Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Rahimi, Leila, Hoque, Mushfiqul, Ahmadisharaf, Ebrahim, Alamdari, Nasrin, Misra, Vasubandhu, Maran, Ana Carolina, Kao, Shih‐Chieh, AghaKouchak, Amir and Talchabhadel, Rocky, (2024). Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique. Earth's Future, 12(8), e2024EF004531-n/a

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  • Sub-type Journal article
    Author Rahimi, Leila
    Hoque, Mushfiqul
    Ahmadisharaf, Ebrahim
    Alamdari, Nasrin
    Misra, Vasubandhu
    Maran, Ana Carolina
    Kao, Shih‐Chieh
    AghaKouchak, Amir
    Talchabhadel, Rocky
    Title Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique
    Appearing in Earth's Future
    Volume 12
    Issue No. 8
    Publication Date 2024-08-20
    Place of Publication Florida
    Publisher AGU
    Start page e2024EF004531
    End page n/a
    Language eng
    Abstract Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.
    Copyright Holder author(s)
    Copyright Year 2024
    Copyright type Creative commons
    DOI https://doi.org/10.1029/2024EF004531
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    Created: Mon, 21 Oct 2024, 04:45:26 JST by Haideh Beigi on behalf of UNU INWEH