Increasing the maturity of measurements of essential climate variables (ECVs) at Italian atmospheric WMO/GAW observatories by implementing automated data elaboration chains
| Autor: | Eleonora Aruffo, Massimiliano Vardè, Piero Di Carlo, Giorgio Resci, Davide Putero, F. Roccato, Paolo Bonasoni, Angela Marinoni, Nicola Pirrone, Federico Dallo, Mariantonia Bencardino, Paolo Cristofanelli, Luca Naitza, Francescopiero Calzolari, Maurizio Busetto, Carlo Barbante, Damiano Sferlazzo, Francesco D'Amore, Jacopo Gabrieli, Francesca Sprovieri |
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| Přispěvatelé: | Naitza, L., Cristofanelli, P., Marinoni, A., Calzolari, F., Roccato, F., Busetto, M., Sferlazzo, D., Aruffo, E., Di Carlo, P., Bencardino, M., D'Amore, F., Sprovieri, F., Pirrone, N., Dallo, F., Gabrieli, J., Varde, M., Resci, G., Barbante, C., Bonasoni, P., Putero, D. |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
Traceability Process (engineering) Atmosphere Automatic processing Data analysis Data flagging Essential climate variables Settore GEO/12 - Oceanografia e Fisica dell'Atmosfera 02 engineering and technology 01 natural sciences Disk formatting Data file 0202 electrical engineering electronic engineering information engineering Data analysis Data flagging Atmosphere Essential climate variables Automatic processing Settore CHIM/01 - Chimica Analitica Computers in Earth Sciences 0105 earth and related environmental sciences business.industry Flagging 020206 networking & telecommunications Data analysi Data science Reference data 13. Climate action Environmental science Data center Raw data business Information Systems |
| Zdroj: | Computers & geosciences 137 (2020). doi:10.1016/j.cageo.2020.104432 info:cnr-pdr/source/autori:Naitza, Luca; Cristofanelli, Paolo; Marinoni, Angela; Calzolari, Francescopiero; Roccato, Fabrizio; Busetto, Maurizio; Sferlazzo, Damiano; Aruffo, Eleonora; Di Carlo, Piero; Bencardino, Mariantonia; D'Amore, Francesco; Sprovieri, Francesca; Pirrone, Nicola; Dallo, Federico; Gabrieli, Jacopo; Varde, Massimiliano; Resci, Giorgio; Barbante, Carlo; Bonasoni, Paolo; Putero, Davide/titolo:Increasing the maturity of measurements of essential climate variables (ECVs) at Italian atmospheric WMO%2FGAW observatories by implementing automated data elaboration chains/doi:10.1016%2Fj.cageo.2020.104432/rivista:Computers & geosciences/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume:137 |
| DOI: | 10.1016/j.cageo.2020.104432 |
| Popis: | In the framework of the National Project of Interest NextData, we developed automatic procedures for the flagging and formatting of trace gases, atmospheric aerosols and meteorological data to be submitted to the World Data Centers (WDCs) of the Global Atmosphere Watch program of the World Meteorological Organization (WMO/GAW). In particular, the atmospheric Essential Climate Variables (ECVs) covered in this work are observations of near-surface trace gas concentrations, aerosol properties and meteorological variables, which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG), the World Data Center for Reactive Gases, and the World Data Center for Aerosol (WDCRG and WDCA). We developed an overarching processing chain to create a number of data products (data files and reports) starting from the raw data, finally contributing to increase the maturity of these measurements. To this aim, we implemented specific routines for data filtering, flagging, format harmonization, and creation of data products, useful for detecting instrumental problems, particular atmospheric events and quick data dissemination towards stakeholders or citizens. Currently, the automatic data processing is active for a subset of ECVs at 5 measurement sites in Italy. The system represents a valuable tool to facilitate data originators towards a more efficient data production. Our effort is expected to accelerate the process of data submission to WMO/GAW or to other reference data centers or repositories. Moreover, the adoption of automatic procedures for data flagging and data correction allows to keep track of the process that led to the final validated data, and makes data evaluation and revisions more efficient by improving the traceability of the data production process. |
| Databáze: | OpenAIRE |
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