Publication Type
Journal Article
Journal Name
Data in Brief
Publication Date
9-1-2016
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.
Keywords
Climate change, Local scale, Modeling, Spatial climate data
Recommended Citation
Mwalusepo, S., Massawe, E., & Johansson, T. (2016). Spatially continuous dataset at local scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania. Data in Brief, 8, 1115-1119. https://doi.org/10.1016/j.dib.2016.07.041