Spatially Continuous Dataset at Local Scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Climate 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.
Description
Full text can be accessed at
http://www.sciencedirect.com/science/article/pii/S2352340916304772
Keywords
Spatial climate data, Climate change, Modeling, Local scale
Citation
Mwalusepo, 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.