通过预测海面温度的光谱变换进行十年干旱预测

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Ze Jiang, Ashish Sharma
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引用次数: 0

摘要

了解即将到来的干旱对水资源规划和管理有很大帮助。本文介绍了一种新的年代际干旱预测框架,该框架依赖于气候模式对未来十年的海表温度异常(SSTA)指数的预测和光谱变换方法,以最大限度地提高预测技能。年代际气候预测项目(DCPP)的年代际海温预估采用小波系统预测(WASP)进行光谱变换。WASP通过调节预测变量的频谱,更好地模拟干旱指数的响应谱。然后将转换后的SSTA指数用于多元线性回归(MLR)模型中,对多个时间尺度的干旱指数进行预测。这一框架大大提高了干旱预测技能,特别是提前期超过24个月的预测技能。虽然在澳大利亚得到了示范,但MLR-WASP框架可转移到其他地区,通过预测未来十年的干旱风险,为长期水资源管理提供可靠的工具。这项研究的意义超出了水文气候学,影响了环境科学与工程、可持续规划和适应气候变化的努力。预测未来十年的干旱风险对于有效的长期水资源管理至关重要。这项研究提出了一个新的框架,通过优化年代际气候模型数据,可靠地预测未来10年的干旱条件。它使用光谱转换技术来调整海面温度异常等预测指标,以更好地匹配干旱模式。然后将这些转换后的预测因子整合到回归模型中来预测干旱指数。当应用于澳大利亚时,该方法明显优于现有方法,特别是对于2年预测。通过将先进的气候预测与以预测为导向的数据转换相结合,该框架能够实现可靠的十年后干旱风险预测,为全球干旱易发地区的主动规划提供宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Decadal drought prediction via spectral transformation of projected Sea Surface Temperatures

Decadal drought prediction via spectral transformation of projected Sea Surface Temperatures
Knowledge of impending drought can help significantly with water planning and management. This study introduces a novel forecasting framework for decadal drought projection which relies on climate model projections of Sea Surface Temperature Anomaly (SSTA) indices over the next decade and a spectral transformation methodology to maximise forecast skill. Decadal SSTA projections from the Decadal Climate Prediction Project (DCPP) undergo spectral transformation using Wavelet System Prediction (WASP). WASP modulates the frequency spectrum of predictor variables to better mimic the response spectrum of drought indices. The transformed SSTA indices are then used in a multiple linear regression (MLR) model to forecast drought indices across multiple time scales. This framework significantly improves drought forecasting skills, especially for lead times exceeding 24 months. While demonstrated for Australia, the MLR-WASP framework is transferable to other regions, offering a reliable tool for long-term water resource management by projecting drought risk over the coming decade. The implications of this research extend beyond hydroclimatology, impacting environmental science and engineering, sustainable planning, and adaptation efforts to climate change.

Plain language summary

Projecting drought risk over the next decade is essential for effective long-term water resources management. This study presents a new framework that reliably projects drought conditions up to 10 years ahead by optimizing decadal climate model data. It uses a spectral transformation technique to adjust predictors like Sea Surface Temperature Anomalies to better match drought patterns. These transformed predictors are then integrated into a regression model to forecast drought indices. When applied to Australia, this approach significantly outperformed existing methods, especially for 2-year forecasts. By combining advanced climate predictions with prediction-oriented data transformation, this framework enables reliable drought risk projections a decade out, offering invaluable insights for proactive planning in drought-prone regions worldwide.
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来源期刊
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
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