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

IF 7.3 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Earths Future Pub Date : 2024-08-20 DOI:10.1029/2024EF004531
Leila Rahimi, Mushfiqul Hoque, Ebrahim Ahmadisharaf, Nasrin Alamdari, Vasubandhu Misra, Ana Carolina Maran, Shih-Chieh Kao, Amir AghaKouchak, Rocky Talchabhadel
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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.

Abstract Image

南佛罗里达未来气候预测:利用混合统计偏差校正技术提高气温和降水极端值的准确性
预测未来的气候变量对于了解洪水和干旱等水文气候灾害的潜在影响至关重要。由于全球气候模型(GCM)的空间分辨率较低,评估这些影响具有挑战性;因此,偏差校正被广泛使用。在此,我们采用了两种统计方法--标准经验量化绘图(EQM)和一种混合方法--EQM 与线性校正(EQM-LIN)--对九个 GCM 模拟的降水和气温进行了偏差校正。我们利用南佛罗里达州 20 个气象站的历史观测数据,预测了三种共同社会经济路径 (SSP) 下的未来气候。与 EQM 相比,混合 EQM-LIN 方法将历史时期每日定量值的 R2 提高了 30%,并将包含最多极端值的月份的 MAE 提高了 70%。气象站预测的极端降水量显示,与 EQM-LIN 方法相比,EQM 方法在 SSP585 中低估了高达 26% 的高定量值。从历史时期(1985-2014 年)到近期未来(2040-2069 年)和远期未来(2070-2100 年),整个研究区域的年最大降水量预计变化在 2% 到 16% 之间。预测的未来降水量表明,夏季降水量略有减少,但秋季降水量有所增加。这与夏季气温升高一起表明,在未来气候条件下,南佛罗里达州可能会经历夏季变暖和秋季洪水增加的快速波动。此外,我们与全球和国家降尺度研究的比较分析表明,这种粗尺度研究不能很好地代表极端气候,尤其是高量级降水。
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来源期刊
Earths Future
Earths Future ENVIRONMENTAL SCIENCESGEOSCIENCES, MULTIDI-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
11.00
自引率
7.30%
发文量
260
审稿时长
16 weeks
期刊介绍: Earth’s Future: A transdisciplinary open access journal, Earth’s Future focuses on the state of the Earth and the prediction of the planet’s future. By publishing peer-reviewed articles as well as editorials, essays, reviews, and commentaries, this journal will be the preeminent scholarly resource on the Anthropocene. It will also help assess the risks and opportunities associated with environmental changes and challenges.
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