Seasonal forecasting and health impact models: challenges and opportunities
Seasonal forecasting and health impact models: challenges and opportunities
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DOI：
10.1111/nyas.13129
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发表时间：
2016-01-01
期刊：
影响因子：
--
通讯作者：
Rodo, Xavier
中科院分区：
文献类型：
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作者：
Ballester, Joan;Lowe, Rachel;Rodo, Xavier
经过几十年的深入研究，对气候系统的理解和建模不断改进，导致了气候服务时代第一代可操作的健康预警系统的开发。这些计划基于跨学科的合作，汇集了实时气候和健康数据收集，最先进的季节性气候预测，基于历史数据的流行病学影响模型，以及对最终用户和利益相关者需求的理解。在这篇综述中，我们讨论了这种复杂的多学科合作的挑战和机遇，重点是限制季节性预测作为气候影响模型可预测性来源的因素。
After several decades of intensive research, steady improvements in understanding and modeling the climate system have led to the development of the first generation of operational health early warning systems in the era of climate services. These schemes are based on collaborations across scientific disciplines, bringing together real-time climate and health data collection, state-of-the-art seasonal climate predictions, epidemiological impact models based on historical data, and an understanding of end user and stakeholder needs. In this review, we discuss the challenges and opportunities of this complex, multidisciplinary collaboration, with a focus on the factors limiting seasonal forecasting as a source of predictability for climate impact models.