Spatially Continuous Dataset at Local Scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania

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dc.creatorMwalusepo, Sizah
dc.creatorMassawe, Estomih S.
dc.creatorJohansson, Tino
dc.date2016-09-21T13:19:32Z
dc.date2016-09-21T13:19:32Z
dc.date2016
dc.date.accessioned2018-03-27T08:58:07Z
dc.date.available2018-03-27T08:58:07Z
dc.descriptionFull text can be accessed at http://www.sciencedirect.com/science/article/pii/S2352340916304772
dc.descriptionClimate change is a global concern, requiring local scale spatially continuous dataset and modeling of meteorological variables. This dataset article provided the interpolated temperature, rainfall and relative humidity dataset at local scale along Taita Hills and Mount Kilimanjaro altitudinal gradients in Kenya and Tanzania, respectively. The temperature and relative humidity were recorded hourly using automatic onset THHOBO data loggers and rainfall was recorded daily using GENERALR wireless rain gauges. Thin plate spline (TPS) was used to interpolate, with the degree of data smoothing determined by minimizing the generalized cross validation. The dataset provide information on the status of the current climatic conditions along the two mountainous altitudinal gradients in Kenya and Tanzania. The dataset will, thus, enhance future research.
dc.identifierMwalusepo, S., Massawe, E.S. and Johansson, T., 2016. Spatially continuous dataset at local scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania. Data in Brief.
dc.identifierhttp://hdl.handle.net/20.500.11810/3918
dc.identifier10.1016/j.dib.2016.07.041
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3918
dc.languageen
dc.publisherElsevier
dc.subjectSpatial climate data
dc.subjectClimate change
dc.subjectModeling
dc.subjectLocal scale
dc.titleSpatially Continuous Dataset at Local Scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania
dc.typeJournal Article, Peer Reviewed

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