Sea levels and impact on the United States.

[telemann.livejournal.com]

As a follow-up to airiefairie's excellent post on March 11, 2012 ("The drowning country: a case of climate migration"), I wanted to share a new report that has been released in the interim.


NBC Nightly News featured a new scientific report suggesting significant changes in sea levels will impact the United States much sooner than thought. The report entitled Surging Seas

finds the odds of “century” or worse floods occurring by 2030 are on track to double or more, over widespread areas of the U.S. These increases threaten an enormous amount of damage. Across the country, nearly 5 million people live in 2.6 million homes at less than 4 feet above high tide — a level lower than the century flood line for most locations analyzed. And compounding this risk, scientists expect roughly 2 to 7 more feet of sea level rise this century. [see graphic below]

The report has been made available online, and Climate Central has designed a super elegant and user friendly interactive map to see what impact sea level changes will have on your own community. The map draws its information from a peer reviewed study. And it uses the National Elevation Dataset, a product of the U.S. Geological Survey.



The effects of a five foot sea rise on my home town of Hampton, Virginia. The solid blue line indicates the current shoreline, gray shows the areas affected by rising sea levels with the interior blue line the new coast line. The "city" of Poquoson would be completely wiped out. This portion of Virginia is called "Tidewater" and it would be affected the most because of the low laying tidal flats and swampy areas. On a personal note, two weeks ago, my insurance agency dropped home coverage due to my proximity to living near a flood zone in Brooklyn. The letter cited increased risks from hurricanes and other issues associated with climate change (i.e. rising sea levels).

Here what happens to Staten Island, Brooklyn, and Queens (5 foot rise):




This is the full feature from NBC Nightly News (you *MAY* have to refresh your browser page to reload the embedded video correctly ;)

Comments

[mrbogey.livejournal.com]

'Anyone who believes Krugman's arguments could have written your reply word-for-word except for the name.

Of course. They're perfectly capable. I meant it more of a joke than a serious argument against Krugman.

Let's roll this back to climatology. We're talking primarily about the accuracy of models, right?

How can we be certain models are accurate? Maybe the problem here is that the people who support the current models that I talk to online don't have the knowledge to accurately relay the critique or explain it. Certainly possible. But when I'm told that the models are accurate because they fit past events, the question I have is that "isn't that to be expected?"

When you model something based on past events, you're going to have by that very nature a model that matches it. It's a sound logical premise to me. That should be able to be explained to me or at least answered in such a way that I could pose it to a "denialist" for a rebuttal.

The only problem I see with my argument about weighing knowledge is humanity is stubborn and will generally refuse to admit errors. But I can't be faulted for the failings of others to accept the errors of their arguments. Clearly when my argument is right.

(yes, that last set of sentences was a joke)

[spaz-own-joo.livejournal.com]

The answers you're looking for with this objection lie in information theory, actually. If you're a computer type this should work well for you.The Shannon entropy (http://en.wikipedia.org/wiki/Entropy_(information_theory)) of a climate model or of a historical dataset is essentially the amount of actual information contained in it. Not proportional to the length of the data, but to the length of the shortest program one could write to print that data.

Models where the algorithm itself contains more information than the information contained in the accurate component of their 'predictions' of past data, are to be suspected of being post-hoccy.

Models where the algorithm manages to create more 'correct' data than it itself contains, are nearly certain to have demonstrated at least a partial algorithmic underpinning of the climate dataset.

[mrbogey.livejournal.com]

Nteresting, I'll have to review this.

[spaz-own-joo.livejournal.com]

By analogy, the fact that FLAC, mp3, and other audio codecs really do achieve a reduction in file size, actually constitutes a rigorous scientific proof of the algorithms' underlying assumption - that audio data (or at least, the kinds of audio data that humans are ever interested in listening to) is at least partially predictable.

The Shannon entropy in a minute of truly random CD-quality white noise approximately equals the size of that .WAV file, but the Shannon entropy of a minute of music is far lower. That's why it can be compressed at all!