Tag Archives: charts and graphs

From NOAA’s November 2022 Global Climate Report:

The November 2022 global surface temperature departure was the ninth highest for November in the 143-year record at 0.76°C (1.37°F) above the 20th century average of 12.9°C (55.2°F). Despite ranking among the ten warmest Novembers on record, this November was the coolest November since 2014. November 2022 marked the 46th consecutive November and the 455th consecutive month with temperatures, at least nominally, above the 20th century average.

A few of highlights:

Europe tied 2000 for its third-warmest November on record.

The contiguous U.S. had a November that was 0.7°F cooler than average.

However, New Zealand recorded its warmest November on record according to its state meteorological agency. The warmest three Novembers in New Zealand have all occurred since 2019.

Time series data is available near the top of the page.

The answer to the question depends on where you live, which will dictate the odds of snow on the ground on Dec 25.  If you aren’t sure then take a look at the map on the NOAA’s climate.gov article Interactive map: Are you dreaming of a white Christmas? by Rebecca Lindsey and Susan Osborne (12/6/2022).

The interactive map on the page allows you to zoom in on a dot and get information about the chance of at least an inch of snow on the ground on Dec 25.  Here in Ithaca we have a 51% chance of at least an inch of snow on the ground. The page includes links to other maps and at the bottom there are links to other snow related resources. There is a link to download a spreadsheet of the data which includes the state and location name, along with elevation and the chance of snow. Is there relationship between elevation and snow on Dec 25? This seems like a stats project in the making.

In a follow up to the last post, How much has sea level risen locally? (12/1/2022), we have the IPCC Sea Level Projection Tool. The NOAA sea level trends tool looks at the historic data and adds linear regression lines. The IPCC tool has projections based on the different IPCC scenarios. For example, when you first land on the page you will see blue dots on a map. A dot with a number means there are a cluster of dots nearby so zoom in.  I went to the Miami beach dot. Click on the dot and then click full projections. This will bring you to a page with two interactive maps. The first is a curve of seal level change (relative to the 1995-2014 baseline) projected out to 2150. You can select one of the six IPCC scenarios.

The other graph, seen here, allows you to select an increase in sea level and provides estimates for when that will occur, with the black circle being the median year.  The graph here is the data at which we see about one foot of sea level rise in Miami. In both graphs there is a link to download the data.

A related article from NASA, NASA Study: Rising Sea Level Could Exceed Estimates for U.S. Coasts by Sally Younger (11/15/2022) provides some interesting context such as:

The hazards of rising sea level are amplified by natural variabilities on Earth.

For instance, by the mid-2030s, every U.S. coast will experience more intense high-tide floods due to a wobble in the Moon’s orbit that occurs every 18.6 years. Hamlington said that this lunar cycle, in combination with rising sea level, is projected to worsen the impacts of high-tide flooding during the 2030s and 2040s.

The World Bank Data Blog provides information on food prices in the article Food prices eased but risks remain elevated by John Baffes & Kaltrina Temaj (11/21/2022)

The World Bank’s Food Price Index declined 12% in the third quarter of 2022 (q/q) after reaching an all-time high in April. The index remains almost 20% higher than a year ago.  In domestic currency terms, however, food prices remain elevated due to currency deprecations. Food prices are expected to fall 5% in 2023 before stabilizing in 2024. Despite the expected declines, most food prices will remain high by historical norms. The forecasts are also subjected to numerous risks.

The article has total of 7 graphs, most of them are interactive, and interesting information:

Supply disruptions, increasing production costs, and appreciation of the U.S. dollar have exerted upward pressure on domestic food price inflation in most countries.  Food price inflation in South Asia averaged 20% in the first three quarters of 2022 (y/y); the average for most other regions was 14%. The exception was the East Asia and the Pacific region where food price inflation averaged just 6%, in part due to stable rice prices, a key staple in the region.

There are links to the data but it may take some work to get it. This is a rich QL article. For example, a good assignment is use the graph to verify the percentages in the first quote above.

From NOAA’s October 2022 Global Climate Report:

October 2022 was the fourth-warmest October in NOAA’s 143-year record. The October global surface temperature was 1.60°F (0.89°C) above the 20th-century average of 57.1°F (14.0°C). The past seven Octobers were among the ten warmest Octobers on record.

A few highlights:

Europe had its warmest October on record at 2.6°C (4.6°F) above the 1910-2000 average. This surpassed the previous record, set in 2020, by 0.38°C (0.68°F). More than seven countries in Europe recorded their warmest or joint-warmest October on record.

Austria had its warmest October on record. Austria’s national weather service reported that the average temperature was 2.8°C above the 1991-2020 baseline in the lowlands, and 4.0°C warmer in the mountains.

According to MeteoSwiss, Switzerland had its warmest October since the country began its records in 1865, with an average temperature 3.7°C above the 1991-2020 average.

Belgium tied 2001 for its warmest October on record, 3.1°C warmer than the 1991-2020 average, according to Belgium’s Royal Meteorological Institute.

MeteoFrance reported that France had its warmest October since records began in 1945, about 3.5°C above the 1991-2020 normal.

The time series data is available near the top of the page under Additional Resources.

From Our World in Data’s post Data Update: We’ve just updated all of our global CO2 emissions data by Pablo Rosado, Hannah Ritchie, and Edouard Mathieu (11/11/2022):

There is one major update in this year’s carbon budget.

National emissions data was only available for CO₂ emissions from fossil fuels and industrial processes (such as cement production). It did not include emissions from land use change.

This year’s update – for the first time – now includes land use estimates for countries, extending back to 1750.

The CO2 Data Explorer is a great tool.  Users can select countries, different emission types (cement is interesting), total or per capita, etc. The data can also be downloaded. Go explore.

The UNESCO press release, UNESCO finds that some iconic World Heritage glaciers will disappear by 2050 by François Wibaux (11/3/2022) provides a list of glaciers likely to be gone by 2050. For example,

According to available data, glaciers in all World Heritage sites in Africa will very likely be gone by 2050, incl. Kilimanjaro National Park and Mount Kenya

Glaciers in Yellowstone National Park (United States of America) – very likely to disappear by 2050

Glaciers in Yosemite National Park (United States of America) – very likely to disappear by 2050

The graph here is from the full report (link in the press release) which also contains some useful tables of data. A quote  speaking calculus in the press release:

But a new study by UNESCO, in partnership with IUCN, shows these glaciers have been retreating at an accelerated rate since 2000 due to CO₂ emissions, which are warming temperatures. They are currently losing 58 billion tons of ice every year – equivalent to the combined annual water use of France and Spain– and are responsible for nearly 5% of observed global sea-level rise.

Why does this all matter:

Half of humanity depends directly or indirectly on glaciers as their water source for domestic use, agriculture, and power. Glaciers are also pillars of biodiversity, feeding many ecosystems.

In the past I’ve posted about pew surveys presenting very split opinions by the D and the R teams. Today we have an interesting one within the D team in the Pew article Violent crime is a key midterm voting issue, but what does the data say? by John  Gramlich (10/31/2022). Key quote:

Differences by race are especially pronounced among Democratic registered voters. While 82% of Black Democratic voters say violent crime is very important to their vote this year, only a third of White Democratic voters say the same.

There are a couple of graphs in the article and plenty of quantitative information. What is particularly nice is the discussion about views on violent crime and some disconnects. The article does a great job of discussion possible reasons for this disconnect.

How we answer this questions depends on what we mean by best and the comparison group. For today we’ll look at the share of income by the top 1% and compare mostly western Europe countries. The graph here is from the world income database. It is good to be in the top 1% in the U.S. where they take home home 19% of the countries income in 2021. China is next at 14%. Note that this is a statement of the share of income and not what the income is.

The link will take you to the page where the graph is from. There is also a map colored by ranges of income by the top 1% and if you click on the country in the map it is added to the time series. The U.S. just missed the top color of 19-31% (I’m assuming it starts at greater than 19). Try to guess the countries in the top category and which one is tops at 31%. There is also a link to download the data, as well as other indicators to choose from.

If you pay attention to my monthly global temperature updates you might get the impression that global warming has slowed or even stopped. One key variable here is the ENSO (El Niño – Southern Oscillation). The graph here is from NOAA’s Monthly Temperature Anomalies Versus El Niño | September 2022 Global Climate Report:

Several observations are apparent in the figure. First, nearly every month since the late 1970s has been above the 20^th century average, and has generally warmed through the period. Second, El Niño-like conditions (those months in red) tend to be warmer than neighboring periods, and La Niña-like conditions (blue) tend to be cooler. Third, protracted El Niño-like episodes tend to warm through the event, while La Niña-like episodes tend to cool through the event. Fourth, and finally, there are exceptions to all of the above points.

We haven’t had an El Niño event since 2018-2019 and have been in a La Niña period for quite some time. We have generally been warmer over the last year than all but the last two El Niño events. Fear not, we’ll set records again when the next El Niño comes around. BTW, this a great graph which shows how adding a third variable by way of color reveals important information.