Model initialization is a key process of climate predictions using dynamical models. In this study, the authors evaluated the performances of two distinct initialization approaches--anomaly and full-field initializati...Model initialization is a key process of climate predictions using dynamical models. In this study, the authors evaluated the performances of two distinct initialization approaches--anomaly and full-field initializations--in ENSO predictions conducted using the IAP-DecPreS near-term climate prediction system developed by the Institute of Atmospheric Physics （lAP）. IAP-DecPreS is composed of the FGOALS-s2 coupled general circulation model and a newly developed ocean data assimilation scheme called＇ensemble optimal interpolation-incremental analysis update＇ （EnOI-IAU）. It was found that, for IAP-DecPreS, the hindcast runs using the anomaly initialization have higher predictive skills for both conventional ENSO and El Nino Modoki, as compared to using the full-field initialization. The anomaly hindcasts can predict super El Nino/La Nina 10 months in advance and have good skill for most moderate and weak ENSO events about 4-7 months in advance.The predictive skill of the anomaly hindcasts for El Nino Modoki is close to that for conventional ENSO. On the other hand, the anomaly hindcasts at 1- and 4-month lead time can reproduce the major features of large-scale patterns of sea surface temperature, precipitation and atmospheric circulation anomalies during conventional ENSO and El Nino Modoki winter.展开更多
Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in ...Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in the near-term period 2017-35 are projected at global and regional scales based on a refined multi-model ensemble approach that considers both the secular trend(ST) and multidecadal variability(MDV) in the Coupled Model Intercomparison Project Phase 5(CMIP5) simulations. The ST and MDV components are adaptively extracted from each model simulation by using the ensemble empirical mode decomposition(EEMD) filter, reconstructed via the Bayesian model averaging(BMA) method for the historical period 1901-2005, and validated for 2006-16. In the simulations of the "medium" representative concentration pathways scenario during 2017-35, the MDV-modulated temperature change projected via the refined approach displays an increase of 0.44℃(90% uncertainty range from 0.30 to 0.58℃) for global land, 0.48℃(90% uncertainty range from 0.29 to 0.67℃) for the Northern Hemispheric land(NL), and 0.29℃(90% uncertainty range from 0.23 to 0.35℃) for the Southern Hemispheric land(SL). These increases are smaller than those projected by the conventional arithmetic mean approach. The MDV enhances the ST in 13 of 21 regions across the world. The largest MDV-modulated warming effect(46%) exists in central America. In contrast,the MDV counteracts the ST in NL, SL, and eight other regions, with the largest cooling effect(220%) in Alaska.展开更多
沙尘天气对社会经济与生态环境产生不利影响,认识其年代际变化并探索其未来态势具有重要意义。本文使用站点资料与再分析数据,研究了调控1961—2020年3—4月华北地区沙尘日数年代际变化的关键大气环流,并利用CMIP6和CESM-LE两套模式数...沙尘天气对社会经济与生态环境产生不利影响,认识其年代际变化并探索其未来态势具有重要意义。本文使用站点资料与再分析数据,研究了调控1961—2020年3—4月华北地区沙尘日数年代际变化的关键大气环流,并利用CMIP6和CESM-LE两套模式数据预估其近期变化。结果表明,华北地区沙尘日数在20世纪80年代末90年代初发生了显著突变,高发时期(1961—1989年,P1)的沙尘日数大约是低发时期(1992—2020年,P2)的3.5倍。这一变化受到由西欧平原东传至乌拉尔山及蒙古高原的波列系统(西欧低压-乌拉尔山高压-蒙古低压异常,anomaly of geopotential height in Western Europe,Ural Mountains and Mongolia,简称EUM)影响。相较于P2时期,P1时期波列较强,乌拉尔山地区位势高度升高,其东部异常偏北气流有利于冷空气南下。蒙古地区位势高度降低,显著的蒙古气旋异常为华北地区沙尘天气提供了动力条件。同时沙源地上空水汽辐散,不利于降水。EUM指数具有与华北地区沙尘日数较为一致的年代际变化特征,对后者未来变化有一定的指示作用。但不同模式对EUM年代际变化的模拟能力差异较大。通过筛选能够再现EUM年代际减弱特征的最优模式集合,发现在高排放情境下,未来近期(2021—2050年,P3)EUM显著增强,有利于华北地区沙尘天气增加。展开更多
气候预测系统的海洋初始化积分试验考虑了海气相互作用,可以视为一种弱耦合同化试验。海温(SST)和层积云的关系是检验海气相互作用过程模拟效果的重要参考。分析了基于耦合气候系统模式FGOALS-s2的中国科学院大气物理研究所近期气候预...气候预测系统的海洋初始化积分试验考虑了海气相互作用,可以视为一种弱耦合同化试验。海温(SST)和层积云的关系是检验海气相互作用过程模拟效果的重要参考。分析了基于耦合气候系统模式FGOALS-s2的中国科学院大气物理研究所近期气候预测系统IAP Dec Pre S的海洋初始化模拟实验(简称EnOI-IAU试验)所模拟的海温—云关系。结果表明,EnOI-IAU试验较好地模拟出了SST和低云的气候态空间分布,但在主要层积云区低估了低云云量和云水,SST模拟偏高,特别在副热带东大洋沿岸和南大洋。部分原因是这些地区实际影响海表温度模拟的是模式的内部过程,而低云模拟不足导致了海表入射更多的短波辐射(强度约偏强20 W/m^2),迫使局地SST模拟过高。分析显示,低云模拟不足主要是由于EnOI-IAU试验不能再现合理的边界层逆温结构,表现为大气垂直速度、温度和湿度过于集中在近地层,使得边界层垂直热输送较弱、边界层无法充分混合,进而无法有效模拟出层积云。这些结果表明,未来引入大气观测数据同化,特别是改善边界层结构的模拟,对形成完整的耦合同化系统具有必要性。展开更多
基金jointly supported by the National Key Research and Development Program of China(grant number2017YFA0604201)the National Natural Science Foundation of China(grant numbers.41661144009 and 41675089)the R&D Special Fund for Public Welfare Industry(meteorology)(grant number GYHY201506012)
文摘Model initialization is a key process of climate predictions using dynamical models. In this study, the authors evaluated the performances of two distinct initialization approaches--anomaly and full-field initializations--in ENSO predictions conducted using the IAP-DecPreS near-term climate prediction system developed by the Institute of Atmospheric Physics （lAP）. IAP-DecPreS is composed of the FGOALS-s2 coupled general circulation model and a newly developed ocean data assimilation scheme called＇ensemble optimal interpolation-incremental analysis update＇ （EnOI-IAU）. It was found that, for IAP-DecPreS, the hindcast runs using the anomaly initialization have higher predictive skills for both conventional ENSO and El Nino Modoki, as compared to using the full-field initialization. The anomaly hindcasts can predict super El Nino/La Nina 10 months in advance and have good skill for most moderate and weak ENSO events about 4-7 months in advance.The predictive skill of the anomaly hindcasts for El Nino Modoki is close to that for conventional ENSO. On the other hand, the anomaly hindcasts at 1- and 4-month lead time can reproduce the major features of large-scale patterns of sea surface temperature, precipitation and atmospheric circulation anomalies during conventional ENSO and El Nino Modoki winter.
基金Supported by the National Key Research and Development Program of China(2016YFA0600404)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2016075)Jiangsu Collaborative Innovation Center for Climate Change
文摘Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in the near-term period 2017-35 are projected at global and regional scales based on a refined multi-model ensemble approach that considers both the secular trend(ST) and multidecadal variability(MDV) in the Coupled Model Intercomparison Project Phase 5(CMIP5) simulations. The ST and MDV components are adaptively extracted from each model simulation by using the ensemble empirical mode decomposition(EEMD) filter, reconstructed via the Bayesian model averaging(BMA) method for the historical period 1901-2005, and validated for 2006-16. In the simulations of the "medium" representative concentration pathways scenario during 2017-35, the MDV-modulated temperature change projected via the refined approach displays an increase of 0.44℃(90% uncertainty range from 0.30 to 0.58℃) for global land, 0.48℃(90% uncertainty range from 0.29 to 0.67℃) for the Northern Hemispheric land(NL), and 0.29℃(90% uncertainty range from 0.23 to 0.35℃) for the Southern Hemispheric land(SL). These increases are smaller than those projected by the conventional arithmetic mean approach. The MDV enhances the ST in 13 of 21 regions across the world. The largest MDV-modulated warming effect(46%) exists in central America. In contrast,the MDV counteracts the ST in NL, SL, and eight other regions, with the largest cooling effect(220%) in Alaska.
文摘沙尘天气对社会经济与生态环境产生不利影响,认识其年代际变化并探索其未来态势具有重要意义。本文使用站点资料与再分析数据,研究了调控1961—2020年3—4月华北地区沙尘日数年代际变化的关键大气环流,并利用CMIP6和CESM-LE两套模式数据预估其近期变化。结果表明,华北地区沙尘日数在20世纪80年代末90年代初发生了显著突变,高发时期(1961—1989年,P1)的沙尘日数大约是低发时期(1992—2020年,P2)的3.5倍。这一变化受到由西欧平原东传至乌拉尔山及蒙古高原的波列系统(西欧低压-乌拉尔山高压-蒙古低压异常,anomaly of geopotential height in Western Europe,Ural Mountains and Mongolia,简称EUM)影响。相较于P2时期,P1时期波列较强,乌拉尔山地区位势高度升高,其东部异常偏北气流有利于冷空气南下。蒙古地区位势高度降低,显著的蒙古气旋异常为华北地区沙尘天气提供了动力条件。同时沙源地上空水汽辐散,不利于降水。EUM指数具有与华北地区沙尘日数较为一致的年代际变化特征,对后者未来变化有一定的指示作用。但不同模式对EUM年代际变化的模拟能力差异较大。通过筛选能够再现EUM年代际减弱特征的最优模式集合,发现在高排放情境下,未来近期(2021—2050年,P3)EUM显著增强,有利于华北地区沙尘天气增加。
文摘气候预测系统的海洋初始化积分试验考虑了海气相互作用,可以视为一种弱耦合同化试验。海温(SST)和层积云的关系是检验海气相互作用过程模拟效果的重要参考。分析了基于耦合气候系统模式FGOALS-s2的中国科学院大气物理研究所近期气候预测系统IAP Dec Pre S的海洋初始化模拟实验(简称EnOI-IAU试验)所模拟的海温—云关系。结果表明,EnOI-IAU试验较好地模拟出了SST和低云的气候态空间分布,但在主要层积云区低估了低云云量和云水,SST模拟偏高,特别在副热带东大洋沿岸和南大洋。部分原因是这些地区实际影响海表温度模拟的是模式的内部过程,而低云模拟不足导致了海表入射更多的短波辐射(强度约偏强20 W/m^2),迫使局地SST模拟过高。分析显示,低云模拟不足主要是由于EnOI-IAU试验不能再现合理的边界层逆温结构,表现为大气垂直速度、温度和湿度过于集中在近地层,使得边界层垂直热输送较弱、边界层无法充分混合,进而无法有效模拟出层积云。这些结果表明,未来引入大气观测数据同化,特别是改善边界层结构的模拟,对形成完整的耦合同化系统具有必要性。
