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Cumulonimbus cloud detection with weather radar at Helsinki-Vantaa airport

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dc.date.accessioned 2021-04-14T12:24:17Z
dc.date.available 2021-04-14T12:24:17Z
dc.date.issued 2021-04-14
dc.identifier.uri http://hdl.handle.net/123456789/35140
dc.title Cumulonimbus cloud detection with weather radar at Helsinki-Vantaa airport en
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingin yliopisto fi
ethesis.university University of Helsinki en
ethesis.university Helsingfors universitet sv
dct.creator Tuomola, Laura
dct.issued 2021
dct.language.ISO639-2 eng
dct.abstract Cumulonimbus (Cb) clouds form a serious threat to aviation as they can produce severe weather hazards. Therefore, it is important to detect Cb clouds as well as possible. Finnish Meteorological Institute (FMI) provides aeronautical meteorological services in Finland, including METeorological Aerodrome Report (METAR). METAR describes weather at the aerodrome and its vicinity. Significant weather is reported in METARs, and therefore Cb clouds must be included in it. At Helsinki-Vantaa METARs are done manually by human observer. Sometimes Cb detection can be more difficult, for example, when it is dark, and it is also expensive to have human observers working around the clock all year round. Therefore, automation of Cb detection is a topical matter. FMI is applying an algorithm that uses weather radar observations to detect Cb clouds. This thesis studies how well the algorithm can detect Cb clouds compared to manual observations. The dataset used in this thesis contains summer months (June, July and August) from 2016 to 2020. Various verification scores can be calculated to analyse the results. In addition, daytime and night-time differences are calculated as well as different years and months are compared together. The results show that the algorithm is not adequate to replace human observers at Helsinki-Vantaa. However, the algorithm could be improved, for instance, by adding satellite observations to improve detection accuracy. en
dct.subject Meteorology
dct.subject cumulonimbus
dct.subject radar
dct.language en
ethesis.isPublicationLicenseAccepted true
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language englanti fi
ethesis.language English en
ethesis.language engelska sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.ethesis E-thesisID:f6d8f620-6291-4fb3-ab58-85e4ff355d46
dct.identifier.urn URN:NBN:fi:hulib-202104141887
dc.type.dcmitype Text
dct.alternative Cumulonimbus pilvien tunnistaminen säätutkalla Helsinki-Vantaan lentokentällä fi
ethesis.facultystudyline Meteorologia fi
ethesis.facultystudyline Meteorology en
ethesis.facultystudyline Meteorologi sv
ethesis.facultystudyline.URI http://data.hulib.helsinki.fi/id/SH50_049
ethesis.mastersdegreeprogram Ilmakehätieteiden maisteriohjelma fi
ethesis.mastersdegreeprogram Master's Programme in Atmospheric Sciences en
ethesis.mastersdegreeprogram Magisterprogrammet i atmosfärsvetenskaper sv
ethesis.mastersdegreeprogram.URI http://data.hulib.helsinki.fi/id/MH50_006

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