Guest essay by Larry Hamlin
NOAA has released its latest August 2023 Average Temperature Anomaly for the Contiguous U.S. using its most accurate USCRN temperature anomaly measurement system as shown below.
Listed below are NOAA’s measured top ten August average temperature anomaly measurements since the USCRN System went into operation in 2005.
A climate emergency, forsooth.
OMG it’s worse than we thought, our climate emergency has gone missing!
The Climate emergency has disappeared up its own fundament. Climate Science Needs and ENEMA, NOW! Quick, ring a proctologist.
More information about…. “NOTHING HAPPENING with CLIMATE in the USA”
Global Boiling Summer In The USA | NOT A LOT OF PEOPLE KNOW THAT (wordpress.com)
Maybe it’s been hot elsewhere, but east Texas has had a moderate to typical summer. I certainly feel no sense of emergency.
Cooler and wetter than typical along the Front Range of Colorado basically all year. Irrigation ditches are still running and I could see my breath yesterday morning from the cold.
A record hot year just north of east Texas where I live in eastern Oklahoma would be 65 days during the summer of 100F or more.
We had about 20 days of 100F or more this year. That ought to put things in perspective.
It’s been a pretty good summer. Not too hot, for too long, and more than a usual amount of moisture.
Now the big cooldown has started.
In the North Houston area you would have to go back to 2011 to find a summer this bad. Numerous high temp records were blown away daily this year.
Oh my Gawd! An increase that is just outside measurement error! We all gonna die!
Who are you quoting and what is the context of the ‘Climate Emergency’? Any segment of the world can be experiencing warmer than normal temps while another segment is colder than normal. You can bet on it. Please give some context. This taking a bit of info to represent the whole complex system is what the warmistas do. So what?
Most of the US average warm temperature state records were set long ago. The 1930’s have 24 state warm temperature records that still stand compared to 3 new state records in the last 10 years.
https://en.wikipedia.org/wiki/U.S._state_and_territory_temperature_extremes
Fewer major Tornadoes, fewer landfalling major hurricanes, fewer 100-degree days, No Positive Feedback Loop exist after years of looking for it outside of models, NO Lower Tropospheric “hot spot” exist after 30 years of looking, lowest storm index in the last 42 years on and on and on and on and on……
Then this article come along,
The Climate Alarmist’s Greatest Fear
LINK
Lot more here with base sources and 65 charts:
Where is the Climate Emergency?
LINK
Warmist/alarmists have yet to realize they lost the science argument years ago all they run on now is media sensationalism, stupid hyperbole and lies.
That is the problem, it is not about science at all, it is about political fear and control.
Please define “highest average temp anomaly since 2005”.
My apology, I concentrated on the bold text too much.
it’s barely noticeable- we forgive you!
Where is the climate emergency?
With beauty-in the mind of the beholder.
DMA, the climate emergency is in the FEELINGS of the WOKE idiots. Your data does not trump (MAGA!) their feelings.
Where is the Climate Emergency?
In all the (head)lines of MSM where almost all pay-my-rent-seeking and free-rider (pro)journalist around the world don´t know what USCRN is (:)
You’ll find it right where they left it, under Barry’s birth certificate.
It’s behind the fridge…
Good work, I was looking down the back of the sofa!
Leftists just gotta have SOMETHING to beat others over the head with, and it is always fake bologna! I wish they would give the climate scare a rest so that society can work on REAL problems.
Yea, we can tell how accurate it is.
You missed the point of the article which was very easy to see but amazingly you missed it.
Read it again……..
It sure isn’t going ever high like CO2 concentrations. The Sun has probably warmed the oceans so much that they can’t absorb atmospheric CO2 as much as when they were cooler.
ClimDiv didn’t exist before 2005. (was called something else…. replaced GHCN-D)
It also didn’t have USCRN as a control on agenda-driven adjustments.
We know GHCN is highly corrupted with numerous “adjustments” to bring down the warmer temperatures of the 1930s/40s
Please stick just to USCRN if you want to make a relevant comment.
Ya it’s called a time of observation bias. You have to correct for it.
Which has been proven to be a FAKE agenda driven “adjustment.”
FAKE agenda driven.. describes basically the whole AGW scam. !
Where has it been proven to be a fake adjustment?
Trend on morning v afternoon readings is exactly the same.
(afternoon readings are cooler because they tend to come from cooler sites)
If you are too clueless to realise what means, no-one can educate you.
TOBs is a sampling issue, it’s not about a trend difference between min and max temperatures. If you take a reading near the hottest part of the day on a warm day and reset the instrument, it’s going to read the same high temperature as tomorrow’s high temperature, even if tomorrow is cooler. Contrariwise, if you read at the coolest part of the day on a cold day and reset the instrument, it’s going to read the same low for tomorrow, even if tomorrow is warmer. Thus you’re either over-counting cool days or over-counting warmer days, depending on the time of observation. If there is a systematic change in the time of observation across the network, this will introduce a trend bias.
We know that in the US there was exactly such a systematic change, because volunteers were instructed to switch from afternoon readings (overcounting warm) to morning readings (overcounting cool) to aid with precipitation measurements (you want to read precipitation before a bunch of evaporation has occurred so it’s best to do it in the cool of the morning). This introduced a spurious trend drift into the US station network.
You can try to argue that the adjustment being applied is inappropriate if you wish, but you cannot successfully deny that such a bias is present in the unadjusted station network, because we have historical documentation of it along with statistical evidence. The fact that the adjusted USHCN aligns perfectly with the unadjusted and pristine USCRN, as shown above, is strong evidence that the adjustments are successfully removing such biases.
Only since 2005. Prior to USCRN there is no control data so we have no idea as to the appropriateness of any adjustments. Give it a few years.
The adjustments are the same before and after 2005, why would you think they would be appropriate after and not before?
Bullshit !
First…as AlanJ already mentioned the PHA is applied the same way both before and after 2005. The overlap period from 2005 to 2023 provides a good test for effectiveness.
Second…your statement isn’t even true. The TOB bias is a very large contributor to the USHCN/nClimDiv error. Its magnitude can be quantified by comparing the daily Tmax/Tmin observations with the hourly T observations like what [Vose et al. 2003] did. This extends the control period back to at least 1965. With more hourly observations being digitized since the Vose et al. publication it is likely it goes back even further still.
More climate pseudoscience data fraud.
AlanJ produces yet another meaningless anti-science load of wordy garbage. which says absolutley nothing.
So funny
The fact that ClimDiv aligns so well with USCRN, shows that USCRN is now controlling the adjustments…. hence, the FAKED warming stops.
Exactly the response I predicted. An ad-hominem that contributes nothing to the discussion. Clearly, I did my research and you have not.
USCRN is the reference network. It is not adjusted. Nor is it an entity – it is not “controlling” the adjustments made to the full station network. The same adjustments made after the start of the CRN are made before its start.
I recognize that use of full sentences and paragraphs might come off as “wordy” to you, but you really should attempt to engage in long format reading some day. Perhaps pick up a book. It will be good for your attention span.
You must be new to all of these shenanigans?
ps, data comparison shows that the total bias caused by afternoon TOBS is a little more than 0.1C (0.2F)
The total NOAA adjustment is nearly two degrees F.
It is unsupportable nonsense, and tantamount to fraud.
Can you refer me to the evidence behind this statement?
Time to go do your own research, muppet. !
Oh ok. Thanks for confirming there isn’t any evidence.
Try this for starters, you clueless troll:
https://wattsupwiththat.com/2020/11/24/the-u-s-national-temperature-index-is-it-based-on-data-or-corrections/
Tony Heller has done dozens of YouTube videos detailing the corruption and manipulation of historical temperature data to support the CAGW narrative.
Keep in mind that Tony Heller’s “detailing the corruption and manipulation of historical temperature data” was so egregiously wrong it was the initial impetus that eventually led to his banning on this very site.
Here is a brief bibliography of the time of observation problem.
Donnel 1914 – The Effect of Time of Observation on Mean Temperatures
Hartzell 1919 – Comparison of Methods for Computing Daily Mean Temperature
Rumbaugh 1934 – The Effect of Time of Observation on Mean Temperature
Mitchell 1958 – Effect of Changing Observation Time on Mean Temperature
Karl 1985 – A Model to Estimate Time of Observation Bias
Vose 2003 – An evaluation of the time of observation bias adjustment in USHCN
Menne 2009 – Homogenization of Temperature Series via Pairwise Comparison
Williams 2012 – Benchmarking the performance of pairwise homogenization
Hausfather 2016 – Evaluating the impact of USHCN homogenization using USCRN
As you can see the problem has been known since at least 1914. Vose 2003 is probably the best place to start for those interested in the topic. They quantify the magnitude of the TOB bias by comparing daily Tmax and Tmin observations to hourly observations.
Another data fraud advocate.
Funny how “corrections” to all those TOBs cool the past and warm the present.
Then identify it for each site.. if it even exists.
Blanket adjustments that continue into infinity are just basic anti-science nonsense.
All these studies make erroneous assumptions about the abilities of people making the earlier measurements. They were NOT idiots like the current clueless lot.
When you see names like Hausfather.. you KNOW you are being conned. !
The breakpoint analysis including but not limited to TOB changes for each site is available here.
Who are “you”? I don’t do data fraud.
Where you ask, in the mind like any religion. Once sufficiently stirred and baked in, it’s there forever. No amount of documentation will alter that now. The imagemakers have moved on and departure from orthodoxy is prohibited anyway.
The emergency is related to lining their pockets!
Well, it sure isn’t following the ever increasing CO2 level.
The Sun has been warming the oceans so they can’t absorb as much CO2 as in the past. That is probably the main reason for atmospheric CO2 increasing.
Where’s the hockey stick?
The average global temperature in the bar to the right is 57.59 F or 14.22 C. That is too cold for humans to live at without lots of technology in the form of warm clothes, warm houses, warm transportation and warm workplaces. Maybe in the tropics they don’t need much warming technology but in the temperate parts of the world warming technologies are essential for people to live there all year round.
Are there plots available for viewing, or is there a reasonably easy way to generate plots without knowing a suitable programming language and making your own program(s), of the individual USCRN stations?
The climate crisis is in the fever dreams of those who wish to rule us all, and in the darkness, bind us.
There you go again, believing your d*** lying eyes!
This puts the USCRN trend at +0.53 F/decade.
And because that trend calculation goes through the 2015/2016 El Nino bulge in the latter half, that trend will gradually decrease over time.
Before that El Nino, the trend was essentially zero.
Certainly there is no evidence of any CO2 warming, or of any “crisis” whatsoever…
… unless you call “climate doing-nothing” a crisis.
The ONI has averaged -0.14 over the same period.
You obviously don’t understand how linear trend calculators work, and what affects the final result.
Monkey with a ruler. !
Perhaps you can help me understand what I did wrong. I downloaded the USCRN data here and the ONI data here. I copied the USCRN data and ONI data to cells A1:A224 and B1:B224 respectively. I then did a @LINEST(A1:A224) * 120 and an AVERAGE(B1:B224) on those timeseries. What did I do wrong? Thanks in advance.
Let’s look at the uncertainty arising from the use of the ONI database.
Here are the numbers I obtained from Google Sheets
Sum 23743.6 -0.4
Count 883 883
Mean 26.9 -0.0005
Variance 0.88 0.69
Standard Deviation 0.94 0.83
Uncertainty 0.9 0.8
Stated Value 26.9 ± 0.9° C -0.0005 ± 0.8° C
Intervals 26 to 27.8° C 0.7995 to 0.8005
The uncertainties are so wide that the calculated values are meaningless. This is the problem with measuring different things under non-repeatable conditions. The GUM warns about this numerous times. NIST TN 1900 Example 2 is very decisive in the measurand being Tmax for a month and describes the same thing, same device, at the same location being repeatable conditions.
I did a quick check on the distribution to see if it was normal and got this.
# > 0.8 132
# < -0.8 144
Total <> 276
Total >< 607
% from -0.8 to 0.8 69%
As you can see, the distribution is mostly normal, albeit a little skew. I have attached an image of the histogram of the temperature data.
You need to decide why the mean ΔT is a -0.0005. I’ve dealt with trends in the past, and this is one of the things I always look for. This data has its mean so close to zero it is not funny.
Any article about air temperatures invariably brings out the trendology nutters.
I was curious to see what the trend would be if you omitted 2016 but kept the rest of the data even that following the El Nino. Slope came to .00013 so pretty near no trend, which isn’t to discount warming, more just making the point that a large El Nino spike on a short data set does seem to skew the warming per decade trend much higher than it otherwise would be.
That’s odd. I get a slope of 0.0040 F/month (0.48 F/decade) when I omit 2016. And just eyeballing the trendline in your graph it looks like almost a 1 F increase from 2005 to 2023 which would be about 0.5 F/decade.
I think I see what is going on. I think your x units are days. 0.00013 F/day is 0.48 F/decade.
yeah, you are right. I messed up the units on the chart. I’ll make sure to double check next time I graph 🙂
bdg is correct (I did my own research), but I made a similar unitary error just a few days ago. Your comment correcting yourself puts you a cut above most who post here..
As they get cornered more with the facts every month, the hysterical blindness becomes more and more evident. I would say that it nadired last week with over a hundred posts insisting that standard deviation, as universally defined, can be both positive and negative, but who knows….?
“ the hysterical blindness becomes more and more evident. “
Your mindless anti-science zealotry becomes more and more evident. !
Current US temperatures now are basically the same as in 2005.
GET OVER IT !!
“Current US temperatures now are basically the same as in 2005.”
I’ve got good news and bad news for you. The good news is that your sentence might be correct. The bad news is that the chance that it is correct is ~1.5%.
The trend is ~0.053 degF/year, with a standard error of ~0.024 degF/year. Use the openware norm.dist function to find the chance that the trend is flat/down…
But feel free to expand on your loosey goosey “basically” and we can further quantify….
Bull puckey. Standard error only tells you the accuracy of the mean. That assumes the distribution being used is normal. Have you checked that? Additionally the standard error is only meaningful when you are measuring the same exact thing multiple times under repeatable conditions. Temperature from different stations, especially different hemispheres, in no way meet repeatable conditions.
Uncertainty with non-repeatable measurements must use the Standard Deviation of the data for an indication of the dispersion of measurements surrounding the mean.
Read this from the NIH.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2959222/#
“”””The SEM is a measure of precision for an estimated population mean. SD is a measure of data variability around mean of a sample of population. Unlike SD, SEM is not a descriptive statistics and should not be used as such.”””
“Standard error only tells you the accuracy of the mean.
“mean” = expected value. In this case, the expected value of the trend. And the term that I described, it’s standard error, does indeed measure its accuracy. A.k.a. standard deviation, It tells you when ~68.3% of the area under the curve is covered, ~34% above and below the expected value. You can find he standard deviation for any distribution for which you can find each deviation from its expected value, square it, multiply it by its probability, add the products, and take the positive square root. I.e., many more than just the normal distribution.
I recall Bellman schooling you on this. Sorry for the Dan Kahan System 2 amygdal overamp that is blocking you from realization….
‘Have you checked that?”
Not this one. But every statistically significant trend that I have checked in the past – both for sea level and for temp – whether linear or with acceleration – has been functionally normal. OTOH, AFAIK, you have never found one that was not….
Here’s an example I did a few months ago. FYI, I did the same for the data just now under discussion. Same terrific fit…
So this graph means there is a climate emergency?
“So this graph means there is a climate emergency?”
[Scene notes. Everyone in the room looks quizzically at Homer for 15 seconds, in dead silence].
Well – no – karlomonte. It visually demonstrates how well the trend residuals undr discussion are normally distributed.
“undr” – “under”.
BFD — all you ruler monkeys dance around the real issues, debating tiny squiggles ad nausuem, while acting like you are authorities about something (no one knows what).
Bellcurvewhinerman?
Schooling?
HAHAHAHAHAHAHAHAAH
And just for the record, you ruler monkeys still can’t comprehend that uncertainty is not error.
Measurement uncertainty is about informing people of the range of values that can be expected when measuring a sample under the same conditions as the original measurements. The purpose is NOT giving them unreasonable intervals that require purchasing unneeded precision measuring devices that still won’t show the stated values because those measurements don’t really exist!
“””” “mean” = expected value. In this case, the expected value of the trend. And the term that I described, it’s standard error, does indeed measure its accuracy. “””””
You have basically repeated what I said. Glad you agree that the SEM (standard error of the mean) only provides an interval where the mean may lay.
Now, let’s discuss measurement uncertainty.
The SEM is applicable in only one instance of measurement. When you measure the same exact thing, multiple times, with the same device and obtain a normal distribution of the measurements. When this occurs only small errors are left after averaging and adequately are addressed by the SEM.
From the GUM.
F.1.1.2
“an evaluation of a component of variance arising from possible differences among samples must be added to the observed variance of the repeated observations made on the single sample. ”
B.2.18 uncertainty (of measurement)
“NOTE 2 Uncertainty of measurement comprises … can be characterized by experimental standard deviations.”
C.3.2 Variance
The variance of the arithmetic mean or average of the observations, rather than the variance of the individual observations, is the proper measure of the uncertainty of a measurement result.
The experimental standard deviation is NOT the SEM.
You guys want to keep applying the wrong statistics to measurements. At sometime you learned in statistics that the SEM is a measure of sampling error and tells you how close the estimated mean is to the true mean of a population. This is not what measurement uncertainty is about.
It is about informing people of the range of values that can be expected when measuring a sample under the same conditions as the original measurements. The purpose is NOT giving them unreasonable intervals that require purchasing unneeded precision measuring devices.
I wish you had to explain how you obtained such precision measurements to someone who just spent $10,000 dollars on a device with the precision you stated but still can’t get the values you claim.
He won’t understand.
Don’t sweat it. I’ve actually mixed up the units on linear regression trends more than once myself.
And “we” all know how deadly important the linear regression air temperature trends are.
“This puts the USCRN trend at +0.53 F/decade.”
OMG everyone throw their arms up in the air, wave them all about, and go into a manic PANIC !!
Oh.. and don’t forget to yell and screech… “CRISIS, CRISIS, CRISIS. !!”
We are not in a climate crisis, CO2 is not the control knob for our climate, we are not going to reach a tipping point and suffer irreversible global warming. We need to fire up our fossil fuel and nuclear generators, build new fossil fuel and nuclear generators, strengthen and upgrade the grid, remove all wind and solar from the grid and abandon all subsidies, tax preferences and mandates for renewable energy and electric vehicles. No bailouts for these failed projects.
Now, if only all our Republican politicians would adopt your great attitude and recommendations.
In fact CONUS August had one of the few coolish areas in the world, in the NE. In the globe as aa whole, it was the hottest August in the record by a long way (about 0.24C)
On record? What record? Going back how many years? The earth is roughly 4.5 billion years old, btw.
Back to 1900, in my case. Which covers most of the time we have tried to sustain a multi-billion population.
A population that is increasingly urban, swamping surface sites..
… and making them TOTALLY UNFIT for climate purposes.
The chart is FAKE and meaningless.
But you KNOW that, don’t you Nick !
Not to mention the overzealous use of warm colours.
WRONG at every level.
There were little to no ocean measurements before 2005 in the oceans
There has been massive urban development, causing massive corruption of surface data.
An “anomaly base 1951-1980” is not remotely possible.
That means that your chart is essentially FAKE and totally MEANINGLESS. !
Current global temperatures are just a small bump above the COLDEST period in 10,000 years.
Most of the last 10,000 years was much warmer than now.
Yet NOAA’s USCRN, the supposedly “pristine” US data set, is running warmer than its so-called urban heat island-affected ClimDiv data over their joint period of reference (since 2005).
So how does that work, exactly?
Maybe they’re adjusting it :/ to look like the USCRN.
“to look like the USCRN.”
roflmao… !
Another mindless moron that doesn’t even know the data fabrications being used. !
No, I don’t perhaps you can provide evidence for your claims. You failed to last time. But I’ll give you another shot?
You are talking gibberish.
You don’t even know what data Nick’s chart is based on, do you. !
Stop being a brainless little monkey !
Asking for one’s evidence is talking gibberish?
You still haven’t figured out that Nick’s little picture is nothing to do with ClimDiv or USCRN have you little monkey..
So funny !
This one has a brand new pair of socks, methinks.
OMG… This chart is not even using ClimDiv, !!
Why are you so utterly CLUELESS !!
Where do the numbers from the South Indian ocean come from?
This is an infilled temperature modeling chart there are many areas of no coverage, but those areas get infilled with modelled temperature numbers.
I will stick with Satellite data instead.
They are also infilled, and more, because they have to model the third dimension. Here are Spencer and Christy describing just a part of what is done:
“The LT retrieval must be done in a harmonious way with the diurnal drift adjustment, necessitating a new way of sampling and averaging the satellite data. To meet that need, we have developed a new method for computing monthly gridpoint averages from the satellite data which involves computing averages of all view angles separately as a pre-processing step. Then, quadratic functions are statistically fit to these averages as a function of Earth-incidence angle, and all further processing is based upon the functional fits rather than the raw angle-dependent averages.”
A petty and deceitful attempt at distraction by Nick.
We expect nothing else.
He is well aware that most of the data relied on from the chart he posted is total fabrication.
Where did all the ocean data come from for the 1950s, Nick?
Where did all the data for the 1950s for the centre of South America come from, Nick?
Where is all the data for the 1950s for Northern Siberia come from , Nick
Where did the data for the 1950s for Chad/Sudan etc come from, Nick.
And even besides the fabrication of data, the 1951-1980 period was the ” global cooling” scare period…
So, Nick.. your chart remains absolutely MEANINGLESS
And they throw all the standard deviation from all these averages in the trash.
They don’t even report how many values are averaged.
I will stick with Satellite data despite your dishonest attempt with your misleading infilling argument as Satellites covers more area over all and the atmosphere going up to 30,000 feet while PISS land temperature data only covers the top 2 feet or so…..
HAW HAW HAW HAW HAW……..
That is patently false. As you can see straight from Dr. Spencer and Dr. Christy satellite coverage is horrible. This is why UAH has to rely so heavily on infilling.
[Spencer et al. 1990]
Satellite data is infilled and adjusted even more aggressively than the traditional surface datasets. They even have to infill in the time dimension as well.
Year / Version / Effect / Description / Citation
Adjustment 1: 1992 : A : unknown effect : simple bias correction : Spencer & Christy 1992
Adjustment 2: 1994 : B : -0.03 C/decade : linear diurnal drift : Christy et al. 1995
Adjustment 3: 1997 : C : +0.03 C/decade : removal of residual annual cycle related to hot
target variations : Christy et al. 1998
Adjustment 4: 1998 : D : +0.10 C/decade : orbital decay : Christy et al. 2000
Adjustment 5: 1998 : D : -0.07 C/decade : removal of dependence on time variations of hot target temperature : Christy et al. 2000
Adjustment 6: 2003 : 5.0 : +0.008 C/decade : non-linear diurnal drift : Christy et al. 2003
Adjustment 7: 2004 : 5.1 : -0.004 C/decade : data criteria acceptance : Karl et al. 2006
Adjustment 8: 2005 : 5.2 : +0.035 C/decade : diurnal drift : Spencer et al. 2006
Adjustment 9: 2017 : 6.0 : -0.03 C/decade : new method : Spencer et al. 2017 [open]
That is 0.307 C/decade worth of adjustments jumping from version to version netting out to +0.039 C/decade. And that does not include the adjustment in the inaugural version.
Pay particular attention to their infilling strategy.
15 grids representing 2.5° of longitude each at the equator is 4175 km. Compare this to
GISTEMP which only interpolates to a maximum of 1200 km. And GISTEMP does not perform any temporal interpolation.
No , GISS just performs wholesale adjustment driven by their agenda, with specific aim of creating non-real warming trends.
Versus the scientific adjustments for satellite movement and changes, as done by UAH.
Sad that you can’t tell the difference between science and agenda.
Perhaps you can help me learn then. Which line(s) of source code contain agenda driven adjustments?
The whole adjustment methodology is agenda driven.
Are you really so DUMB you don’t realise that !
It is designed to smear very localised urban warming over the whole globe.
Wake up that tiny mind of your, if you can. !
It is simple request. If your next post does not include the file names and line numbers then I have no choice but to accept that you are unable to provide the information and I’ll move on.
You poor gullible little child.
Find the real data, and see what the AGW scammers do to it.
It is tantamount to fraud.. and people like you support it. SAD !
Yes you should move on, you are making a fool of yourself.
Yea some “skeptics” these people are.
Why, oh why did Guido insist on setting programming languages back 50 years by making indentation levels count?
step2.py does appear to try to correct for UHI to some extent. That does rely very heavily on urban stations being tagged correctly.
Yeah. I’m not a fan of python’s required indentation. Braces work just fine. Anyway, the nice thing about the GISTEMP source code and running it on your own machine is that you can remove the UHI adjustment, It turns out that it doesn’t make much of a difference either way.
BTW…one thing I don’t like about the source code is that the subboxing of the ERSST data is still done in Fortran as a secondary program. I really whish they’d get that incorporated into the python code as one of the steps.
Just skimming gio.py and fortran.py, it looks like the ERSST data file is still in fixed length binary (if Guido set languages back 50 years, the ERSST data sets data structures back 70).
The binary file format is read in with byte swapping if necessary.
T’aint nuffin to do with FORTRAN as such, just how they used to do things back then. It was mostly to give consistent record lengths for tape i/o.
Fortran…. My memories are of swapping formatting cards back and forth, and waiting for our decks to run at 2AM. At our “Mines” school, some of our extremely short supply of pre-engineerettes became women in the wooded area nearby the computer lab. Out of sheer boredom with the waits. Me and the also (pre STEM missus slept in bags on the floor, waiting for outputs.
Fortran is ugly. Fortunately I had to deal with it once professionally and that was back in the 90s.
It does have the redeeming vice of making one really appreciate the algol-like languages.
The ERSST data file is SBBX.ERSSTv5.gz. It is one of the inputs to the python code. It is prepared by GISS and posted each month at https://data.giss.nasa.gov/pub/gistemp/.
Yep, the bloody thing is binary. Why would anybody still have done that 30 years ago, let alone in the 21st century? It’s not like they’re still using 3480s for extending storage during runs.
H/ow hard would it be to dump it as delimited ASCII records?
Is that with or without SSTs? They’re going to dominate the result.
The ERSST data is provided in both ASCII and NetCDF formats here. My annoyance is that the python code does not use either as its input. Instead it uses the GISS prepared proprietary file. This is annoying because I have to wait until another 7-14 days for the SBBX.ERSSTv5.gz file to appear before I can run GISTEMP on my machine. Note that ERSST publishes their data around the 5th of each month, but the SBBX.ERSSTv5.gz file doesn’t appear on the GISS website until around the 14th even though the file itself is timestamped much earlier. It wouldn’t be a big deal except if you want to get an early lead on the most recent month’s update to get an edge in the prediction markets.
Yeah. SSTs dominating the result is certainly one a reason why it doesn’t really matter, but it’s also because the UHI bias (not the effect) just isn’t very large to begin with as can be seen by disabling step 2 and looking at the land-only result. This is something Nick Stokes has verified with his own dataset which does not apply any adjustments at all.
The data sources are specified in a config file, so that’s easy enough to change.
It shouldn’t take long to modify gio.py to read the ASCII data rather than jumping through all the hoops to read the binary data. As a bonus, that would speed up the SST processing considerably.
Having the data available from the horse’s mouth in a sane format only makes it all the more perverse for GISS to go to the trouble to convert it to their archaic binary format.
Maybe they’re still using the antediluvian F66 code for some internal processing because it’s so convoluted that nobody can work out what it does or is supposed to do (rarely the same thing with FORTRAN written by scientists)
I think I’ll revise that opinion.
SBBX.ERSSTv5.gz has already been pre-processed to put everything into sub-boxes, which is what the shouted SBBX prefix designates.
It’s too nice a day to be inside delving into Python code, but I’ll dig some more this evening.
These are CORRECTIONS which have been incorporated and updated while your interpolation argument is blatantly dishonest as there were ZERO widespread direct water temperature data before 2005 in the PISS data set up.
Notice you didn’t mention RSS at all who uses failing and far out of orbital drift satellites for the bulk of their data….. LOLOLOLOL.
Your interpolation comparisons are profoundly dishonest.
You say corrections. Everyone says adjustments. BTW…[Spencer et al. 2017] use the terms interchangeably.
I literally quoted Dr. Spencer and Dr. Christy. If you think their quote forms the basis of a dishonest argument then take that up with them.
RSS, UAH, and STAR use the same satellites. It is important to note that all 3 ignore NOAA-16 and NOAA-17 altogether. They each have slightly different criteria for the cutoff of NOAA-14 and NOAA-15 with STAR utilizing most data, RSS the 2nd, and UAH the least, but all 3 datasets do use them.
[Spencer et al. 2017]
[Mears et al. 2017]
[Zou et al. 2023]
[Spencer & Christy 1992] pg. 850, left column, paragraph 3
[Hansen & Lebedeff 1987] pg. 13347, right column paragraph 3
Considering you are indicting me of dishonesty I expect exact page numbers and paragraphs from publications authored by the parties involved in your next post demonstrating 1) that what I present here is wrong and 2) that I presented it in bad faith. If you are unwilling or unable to do that then I’ll have no choice but to dismiss your accusation as yet another vacuous comment from someone who only wants to “nuh-uh” my posts without backing up their position. As always I give you the benefit the first.
I didn’t notice that 0.24C° nor the hotness of the orange color where I live.
I also wonder why the base period is 1951-80 that includes the cool spell in the 1970s but not the warm time in the 1930s.
I think skepticism is under rated.
With the exception of the US and Europe, most of the data for the baseline in your map are at best doubtful or simply made up. You genuinely think there was good coverage of Central Africa or the Pacific Ocean back in the 1950’s?
He won’t answer.
The 30-year climate anomaly base of 1951-80 was the coldest 30-year period of the 20th Century. Why use it? Didn’t like the 1991-2020 color palate?
Its warmed since the Little Ice Age. So what?
It is here:
There is a fifth dimension beyond that which is known to man. It is a dimension as vast as space and as timeless as infinity. It is the middle ground between light and shadow, between science and superstition, and it lies between the pit of man’s fears and the summit of his knowledge. This is the dimension of imagination. It is an area which we call “The Climate Zone”.
Love it!
These figures are yet another reminder that there is no climate emergency, but anyone who examines the alarmists’ rhetoric will find that they’re ready to pounce on any even mildly extreme weather-related event and blow it out of proportion. So it’s wise to take their ranting, not merely with a grain of salt, but with a heaping tablespoon.
The USCRN chart is always shown here without a trendline, which shows warming (below).
Also, since it’s start in Jan 2005, USCRN has shown a much warmer trend (+0.53 F/dec) than the much maligned (here) NOAA US ClimDiv data (+0.40 F/dec).
So the “most accurate” representation of US surface temperatures is running warmer than the one that’s supposed to be more influenced by the urban heat island effect.
There seems to be a collective blindness to this fact on this site.
The monkey with a ruler hits again.
The only reason there is a slight positive trend is because the 2015/16 El Nino bulge is toward the right side of the data. It was essentially zero trend before that El Nino.
And of course, the difference is insignificant.
Gotta use those El Ninos.. they are the ONLY warming there has been.
Show us the “human” warming signature in that charge, foolish nit-wit.!
And yes, ClimDiv is being controlled by USCRN…
They would look even more stupid than you, if they kept mal-manipulating the ClimDiv data to show warming.
None of the above nonsensical excuses explain why the so-called “most accurate” US data set shows a faster warming trend than the one that’s supposed to be affected by urban heat island affect.
How can that possibly be?
And could you possibly confine yourself to answering that simple question please, rather than regurgitating another Gish-gallop of irrelevant nonsense?
Thank you.
Sure. Can you show me a picture of a thermometer registering the difference between the two datasets, please? I believe it is 0.13°F, isn’t it?
OMG, you are sooooo THICK.
They would look pretty stupid if it came out “exactly” the same as USCRN.
So they make sure it’s a bit either way.
Just pure circumstance the trend turned out slightly less.
Still waiting for you to show us the “human” caused warming trend in the US.
You have failed utterly and completely so far.
—-
And please tell us all…
why are you in a MANIC PANIC about a warming trend of 0.5ºF per decade.??
That shows just how incredibly brainless and chicken-little you lot really are !!!
You still don’t comprehend statistical significance, do you, foolish nonce.
They have to convert to °F in order to get larger number.
And , of course, Since 2015, all three of USCRN, UAH-USA48 and ClimDiv have been trending DOWN at about 0.6c/decade.
SCARED YET ?
Would you describe this as a tacit admission that you might be looking at too short a time interval to establish statistically significant trends?
What you have just admitted is that you have to use El Ninos to get a trend.
Finally you got there..
Maybe you are not a incredibly dumb as you seem.
TFN. Well if you pick April, the trend is DOWN….maybe select “all months” there TFN
https://www.ncei.noaa.gov/access/monitoring/national-temperature-index/time-series/anom-tavg/1/4
If there is temperature trend, why should it be linear?
It doesn’t have to be linear. Any order of regression analysis is possible. This site seems to favor ordinary linear regression which is probably why most of us just stick to that. When I point out that the 2nd order regression on the satellite data shows acceleration in the warming I get told that it is an unacceptable form of analysis.
Who are “us”?
Thinking the climate data is parabolic.
No-one could say anything more stupid. !!
That was s because exponential equations are nothing but curve fitting. They are only good for displaying what has happened. The end point seldom point even in the right direction in the past or future.
Multivariate cycles are what predominates on the earth. Day/night, month to month, season to season, sunspot to sunspot, on and on. Think sine and cosine combinations of multiple variables, kinda like an orchestra.
“Where is the Climate Emergency?”
Response:
“Where are the uncertainty numbers for these temperatures?”
Geoff S
Bingo. It’s hiding in the noise!
Autumn in the northeastern US.
Hurricane Lee is approaching the east coast of the US.
Before announcing that he was going to bed, Biden stated that if the global temperature exceeded 1.5C it would be worse than a global nuclear war.
Don’t panic people: pretty much everything that this poor old befuddled man says is imaginary. For example, months ago when US inflation was around 10% he stood in front of the cameras and stated that inflation was zero.
The real crisis is that he’s the president of the United States and the most powerful man in the world. Thank God for Donald Trump!
Chris
The US is less than 2% of the earth’s surface area, and 18 years is well within the bounds of regional variability. The region is also not necessarily experiencing the same weather – parts of the southwestern US were warmer than usual last month, for instance, while some parts were cooler than usual:
Looking at the long term record for the region you can see that the trend is positive:
LOL, both of these are based on FAKE, highly corrupted or non-existent data.
Why are you so incredibly dumb that you haven’t figured that out yet.
They are TOTALLY and UTTERLY MEANINGLESS. !
Where did all the ocean data come from for the 1950s, AnalJ?
Where did all the data for the 1950s for most of South America come from, AlanJ?
Where is all the data for the 1950s for Libya and Algeria come from, AnalJ?
Where did the data for the 1950s for Antarctica come from, lolJ?
Where does the data from 1950s for north of Alaska, come from, AlunJ?
You do know the 1950-1980 was the period of the “New Ice Age” scare, don’t you, child?
I generally ignore your comments because they’re just noise. If you can articulate a coherent comment summarizing your objection to the data provided I’ll entertain it. If you genuinely need data sources I can provide citations for those, but I suspect you are not asking in earnest so will refrain for the time being.
You need to explain the information you are posting. When you post a graph provide a cite for its location. If it is of your creation say so. Tell folks what day was used. Answer questions about the data, don’t just promote as true, that is propaganda.
The map is from GISS. It is, as it says, for the month of July. It is almost identical to the map I get for July
Yes, it is GISS,
Therefore we KNOW it is mostly FAKED data. !
Thanks Nick. !
It’s a model map you never admit.
LOL
Your pathetic evasion is noted. !
It is as though you KNOW the whole thing is an abject FAKE, based on non-data.
So funny !
The more you run from producing data…
… the more people can see that I am correct.
And please, don’t just say “GISS” or “HADwhatever.”
Where did they get the data from.
Where was it measured? show us.
“I generally ignore your comments because they’re just noise.”
I like your comments….
,.. they show the absolute arrogance and IGNORANCE of the below-normal-IQ, gullible, brain-washed, climate zealot.
They show just how incredibly little you actually know.
You do know that actual measured temperatures for the USA look NOTHING like that, don’t you !
Why do you unthinkingly accept all the CORRUPTED and MANIPULATED garbage that the AGW scammer put out??.
Is it that you are incapable of actually thinking ?
I’ll ask you since Nitpick Nick won’t answer:
Where do the numbers from the South Indian Ocean come from?
I believe NASA is using a combination of HadISST1 and OISST for ocean temps in their analysis.
If they (and you) were honest, the areas without data would be so indicated (like white or black).
Areas with missing data are indicated in gray, as stated in the caption on the graphic.
That is data missing for this July
I want to know about data from the 1950-1980 period
Where did it originate.
Waiting ! and waiting….
There does not seem to be substantial missing data for this period:
If you want to know where the data originated I refer you to the primary literature, which should always be your first stop:
https://data.giss.nasa.gov/gistemp/references.html
So you admit to using data you must know is totally corrupted by urban warming, airports, agenda adjustments etc etc etc.. or just toatlly fabricated.
You still haven’t shown where the data actually came from.
You GISS chart above says absolutely nothing.. and is as FAKE as anything else from GISS.
You do know there is basically no real data for the southern oceans before ARGO, don’t you.
Or are you totally ignorant of that fact as well
Where did all the ocean data come from for the 1950s?
Where did all the data for the 1950s for most of South America come from?
Where is all the data for the 1950s for Libya and Algeria come from?
Where did the data for the 1950s for Antarctica come from?
Where does the data from 1950s for north of Alaska, come from?
You have FAILED to answer.. yet again…
Come on.. show us the sites. !
Or continue to run around like a headless chook in manic evasion.
Sparse data tends to not matter much when you are looking at very long time periods. If you look at an individual month, say, June of 1950, you can see much larger gaps in coverage for the southern ocean:
But as we see above, those gaps close up when you’re looking at many months of data in annual means.
My answer now is the same as before: please refer to the primary literature to obtain information about the data used in these analyses.
NASA also has a tool to show individual surface station records. Here is the location of stations reporting in 1950 for Antarctica:
Alaska:
South America:
Africa:
The surface of the planet is only 29% and the waters are the other 71% WHICH Had zero direct water temperature data before 2005 which even now is still sparse in coverage thus an incomplete temperature profile is all we have.
No on the spot water temperature data before year 2005 thus nothing for the previous 1 BILLION years……
Don’t be this weak and foolish Alan.
That is patently false. World Ocean Database.
Yeah right. Made up data from ship measurements in the trade routes.
From NOAA about Argo.
“Deployments of Argo floats began in 1999, and the 3,000-float goal was reached in November 2007.”
So, ARGO wasn’t even done until 2007. And, it doesn’t really cover the ocean well enough to establish a clear view of ocean heat throughout all of the oceans.
Even Phil Jones admitted that data from the southern oceans was “mostly made up”
But that is what the whole FAKE mess hangs on, isn’t it.
I asked where the data for the 1950s came from for several areas.
You have FAILED to produce.
Show the sites it was measured at..
Show it wasn’t just “mostly made up”
Remember these values are averages. Assuming a normal distribution (not likely) they probably have a standard deviation of ±2° C.
So in 1998, 68% of the stations should be in an interval of -1° to 3° C. Remember, these are annual means. That means 34% of stations for every month had to be in the interval of +1.11°C to +3°C to have a mean of ~1° C. Likewise, 34% of stations had to be in the interval of +1.11° C to -1° C.
Where are the stations that had a +3° C or better anomaly? There should be ~16% > 3°C.
Where are the stations that have an anomaly of a -1°C or less? There should be ~16% < -1° C.
You aren't doing science if you can't answer these questions. You are only doing magic math psuedoscience.
Just checked today’s reported morning low temps for the area west of Spokane, WA. Spokane Intl Airport (GEG), with the sensor surrounded by acres of pavement shows a low of 51F. Seventeen miles south, the USCRN site near Cheney, WA, reports a low of 31F. A difference of 20 degrees is not uncommon; largest difference I have seen is 23 degrees. Interestingly, the high temps do not vary much. For example, high temp yesterday (9/13/23) was 77F at both locations.
That is why the increase in Tmin is hidden underneath the Tavg temperature. Tmax doesn’t grow, Tmin does but no one will see it
I follow the official temp at SeaTac airport and compare that to the downtown Seattle temp at KIRO TV. Both temp stations use a standard Stevenson Screen set up. The high temp for each day is consistently 1 degree F to 3 degrees F higher at the airport, compared to downtown. After midnight, the low temps are almost always equal or 1 degree F warmer at SeaTac. I assumed that SeaTac cooled off fast because of the openess. Seeing that huge low temp difference at Spokane Airport and Cheney, I think I will have to come up with a new theory!
Since the UN IPCC AR6 scientific data shows no increase in extreme weather in over 120 years, where is the emergency?
For the progressive wing-nuts the climate emergency is that there is no climate emergency.
Off Topic – Possibly USA Temp Relevant in Near Future
Re: ENSO/SST Global Ocean Temp Map – scroll to it on the right hand margin of this page
For the last three months, the warmest ocean water in the world [+5 C] has been concentrated around northern Japan, Korea, and Sakhalin Island.
The surface area of that warm water has increased significantly in the last month, and west-to-east surface currents appear to be moving it straight at Washington state.
Among other thoughts – does anyone think this water should be tested for radioactivity from the nuclear power plant meltdown in northern Japan, or from North Korea nuclear weapons?