\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[greek,english]{babel}



\usepackage{float}








\begin{document}

\title{\selectlanguage{greek}Α \selectlanguage{english}Hybrid Approach to Atmospheric Modeling that Combines Machine Learning
with a Physics-Based Numerical Model\selectlanguage{english}}



\author[1,1,1]{Troy Arcomano}%
\author[1,1,1]{Istvan Szunyogh}%
\author[2,2,2]{Alexander Wikner}%
\author[3,3,3]{Jaideep Pathak}%
\author[2,2,2]{Brian R Hunt}%
\author[2,2,2]{Edward Ott}%
\affil[1]{Texas A\&M University}%
\affil[2]{University of Maryland}%
\affil[3]{Lawrence Berkeley National Laboratory}%


\vspace{-1em}



  
  \date{May 05, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
This paper describes an implementation of the Combined Hybrid-Parallel
Prediction (CHyPP) approach of Wikner et al. (2020) on a low-resolution
atmospheric global circulation model (AGCM). The CHyPP approach combines
a physics-based numerical model of a dynamical system (e.g., the
atmosphere) with a computationally efficient type of machine learning
(ML) called reservoir computing (RC) to construct a hybrid model. This
hybrid atmospheric model produces more accurate forecasts of most
atmospheric state variables than the host AGCM for the first 7-8
forecast days, and for even longer times for the temperature and
humidity near the earth's surface. It also produces more accurate
forecasts than a model based only on ML, or a model that combines linear
regression, rather than ML, with the AGCM. The potential of the approach
for climate research is demonstrated by a 10-year long hybrid model
simulation of the atmospheric general circulation, which shows that the
hybrid model can simulate the general circulation with substantially
smaller systematic errors and more realistic variability than the host
AGCM.%
\end{abstract}%



\sloppy




\selectlanguage{english}
\FloatBarrier
\end{document}

