Downscaling global climate models statistically and generating projections of changes in precipitation and temperature at meteorological stations in Zambia
Date
2019
Authors
Chota, Monday
Journal Title
Journal ISSN
Volume Title
Publisher
The University of Zambia
Abstract
Zambia has been experiencing adverse impacts of climate change. Generation of climate
information about changes in future precipitation and temperature is useful in designing
adaptive measures. Currently, global climate models (GCMs) are primary tools utilized to
simulate the present and future climate under different greenhouse emission scenarios.
Owing to their coarse resolution of approximately 100 – 300 km per grid box, GCMs
outputs are not suitable for direct use in assessing climate change impacts and designing
adaptation strategies at local-scale. In this study, a statistical downscaling approach has been
used to downscale GCMs at meteorological station level in order to improve GCMs coarse
resolution to match with local needs for impact assessment. Further, the study used the
downscaled time series to generate projected changes in precipitation and temperature at
meteorological stations of Zambia for the period 2020 – 2049 relative to 1971 – 2000. A
non-parametric analogue method based on nearest neighbour was used to downscale daily
precipitation, minimum temperature and maximum temperature over 19, 13 and 11
meteorological stations, respectively, across Zambia from three GCMs: CanESM2, CNRMCM5
and MPI-ESM-MR under RCP4.5 and RCP8.5 emission scenarios. ERA-Interim
reanalysis and station datasets for a common period 1981 – 2010 were used to train the
downscaling model. Findings presented are based on the ensemble of models. The ensemble
mean at each station and local variable was computed from at least two GCMs with the
same sign of change. Minimum and maximum temperatures are projected to increase at
each meteorological station under both emission scenarios. The increase is higher towards
the south of Zambia and for emission scenario RCP8.5 as compared to RCP4.5 scenario.
Results also show decrease in precipitation over most stations in the Northern and Eastern
parts of the country, increase in the western and Southern parts and exhibit a mixed signal
for stations in the central part of the country. The downscaled precipitation and temperature
scenarios can be used as inputs in climate impact models such as crop and hydrological
models.
Key words: CMIP5 models, Statistical downscaling, Temperature, Precipitation, Climate
models, Representative concentration pathways
Description
Thesis
Keywords
Statistical downscaling--Zambia , Climate change--Zambia , Global climate models