In this research, we assess the impact of short-term events, combined with sea-level rise, through synoptic climatological analysis, exploring whether circulation pattern identification can be used to enhance probabilistic forecasts of flood likelihood. Self-organizing maps (SOMs) were created for two discrete atmospheric variables: 700-hPa geopotential height (700z) and sea-level pressure (SLP). For each variable, a SOM array of patterns was created based on data spanning 25°-50°N and 60°-90°W for the period 1979-2014. Sea-level values were derived from tidal gauges between Cape May, New Jersey and Charleston, South Carolina, along the mid-Atlantic coast of the US. Both anomalous sea-level values, as well as nuisance flood occurrence (defined using the local gauge threshold), were assessed. Results show the impacts of both the inverted barometer effect as well as surface wind forcing on sea levels. With SLP, higher sea levels are associated with either patterns that were indicative of on-shore flow or cyclones. At 700z, ridges situated along the east coast are associated with higher sea levels. As the SOM matrix arranges atmospheric patterns in a continuum, the nodes of each SOM show a clear spatial pattern in terms of anomalous sea level, including some significant sea-level anomalies associated with relatively ambiguous pressure patterns. Further, multi-day transitions are also analyzed, showing rapidly deepening cyclones, or persistent onshore flow, can be associated with the greatest likelihood of nuisance floods.