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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >Assessment of uncertainty in multi-model means of downscaled South Florida precipitation for projected (2019-2099) climate
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Assessment of uncertainty in multi-model means of downscaled South Florida precipitation for projected (2019-2099) climate

机译:计算南部佛罗里达州较低南部佛罗里达州的多模型手段的不确定性评估(2019-2099)气候

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South Florida resource management, particularly the Everglades restoration effort, is beginning to consider projections of precipitation from multiple climate models for decision-making. Because precipitation changes can significantly affect the Everglades ecosystem, characterization of precipitation projection uncertainty is important for resource management decisions, and reduction of uncertainty is desired for better decision-making. Though uncertainty of precipitation projections has been characterized for many regions, uncertainty has not been sufficiently quantified for South Florida. This study builds upon prior results for projected Florida precipitation by considering recent climate model simulations, seasonal and spatial information, and uncertainty quantification and reduction. We identify the multi-model mean change in South Florida precipitation and characterize the uncertainty of 37 statistically downscaled Coupled Model Intercomparison Project Phase 5 models. For 2019-2045, there is a likely (over 60% of ensemble members) increase in South Florida annual mean precipitation owing to a likely to very likely (near 90% of ensemble members) increase in dry season (November, December, and January) precipitation, while wet season (June, July, and August) shows a more likely than not (over 50% of ensemble members) decrease in precipitation in the southern region and increase in precipitation in the northern region of South Florida. As South Florida agencies are on the verge of including precipitation projections in their upcoming planning horizon, this information will aid South Florida climate data users in decisions influenced by future rainfall.
机译:南佛罗里达资源管理,特别是沼泽地恢复努力,开始考虑从多种气候模型进行降水的预测。由于降水变化可以显着影响大沼泽地生态系统,所以降水投影不确定性的表征对于资源管理决策是重要的,并且需要更好地决策的不确定性的降低。虽然降水投影的不确定性已经表现了许多地区,但对于南佛罗里达州来说,不确定度并未充分量化。本研究通过考虑最近的气候模型模拟,季节性和空间信息以及不确定量化和减少来实现预测的佛罗里达州降水的结果。我们确定南佛罗里达州南部降水的多模型平均变化,并表征了37个统计上较低的耦合模型相互熟练项目第5款的不确定性。对于2019 - 2019-2045,有可能(超过60%的集合成员)南佛罗里达州年平均降水量由于可能(近90%的集成会员)旱季(十二月,12月和1月)增加)降水,而潮湿的季节(六月,7月和8月)表现出比没有(超过50%的集合成员)南部地区降水减少,南部佛罗里达州北部地区的降水量增加。随着南佛罗里达州代理商在其即将到来的规划地平线中包括降水预测,这些信息将帮助南佛罗里达州气候数据用户在未来降雨的决策中受到决定。

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