It has been a rough winter in New Jersey, especially on the coast. First, Post Tropical Storm Sandy struck Atlantic County on October 29th 2012, becoming the costliest natural disaster in New Jersey’s history. Over the next 5 months, several additional strong storms made their way across the state, bringing with them heavy winds, coastal and inland flooding and significant snowfalls.
Strong storms, many of which are called Nor’easters, are common occurrences in the Mid-Atlantic during winter months. Their strong winds also lead to high waves in the ocean. But this past winter was rather exceptional.
The above graph shows an analysis of wave heights measured by NDBC Station 44025. Each bar depicts the maximum wave height reached for each of the 12 largest events (each lasting 2-3 days) recorded over the past eight years (from January 2005 to today). Of the 12 events with the highest waves, 6 of them have been in the last 6 months. The largest recorded wave event was, of course, due to Sandy. The 12th largest occurred during the nor’easter that struck earlier this month.
It’s important to note that this does not (yet) represent a significant trend. Taking the top 20 events into account, only the same 6 events occurred this winter. Extreme events can often occur in spurts, triggered by prevailing climatic conditions, so the likelihood of many major events coinciding is not uncommon. In addition, an 8-year dataset is far too limited to make any assumptions about long-term climate changes.
However, it should be quite clear from this evidence that New Jersey residents are certainly ready for Spring, and more importantly, calmer weather.
Great stuff in this Visual Ocean blog, but there’s a typo in this analysis of major wave events.
It says “… the 12 largest events (each lasting 2-3 days) recorded over the past eight years (from January 2012 to today).” Obviously, eight-years-ago is sometime in 2005, not 2012.
Keep up the good work!
Thanks Bruce for catching that. I’ve fixed the text above.
One of the problems of analyzing various time periods is that you can sometimes confuse them. The graph above was created with an 8+ year dataset, but I also spent time looking at the most recent year by itself, as that year had a lot of significant events (hence the title of the post). But I also wanted to include that year within a larger context so that significance could stand out, and so I added additional years to the analysis. (I would have added more, but I didn’t have time to deal with the different data format the older data was in. A project for another day.)