Spatially continuous dataset at local scale of Taita Hills in Kenya and Mount Kilimanjaro in Tanzania.

Autor: Mwalusepo S; icipe-African Insect Science for Food and Health, P.O. Box 30772-00100, Nairobi, Kenya; Department of General Studies, Dar es Salaam Institute of Technology, P.O. Box 2958, Dar es Salaam, Tanzania., Massawe ES; Department of M athematics, University of Dar es Salaam, P.O. Box 35062, Dar es Salaam, Tanzania., Johansson T; icipe-African Insect Science for Food and Health, P.O. Box 30772-00100, Nairobi, Kenya; Department of Geosciences and Geography, University of Helsinki, P.O. Box 68, FI-00014, Finland.
Jazyk: angličtina
Zdroj: Data in brief [Data Brief] 2016 Jul 26; Vol. 8, pp. 1115-9. Date of Electronic Publication: 2016 Jul 26 (Print Publication: 2016).
DOI: 10.1016/j.dib.2016.07.041
Abstrakt: 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 (TH)HOBO data loggers and rainfall was recorded daily using GENERAL(R) 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.
Databáze: MEDLINE