What is it about?

Biases in climatic data are deviation of GCM output from the observed time series data.

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Why is it important?

Correcting and accounting for biases in climate model output is vital in producing reliable climate model simulations

Perspectives

Three methods (change factor, bias correction and quantile mapping) were used to correct for bias in precipitation and temperature. Each method gave different outputs. Bias correction methods differ considerably and can influence the expected local scale or regional climate impacts of climate change.

Mr Charles Bwalya Chisanga
University of Zambia

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This page is a summary of: Statistical Bias Correction of Fifth Coupled Model Intercomparison Project Data from the CGIAR Research Program on Climate Change, Agriculture and Food Security - Climate Portal for Mount Makulu, Zambia, British Journal of Applied Science & Technology, January 2017, Sciencedomain International, DOI: 10.9734/bjast/2017/33531.
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