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  2. Landsurf _DSS_Data
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    Datenpaket: Landsurf _DSS_Data

    • RADAR-Metadaten
    • Inhalt
    • Statistiken
    • Technische Metadaten
    Alternativer Identifier:
    -
    Verwandter Identifier:
    (Has Part) 10.58160/HOBXTixmJqWfjLsy - DOI
    (Has Part) 10.58160/wqerBcsyattflLoo - DOI
    (Has Part) 10.58160/vTitxyotGxxOwJXW - DOI
    (Has Part) 10.58160/iJVlXzdTsfivPBvX - DOI
    (Has Part) 10.58160/gTowILLpbwCNbQYy - DOI
    (Has Part) 10.58160/cEmyHYpGbShOetmD - DOI
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    (Has Part) 10.58160/SeqHBcLFsrsWiXge - DOI
    (Has Part) 10.58160/ueNWdUycboiRsAYJ - DOI
    (Has Part) 10.58160/LqTXciPRIYNqJgQi - DOI
    (Has Part) 10.58160/BlpSkbdGcDvQiMPW - DOI
    (Has Part) 10.58160/bJKoWzXDNvFaNZsD - DOI
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    (Has Part) 10.58160/cICtifUShmpIAMrH - DOI
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    (Has Part) 10.58160/YNxWmtEcvCLMQeaH - DOI
    (Has Part) 10.58160/KTlWPDPJrSDKWghL - DOI
    (Has Part) 10.58160/zzsozuQkKXkJwcuc - DOI
    (Has Part) 10.58160/FDAfqNQSbLrWXzVZ - DOI
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    (Has Part) 10.58160/EZboJZoQxaASWQbN - DOI
    (Has Part) 10.58160/FAsRwvhTTlbuABUB - DOI
    (Has Part) 10.58160/SHIvqfscxoITjPZS - DOI
    (Has Part) 10.58160/ptCnKABhxaMOrAgO - DOI
    (Has Part) 10.58160/HcEuxFDJqwOtUGxg - DOI
    (Has Part) 10.58160/UrTvtQJgaffpNSLp - DOI
    (Has Part) 10.58160/HBTRXaNJWwvbTNID - DOI
    (Has Part) 10.58160/QjaUaexUNxushvDa - DOI
    (Is Supplemented By) 10.58160/yPtjnpXSLeXKdgBl - DOI
    (Is Supplemented By) 10.58160/dbplhSwMgPrKwjCM - DOI
    (Is Supplemented By) 10.58160/aQJwqxSYPHAyDBNz - DOI
    (Is Supplemented By) 10.58160/gVFecIBpNdRbDiZk - DOI
    Ersteller/in:
    Ziegler, Katrin https://orcid.org/0000-0002-9152-3135 [Ziegler, Katrin]

    Abel, Daniel https://orcid.org/0000-0001-9663-3248 [Abel, Daniel]

    Otte, Insa https://orcid.org/0000-0001-9704-9668 [Otte, Insa]
    Beitragende:
    (Project Leader)
    Paeth, Heiko https://orcid.org/0000-0001-8145-4706 [Paeth, Heiko]
    Titel:
    Landsurf _DSS_Data
    Weitere Titel:
    (Alternative Title) DSS Data of https://landsurf.geo.uni-halle.de/
    Beschreibung:
    (Abstract) The dataset contains a wide range of climatological, agrometeorological, and remote sensing indices of West Africa for 1981-2100. The climatological and agrometeorlogical index calculation is based on global and regional climate models from CMIP5 and CORDEX-CORE, respectively, and covers the period... The dataset contains a wide range of climatological, agrometeorological, and remote sensing indices of West Africa for 1981-2100. The climatological and agrometeorlogical index calculation is based on global and regional climate models from CMIP5 and CORDEX-CORE, respectively, and covers the period 1981-2100. For the future, a low (RCP2.6) and a high (RCP8.5) greenhouse gas emission scenario are used. A total of 25 indices can be divided into five groups with a focus (1) temperature, (2) precipitation, (3) rainy season, (4) agriculture, and (5) drought. An overview of all indices can be found in the documentation. Temperature indices contain threshold- and percentile-based indices from the ETCCDI as well as heatwave indices. Precipitation indices are taken from the ETCCDI as well. The rainy season is determined based on Liebmann et al. (2016), enabling the identification of a first and a second rainy season. The resulting rainy season mask was used for some of the ETCCDI indices and for calculating the respective onset and cessation days. The agricultural indices depend on the rainy season onset, plant specific crop parameters, and related temperatures and precipitation. In this dataset, three indices of four different plant phases for twelve different crops (Barley_Oats_Wheat_S, Barley_Oats_Wheat_L, Maize_grain_S, Maize_grain_L, Maize_sweet_S, Maize_sweet_L, Millet_S, Millet_L, Sorghum_S, Sorghum_L, Soybean_S, Soybean_L) are available. Drought indices contain SPI and SPEI for four different accumulation time periods. A validation of the climate models in representing the selected precipitation, rainy season, and agricultural indices during 1981-2010 is available by Abel et al. (2024). This reference also describes the calculation of the rainy season mask and the agricultural indices in more detail. The presented remote sensing indicators are based on MODIS and AVHRR data. The data was developed in the frame of the WASCAL WRAP2.0 project LANDSURF. We acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modelling groups for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure.

    The dataset contains a wide range of climatological, agrometeorological, and remote sensing indices of West Africa for 1981-2100. The climatological and agrometeorlogical index calculation is based on global and regional climate models from CMIP5 and CORDEX-CORE, respectively, and covers the period 1981-2100. For the future, a low (RCP2.6) and a high (RCP8.5) greenhouse gas emission scenario are used. A total of 25 indices can be divided into five groups with a focus (1) temperature, (2) precipitation, (3) rainy season, (4) agriculture, and (5) drought. An overview of all indices can be found in the documentation. Temperature indices contain threshold- and percentile-based indices from the ETCCDI as well as heatwave indices. Precipitation indices are taken from the ETCCDI as well. The rainy season is determined based on Liebmann et al. (2016), enabling the identification of a first and a second rainy season. The resulting rainy season mask was used for some of the ETCCDI indices and for calculating the respective onset and cessation days. The agricultural indices depend on the rainy season onset, plant specific crop parameters, and related temperatures and precipitation. In this dataset, three indices of four different plant phases for twelve different crops (Barley_Oats_Wheat_S, Barley_Oats_Wheat_L, Maize_grain_S, Maize_grain_L, Maize_sweet_S, Maize_sweet_L, Millet_S, Millet_L, Sorghum_S, Sorghum_L, Soybean_S, Soybean_L) are available. Drought indices contain SPI and SPEI for four different accumulation time periods. A validation of the climate models in representing the selected precipitation, rainy season, and agricultural indices during 1981-2010 is available by Abel et al. (2024). This reference also describes the calculation of the rainy season mask and the agricultural indices in more detail. The presented remote sensing indicators are based on MODIS and AVHRR data. The data was developed in the frame of the WASCAL WRAP2.0 project LANDSURF. We acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modelling groups for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure.

    Zeige alles Zeige Markdown
    Schlagworte:
    Africa
    temperature
    precipitation
    crop
    vegetation
    irrigation
    drought
    rainy season
    Zugehörige Informationen:
    -
    Sprache:
    Englisch
    Herausgeber/in:
    University of Würzburg
    Erstellungsjahr:
    2021-2024
    Fachgebiet:
    Geography
    Objekttyp:
    Dataset
    Datenquelle:
    -
    Verwendete Software:
    -
    Datenverarbeitung:
    -
    Erscheinungsjahr:
    2024
    Rechteinhaber/in:
    Ziegler, Katrin https://orcid.org/0000-0002-9152-3135

    Abel, Daniel https://orcid.org/0000-0001-9663-3248

    Otte, Insa https://orcid.org/0000-0001-9704-9668

    Paeth, Heiko https://orcid.org/0000-0001-8145-4706

    Thiel, Michael https://orcid.org/0000-0001-8350-0841
    Förderung:
    Federal Ministry of Education and Research - (Verbundprojekt WASCAL WRAP 2.0) 01LG2080A
    Zeige alles Zeige weniger
    Name Speichervolumen Metadaten Upload Aktion
    Status:
    Publiziert
    Eingestellt von:
    dd7b509482ad0a11773b217cbbcdf32f
    Erstellt am:
    2024-07-17
    Archivierungsdatum:
    2024-09-24
    Archivgröße:
    1,7 MB
    Archiversteller:
    851297a882a1411f214c593698f6a7b2
    Archiv-Prüfsumme:
    ebc7490bd540682720549509a1f7295b (MD5)
    Embargo-Zeitraum:
    -
    DOI: 10.58160/gGzexcbDikobkyvK
    Publikationsdatum: 2024-09-24
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    Dieses Werk ist lizenziert unter
    CC BY-NC-SA 4.0
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    Datenpaket zitieren
    Ziegler, Katrin; Abel, Daniel; Otte, Insa (2024): Landsurf _DSS_Data. University of Würzburg. DOI: 10.58160/gGzexcbDikobkyvK
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