Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep learning for Aerosol Forecasting   Reanalysis datasets combining numerical physics models and limited
observations to generate a synthesised estimate of variables in an Earth
system, are prone to biases against ground truth. Biases identified with the
NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2
(MERRA-2) aerosol optical depth (AOD) dataset, against the Aerosol Robotic
Network (AERONET) ground measurements in previous studies, motivated the
development of a deep learning based AOD prediction model globally. This study
combines a convolutional neural network (CNN) with MERRA-2, tested against all
AERONET sites. The new hybrid CNN-based model provides better estimates
validated versus AERONET ground truth, than only using MERRA-2 reanalysis.

12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph