%0 Dataset
%T Physics and Deep Learning Retrieval Fine Mode Fraction (Phy DL FMF)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/8cc0406e-571e-4c5f-b542-fe5b566abdde
%W NCDC
%R 10.12072/ncdc.zenodo.db6527.2024
%A None
%K Phy DL FMF;Aerosol;FMF
%X Aerosol fine fraction (FMF) is a key parameter for distinguishing between anthropogenic and natural aerosols, but it has significant uncertainty in satellite retrieval, especially on land. This dataset integrates physics and deep learning (Phy DL) methods, based on MODIS data, to retrieve aerosol micromodule fractions at the global land scale, and generates 20-year (2001-2020) Phy DL aerosol micromodule fractions (500 nm) at daily time resolution and 1 ° spatial resolution