Examining the Impact of Bias Correction on the Prediction Skill of Regional Climate Projections
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
Atmospheric and Climate Sciences
Abstract
Rainfall is crucial for many applications e.g. agriculture, health, water resources,
energy among many others. However, quantitative rainfall estimation
is normally a challenge especially in areas with sparse rain gauge network.
This has introduced uncertainties in rainfall projections by climate
models. This study evaluates the performance of three representative concentration
pathways, RCP i.e. 4.5, 6.0 and 8.5 over Uganda using the Weather
Research and Forecasting (WRF) model. It evaluates the model output using
observed daily rain gauge data over the period 2006-2018 using Pearson correlation;
relative root mean square error; relative mean error and skill scores
(accuracy). It also evaluates the potential improvement in the performance of
the WRF model with respective RCPs by applying bias correction. The bias
correction is carried out using the quantile mapping method. A poor correlation
with observed rainfall is generally found (−0.4 to +0.4); error magnitudes
in the ranges of 1 to 3.5 times the long-term mean are observed. The RCPs
presented different performances over different areas suggesting that no one
RCP is universally valid. Application of bias correction did not produce realistic
improvement in performance. Largely, the RCPs underestimated rainfall
over the study area suggesting that the projected rainfall cases under these
RCPs could be seriously underestimated. However, the study found RCP8.5
with slightly better performance and is thus recommended. Due to the general
weak performance of the RCPs, the study recommends re-evaluating the
assumptions under the RCPs for different regions or attempt to improve
them using data assimilation.
Description
Keywords
Representative Concentration Pathways, WRF Model, Rainfall Projections
Citation
Mugume, I., Ngailo, T. and Semyalo, R. (2020) Examining the Impact of Bias Correction on the Prediction Skill of Regional Climate Projections. Atmospheric and Climate Sciences , 10, 573-596. https://doi.org/10.4236/acs.2020.104030