Automatic Weather Station Data Tool (ADT) Installation and Training at ANACIM

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cg.contributor.affiliationInternational Research Institute for Climate and Societyen
cg.contributor.donorWorld Banken
cg.coverage.countrySenegal
cg.coverage.iso3166-alpha2SN
cg.coverage.regionAfrica
cg.coverage.regionWestern Africa
cg.creator.identifierJames Hansen: 0000-0002-8599-7895en
dc.contributor.authorFaniriantsoa, Rijaen
dc.contributor.authorHansen, Jamesen
dc.date.accessioned2023-01-05T19:38:45Zen
dc.date.available2023-01-05T19:38:45Zen
dc.identifier.urihttps://hdl.handle.net/10568/126633
dc.titleAutomatic Weather Station Data Tool (ADT) Installation and Training at ANACIMen
dcterms.abstractThe recent expansion of meteorological observation networks has focused on the use of Automatic Weather Stations (AWS). Automatic Weather Stations offer a number of advantages including automated reporting at a very fine temporal resolution (15 minutes on average). The challenge many National Meteorological Services (NMS) have been facing with the exploitation of AWS data is that different initiatives and donors have been providing different types of AWS from different vendors, leading to different AWS systems and networks. The data collected by these different AWS systems are in different formats and may sit on different computers. Although there are applications that come with each AWS network to access and visualize AWS data, access to the data is still done manually and station by station. This complicates data access, processing, and use. In addition, data from the different AWS networks is in different formats, which makes it even more difficult to analyze all the data without additional tools or applications that can convert the data into a common format and combine the data from the different networks. As a result, accessing, processing, and using these data has been a major impediment to the use of data from these varieties of AWS.en
dcterms.accessRightsOpen Access
dcterms.audienceScientistsen
dcterms.bibliographicCitationFaniriantsoa R, Hansen J. 2022. Automatic Weather Station Data Tool (ADT) Installation and Training at ANACIM. AICCRA Workshop Report. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA).en
dcterms.extent12 p.en
dcterms.issued2022-12en
dcterms.languageen
dcterms.licenseCC-BY-NC-4.0
dcterms.publisherAccelerating Impacts of CGIAR Climate Research for Africaen
dcterms.subjectagricultureen
dcterms.subjectclimate-smart agricultureen
dcterms.subjectclimate changeen
dcterms.subjectweatheren
dcterms.typeReport

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