Tag Archives: charts and graphs

The chart here is from the National Center for Health Statistics paper Maternal Mortality Rates in the United States, 2020 by Donna L. Hoyert (2/23/2022). A definition:

A maternal death is defined by the World Health Organization as, “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes” (1). Maternal mortality rates, which are the number of maternal deaths per 100,000 live births, are shown in this report by age group and race and Hispanic origin.

Kevin Drum comments on this in his post The maternal mortality rate has skyrocketed over the past three years. A few quotes:

And the maternal mortality rate for everyone has nearly tripled since the late ’90s. Meanwhile, in Europe, the maternal mortality rate has been steadily dropping and is now about one-third the US rate.

What explains the differences by race according to Drum:

And we’re still in the dark about why Black women suffer such an astonishingly high rate of maternal mortality. As I said three years ago:

Poverty, education level, drinking, smoking, and genetic causes don’t seem to explain the black-white difference in maternal mortality. The timing of prenatal care doesn’t explain it. Medically, the cause of the difference appears to be related to the circulatory system, which is sensitive to stress. This makes the toxic stress hypothesis intuitively appealing, but it has little rigorous evidence supporting it. There’s some modest evidence that wider use of doulas could reduce both infant and maternal mortality, but no evidence that it would reduce the black-white gap.

Low income is weakly associated with higher maternal mortality rates, but it explains very little. The allostatic stress theory is appealing but probably wrong. And racism doesn’t seem to play much of a role either.

The CDC article has links to data.

The climate.gov article Climate Change: Incoming Sunlight by Rebecca Lindsey (9/1/2009 – an oldie but a goodie) gives a comprehensive overview of what we know about the energy from the Sun. A few highlights from an article worth reading:

A comprehensive review of published scientific research by the Intergovernmental Panel on Climate Change concluded that, averaged over the solar cycle, the best estimate of the Sun’s brightness change between the pre-industrial period and the present (2019) is 0.06 Watts per square meter. That increase could be responsible for about 0.01 degrees Celsius—around 1 percent—of the warming the planet has experienced over the industrial era (0.95–1.2 degrees Celsius in 2011–2020 versus 1850–1900).

Additional experiments have compared the impacts of grand solar minimums of different strengths with different emissions paths. For example, for a future in which greenhouse gases follow an intermediate pathway (RCP 6.0), one experiment found that a relatively weak Grand Solar Minimum, during which total solar irradiance dropped by 1.3 Watts per square meters for 5 decades in the middle of this century, could reduce global warming by 10%. To reach a 20% reduction in global warming, the Grand Solar Minimum would have to be very strong: sunlight at the top of the atmosphere would need to drop by nearly 6 Watts per square meter. A drop that large would significantly exceed what our current understanding of the Sun says is realistic.

Another study estimated that at pre-industrial carbon dioxide levels, summer insolation at 65° North need only dip 0.75 standard deviations below the mean—about 15 Watts per square meter—for summers to be too cool to melt all the winter snow, a low that Milankovitch cycles predict we will next hit about 50,000 years from now. At 400 parts per million, summer insolation would need to fall twice as much—a low we will next see 125,000 years from now. At carbon dioxide levels above 560 parts per million, the study predicted, no Milankovitch variation within the next half million years will be low enough to trigger an ice age.

There are a number of graphs and some links to data.

Exploring Our Fluid Earth has some educational materials for science. For example, the page Compare-Contrast-Connect: Seasonal Variation in Ocean Temperature Vertical Profiles includes the graph copied here.  Some of these graph have inflection points which relate (I think) to thermoclines (transition between warmer surface water and colder deep water). There certainly seems to be a calculus connection here. For QL folks the graphs are a little tricky based on the y-axis and math folks would probably prefer the depth as the x-axis (why?). There are links on the right sidebar to other projects and information.

From NOAA’s May 200 Global Climate Report:

The May global surface temperature was 1.39°F (0.77°C) above the 20th-century average of 58.6°F (14.8°C). This ranks as the ninth-warmest May in the 143-year record, 0.30°F (0.17°C) cooler than the warmest May months (2016 and 2020). It was the coolest May since 2013, but it still marked the 46th consecutive May and the 449th consecutive month with temperatures, at least nominally, above the 20th-century average. The ten warmest May months have all occurred from 2010 to present.

Some highlights for May 2022:

There are several top-10 ranks to note for May 2022. In particular, it was the eighth-warmest May for the global ocean, the eighth-warmest for the Northern Hemisphere as a whole, the eighth-warmest for Europe (associated with a heatwave in southwestern Europe), and the sixth-warmest for Asia (associated with above-average temperatures in western Siberia).

Time series data is available at a link near the top of the page.

Pew has a feature, Public Trust in Government: 1958-2022 (6/6/2022), with three interactive graphs answering this question. In general,

When the National Election Study began asking about trust in government in 1958, about three-quarters of Americans trusted the federal government to do the right thing almost always or most of the time. Trust in government began eroding during the 1960s, amid the escalation of the Vietnam War, and the decline continued in the 1970s with the Watergate scandal and worsening economic struggles. Confidence in government recovered in the mid-1980s before falling again in the mid-1990s. But as the economy grew in the late 1990s, so too did confidence in government. Public trust reached a three-decade high shortly after the 9/11 terrorist attacks, but declined quickly thereafter. Since 2007, the shares saying they can trust the government always or most of the time has not surpassed 30%.

The one graph copied here also makes it obvious how opinions by political leaning shift on cue when a president of the other party is elected. Each graph in the article has a link to the data.

The chart here is from the Our World in Data article After millennia of agricultural expansion, the world has passed ‘peak agricultural land’ by Hannah Ritchie (5/30/2022).  Interestingly

Despite this reduction in agricultural land, the world has continued to produce more food. This is true of both crops and livestock.⁵

We see this decoupling in the chart that presents the UN FAO’s data. It shows that global agricultural land – the green line – has peaked while agricultural production – the brown line – has continued to increase strongly, even after this peak.⁶

When we break each agricultural component out individually, or look at it in physical rather than monetary units, we find the same trend: a continued increase in output. You can explore this data for any crop or animal product in our Global Food Explorer.

We should note:

The third, as I mentioned earlier, is that global croplands are still expanding. We see this in the chart. Other sources suggest that this rate of increase might be even faster.¹¹ The World Resources Institute looks at this research in more detail here.

The article has three graphs and the data for each can be downloaded.

One more post from the Manhattan Institute’s* Breaking Down the 2020 Homicide Spike by Christos A. Makridis and Robert VerBruggen (5/18/2022). We first note:

Homicides went up throughout the country, and for every major demographic group, in 2020, but they did not rise for everyone equally, as is clear when we break down the numbers by race, age, sex, urbanicity, and region of the country.

Related to figure 3 (copied here) we have this, which is excellent  QL material:

The racial and ethnic breakdown is perhaps most striking in this regard. Proportionally, homicide rates rose by about 34% for black Americans and about 19% percent for non-Hispanic whites: a notable, but not extreme, gap (Figure 3). But since the black homicide rate was already many times higher than the white one, this translated into 8 additional black deaths for every 100,000 population—an increase similar to the total homicide rate for the country as a whole—while the death rate for whites rose by only 0.5 per 100,000. (Recall that these numbers pertain to the homicide victims, not the killers, though American homicide is overwhelmingly intraracial.)

There is a lot to discuss in this article as well as ample quantitative literacy material. There is a discussion of methods and the CDC data they use is easy enough to locate.

* (This is the same note from Monday’s Post) Yes, MI has a clear political leaning but that doesn’t make their work incorrect. Their data and methods are sound here and this should be engaged not ignored. If someone thinks something is incorrect then let me know.

The Manhattan Institute* has a lengthy report on the increasing homicide rate, Breaking Down the 2020 Homicide Spike by Christos A. Makridis and Robert VerBruggen (5/18/2022), with numerous interesting charts. From the report (figure 7 copied here):

Next, we explore the correlation between two geographic factors—population and GOP vote share—and the growth rate in the homicide rate per capita between 2019 and 2020. Each observation is a county whose size is determined by its population, giving larger counties greater weight. Counties with a higher share of GOP voters not only have lower homicide rates but also a lower growth in homicide rates between 2019 and 2020 (Figures 6 and 7).

There is a positive correlation between population in a county and the growth in the homicide rate, but the correlation between population and just the homicide rate is slightly negative (Figure 8). In this sense, even though there are slightly higher rates of homicide deaths per capita in smaller counties, some of those differences could be driven by spurious factors that are correlated with population.

There is a lot to discuss in this article as well as ample quantitative literacy material. There is a discussion of methods and the CDC data they use is easy enough to locate.

* Yes, MI has a clear political leaning but that doesn’t make their work incorrect. Their data and methods are sound here and this should be engaged not ignored. If someone thinks something is incorrect then let me know.

The climate.gov article Can we detect a change in Atlantic hurricanes today due to human-caused climate change? by Chris Landsea and Tom Knutson (5/11/2022) is a great example of the challenges in understanding complex systems. If all you want is the answer:

Atlantic hurricanes display distinct busy and quiet periods:  Busy hurricane decades occurred in the late 19th century, mid-20th century, and from the mid-1990s onward, but quieter decades in the early 20th century and in the 1970s to early-1990s.

These multi-decadal variations in Atlantic tropical storms and hurricanes have been linked to a phenomenon called the Atlantic Multidecadal Variability, which may be primarily natural internal variability or aerosol-driven.

A detectable greenhouse gas-induced influence on observed Atlantic tropical storm and hurricane behavior to date is difficult to identify because of the 50-80 year variability in hurricane activity.

The bottom-line answer to the question in the title is: No, we cannot confidently detect a trend today in observed Atlantic hurricane activity due to man-made (greenhouse gas-driven) climate change. Some human influence may be present though still below the threshold for confident detection.

There is a difference between more hurricanes and worse hurricanes.

Finally, a number of studies have found that several Atlantic hurricane metrics, including hurricane maximum intensities, hurricane numbers, major hurricane numbers, and Accumulated Cyclone Energy have all increased since around 1980.

However, in a 2019 tropical cyclone-climate change assessment, the majority of authors concluded that the recent hurricane activity increases mentioned above did not qualify as a detectable man-made influences (meaning clearly distinguishable from natural variability). Another hurricane metric, the fraction of rapidly intensifying Atlantic hurricanes, was reported to have increased since around 1980 (Bhatia et al. 2019), and they found that this change was highly unusual compared with simulated natural variability from a climate model, while being consistent in sign with the expected change from human-caused forcing. Even so, however, their confidence was limited by uncertainty in how well the single climate model used was representing real-world natural variability in the Atlantic region.

We tend to think of corporate taxes as a federal issues and less a local issue, but the article Reclaiming corporate tax revenues by Josh Bivens (4/14/2022) in EPI has some key takeaways:

Depending on how it is measured, the effective state and local tax rate on corporate profits shrunk by between a third and a half between 1989 and 2017.

The resulting revenue shortfall is estimated to be at least $43 billion and possibly as high as $57 billion.

The erosion of state corporate income tax revenue has nothing to do with corporations’ ability to pay. Indeed, corporate profits have risen even as corporate tax revenues have declined.

This has real consequences for state and local spending—constraining these governments’ ability to provide basic services to their residents.

State and local (S&L) public investment is more than the Fed:

For most years since 1979—and for all years since 1988—the S&L sector has directed more public investment than the federal government. By 2019 this gap was quite large, with public investment from the S&L sector equaling 2.0% of GDP while investment from the federal government totaled just 0.8% of GDP. In dollar terms, that’s a gap of roughly $220 billion annually.

The article is detailed with numerous charts (and data). Worth reading.