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Preliminary test of quantitative capability in aerosol retrieval over land from MERSI-II onboard FY-3D

  • role： First author第一作者
  • Affiliation：

    School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China

  • Email：yanglk@hpu.edu.cn
  • Introduction：杨磊库，研究方向为气溶胶卫星遥感。E-mail：yanglk@hpu.edu.cn
YANG Leiku1,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Satellite Meteorological Centre, Beijing 100081, China

  • Email：huxq@cma.gov.cn
  • Introduction：胡秀清，研究方向为卫星遥感器定标理论及技术方法。E-mail：huxq@cma.gov.cn
HU Xiuqing2*,  
  • Affiliation：

    School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China

WANG Han1,  
  • Affiliation：

    National Satellite Meteorological Centre, Beijing 100081, China

HE Xingwei2,  
  • Affiliation：

    School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China

LIU Pei1,  
  • Affiliation：

    National Satellite Meteorological Centre, Beijing 100081, China

XU Na2,  
  • Affiliation：

    National Satellite Meteorological Centre, Beijing 100081, China

YANG Zhongdong2,  
  • Affiliation：

    National Satellite Meteorological Centre, Beijing 100081, China

ZHANG Peng2

resumen

The MEdium-Resolution Spectral Imager (MERSI) carried by the Chinese Fengyun-3 (FY-3) satellite belongs to the same type of sensor as MODIS of NASA. Most channels of MERSI are similar in design as MODIS and are capable for aerosol retrieval. However, no reliable, stable, and globally applicable operational products are available for MERSI.On the basis of MODIS Dark Target (DT) algorithm, this paper constructs a globally applicable land aerosol retrieval algorithm for the new generation MERSI-II sensor onboard the newly launched FY-3D satellite. The aim of this paper is to test the quantitative capability of the sensor; hence, the algorithm design is consistent with DT algorithm as much as possible. The improvements of this algorithm from the MODIS DT algorithm are mainly in two aspects: surface estimation model and pixel screen. Considering the difference in channel settings between MERSI and MODIS, a surface reflectance estimation model is proposed for MERSI-II. Moreover, the method of inland water mask is improved to solve the defect of DT algorithm in haze leakage retrieval.By comparing granule retrieval of MERSI-II with aerosol products of MODIS, the spatial distribution and magnitude of AOD value show good consistency with a correlation coefficient above 0.9. After improving the identification method of inland water mask, the high aerosol loading of haze region which was missing in MODIS aerosol product, has been successfully retrieved from MERSI-II in this paper. Finally, we conducted the retrieval test with three-month global observation of MERSI-II. A comparison of the retrieval results with ground-based observation of AERONET shows that the overall accuracy of validation is good, and the correlation coefficient of scatterplots reaches 0.866. Moreover, the number of collocated points falling into the expected error EE = ± (0.05 + 0.15 τ) reaches 65.14%, which is close to the requirement of 2/3. The larger width of MERSI, in addition to its improvement of pixel mask, increases the number of MERSI-retrieved pixels. The proportion of matched collocation points is approximately 20% more than that of MODIS. Furthermore, a comparison between the monthly average results of MERSI-II and MODIS shows that the consistency of their spatial distribution is good. The magnitude of AOD value has good correlation with a coefficient of approximately 0.93.In conclusion, aerosol retrieval from MERSI-II using the proposed algorithm is close to the present similar products. Such performance is an important supplement to the global time series aerosol observation. Therefore, MERSI has good quantitative application ability, and the sensor performance and calibration are gradually becoming mature.

palabra clave

FY-3;MERSI;aerosol optical depth;Dark Target (DT);Haze;inland water mask;surface reflectance estimation;ground-based validation

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