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\begin{document}

\title{Evaluating medium-range forecast performance of regional-scale
circulation patterns.}



\author[1]{Omon Obarein}%
\author[1]{Tyler Smith}%
\author[1]{Cameron Lee}%
\author[1]{Scott Sheridan}%
\affil[1]{Kent State University Kent Campus}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\begin{abstract}
Accurate sub-seasonal to seasonal (S2S) weather forecast between 2 weeks
and several months is crucial to making informed decisions regarding
changes in the risk of extreme weather events, resource management,
agriculture, forestry, public health, energy, etc. However, significant
gaps exist between the needs of society and what forecasters can
produce, especially over longer lead times. Using three goodness-of-fit
metrics, this study examined the ability of the SOMs-generated CFSv2 to
forecast the correct (observed) circulation pattern, as opposed to the
actual observed gridded field over a 90-day forecast period. Mean
sea-level pressure (MSLP), near-surface wind (wnd10m), 850-mb
temperature (t850), and 700-mb geopotential heights (z700) from the
North American Regional Reanalysis were used to categorize the
synoptic-scale circulation for three regions (East, West, and Gulf)
across North America from January 1979 -- December 2016. Expectedly,
forecast skill generally decreased from the first day down to the skill
of climatology (after 10 -15 days) and also varied regionally,
seasonally, and between variables. The forecasts for the winter and
summer seasons outperformed others, while t850 and z700 forecasts
outperformed wnd10m, except in the west region. More importantly, this
study found that the SOMs-generated CFSv2 forecasts improve upon the
skill of the raw CFSv2 forecast near the one 1 -- 2 weeks lead time.
This study thus demonstrates the potential utility of a SOMs-based
forecasting method in medium-range weather forecasts.%
\end{abstract}%



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