Originally tweeted by Ryan | Forecast (@RyanMaue) above December 24, 2021.
Tonight, I’ll be talking about Temperature Abnormality maps and how they’re built, used, abused, and abused for weather and climate, including science and advocacy. This will be fun.
Using weather models or historical observation data, grids are formed of daily, monthly and yearly temperatures over a given period of time which can be 20 years or 100+ years.
This Period of Record (POR) dataset is then used to select or construct a baseline climate, for example 1991-2020.
This map is Japanese grid reanalysis data updated monthly – a kind of weather model result from continuously run forecasts using a modern but original data model from many decades ago. This is meant to faithfully represent the real state of the 3D atmosphere and ocean.
The baseline used here is 1991-2020 known as the Climate Normal Period. You can often see 1981-2010 or 1961-1990 or even 1951-1980. These three decades are designed to represent climate regardless of rapid change.
Compare that to the previous December 2015 in El Niño. The global anomaly is +0.53°C above the 1991-2020 average, while this December 2021 is +0.27°C. Yes, that is a cooling of 0.25°C by comparison. direct.
But you wouldn’t say that global warming has stopped because December 2021 is colder than December 2015. That would be misinformation given the proper context – and that is an upward trend in the long-term data. convincingly.
This is the daily anomaly since 1990 from the same Japanese data set.
This is a daily global temperature anomaly flattened out by running a 30-day average. You will see significant spikes on weekly and monthly time scales amid a slowing global warming trend.
What causes thorns? The oceans and atmosphere are mainly through weather.
Zoom in closer to see small daily changes in global temperature, that is, record daily temperature anomalies of up to 4 times when the Earth is half-dark/half-sun.
Test wild range from -0.4°C to +0.4°C from March 2021 to April 2021. That is +0.8°C for a month. Gosh!
Here’s a current example from ECMWF’s operational weather modeling. The global T anomaly dropped from +0.21°C to -0.12°C in 10 days, significantly cooling the globe by 0.33°C. Yes, that is entirely related to the weather in short time range – and here’s the background on how cold/warm air affects land.
But I see more red than blue, obviously which is warmer. I’d say it’s misleading because maps are planar projections and the most extreme values are most certainly concentrated in narrow or small regions. Plus, this is an instant snapshot while the story is different for 24 hours.
However, I see extremely warm temperatures in the US and a global anomaly of +0.20 °C so that is evidence of climate change.
That is misleading for 2 reasons:
You can’t point to 1% of the Earth and say “climate change” when it’s obvious that there is a cold balance elsewhere.
And, you can’t compare raw temperature anomalies across different parts of the globe at the same time!
Why? The typical background variance or change in temperature on a given day can be +/- 50°F in Alberta or Minnesota compared to just +/- 1°F in the tropics.
You have to normalize!
Taken together, comparing small areas of temperature anomalies across different regions of the globe is doubly wrong, a great sin.
Remember that you need to look at global anomalies on a long time scale, not daily weather map comparisons.
Next, the color scale
If you color the daily temperature anomaly map with only 1 color representing the global anomaly of -0.12°C, it will be gray, with no signal. A blank gray map. All anomalies from -24°C to +30°C are globally averaged gray. Great!
Let’s do the same for the Year to date. The color scale is cut in half so the gray is +/- 0.25°C but the global temperature anomalies are the same.
You can definitely spot La Niña’s dominance in the tropical Pacific (the blues are cooler).
Originally tweeted by Ryan | Forecast (@RyanMaue) above December 24, 2021.
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