro-Meteorological Research

Mashing-Up Weather Networks Data to Support Hydro-Meteorological Research

Tatiana Bedrina (CIMA Research Foundation, Savona, Italy), Antonio Parodi (CIMA Research Foundation, Savona, Italy), Andrea Clematis (Institute of Applied Mathematics and Information Technology, National Research Council, Genoa, Italy) and Alfonso Quarati (Institute of Applied Mathematics and Information Technology, National Research Council, Genoa, Italy)
DOI: 10.4018/978-1-4666-4490-8.ch023
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The use of Web technologies for the collection and visualization of geoscentific data has significantly increased the availability of free sensor data over the Internet. This work aims at designing a Web mashup for the aggregation of meteorological variables (precipitation, humidity, pressure, etc.) published on the Web by several weather networks and the rendering of query results through a graphic interface in a homogeneous way. The mashup approach is particularly suitable to provide an easy to develop and quickly deployed application capable to support HM scientists in their everyday activity. As a significant case study of the adoption of the tool, the authors consider the severe flash-flood event that occurred in fall 2011 in the Liguria region, Italy. To this end, they base their analysis on the aggregated rainfall data observed by an official and a personal weather network.
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It Solutions To Hmr Needs

In 2010, as a major activity of the DRHIMS project (, a series of web polls in the HMR and ICT communities were conducted aimed at better understanding the existing gap between HMR requirements and ICT offer. The HMR polls registered a total amount of 182 answers and the ICT near 100. Amongst the main observations, the analysis of the questionnaires1 revealed data-related issues such as: interoperability (models, formats, metadata, etc.); availability; extensiveness (amount and size of data). This is well testified, for example by the answers to one of the “hot topic” HMR questions: “Rank (in a 5 point scale) the importance to have easy access to data in formats that are easy to handle”. The average result (4.28) testifies the degree of awareness between HM researchers, about the need of tools to tackle data access issues. Moreover, the analysis also pointed out the lack of commonly accepted tools for interchanging and merging scientific data from different sources and of common libraries for processing and visualizing scientific data and metadata. From this survey clearly emerged the urgency to develop IT initiatives and tools enabling rapid data discovery from different sources, from satellites to Personal Weather Stations (PWS), their collection and the development of functionalities to homogenize, compare and visualize these datasets.

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