Remote Sensing Of Aerosol Optical Depth And Haze Detection Over China Sea

Aerosols are a colloidal system of solid and liquid particles suspended in the atmosphere,and have significant impacts on weather,climate,and human health.Aerosols play an important role in earth’s radiation budget and its impact on climate variability by the scattering and absorption of incoming solar energy.They also absorb incoming solar radiation which causes a warming effect in the atmosphere,whereas aerosol forcing at the top of the atmosphere may cause a cooling effect by reflecting solar radiation.A full understanding of the impact of aerosol particles in climate and air quality control strategies requires the retrieval of aerosol amounts and characteristics.Aerosol optical depth（AOD）is one of the most important aerosol optical parameters,which represents the extinction property of aerosols,that is,the extinction effect on solar radiation of aerosol particles.This parameter can be used to estimate aerosol content and evaluate air pollution status.Therefore,the research on the spatial and temporal distribution and variation of aerosol optical thickness has important scientific significance for effectively monitoring regional atmospheric particulate pollution and fully understanding the influence of aerosol on current and future climate conditions.In this study,in order to do validation work about MODerate resolution Imaging Spectroradiometer（MODIS）aerosol products,MODIS Collection 6（C6）level-2 Dark Target（DT）Aerosol Optical Depth（AOD）products at 3 km（DT3K）and 10 km（DT10K）spatial resolutions were validated over the China seas and the eastern Indian Ocean against Maritime Aerosol Network（MAN）Level 1.5 AOD measurements collected through 13 cruises from 2010to 2014.For this,DT3K and DT10K AOD observations were obtained from four Scientific Data Sets（SDS）,i.e.,“Effective Optical Depth Average Ocean”（EODAOAOD）,“Effective Optical Depth Best Ocean”（EODBOAOD）,“Image Optical Depth Land And Ocean”（IODLAOAOD）and“Optical Depth Land And Ocean”（ODLAOAOD）.The MAN AOD measurements were filtered within（i）±2 h,（ii）±4 h,（iii）±6 h,and（iv）±12 h of MODIS overpass time.Results showed that the DT10K and DT3K performed equally over the China seas and the eastern Indian Ocean in terms of retrievals quality and agreement with the MAN AOD measurements,whereas the DT3K has less coincident observations than the DT10K.For seasonal analysis,larger underestimation in the DT algorithm was observed in autumn followed by spring,whereas retrievals were well correlated with the MAN AOD data in summer.Overall,this study found that ODLAOAOD observations for the DT3K and DT10K were much better than EODAOAOD,EODBOAOD and IODLAOAOD in terms of high correlation and a large percentage of the AOD retrievals within the Expected Error（EE=+（0.04+10%）,-（0.02+10%））.Based on validation work on MODIS aerosol products,in this study,MODIS Collection6.1（C6.1）level-2 Dark Target（DT）Aerosol Optical Depth（AOD）observations at 550 nm（AOD550）for the highest quality flag assurance（QA=3）were obtained to analyze spatiotemporal variations of aerosol optical properties over the Yellow and the Bohai Sea from2002 to 2017.Spectral AOD observations at 470 nm（AOD470）and 660 nm（AOD660）were obtained to calculate Angstrom Exponent（AE470–660）and classify the aerosol types including clean continental（CC）,clean maritime（CM）biomass and urban industrial（BUI）,dust（DUST）,and mixed（MXD）aerosol types.Results showed a very distinct spatial pattern of AOD distribution over the Bohai Sea which looks suspicious,i.e.,high aerosol loadings（AOD>0.8）throughout the entire time period,whereas relative low AOD distribution was observed over the adjacent land pixels especially in autumn and winter,which suggested that the DT algorithm might be influenced by a large number of sediments located in the Bohai Sea.Significant differences in spatial distributions were found in different seasons in terms of area coverage as a maximum number of pixels were available during autumn,and regional high and low aerosol loadings were observed during autumn and summer,respectively.Trend analysis from 2002 to2017 showed that AOD was increased up to 0.04 over the Bohai Sea and decreased up to 0.04over the Yellow Sea,and this trend varies from month to month.Aerosol classification showed significant contributions of BUI and CC over the region,and contributions of CM,DUST,and MXD aerosols over the Yellow Sea were relatively high compared to the Bohai Sea.In this study,the sourses of different types of aerosols were analyzed by analyzing meteorological conditions,and it was found that terrigenous input was an important cause of aerosol formation over East China Seas,especially in spring and winter.Haze is one of the most typical aerosol pollution weather.In order to identify and monitor the haze effectively,in this paper,we selected two MODIS images on 4^th October,2013 and 6^thJune,2007,respectively.Based on neural network model,a machine learning algorithm for identification of marine haze was established in this paper.By validation,the accuracy of the algorithm was more than 98%,wheras some modification are need to do.With these haze detection algorithms,we can monitor haze for long time over East China Seas.