Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Post-processing Multi-Model Medium-Term Precipitation Forecasts Using
  Convolutional Neural Networks   The goal of this study was to improve the post-processing of precipitation
forecasts using convolutional neural networks (CNNs). Instead of
post-processing forecasts on a per-pixel basis, as is usually done when
employing machine learning in meteorological post-processing, input forecast
images were combined and transformed into probabilistic output forecast images
using fully convolutional neural networks. CNNs did not outperform regularized
logistic regression. Additionally, an ablation analysis was performed.
Combining input forecasts from a global low-resolution weather model and a
regional high-resolution weather model improved performance over either one.

32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol