Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning for Precipitation Nowcasting from Radar Images   High-resolution nowcasting is an essential tool needed for effective
adaptation to climate change, particularly for extreme weather. As Deep
Learning (DL) techniques have shown dramatic promise in many domains, including
the geosciences, we present an application of DL to the problem of
precipitation nowcasting, i.e., high-resolution (1 km x 1 km) short-term (1
hour) predictions of precipitation. We treat forecasting as an image-to-image
translation problem and leverage the power of the ubiquitous UNET convolutional
neural network. We find this performs favorably when compared to three commonly
used models: optical flow, persistence and NOAA's numerical one-hour HRRR
nowcasting prediction.

37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th