Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stochastic Downscaling to Chaotic Weather Regimes using Spatially
  Conditioned Gaussian Random Fields with Adaptive Covariance   Downscaling aims to link the behaviour of the atmosphere at fine scales to
properties measurable at coarser scales, and has the potential to provide high
resolution information at a lower computational and storage cost than numerical
simulation alone. This is especially appealing for targeting convective scales,
which are at the edge of what is possible to simulate operationally. Since
convective scale weather has a high degree of independence from larger scales,
a generative approach is essential. We here propose a statistical method for
downscaling moist variables to convective scales using conditional Gaussian
random fields, with an application to wet bulb potential temperature (WBPT)
data over the UK. Our model uses an adaptive covariance estimation to capture
the variable spatial properties at convective scales. We further propose a
method for the validation, which has historically been a challenge for
generative models.

11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn