Abstract
Spatio-temporal variations and trends in climatic variables play an essential role in the adaptation and mitigation of climate change policy. This study analyzed spatial and temporal variability of annual and seasonal rainfall in Ho Chi Minh City based on non-parametric statistical trend tests and spatial interpolation techniques. In particular, Sen’s Slope Estimator and Inverse Distance Weighting (IDW) methods were applied to construct the spatial distribution of annual and seasonal rainfall over the city. The outcomes show that annual and seasonal rainfall experienced significant increasing trends. Generally, these findings draw out an overall picture of rainfall variability in terms of space and time, which makes it possible for local decision-makers to promote more promising action plans in order to respond to natural disasters in the context of climate change.
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