A5022170589- Climate variability and models
- Complex Systems and Time Series Analysis
- Meteorological Phenomena and Simulations
- Atmospheric chemistry and aerosols
- Atmospheric Ozone and Climate
- Environmental and Agricultural Sciences
- Atmospheric and Environmental Gas Dynamics
- Chaos control and synchronization
- Remote Sensing and Land Use
- Plant Water Relations and Carbon Dynamics
- Time Series Analysis and Forecasting
- Fractal and DNA sequence analysis
- Complex Network Analysis Techniques
- Ecosystem dynamics and resilience
- Tree-ring climate responses
- Opinion Dynamics and Social Influence
- Energy Load and Power Forecasting
- Environmental Changes in China
- Machine Learning in Bioinformatics
- Air Quality Monitoring and Forecasting
- Global trade and economics
- Global Financial Crisis and Policies
- Advanced Computational Techniques and Applications
- Tropical and Extratropical Cyclones Research
- Air Quality and Health Impacts
Institute of Atmospheric Physics
2014-2024
Chinese Academy of Sciences
2015-2024
University of Wisconsin–Milwaukee
2021
Hydrologic Research Center
2021
Peking University
2007
Significance Here we use newly available methods to examine the dynamical association between cosmic rays (CR) and global temperature (GT) in 20th-century observational record. We find no measurable evidence of a causal effect linking CR overall warming trend; however, on short interannual timescales, significant, although modest, short-term, year-to-year variability GT. Thus, clearly do not contribute measurably trend, they appear as nontraditional forcing climate system providing another...
Abstract In a recent application of networks to 500-hPa data, it was found that supernodes in the network correspond major teleconnection. More specifically, Northern Hemisphere set coincides with North Atlantic Oscillation (NAO) and another is located area where Pacific–North American (PNA) tropical (TNH) patterns are found. It subsequently suggested presence atmospheric teleconnections make climate more stable efficient transferring information. Here this hypothesis tested by examining...
The El Niño-Southern Oscillation (ENSO) influences the global temperature and precipitation patterns. Generally, ENSO influence has been related to its amplitude. We use information-theoretic generalization of Granger causality observe causal phases oscillatory components on scales variability in Yangtze Yellow River basins, with a focus quasi-oscillatory dynamics spanning various timeframes. find that quasi-biennial component effect around annual scale, while amplitude is...
Models and data suggest that the interplay of major climate modes may result in shifts. More specifically it has been shown when network North Atlantic Oscillation (NAO), Pacific Decadal (PDO), El Nino/Southern (ENSO) Index (NPI) synchronizes, an increase coupling between these oscillations destroys synchronous state leads system to a new state. These shifts are associated with significant changes global temperature trend ENSO variability. Here we probe details this network's dynamics...
Abstract. Reanalysis data play a vital role in weather and climate study as well meteorological resource development application. In this work, the East Asia System (EARS) was developed using Weather Research Forecasting (WRF) model Gridpoint Statistical Interpolations (GSI) assimilation system. The regional reanalysis system is forced by European Centre for Medium-Range Forecasts (ECMWF) global ERA-Interim at 6 h intervals. Hourly surface observations are assimilated Four-Dimension Data...
Abstract The identification of causal effects is a fundamental problem in climate change research. Here, new perspective on causality presented using the central England temperature (CET) dataset, longest instrumental record, and combination slow feature analysis wavelet analysis. driving forces were investigated results showed two independent degrees freedom —a 3.36-year cycle 22.6-year cycle, which seem to be connected El Niño–Southern Oscillation Hale sunspot respectively. Moreover, these...
There is growing evidence that major climate modes are involved in determining decadal variability global mean temperature. These represent oceanic and atmospheric signals on scales their collective interplay leads to shifts manifesting themselves as regime changes temperature trend. Here we investigate whether the role of these extended within a regime, i.e. shorter time scales. We apply nonlinear prediction order assess directional influences system. show input from four Atlantic Pacific...
Complex networks have been studied across many fields of science in recent years. In this paper, we give a brief introduction networks, then follow the original works by Tsonis et al (2004, 2006) starting with data surface temperature from 160 Chinese weather observations to investigate topology climate networks. Results show that network exhibits characteristic regular, almost fully connected which means most nodes case same number links, and so-called super very large links do not exist...
The nonstationary behaviors of complex system and their applications to the climate prediction present a significant forward-looking study. Up now, its importance is not yet well understood. In reality, just normal system. However, almost all current theories for prediction, including ones in statistics nonlinear science, are based on one assumption that process stationary which contrary nature process. Probably, this contradictory an important cause resulting being at low reliability level....
Based on the idea of climate hierarchy and theory state space reconstruction, a local approximation prediction model with compound structure is built for predicting some nonstationary process. By means this data sets consisting north Indian Ocean sea-surface temperature, Asian zonal circulation index monthly mean precipitation anomaly from 37 observation stations in Inner Mongolia area China (IMC), regional experiment winter IMC also carried out. When using same sign ratio R between field...
Extracting the signals from non-stationary time series is a difficult task in many fields such as physics, economics, and atmospheric sciences. The theory of hierarchy suggests that varying driving force leads to behavior, so extracting analyzing slowly features can help study dynamical system, which has become compelling question recently. Slow feature analysis (SFA) an effective technique for forces quickly series. basic idea SFA nonlinearly extend reconstructive signal into combination...