The U.S. Bureau of Labor Statistics has an interactive graph of unemployment for cities from Jan 2020 to Jan 2021.
Unemployment rates were higher in January 2021 than a year earlier in 376 of the 389 metro areas, lower in 9 areas, and unchanged in 4 areas. The largest over-the-year unemployment rate increase occurred in Kahului-Wailuku-Lahaina, Hawaii. Rates rose over the year by at least 5.0 percentage points in an additional 11 areas.
Unemployment rates were 10.0 percent or higher in 21 metro areas in January 2021. This was greater than the 4 areas with unemployment rates of at least 10.0 percent in January 2020 but much less than the 339 areas in April 2020, at the onset of the COVID-19 pandemic.
The data is available on the page and provides unemployment rates for metropolitan areas from Jan 2020 to Jan 2021.
The Our World in Data article How much economic growth is necessary to reduce global poverty by Max Roser (2/15/2021) includes the graph copied here. Note that all countries incomes are adjusted for price differences so it is fair comparison from county to country. It is easy to forget how much wealthier the U.S. is compared to almost all other countries.
The reason why such substantial economic growth is necessary for reducing global poverty is that the average income in many countries in the world is very low: 82% of the world population live in countries where the mean income is less than $20 per day.
There are three other graphs in the article, which is suitable for a QL based course. There isn’t data associated with these particular graphs but there are links at the top of the article with related economic data.
Averaged as a whole, the February 2021 global land and ocean surface temperature was 0.65°C (1.17°F) above the 20th century average—the smallest February temperature departure since 2014. However, compared to all Februaries in the 142-year record, this was the 16th warmest February on record.
During the month, La Niña continued to be present across the tropical Pacific Ocean during February, helping dampen the global temperatures. Meanwhile, a strong negative Arctic Oscillation (AO) was also present during the first half of the month. Similar to the ENSO affecting global temperatures, the AO can influence weather patterns across the mid-latitudes. In a negative AO phase, the jet stream weakens and meanders, creating larger troughs and ridges. This allows really cold Arctic air to reach the mid-latitudes. Across the U.S., a trough over the central U.S. combined with a ridge over northern Canada to produce a Rex block, which is a blocking pattern that disrupts the jet stream and leads to more prolonged weather patterns. The AO on February 10–11 was -5.3, which essentially ties February 5, 1978 and February 13, 1969 for the lowest February value on record. They were also among the lowest 35 values for any day of the year (>99.9 percentile). By February 26, it had rebounded to +2.7 (97th percentile). The February mean AO was -1.2.
The time series data is available in the links in the additional resources box near the top of the article.
The climate.gov article Understanding the Arctic polar vortex by Rebecca Lindsey (3/5/2021) is a complete primer on the polar vortex, jet stream, and what we know (and don’t) abut the connection to climate change.
According to NOAA stratosphere expert Amy Butler, people often confuse the polar vortex with the polar jet stream, but the two are in completely separate layers of the atmosphere. The polar jet stream occurs in the troposphere, at altitudes between 5-9 miles above the surface. It marks the boundary between surface air masses, separating warmer, mid-latitude air and colder, polar air. It’s the polar jet stream that plays such a big role in our day-to-day winter weather in the mid-latitudes, not the polar vortex.
Any relationships to climate change is unclear, for example:
The uncertainty due to a relatively short history of observations isn’t the only reason experts can’t dismiss the possibility that something could be up with polar vortex. Some climate model experiments do predict that continued warming will lead to a weakening of the polar vortex. “It’s true that when you run some high-resolution climate models, with a realistic stratosphere, and a realistic sea ice layer, and you reduce sea ice cover, these models predict that the polar vortex gets weaker,” Butler said. And some studies combining models and observations have shown a connection between low sea ice extent in the Barents and Kara Seas of the eastern Arctic, sudden stratospheric warming events, and cold winters in North America.
At the same time, other model simulations predict that warming and sea ice loss will lead to a stronger polar vortex. Part of the reason for the disagreement is that the impact of Arctic surface warming and sea ice loss on the atmospheric waves that can disrupt the polar vortex is very sensitive to exactly where and when the sea ice loss occurs, and that hasn’t been consistent across model simulations.
No data in this article but there are some useful graphs, such as the one copied here, and the article is just generally interesting.
Wages grew largely because more than 80% of the 9.6 million net jobs lost in 2020 were jobs held by wage earners in the bottom 25% of the wage distribution. The exit of 7.9 million low-wage workers from the workforce, coupled with the addition of 1.5 million jobs in the top half of the wage distribution, skewed average wages upward.
There are seven graphs or tables in the article with the associated data. The last two graphs are of the same type as the one copied here but for the 2000 and 2008 recessions, respectively.
In both 2019 and 2020, project developers in the United States installed more wind power capacity than any other generating technology. According to data recently published by the U.S. Energy Information Administration (EIA) in its Preliminary Monthly Electric Generator Inventory, annual wind turbine capacity additions in the United States set a record in 2020, totaling 14.2 gigawatts (GW) and surpassing the previous record of 13.2 GW added in 2012. After this record year for wind turbine capacity additions, total wind turbine capacity in the United States is now 118 GW.
There are two other graphs in the article and an answer to the question of which state generates the most wind power. There are also links to the data.
Voting members of the 116th Congress collectively produced more than 2.2 million tweets and Facebook posts in 2019 and 2020. That means the median member of Congress produced more than 3,000 posts across their profiles on the two social media platforms during this span.
The 3000 sound like a lot but amounts to only about 8 posts a day and I have to imagine that some of it is done by aides.
There are two other charts in the article and a detailed methodology section. There is also a link to a related article which includes the number of laws passed from the 101st through 116th congress.
As we try to quantify the deaths by COVID-19 we need to measure it correctly. For example, deaths should be normalized to population size. Beyond that, we should really look at excessive mortality, that is mortality above what we might see without COVID-19. Some causes of deaths have decreased over the last year. Our World in Data does just this on their Excess mortality during the Coronavirus pandemic (COVID-19) page. Not only do they provide interactive graphs, such as the one copied here but also an explanation of the methodology.
A measure that is more comparable across countries is the P-score, which calculates excess mortality as the percentage difference between the number of deaths in 2020–2021 and the average number of deaths in the same period — week or month — over the years 2015–2019.
While the P-score is a useful measure, it too has limitations. For example, the five-year average death count might be a relatively crude measure of expected deaths because it does not account for trends in mortality or population size. To learn about other measures of excess mortality and their strengths and limitations, see our article with John Muellbauer and Janine Aron.
Note that the graph has times were for, say Italy, deaths were twice what would normally be expected, but at other times actually negative. As always Our World in Data provides the data and other graphics.
Another factor driving changes in U.S. Western wildfires is a greater availability of fuel. Drier air stresses vegetation, making forests more susceptible to severe wildfires, while droughts are creating more dead fuel.
“Climate affects how long, how hot and how dry fire seasons are,” she said. “As climate warms, we’re seeing a long-term drying and warming of both air and vegetation.”
Yet another factor driving changes in Western U.S. wildfires is a greater number of ignition sources, both natural and human-caused.
There are other graphs in the article and a link to the paper that produced the graph copied here.
We are now ready to delve into the core of the dispersion model: the advection scheme . It revolves around a central differential equation that integrates all phenomena at stake to give an estimate of a particle velocity, or the plastic’s speed through water. Basically, our methods calculate the particle’s velocity at a given time with a formula and use it to estimate where the particle will be a few minutes later. We repeat this process over a long period of time to get a series of positions, i.e., a trajectory of where the plastic goes.
Interesting data storage needs:
As this process has to be repeated over years, the datasets containing wind and speeds all around the globe can take up a lot of space. For instance, the LLC4320 global circulation model uses no less than 5 petabytes of data to be stored. At The Ocean Cleanup, we often use HYCOM data for currents (illustrated below), and GFS for the wind; and our datasets require at least 1.5 terabytes to be stored.