Back in 2014, Anthony put up a post called “NOAA shows ‘the pause’ in the U.S. surface temperature record over nearly a decade“. In it, he discussed the record of the US Climate Reference Network (USCRN). I can’t better Anthony’s description of the USCRN, so I’m stealing it to use here:
This data is from state-of-the-art ultra-reliable triple redundant weather stations placed on pristine environments. As a result, these temperature data need none of the adjustments that plague the older surface temperature networks, such as USHCN and GHCN, which have been heavily adjusted to attempt corrections for a wide variety of biases. Using NOAA’s own USCRN data, which eliminates all of the squabbles over the accuracy of and the adjustment of temperature data, we can get a clear plot of pristine surface data.
Here’s a typical USCRN station
So … what does the USCRN show in 2017? Well, about the same as it showed in 2014 … no statistically significant warming since the start of the record. Here’s the graph from their website.
Trend = 0.6 ± 0.9 °C/decade, p-value = 0.31, far from significant. Source: NCDC National Temperature Index time series plotter
So … still no significant trend. Yes, the dataset is short, 13 years … but there are a number of 13-year periods in US temperature history which do have significant trends.
Finally, do you remember January 2006, when the entire US averaged four degrees C above average, twice the scare-factor temperature rise of two degrees C?
Well, me neither. Many people, including scientists who should know better, hyperventilate about a tenth of a degree C, but we hardly remember four degrees C …
Ah, well. Here on the north coast of California it’s raining, which is always a wondrous thing. The leaves on all of the plants are getting a brisk washing, the trees are shrouded in a luminous mist. The only dissenter is the cat …
Best to all, in sunshine or rain,
w.
Note: I trust Willis won’t mind that I improved the title a bit, changing it to “NOAA’s USCRN Revisited – no significant warming in the USA in 12 years”
Also, I had a similar story in 2015 -Anthony
It’s interesting that USCRN show 0.11 C/decade more warming than ClimDiv (based on the large ordinary station network) over the 12 year 10 month period. (I got trends of 0.57 and 0.46 respectively)
Hence, the adjustments by the PHA-algorithm is not creating any spurious warming, on the contrary it seems to hide about one fifth of the warming..
YES,
the adjustment code does Miss some of the real warming.
The key is that UNADJUSTED GOLD STANDARD data is
WARMER Than Adjusted data over the same period.
this will continue for the rest of time.
So after 20 years skeptics of adjustments will still have the same puzzle,,, why is GOLD STANDARD data
warming faster than the adjusted sites
“… this will continue for the rest of time.” Beyond parody!
“this will continue for the rest of time.”
The Farce is strong in this one, Obi-Wan!
Because you guys know you will be caught now if you tamper. So you cooled the old data where it could be obfuscated. Adjustment game is over. All the fake blood has been squeezed from that turnip
Hey guys,
Actually, the adjustments by Mosh & Co increase the mainly natural warming before 1950, but decrease the AGW after 1950:
https://twitter.com/rarohde/status/843799201544900608
I admit that a 0.11 C/decade difference, between the rural pristine gold standard network and the BIG adjusted network, sounds too large, and I doubt that this will last in the long run.
Maybe a long term divergence of 0.010 C/decade, or so, is more reasonable…?
This chart shows the GISS adjustments in the last ten years. If I was in charge of making the trend look better for the AGW cause, I would do exactly what has been done.
First, I would warm the late 1800s and cool the 1930s/1940s. That gets rid of that unwanted global warming before CO2 forcings were big. Want that to look flat. Check.
I would work really hard to get rid of all that heat at the start of the fossil fuel era … first half 1900s. That is the starting point for CAGW so need to make that cooler. Check.
We really need to get rid of that annoying cooling from the 30s to the 70s. Cool the start, warm the finish. Check.
Be careful with recent data. Too easily to verify. Want to be able to claim we actually cooled the trend since important dates of 1880 and since 1979. Check.
I’m sure many of the adjustments are valid. But seems to me it is a case of “heads we adjust, tails we ignore”. The adjustments are all way too neat and tidy and correspond in every case to make the trend a much better match for CAGW proponents.
But, the adjustment game can only go so far. I suspect it has mostly run its course. The “improvement ” in the trend for the CAGW proponents has been roughly offset by the credibility loss from slicing and splicing. If a substantial portion of the warming comes from administrative adjustments, then either (a) the warming is pretty small or (b) our temperature records are not accurate enough to conclude much of anything.
https://postimg.org/image/8ksxqt3wp7/
No, not that interesting at all.
USCRN seems to respond to warmer period more than ClimDIv or the US satellite data.
There has just been a period affected by the Warm Ocean Blob and by the strong 2015.16 El Nino.
Of course the linear trend shows more warming. Basic maths.
The fact that ANYONE thinks this trend is anything but a remnant of the El Nino transient, and then thinks they can extrapolate the units out to ” per century” makes me wonder if I they ever got out of junior high school, except by skipping maths and science classes.
Also, Andy, include the aborted 2014 El Nino temperature increases.
Perhaps Steven Mosher could list and identify the number of stations with completely uninterupted intact temperature records covering the period post 1850, post 1880, post 1900, post 1920, post 1940, and post 1950, through to date.
As I understand it, there are only a handful of such stations. hardly a good base from which to construct a time series data set.
We maintain our own version of the USCRN historical record in table form here:
https://atmos.washington.edu/marka/crn.2016/usa48/histrec.usa48.txt
March 2012 averaged +5.9 F above normal while January 2006 came in at +6.7 F above normal.
From the picture “inside a large wind fence with a single alter”.
Dang, I knew this thing was a religion.
Thanks Willis
Here is something similar that supports your conclusions. See summary of results in Figure 17 page 12
https://ssrn.com/abstract=2763358
Basically, what we see is meaningless linear trend created by a bulge from the 2015/16 El Nino.
The temperature has now dropped back down to essentially level to the pre El Nino zero trend line.
The assumption of linearity is quite anti-science. !.
And the child-minded extrapolation out to “per century” is the level of mathematical understanding expected from a 10 year old.
OK, 1.8e-09 K/s is the nearest I can get to SI units. You have a very strange idea of the role of units. You can freely convert to whatever you find convenient. They publish extensive tables to assist. 0.06°C.year is 0.6°C.Decade is 6.0°C.Century. The latter is the most widely used.
Linear thinking in a cyclical world….
NS,
You said, “The latter is the most widely used.” Might it be because it gives the biggest number and best supports the AGW story line? For 14 years of data, using a trend value per decade would be the most reasonable unit to use. Extrapolating to 10X of that isn’t really justified.
Nick’s comments yet again show HE HAS NO IDEA !!
Converting UPwards from your data length is MEANINGLESS.
It just shows how badly educated you are in actual mathematics.
Great with fudging and misrepresenting numbers, but doesn’t comprehend basic mathematical principles.
Poor ill-educated Nick.
And converting downwards gives you an average only.
Things Nick MISSED in his basic education !!
“Extrapolating to 10X of that isn’t really justified.”
If you convert your height from 2 yards to 6 ft, it would be unusual to describe that as “extrapolating to 3X”. It’s just units.
Units do NOT imply extrapolation.
When my local veg shop sells endives at 1.95 per 100g ( because he’s too embarassed ) , I told him jeez, that’s almost 20 euros per kilo.
He replies : don’t be stupid that’s not the real price, you’re just extrapolating !!
Explaining the intricacies of basic mathematics to people who aren’t interested in knowing, is a pointless exercise, Greg.
Nick is just NOT interested in learning anything other than what he thinks he knows.
He has shown that on other threads, as well. Sad really.
Hey Greg, tomatoes were at $2990/tonne in the supermarket the other day. ! 🙂
Poor shopping trolley just could not cope ! 🙁
AndyG55, you’ve more than made your point, multiple times. Seems to me the bait has been dangled in front of you and you’ve devoured it repeatedly. I ain’t the moderator, but I do have an opinion and I find your comments very tiresome.
NS,
You said, ” It’s just units.” No, that isn’t true! If you were converting between F and C, that would be converting units. When you use a denominator of 100 years instead of 10 years, you are implying an extrapolation for a longer period of time, which isn’t justified for such a short period of time. It is examples of sophistry like this that earn you deserved criticism.
Clyde,
“When you use a denominator of 100 years instead of 10 years, you are implying an extrapolation for a longer period of time, which isn’t justified for such a short period of time.”
No, that’s absurd. It is just units. If you read any account of speed of tennis serves (eg here), it is given in mph (or km per hour). The record seems to be 157 mph. You could say 69 m/s, but few seem to. Or 0.069 km/s. But the duration less than 1 sec. No-one has any trouble using mph as the unit here. No-one thinks it means the ball will travel 157 miles. People just convert to the units they find most familiar. I think more people find °C/Cen as more familiar (I do), but by all means use °C/decade if you like. Due to the wonders of the decimal system, conversion is easy.
The station equipment includes both ground temperatures and air temperatures. (1.5 m above ground.) “Back” welling theory says that after sun set ground gets cold and downwelling air keeps it warm. Does actual data show that?
It could be interesting to see this chart matched with and WUWT US station chart that goes back 100 years.
Nick Stokes
November 8, 2017 at 3:52 pm: And Prof Wood refuted Arrhenius soon after. The first of many.
Prof Wood had nothing to do with Arrhenius. Or anything else much.
“Trend = 0.6 ± 0.9 °C/decade, p-value = 0.31, far from significant. Source: NCDC National Temperature Index time series plotter …
Finally, do you remember January 2006, when the entire US averaged four degrees C above average, twice the scare-factor temperature rise of two degrees C? Well, me neither.”
If you look at the entire dataset, the average monthly anomaly is +0.7766. But you must take into account the fact that the temperature series starts with an anomaly of +1.75 (Not 0 as any other “reference” would be) and the average anomaly of the first 12 months is +0.7783.
I don’t think you can get much flatter than a +0.7783 anomaly over the first year extending to a +0.7766 anomaly over the entire record. It’s flatter than a pancake.
“Finally, do you remember January 2006, when the entire US averaged four degrees C above average, twice the scare-factor temperature rise of two degrees C?
Well, me neither.”
You probably missed it. West coast missed out. The NOAA report is here. Their map is here:
http://www.wunderground.com/hurricane/history/jan2006temp.png
Looking at that map/plot, I am surprised that it was only 4 degrees, but I bet it was very welcome relief from an otherwise cold winter.
Yes, temperatures routinely vary by a large amount from place to place, day to day, month to month, year to year.
And life goes on.
Making a mockery, on a daily basis, of the notion that 2C is somehow an amount of warming that will be catastrophic, or even a problem.
Even if you did not know that the 2C number is just a number, pulled at random out of the air and having exactly zero physical meaning as a limit or a reason to create alarm.
What is really is, is an amount at which most people will be able to have a perception that the temperature has changed. if they concentrate very hard and pay attention.
Now this begins to look like real data at last…
A classic example of linear regression farcically applied to non-linear series. There is no ‘trend’, only the here and now. Tomorrow’s chaos will merely yield another political perspective on the same variability.
Oops, wrong one. Not that it’s significant 🙂
Lol, I’d like to see AndyG55’s reasoning applied in court!
I wasn’t going 60 miles per hour your honor. I only traveled one mile, and only drove for one minuet! I was only going 1 mile per minute. I didn’t drive for 1 hour or 60 miles, so your extrapolation is unreasonable, and my ticket should be dismissed!
This recent posting sent me off in search of USCRN data. I was looking for data that included both air and ground/soil temperatures. After some links and guidance from Michael Palecki and struggling with Excel I plotted several annual graphs. Aberdeen, SD was the first site I discovered that reported soil temperatures at various depths.
One of the assumptions of RGHE is that at an upwelling LWIR of 396 W/m2 (K-T) the ground will lose muchly heat so fastly that its temperature would fall bigly if not for the downwelling “back” radiation from the GHGs. That suggests that the air would/must be at a higher temperature than the ground.
What I discovered from graphing: USCRN T Air ave, 5 cm, 10 cm, 20 cm, 50 cm, and 100 cm soil temperatures is that during the winter there is a temperature gradient from 100 cm in the cold direction and in the summer a temperature gradient from 100 cm in the warm direction all of it obviously driven by the variation in solar insolation due to the tilted axis and the oblique dispersion of insolation.
What I see from real actual data is absolutely zero evidence of the RGHE assumption mentioned above.
If the globe were to warm by 2 degrees, it begs the fundamental question:
How much would each country warm by, what would be its daytime highs, nighttime lows, summer highs, winter lows?
We can then make a comparison with what we know about how people presently live in different climates to see whether there is a problem.
Bit off topic but UK met Office are still using this weather station I believe.
Hey guys, just some questions as I try to keep up. First, the NOAA still presents data of rising global temperatures, even though it also presents evidence of no trend in the US:
https://www.ncdc.noaa.gov/data-access/marineocean-data/noaa-global-surface-temperature-noaaglobaltemp
What accounts for this? Is it because they don’t use the USCRN recording stations worldwide? Is USCRN a relatively new data source?
The USCRN data base reports soil temperatures at 5, 10, 20, 50 and 100 cm depths. (and a ton of other stuff, too.) I suppose that’s so farmers know when to plant.
Daily Documentation: https://www1.ncdc.noaa.gov/pub/data/uscrn/products/daily01/README.txt
Daily station-year files: https://www1.ncdc.noaa.gov/pub/data/uscrn/products/daily01/
USCRN data tables: select all, copy/paste into Excel, in data tab select “text to column,” delimited, by spaces and POOF Excel rows and columns ready for analysis. Change date column to 01/01/xx date format otherwise the insert graph feature goes nuts.
Goes back to 2000.