Comment of the US temperature data

The following graph was published and the source is wattsupwiththat.com

It is a snapshot from June 2005 to May 2022, taken from data available at the US Climate Reference Network: ref: https://www.ncei.noaa.gov/access/crn/qcdatasets.html

Using the same data I have constructed the same graph – verified.

At first, glance that looks like a 15-year pause.

Research Question: Is it reasonable to conclude that there has been no increase in temperature in the USA since 2005, and what if anything can be said about the worldwide situation?

Based on the trend shown in the graph from 2005 it looks like there is an upward trend – see the higher highs, see the bunching effect near 2015-2022, but maybe I see incorrectly – biased.

Time series are hard to study. There are often trends that are hard to see.

One thing to do is consider a moving average and look at the yearly trend.

If we do this a trend is easier to spot. The lower average temperatures are increasing and the time period is shorter.

The top is fluctuating, much like the first graph. But you will notice that the trend line shows a positive gradient (i.e. the number in front of x)

The UAH is satellite reconstruction by Dr Spence and RSS is via a private firm. You notice the key thing is that they agree.

This is not a trick it is a simple well-used method to detect trends.

It is very clear there is an upward trend.

The full set of data from 1900 shows the entire trend.

This graph captures nicely the way the average has moved upward over time.

Initially, it was low, then there was a jump and then a fall and plateau and then a gradual rise.

Let’s look at some other indicators

These can be found at https://www.epa.gov/climate-indicators

  1. High and Low temperature pattern

What you will notice is these are both increasing and Min more it is more than Max. This is exactly what has been stated by climate science.

  1. Heat Extremes

The trend is clear, extremes of heat is increasing.

  1. Seasonal patterns

As I said earlier a time series is hard to study. A time series of data is made up of the raw data + trends + seasons + errors.

What is shown above is the seasonal data. Winter shows a clear trend.

In conclusion

I have recently completed a study of the time series data for the Arctic Sea Ice Extent ie how much ice there is at any point in time. The data is derived from Satellite readings since 1978. The basic finding is that the amount of the max sea ice has fallen from 16mk^2 to 14mk^2. It will get published in due course.

Back to the original research question. I think it is clear the original graph on its own does not present sufficient evidence that (a) warming is not or has not occurred in the US and (b) it says nothing about the world.

There is also much discussion on blogs about Urban Heat Island (and airports). The data that you see is adjusted to these effects. Raw data suggests a significant bias, which is why it is removed. Much of what humans do is set around bias either personal or hidden in the data. For this reason, researchers spend a lot of time detecting and removing it.

Covid Models

SIR model

In the model, the variable trans is the rate of infection per day and recov is the rate infected persons move to recovered persons. Hence, if an infected person can during their infectious period of n days infects on average say 4 people trans = 4/n. If the average infectious period is n days then 1/n recover each day.

Ro = trans/recov, if > 1 there is spread

example: assume mean recovery period is 8 days, hence recov = 1/8 = 0.125 and that an infectious person can infect 5 people in 8 days, hence set trans = 5/8 = 0.625. This gives Ro = 0.625/0.125 = 5, which > 1 hence spread.

1-1/Ro gives an estimate of the herd immunity percentage, using our example we have 1-1/5 = 0.80 suggesting a threshold of 80% of the population needs to be fully vaccinated to see a gradual decline in infections.

****Please let me know if I have these concept incorrect

https://www.geogebra.org/m/wk6tbw6r

SIR Model using a Spreadsheet

https://docs.google.com/spreadsheets/d/1Qpkczrpz95zwHx2ylIDZ62-dwddAoSR9/edit?usp=sharing&ouid=115822802180325365262&rtpof=true&sd=true

To get a handle on what 80% herd immunity means we need to consider first that there are around 4,700,000 children aged less than 15 (19% of the population), assume this is the cut-off age for vaccination. Hence we are really talking about 80% of the remaining adults and this would give around 4,000,000 adults who would not be vaccinated. Together 40% of our 25m would be unvaccinated. Let’s get an estimate of cases and deaths.

Look at the models and use different parameters. You will see that the curve representing infections peaks at around the top of the green curve – 50%! of the unvaccinated and some much smaller percentage vaccinated.

In the UK they currently have about 30,000 cases per day (this includes children) from an unvaccinated adult population of 8m and 13m children less than 15. If we extrapolate that to Australia we get a very rough approximation of 12,000 cases per day. There would also be a death rate of around 15-20 per day or 600 per month. Both cases and deaths would decrease as further vaccination percentage increased.

Please note these figures are purely estimates to show the dimension of the cases.

As has been reported in the News, there are around 160,000 deaths per year in Australia, Flu accounts for approximately 700-800 deaths per year and it fluctuates yearly, currently, there are few direct deaths from Flu. Pneumonia deaths are about 3500 per year and some of these are related to the Flu.

Reverse Loop Model Trains

To reverse the direction of a model train you can use two main options.

This video link shows is the simplest option and least expensive option. Watch the video and it saves me drawing.

You need two points or turnouts, here we use two RH ones.

Both are connected to the main loop. The top points accepts the train coming in clockwise direction. Our aim is to get the train to come out traversing counterclockwise. Thus the points need to be set, firstly to take the train off and then to allow the train to move back onto the main track.

Both points are connected with a separate track, its length and shape depends on dimensions of your layout.

This section of track needs to be isolated with its own power. I have placed the isolation sections at the end of each point to the connecting track.

The polarity of this isolated track will match that of the incoming train.

As the train enters the isolated section you need to switch the polarity of the outer track in this video to counterclockwise wise. The train will then travers the point and move back onto the outer track in the opposite direction.