Ensemble-based analysis of the pollutant spreading intensity induced by climate change

被引:10
|
作者
Haszpra, Timea [1 ,2 ]
Herein, Matyas [1 ,2 ]
机构
[1] Eotvos Lorand Univ, Inst Theoret Phys, H-1117 Budapest, Hungary
[2] MTA ELTE Theoret Phys Res Grp, H-1117 Budapest, Hungary
关键词
NCEP-NCAR REANALYSIS; CYCLONE ACTIVITY; VARIABILITY; INTENSIFICATION; DISPERSION; ERA-40;
D O I
10.1038/s41598-019-40451-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The intensity of the atmospheric large-scale spreading can be characterized by a measure of chaotic systems, called topological entropy. A pollutant cloud stretches in an exponential manner in time, and in the atmospheric context the topological entropy corresponds to the stretching rate of its length. To explore the plethora of possible climate evolutions, we investigate here pollutant spreading in climate realizations of two climate models to learn what the typical spreading behavior is over a climate change. An overall decrease in the areal mean of the stretching rate is found to be typical in the ensembles of both climate models. This results in larger pollutant concentrations for several geographical regions implying higher environmental risk. A strong correlation is found between the time series of the ensemble mean values of the stretching rate and of the absolute value of the relative vorticity. Here we show that, based on the obtained relationship, the typical intensity of the spreading in an arbitrary climate realization can be estimated by using only the ensemble means of the relative vorticity data of a climate model.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Ensemble-based analysis of the pollutant spreading intensity induced by climate change
    Tímea Haszpra
    Mátyás Herein
    Scientific Reports, 9
  • [2] Validation of Ensemble-Based Probabilistic Tropical Cyclone Intensity Change
    Torn, Ryan D.
    DeMaria, Mark
    ATMOSPHERE, 2021, 12 (03)
  • [3] An ensemble-based approach to climate reconstructions
    Bhend, J.
    Franke, J.
    Folini, D.
    Wild, M.
    Broennimann, S.
    CLIMATE OF THE PAST, 2012, 8 (03) : 963 - 976
  • [4] Ensemble-based sensitivity analysis
    Torn, Ryan D.
    Hakim, Gregory J.
    MONTHLY WEATHER REVIEW, 2008, 136 (02) : 663 - 677
  • [5] CORDEX Ensemble-based drought projections for Sindh Province of Pakistan under climate change
    Hussain, Zafar
    Wang, Zongmin
    Yang, Haibo
    Aziz, Rizwan
    Azam, Muhammad Imran
    Usman, Muhammad
    Arfan, Muhammad
    Faisal, Muhammad
    Gao, Meiyan
    Journal of Water and Climate Change, 2024, 15 (11) : 5501 - 5517
  • [6] Temperature fluctuations in a changing climate: an ensemble-based experimental approach
    Miklós Vincze
    Ion Dan Borcia
    Uwe Harlander
    Scientific Reports, 7
  • [7] Temperature fluctuations in a changing climate: an ensemble-based experimental approach
    Vincze, Miklos
    Borcia, Ion Dan
    Harlander, Uwe
    SCIENTIFIC REPORTS, 2017, 7
  • [8] Ensemble-based convergence analysis of biomolecular trajectories
    Lyman, Edward
    Zuckerman, Daniel M.
    BIOPHYSICAL JOURNAL, 2006, 91 (01) : 164 - 172
  • [9] Neglected Spatiotemporal Variations of Model Biases in Ensemble-Based Climate Projections
    Song, Tangnyu
    Huang, Guohe
    Wang, Xiuquan
    GEOPHYSICAL RESEARCH LETTERS, 2022, 49 (16)
  • [10] Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale
    Mahajan, Salil
    Gaddis, Abigail L.
    Evans, Katherine J.
    Norman, Matthew R.
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS 2017), 2017, 108 : 735 - 744