Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States
Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States
复制标题
受美国本土降水观测约束的气候模型预测的贝叶斯模型平均
DOI：
10.1175/jhm-d-19-0258.1
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发表时间：
2020
影响因子：
3.8
通讯作者：
D. Waliser
中科院分区：
文献类型：
--
作者：
E. Massoud;Huikyo Lee;P. Gibson;P. Loikith;D. Waliser
本研究利用贝叶斯模式平均（BMA）作为框架来限制美国相邻地区（CONUS）降水气候预估中不确定性的传播。我们使用了来自耦合模式比较项目第5阶段（CMIP5）的历史模式模拟和未来模式预测（RCP8.5）的子集。我们利用NASA热带降雨测量任务（TRMM）卫星的观测资料评估了历史模拟中五个降水概要指标的代表性。摘要指标包括平均、年际和年际变率，以及降水极端值的最大值和最小值。利用BMA估算的模式平均值在模拟平均降雨量方面比综合平均值具有更高的精度（BMA的RMSE为0.49，而综合平均值的RMSE为0.65），并且与多模式综合相比，不确定性的分布更受约束，约占总不确定性的三分之一。结果表明，到本世纪末，预计美国东海岸和西北部大部分地区的日平均降雨量将增加，美国南部可能减少，西南部预计变化不大。在极端情况下，预计在CONUS的大部分地区，有史以来最潮湿的年份将变得更潮湿，而最干燥的年份将变得更干燥。我们表明，BMA提供了一个框架，可以更准确地估计和限制未来气候不确定性的传播，如CONUS上的降水变化。
This study utilizes Bayesian model averaging (BMA) as a framework to constrain the spread of uncertainty in climate projections of precipitation over the contiguous United States (CONUS). We use a subset of historical model simulations and future model projections (RCP8.5) from the Coupled Model Intercomparison Project phase 5 (CMIP5). We evaluate the representation of five precipitation summary metrics in the historical simulations using observations from the NASA Tropical Rainfall Measuring Mission (TRMM) satellites. The summary metrics include mean, annual and interannual variability, and maximum and minimum extremes of precipitation. The estimated model average produced with BMA is shown to have higher accuracy in simulating mean rainfall than the ensemble mean (RMSE of 0.49 for BMA versus 0.65 for ensemble mean), and a more constrained spread of uncertainty with roughly a third of the total uncertainty than is produced with the multimodel ensemble. The results show that, by the end of the century, the mean daily rainfall is projected to increase for most of the East Coast and the Northwest, may decrease in the southern United States, and with little change expected for the Southwest. For extremes, the wettest year on record is projected to become wetter for the majority of CONUS and the driest year to become drier. We show that BMA offers a framework to more accurately estimate and to constrain the spread of uncertainties of future climate, such as precipitation changes over CONUS.