Jiandong Li

Dr. Jiandong Li

Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 October 2015 in Science China Earth Sciences
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GWGuoxiong Wu
Guoxiong Wu
zhanqing lizhanqing li
zhanqing li
CFCongBin Fu
CongBin Fu
XZXiaoYe Zhang
XiaoYe Zhang
RZRenYi Zhang
RenYi Zhang
RHRongHui Huang
RongHui Huang

30 April 2019 in Journal of Advances in Modeling Earth Systems
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JLJinxiao Li
Jinxiao Li
Qing BaoQing Bao
Qing Bao
YLYimin Liu
Yimin Liu
GWGuoxiong Wu
Guoxiong Wu
LWLei Wang
Lei Wang
JLJiandong Li
Jiandong Li
We evaluate the ability of the latest generation atmospheric general circulation model from State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (namely, FAMIL2) in simulating some key characteristics (genesis location, track, number, and intensity) of tropical cyclones (TCs) in terms of their climatology and seasonal to interannual variability. A standard 1° × 1° atmospheric model intercomparison project experiment is carried out for the period 1979–2002, and the last 20 years of outputs are used for analysis. The same period from International Best Track Archive for Climate Stewardship (IBTrACS) is used as the observation for comparison purposes. The evaluations focus on TC activity at the global scale as well as in the three key regions of the northern Indian Ocean (NIO), western Pacific (WP) and northern Atlantic (NA). With respect to the simulated TC climatology, FAMIL2 shows notable ability in correctly reproducing the main characteristics of the genesis locations, tracks, and numbers of TC, particularly over the key regions of TC activity in the Northern Hemisphere; whereas, it underestimates the intensities of TC, as is the case with many state‐of‐the‐art climate models operating at a medium resolution. On seasonal‐to‐interannual time scales, meanwhile, FAMIL2 successfully reproduces the seasonal cycles of TC numbers over the NIO and WP regions, the former being characterized by double TC peaks (in May and October) and the latter by a maximum peak season in August. However, the model only captures these features approximately. For the simulated interannual variability of TC activity, the correlation coefficients of 20‐year TC numbers between FAMIL2 and IBTrACS are 0.22, 0.51 (95% confidence interval), and 0.49 (95% confidence interval) for the NIO, WP, and NA, respectively. We also examine the possible reasons behind the performance of FAMIL2 by investigating its subseasonal signs related to the Madden‐Julian Oscillation (MJO) and convectively coupled equatorial waves. The TC genesis potential index is employed to investigate the possible impacts of the large‐scale dynamic fields on the simulation of TC activity. Finally, the biases of simulated TC activity, as well as possible solutions for these biases, are discussed with respect to the horizontal resolution of the model. A TC forecasting case study is introduced as a first step in applying FAMIL2 to a TC forecasting system.

18 January 2018 in Journal of Geophysical Research: Atmospheres
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XXXiaoning Xie
Xiaoning Xie
XLXiaodong Liu
Xiaodong Liu
HCHuizheng Che
Huizheng Che
XXXiaoxun Xie
Xiaoxun Xie
HWHongli Wang
Hongli Wang
YLYangang Liu
Yangang Liu

13 January 2017 in Climate Dynamics
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JLJiandong Li
Jiandong Li
WWWei-Chyung Wang
Wei-Chyung Wang
XDXiquan Dong
Xiquan Dong
JMJiangyu Mao
Jiangyu Mao

5 May 2021 in Journal of Geophysical Research: Atmospheres
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JLJiandong Li
Jiandong Li
ZSZhian Sun
Zhian Sun
YLYimin Liu
Yimin Liu
QYQinglong You
Qinglong You
GCGuoxing Chen
Guoxing Chen
Qing BaoQing Bao
Qing Bao
This study investigates the top‐of‐atmosphere (TOA) radiation budget (RT) and cloud radiative effects (CREs) over the Tibetan Plateau (TP) and adjacent Asian monsoon regions including Eastern China (EC) and South Asia (SA) using the Coupled Model Intercomparison Project 6 (CMIP6) simulations. Considerable simulation biases occur but specific causes differ in these regions. Most models underestimate the intensity of annual mean RT and cloud radiative cooling effect over the TP, and the RT during the cold‐warm transition period is hard to capture. The biases in surface temperature and cloud fractions substantially contribute to cloud‐radiation biases over the western and eastern TP, respectively. Over EC, the intensity of RT and cloud radiative cooling effect is seriously underestimated especially in the springtime when the model spread is large, and their biases are closely related to less low‐middle cloud fractions and weaker ascending motion. Over SA, simulation biases mainly arise from longwave radiative components associated with less high cloud fraction and weaker convection, with the large model spread in the summertime. The annual cycles of RT and CREs over EC and SA can be well reproduced by most models, while the summertime peak of the net CRE over the TP occurs later than the observation. The RT and its simulation bias strongly depend on the cloud radiative cooling effect over EC and SA. Our results demonstrate that contemporary climate models still have obvious difficulties in representing various complex cloud‐radiation processes in Asian monsoon regions.

22 March 2022 in Journal of Geophysical Research: Atmospheres
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Closed access
GCGuoxing Chen
Guoxing Chen
WWWei‐Chyung Wang
Wei‐Chyung Wang
Qing BaoQing Bao
Qing Bao
JLJiandong Li
Jiandong Li