Gore on the Arctic (again)

ANOTHER BOLD PREDICTION OF AN ICE-FREE ARCTIC

Guest post by Mark Johnson

Al Gore trumpets the latest conclusions of Climate Change Advocate David Barber. “Sea ice in Canada’s fragile Arctic is melting more quickly than anyone expected,” says University of Manitoba Prof. David Barber, the lead investigator of the Circumpolar Flaw Lead System study released Friday. Barber is the lead investigator in the largest climate change study done in Canada. Barber said before the expedition, scientists were working under the theory that climate change would happen much more slowly.

It was assumed the Arctic would be ice-free in the winter by 2100. “We expect it will happen much faster than that, much earlier than that, somewhere between 2013 and 2030 are our estimates right now. So it’s much faster than what we would expect to happen. That can be said for southern climates as well.” “We’re seeing it happen more quickly than what our models thought would happen,” Barber said.

When you read the article, notice a few things:

1) The conclusions are ALL Based on CLIMATE MODELS.

2) Canada Government paid $156-million to Barber et al for the study.

3) The Inuit population are starting to chase the cash cow as well: “There’s also the need for economic development,” Hmmmmmm.

We have finally heard from the Great Climate Change Advocate Al Gore. On his obscure blog, Al says “Its worse than we thought.” Are you kidding me?

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Obscure blog? Let’s look at the numbers for Al Gore -vs- WUWT and find out.

Yup.

In fact, WUWT does pretty well when you look at the entire family of web offering by Gore’s enterprises:

Keep those hits and links coming folks. Thanks – Anthony

NOTE: In the Alexa generated graphs above, the lower number the better for traffic rank. For example in the top graph, WUWT is around the top 10,000 trafficked sites on the web while alogore.com is in the top 100,000 trafficked sites on the web. It’s RANK not HITS.

Since some commenters are confused, here is the description from Alexa:

What is Traffic Rank?

The traffic rank is based on three months of aggregated historical traffic data from millions of Alexa Toolbar users and data obtained from other, diverse traffic data sources, and is a combined measure of page views and users (reach). As a first step, Alexa computes the reach and number of page views for all sites on the Web on a daily basis. The main Alexa traffic rank is based on a value derived from these two quantities averaged over time (so that the rank of a site reflects both the number of users who visit that site as well as the number of pages on the site viewed by those users). The three-month change is determined by comparing the site’s current rank with its rank from three months ago. For example, on July 1, the three-month change would show the difference between the rank based on traffic during the first quarter of the year and the rank based on traffic during the second quarter.

How Are Traffic Trend Graphs Calculated?

The Trend graph shows you the site’s daily traffic rank, charted over time. The daily traffic rank reflects the traffic to the site based on data for a single day. In contrast, the main traffic rank shown in the Alexa Toolbar and elsewhere in the service is calculated from three months of aggregate traffic data.

Daily traffic rankings will sometimes benefit sites with sporadically high traffic, while the three-month traffic ranking benefits sites with consistent traffic over time. Since we feel that consistent traffic is a better indication of a site’s value, we’ve chosen to use the three-month traffic rank to represent the site’s overall popularity. We use the daily traffic rank in the Trend graphs because it allows you to see short-term fluctuations in traffic much more clearly.

It is possible for a site’s three-month traffic rank to be higher than any single daily rank shown in the Trend graph. On any given day there may be many sites that temporarily shoot up in the rankings. But if a site has consistent traffic performance, it may end up with the best ranking when the traffic data are aggregated into the three-month average. A good analogy is a four-day golf tournament: if a different player comes in first at each match, but you come in second at all four matches, you can end up winning the tournament.