Follow Up: How old is Arctic Ice?

In a follow up to our May 28, 2018 post, How old is Arctic Ice?, the Washington Post has an article, The Arctic Ocean has lost 95 percent of its oldest ice — a startling sign of what’s to come by  Chris Mooney (12/11/18). It notes:

In 1985, the new NOAA report found, 16 percent of the Arctic was covered by the very oldest ice, more than four years old, at the height of winter. But by March, that number had dropped to under 1 percent. That’s a 95 percent decline.

At the same time, the youngest, first-year ice has gone from 55 percent of the pack in the 1980s to 77 percent, the report finds. (The remainder is ice that is two to three years old.)

The loss of sea ice creates a feedback loop:

There is a well-known feedback loop in the Arctic, caused by the reflectivity of ice and the darkness of the ocean. When the Arctic Ocean is covered by lighter, white ice, it reflects more sunlight back to space. But when there is less ice, more heat gets absorbed by the darker ocean — warming the planet further. That warmer ocean then inhibits the growth of future ice, which is why the process feeds upon itself.

and

Because of this, Arctic sea ice loss has already increased the warming of the planet as a whole. Ramanathan said the impact is equivalent to the warming effect of 250 billion tons of carbon dioxide emissions, or about six years of global emissions.

Ramanathan fears that entirely ice-free summers, if they began to occur regularly, could add another half- degree Celsius (0.9 degrees Fahrenheit) of warming on top of whatever else the planet has experienced by that time.

The Washington Post article has a few nice animated graphics. The graph and map here is from the sea ice sections of the Arctic Report Card: Update for 2018 – Effects of persistent Arctic warming continue to mount from NOAA. The Arctic Report card contains a half dozen charts and graphs including one that compares March and September sea ice extent. A data and project for this is in our Statistics Project page.

Which country emits the most CO2?

The country that emits the most CO2 depends on how it is measured. Our World in Data has a graph of annual share of CO2 emissions by country. By this measurement, a graph with the top 5 countries (China, U.S., India, Russia, & Germany) in 2016 was downloaded from Our World in Data.  In this case, China has been the largest contributor of CO2 since 2005.  In fact, in 2016 China emitted 10,295 million metric tons of CO2 compared to 5,240 million metric tons by the U.S.  On the other hand, from EIA data, in 2016 each person in China emitted 7.3 tons of CO2 compared to a person in the U.S. at 16.2 tons.  The EIA data dates back to 1980, and from 1980 to 2106 China emitted 177,547 million metric tones of CO2 compared to 197,176 for the U.S.  Which is more important, per person, current, or total historical emissions?  How does this create challenges in climate talks? Further analysis with other countries can be done with EIA data. Data can also be downloaded from the Our World in Data post.  The Calculus Projects page has an example of using this data in a calculus class.

How fast is runoff from Greenland ice sheet increasing?

The Nature article Nonlinear rise in Greenland runoff in response to post-industrial Arctic warming by Luke Trusel et. el. (12/5/18)  reports on Greenland ice sheet runoff.  Referring to fig 4a (copied here) in their paper

We show that an exceptional rise in runoff has occurred over the last two decades, equating to an approximately 50% increase in GrIS-integrated runoff compared to pre-industrial runoff, and a 33% increase over the twentieth century alone.

The Woods Hole Oceanographic Institution (WHOI) provides a less technical summary of the paper in their post Greenland Ice Sheet Melt ‘Off the Charts’ Compared With Past Four Centuries (12/5/18).

Ice loss from Greenland is one of the key drivers of global sea level rise. Icebergs calving into the ocean from the edge of glaciers represent one component of water re-entering the ocean and raising sea levels. But more than half of the ice-sheet water entering the ocean comes from runoff from melted snow and glacial ice atop the ice sheet. The study suggests that if Greenland ice sheet melting continues at “unprecedented rates”—which the researchers attribute to warmer summers—it could accelerate the already fast pace of sea level rise.

“Rather than increasing steadily as climate warms, Greenland will melt increasingly more and more for every degree of warming. The melting and sea level rise we’ve observed already will be dwarfed by what may be expected in the future as climate continues to warm,” said Trusel.

The WHOI post includes a short video with a graph similar to the one copied here and a summary of the science.  The Nature article has data available.

As an aside, while we are talking about Greenland,  in NASA news International team – NASA make unexpected discovery under Greenland ice (11/15/18)

An international team of researchers, including a NASA glaciologist, has discovered a large meteorite impact crater hiding beneath more than a half-mile of ice in northwest Greenland. The crater — the first of any size found under the Greenland ice sheet — is one of the 25 largest impact craters on Earth, measuring roughly 1,000 feet deep and more than 19 miles in diameter, an area slightly larger than that inside Washington’s Capital Beltway.

The NASA article includes a short video.

What are six trends in western U.S. wildfires?

NASA’s Earth Right Now blog post  Six trends to know about fire season in the western U.S. by Kasha Patel (12/5/18) provides these trends.  The first (see graph copied here from NASA RECOVER/Keith Weber),

Over the past six decades, there has been a steady increase in the number of fires in the western U.S. In fact, the majority of western fires—61 percent—have occurred since 2000.

There are five other trends with another graph and three maps. The last one notes

Research suggests that global warming is predicted to increase the number of very large fires (more than 50,000 acres) in the western United States by the middle of the century (2041-2070).

The map below shows the projected increase in the number of “very large fire weeks”—periods where conditions will be conducive to very large fires—by mid-century (2041-2070) compared to the recent past (1971-2000). The projections are based on scenarios where carbon dioxide emissions continue to increase.

There isn’t a direct link to the data for the graph here or the other one, but the link to the slides of Keith Weber include an email address. Requests for data for educational purposes are often successful.

More than half the U.S. population lives in what percent of counties?

The answer is the title of the Census Bureau post More Than Half of U.S. Population in 4.6 Percent of Counties by Haya el Nasser (10/24/18). The map copied here shows the counties.

At the county level, the geographic distribution of the estimated 325.2 million people in the United States clearly distinguishes two main areas where people live: “big” counties and “small” counties.

More than half of all residents live in just 143 big counties (in terms of the number of residents), according to an analysis of U.S. Census Bureau county estimates. That means less than half of the population is spread out across the remaining 2,999 small counties.

The post has a short video with more information. For instance the average population density of big counties is 926 people per square mile and only 48 people per square mile for small counties. Small counties are almost 75% non-Hispanic white, while big counties are under 50% non-Hispanic white.

There is also a notable difference in the rate of growth. “Big-county America is growing nearly twice as fast as small-county America,” Sink said. “They’re not only getting bigger but increasingly more diverse.” Thus, if current trends continue, it’s likely that the divide between big and small will continue to become more pronounced in the future.

The post has  another map and some useful tables which include the distribution of small and large counties.

What are the demographics of 6- 21 year olds?

The Pew article Early Benchmarks Show ‘Post-Millennials’ on Track to Be Most Diverse, Best-Educated Generation Yet – A demographic portrait of today’s 6- to 21-year-olds by Richard Fry and Kim Parker (11/15/18)  provides demographic information comparing early boomers, gen xers, millennials, and post millennials.  For example, the graph copied here shows the changes in racial groups across the four generations. The trend toward cities contiues:

The geography and mobility of post-Millennials differ from earlier generations. Reflecting broader national trends, post-Millennials overwhelmingly reside in metropolitan as opposed to rural areas. Only 13% of post-Millennials are in rural areas, compared with 18% of Millennials in 2002. By comparison, 23% of Gen Xers lived in rural areas when they were ages 6 to 21, as did 36% of early Boomers.

The distribution of racial groups by region differs (also see the second graph):

In the West, post-Millennials are just as likely to be Hispanic as non-Hispanic white (both 40%). This stands in contrast to older generations. Among those residing in the West, 45% of Millennials, 50% of Gen Xers and 64% of Boomers are non-Hispanic white. Minority representation among post-Millennials is lowest in the Midwest, where roughly a third (32%) of 6- to 21-year-olds are racial or ethnic minorities.

The Pew report includes 12 charts and a methods section with links to the data.

How effective is gerrymandering?

The article in Isthmus No contest – Dems sweep statewide offices in midterms but remain underrepresented in Assembly by Dylan Brogan (11/15/18) presents the graphic copied here. In short the dems won all races in terms of the popular vote but control only 36 of the 99 seats in the assembly.

“The biggest obstacle remains gerrymandering. There are only a handful of districts that are remotely competitive. That’s why a district court ruled the [legislative] maps unconstitutional and why we still have a case before that court,” says Hintz, referring to Gill v. Whitford which the U.S. Supreme Court sent back to the lower federal court for reargument. “Gerrymandering doesn’t just have an impact on the outcome. It has an impact on being able to recruit candidates. There aren’t a lot of people willing to run when they know they don’t have a shot.”

Three sources to learn more about the mathematics of gerrymandering: The Math Behind Gerrymandering and Wasted Votes by Patrick Honner (10/12/17), Countermanding Gerrymandering with a short podcast with Moon Duchin, and Detecting Gerrymandering with Mathematics by Lakshmi Chandrasekaran (8/2/18) .

Our recent post How do you tell a story with data and maps – Beto vs Cruz? (11/15/18) notes how to obtain election data. The chart made here for WI can be done for other states as a stats project.

What are the predictions for antimicrobial resistance?

The OECD has resources related to antimicrobial resistance (AMR). A summary can be read in the article Stopping antimicrobial resistance would cost just USD 2 per person a year (7/11/18), which included the chart copied here.  The article is rich with quantitative information.

While resistance proportions for eight high-priority antibiotic-bacterium combinations increased from 14% in 2005 to 17% in 2015 across OECD countries, there were pronounced differences between countries. The average resistance proportions in Turkey, Korea and Greece (about 35%) were seven times higher than in Iceland, Netherlands and Norway, the countries with the lowest proportions (about 5%).

Resistance is already high and projected to grow even more rapidly in low and middle-income countries. In Brazil, Indonesia and Russia, for example, between 40% and 60% of infections are already resistant, compared to an average of 17% in OECD countries. In these countries, growth of AMR rates is forecast to be 4 to 7 times higher than in OECD countries between now and 2050.

The full report is available: Stemming the Superbug Tide Just A Few Dollars More. Two other pages have graphs. The Nov 11 post under the same title, Stemming the Superbug Tide Just A Few Dollars More, includes a map and two sets of graph with AMR trends by countries.  On another page, Trends in AMR prevalence rates 2005-2030, users can select up to eight specific bacteria resistance rates, such as Penicillin-resistant S. Pneumoniae prevalence rates, along with any country to create interactive charts of present and projected rates.  The data does not appear to be accessible, but the first article contains contact information at the bottom that might help in getting the data in these reports.

How do you tell a story with data and maps – Beto vs Cruz?

FiveThirtyEight has an excellent article on the 2018 senate race and the possible implications for future elections. The article, What Really Happened In Texas by Kirk Goldsberry (11/14/18) analyzes voting patterns by county and compares 2014 to 2018.  Their graph copied here is the fourth in a series of maps and mostly summarizes the previous maps.

Cruz won by 220,000 votes last week. But in Harris County alone, 500,000 more people voted in the 2018 midterms than had voted in 2014. In Dallas County, 300,000 more people voted than in the last midterms, and in Travis, Bexar and Tarrant counties, 200,000 more people voted.

Indeed, aside from some noteworthy increase in voter numbers in suburban Dallas, the biggest white circles on the map above tend to hover over Beto country. Meanwhile, the darkest red counties — the places that carried Cruz back to Washington — have exhibited very little, if any, change in the number of votes cast compared to 2014. Those areas may be staunchly red, but they’re also staunchly stagnant too. O’Rourke almost won in 2018 by taking roughly 60 percent of the vote in the big five counties. This map suggests that if Democrats can repeat that feat as these places continue to grow, that may be all they need to turn Texas blue.

The data for their analysis comes from the Texas Secretary of State election results.  The 2014 data is available by following the Historical Election Results (1992-current) link. The 2018 data is available through a link along the top. This is a stats project in the making (do this for you home state). The article can also  be used in a QL course.