Multivariate bias‐correction of high‐resolution regional climate change simulations for West Africa : performance and climate change implications
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | e2021JD034836 |
Journal / Publication | Journal of Geophysical Research: Atmospheres |
Volume | 127 |
Issue number | 5 |
Online published | 13 Feb 2022 |
Publication status | Published - 16 Mar 2022 |
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DOI | DOI |
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85126647644&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(636b319c-23c4-41dc-b2ed-0c34ed049b61).html |
Abstract
A Multivariate Bias Correction based on N-dimensional Probability Density Function transform (MBCn) technique is applied to four different high-resolution regional climate change simulations and key meteorological variables, namely precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling solar radiation, relative humidity, and wind speed. The impact of bias-correction on the historical (1980-2005) period, the inter-variable relationships, and the measures of spatio-temporal consistency are investigated. The focus is on the discrepancies between the original and the bias-corrected results over five agro-ecological zones. We also evaluate relevant indices for agricultural applications such as climate extreme indices, under current and future (2020-2050) climate change conditions based on the RCP4.5. Results show that MBCn successfully corrects the seasonal biases in spatial patterns and intensities for all variables, their intervariable correlation, and the distributions of most of the analyzed variables. Relatively large bias reductions during the historical period give indication of possible benefits of MBCn when applied to future scenarios. Although the four RCMs do not agree on the same positive/negative sign of the change of the seven climate variables for all grid points, the model ensemble mean shows a statistically significant change in rainfall, relative humidity in the Northern zone and wind speed in the Coastal zone of West Africa and increasing maximum summer temperature up to 2°C in the Sahara.
Research Area(s)
- A multivariate bias correction (MBCn)onal climate simulations, Climate extreme indices, High-resolution regional climate change simulations, The bias correction is found to influence the probability of extreme events, The model ensemble mean shows a statistically significant change, West Africa
Citation Format(s)
Multivariate bias‐correction of high‐resolution regional climate change simulations for West Africa: performance and climate change implications. / Dieng, Diarra; Cannon, Alex J.; Laux, Patrick et al.
In: Journal of Geophysical Research: Atmospheres, Vol. 127, No. 5, e2021JD034836, 16.03.2022.
In: Journal of Geophysical Research: Atmospheres, Vol. 127, No. 5, e2021JD034836, 16.03.2022.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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