Characterizing variability and predictability for air pollutants with stochastic models
Author:
Affiliation:
1. Max-Planck Institute for the Physics of Complex Systems, Dresden D-01187, Germany
2. Institute of Future Cities, The Chinese University of Hong Kong, Shatin, Hong Kong, China
Funder
CUHK Research Committee
Publisher
AIP Publishing
Subject
Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics
Link
https://aip.scitation.org/doi/pdf/10.1063/5.0041120
Reference43 articles.
1. Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations
2. Variability of depolarization of aerosol particles in the megacity of Beijing: implications for the interaction between anthropogenic pollutants and mineral dust particles
3. Long-memory processes in ozone and temperature variations at the region 60° S–60° N
4. On the limit to the accuracy of regional-scale air quality models
5. Confidence intervals for time averages in the presence of long-range correlations, a case study on Earth surface temperature anomalies
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