东亚地区高分辨率对流层二氧化氮垂直柱浓度数据集POMINO-TROPOMI v1.2（2018-2022）

POMINO-TROPOMI数据基于北京大学ACM研究组自行开发的POMINO-TROPOMI反演算法。该算法使用并行LIDORT辐射传输模式驱动的AMFv6软件包，重点改进了对流层NO2大气质量因子（AMF）的计算。POMINO-TROPOMI算法使用了MODIS MCD43C2.006数据集的逐日BRDF系数和OMLER v3地表反照率数据计算地表反射率。算法使用了嵌套的GEOS-Chem (v9-02)模式的气溶胶数据来显性表征气溶胶光学效应。此外，该算法使用了MODIS MYD04_L2的月平均AOD数据对模拟的AOD进行修正。在计算对流层NO2 AMF之前，POMINO-TROPOMI算法使用了一致的先验参数和TROPOMI PAL v2.3.1数据提供的云气压对云分数进行了重新反演。基于POMINO-TROPOMI算法的对流层NO2 AMF以及TROPOMI PAL v2.3.1数据的对流层NO2斜柱浓度，得到POMINO-TROPOMI对流层NO2垂直柱浓度。详细信息和更多数据请访问http://www.pku-atmos-acm.org/acmProduct.php/#TROPOMI.

The POMINO-TROPOMI dataset is developed based on the POMINO-TROPOMI retrieval algorithm independently developed by the ACM Research Group at Peking University. This algorithm employs the AMFv6 software package driven by the parallelized LIDORT radiative transfer model, with key improvements made to the calculation of tropospheric NO2 atmospheric mass factor (AMF). The POMINO-TROPOMI algorithm uses the daily BRDF coefficients from the MODIS MCD43C2.006 dataset and the OMLER v3 surface albedo data to calculate surface reflectance. The algorithm adopts aerosol data from the nested GEOS-Chem (v9-02) model to explicitly characterize aerosol optical effects. In addition, the algorithm uses the monthly averaged AOD data from MODIS MYD04_L2 to correct the simulated AOD. Prior to calculating the tropospheric NO2 AMF, the POMINO-TROPOMI algorithm performs a re-retrieval of cloud fraction using consistent prior parameters and the cloud pressure provided by the TROPOMI PAL v2.3.1 dataset. The POMINO-TROPOMI tropospheric NO2 vertical column concentration is derived based on the tropospheric NO2 AMF generated by the POMINO-TROPOMI algorithm and the tropospheric NO2 slant column concentration from the TROPOMI PAL v2.3.1 dataset. For detailed information and more data, please visit http://www.pku-atmos-acm.org/acmProduct.php/#TROPOMI.

搜集汇总

背景与挑战

背景概述

该数据集提供了东亚地区2018-2022年高分辨率对流层二氧化氮垂直柱浓度数据，基于改进的POMINO-TROPOMI反演算法，结合多种遥感数据源，具有1km-10km的空间分辨率和月时间分辨率。