Boosting meterological statistics and analysis with big data assimilation: clusterization of a large amount of weather data

For a meterological monitoring center, it’s very important the presence of an archive with meteorological data of the past that is however continuously updated with new data added daily and hourly. This data is fundamentally used to make analysis and statistics about old events and not simply for meteorological forecasting. Storing a huge quantity of data with an usual relational database is obviously possible but more data is stored more time is necessary in order that the query, used to retrieve requested information, has been elaborated. We firstly present an analysis of the database used nowadays by a meterological monitoring center both the same database with more stored data in order to make a prediction of the future situation about the response time, secondly we consider a Big Data structure and we propose a solution to improve the response time, comparing the previous situation based on a relational database with the system based on NOSQL.