The effect of a well-resolved stratosphere on East Asian winter climate

Wei, Ke; Cai, Zelin; Chen, Wen; Xu, Lujun

doi:10.1007/s00382-016-3419-6

Cited by 13 publications

(6 citation statements)

References 37 publications

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“…Nevertheless, in this study, there were few differences in the skill of both CMIP5 and CMIP6 high and low-top models in reproducing long-term observed precipitation trends. Several studies have indicated that accurate representation of the stratosphere is required to properly replicate the various atmospheric processes in the troposphere (Cagnazzo and Manzini 2009;Wei et al 2018a;Haase et al 2018). Low-top models do not explicitly reproduce stratospheric dynamical variability, which may have consequences for the identification of tropospheric impacts of the SAM and NAM, which have a major influence on precipitation variability at high latitudes and in subtropical regions.…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies have evaluated the effectiveness of high-top models to capture the observed signal in precipitation and the different atmospheric mechanisms driving multidecadal variability (e.g. Cagnazzo and Manzini 2009;Lee and Black 2014;Wei et al 2018a;Haase et al 2018). Others indicate that models without a well-resolved stratosphere show limitations in identifying atmospheric circulation mechanisms (Deser et al 2012;Osprey et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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Do CMIP models capture long-term observed annual precipitation trends?

et al. 2021

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This study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891–2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Do CMIP models capture long-term observed annual precipitation trends?

et al. 2021

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“…The climate change projections based on models with cold biases in the boreal polar vortex need to be reconsidered. For example, Wei et al [60] have shown that the discrepancies in the winter surface air temperature in East Asia between the HTOP and LTOP models can be up to 1.3 K by the end of the 21st century under different RCP scenarios. Hence, global and regional climate projections need to be reevaluated based on models that are better able to characterize the stratospheric circulation; otherwise, adaptation and mitigation policies might produce insufficient responses to the effects of anthropogenic global warming over the coming decades.…”

Section: Summary and Discussionmentioning

confidence: 99%

The Influences of the Model Configuration on the Simulation of Stratospheric Northern-Hemisphere Polar Vortex in the CMIP5 Models

Cai

Wei

et al. 2017

Advances in Meteorology

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As a basic part of the atmosphere, the stratosphere plays an important role in the tropospheric climate and weather systems, especially during the winter, when the stratosphere and troposphere have their strongest interactions. This study assesses the abilities of the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and CMIP3 models to simulate the boreal winter stratospheric polar vortex. Analysis indicates that the models with well-resolved stratospheres, that is, with a high model top (HTOP) covering the whole stratosphere, a high vertical resolution (HVer) of the stratosphere, and nonorographic gravity wave drag (NOG), rank higher in both the temporal scoring system and the spatial scoring system. The extreme cold polar vortex bias, which was found in the CMIP3 models, vanishes in the CMIP5 models with HTOP, HVer, and NOG but persists in the other CMIP5 models. A dynamical analysis shows that the heat flux propagating into the stratosphere is stronger in models with HTOP, HVer, and NOG, but these propagations are still weaker than those in the ERA40 reanalysis, indicating the lack of variability in the current CMIP5 models.

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“…Numerical models prescribed by forcings under different scenarios are employed to project climate changes under future global warming. Numerous studies have been performed to investigate changes in the climatology and interannual to decadal variability of the EAWM under global warming in the late 21st century with respect to the present day (Hu et al ., 2000; Bueh, 2003; Kimoto, 2005; Hori and Udea, 2006; Ding et al ., 2007; Li and Zhou, 2010; Jiang and Tian, 2013; Li and Gao, 2015; Xu et al ., 2016; Hong et al ., 2017; Kitoh, 2017; Zou and Zhou, 2017; Gong et al ., 2018; Wei et al ., 2018). Most of these studies indicate that the Siberian high, East Asian trough and subtropical westerly jet would weaken, and the Aleutian low and East Asian subtropical westerly jet would move northward (e.g., Jiang and Tian, 2013; Xu et al ., 2016; Hong et al ., 2017).…”

Section: Introductionmentioning

confidence: 99%