Evaluation of the performance of CORDEX regional climate models in simulating present climate conditions of Tanzania
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Date
2016-06
Journal Title
Journal ISSN
Volume Title
Publisher
ResearchGate
Abstract
Regional climate models (RCMs) are widely used in regional assessment of
climate change impacts. However, the reliability of individual models needs to
be assessed before using their output for impact assessment. In this study, we
evaluate the performance of RCMs from the Coordinated Regional Climate
Downscaling Experiment program (CORDEX) to simulate minimum air temperature (TN), maximum air temperature (TX) and rainfall over Tanzania. Output from four RCMs driven by boundary conditions from three General Circulation Models (GCMs) and ERA-Interim data are evaluated against observed data
from 22 weather stations. The evaluation is based on determining how well the
RCMs reproduce climatological trends, interannual, and annual cycles of TN,
TX and rainfall. Statistical measures of model performance that include the bias,
root mean square error, correlation and trend analysis are used. It is found that
RCMs capture the annual cycle of TN, TX and rainfall well, however underestimate and overestimate the amount of rainfall in March–April–May (MAM)
and October–November–December (OND) seasons respectively. Most RCMs
reproduce interannual variations of TN, TX and rainfall. The source of uncertainties can be analysed when the same RCM is driven by different GCMs and
different RCMs driven by same GCM simulate TN, TX and rainfall differently.
It is found that the biases and errors from the RCMs and driving GCMs contribute roughly equally. Overall, the evaluation finds reasonable (although variable) model skill in representing mean climate, interannual variability and temperature trends, suggesting the potential use of CORDEX RCMs in simulating
TN, TX and rainfall over Tanzania.
Description
Journal article
Keywords
CORDEX models for Tanzania, climate models, climate conditions, agricultural systems, Global Climate Models, Regional climate models