Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China

نویسندگان

چکیده

Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China. Evaluation of long-term aerosol optical depth (AOD) data from models reanalysis, can greatly promote understanding spatiotemporal variations To do this, AOD (550 nm) values 2000 2014 were obtained the Coupled Model Inter-comparison Project (CIMP6), second version Modern-Era Retrospective analysis for Research, Applications (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS; flying on Terra satellite) combined Dark Target Deep Blue (DTB) product. We used Terra-MODIS DTB (hereafter MODIS AOD) as standard evaluate CMIP6 Ensemble MERRA-2 reanalysis AOD). Results show better correlations smaller errors between AOD, than most regions China, at both annual seasonal scales. However, significant under- over-estimations also observed relative AOD. The (2000–2014) distributions highest over North China Plain (0.71) followed by Central (0.69), Yangtse River Delta (0.67), Sichuan Basin (0.64), Pearl (0.54) regions. lowest recorded Tibetan Plateau (0.13 ± 0.01) Qinghai (0.19 0.03) Gobi Desert (0.21 0.03). Large amounts sand dust particles emitted natural sources (the Taklamakan Deserts) may result higher spring compared summer, autumn, winter. Trends calculated 2000–2005, 2006–2010 (when introduced strict control policies during 11th Five Year Plan or FYP), 2011–2014 (during 12th FYP). An increasing trend was throughout country 2000–2014. uncontrolled industrialization, urbanization, rapid economic development that mostly occurred 2005 probably contributed overall increase Finally, China's helped reduce country; this more evident FYP period (2011–2014) (2006–2010). Therefore study strongly advises authority retain extend these future improving quality.

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ژورنال

عنوان ژورنال: Geoscience frontiers

سال: 2022

ISSN: ['2588-9192', '1674-9871']

DOI: https://doi.org/10.1016/j.gsf.2021.101325