April globally was the warmest on record---noaa

[Crick]

Such certainty that that data do not show what NOAA/NCDC says it shows must be based on evidence. Let's see it.

I personally have given many many examples of large changes made to the records. You, and most of the other posters here just ignore the subject.

That the records have been changed is not evidence that they have been falsified. But that's been the charge.

 

[flacaltenn]

Hey.. How come none of you robed warmers can go fetch the previous Aprils from NOAA so that they can be compared to the sat record?? Might learn a thing or two...

Even more interesting would be a comparison of April temps as they stand this year, against what they were two years ago, five years ago, ten years ago, and twenty years ago. I think the more moderate warmers would feel some disquiet over the changes. All in the direction of adding to the warming trend. But then again we all know that humanity wasn't technologically capable of reading thermometers 5, 10 and especially 25 or 50 years ago.

Absolutely. But with this group of lazy asscrackers, you gotta take baby steps..
So be prepared for Step 3 !!!!!!

Step 1 ----- Obtain the April readings from 2000 to 2014.. Note that by SAT -- this April was 4th warmest JUST IN THIS DECADE.. Also note that the 5th in this decade was just 0.02degC less.. In the NOAA data -- notice that this April WAS NOT the warmest ever recorded, since it tied with 2010. A fact that didn't make the propaganda as sweet.

Big news is that the 2014 reading is the 2nd largest DISAGREEMENT with satellite data in the decade. And that when you subtract the two data vectors -- the resultant trend line SHOULD BE a flat line. It is not. The NOAA 15,000 thermometer and cooked data has about a 0.05degC/decade RISE compared to SAT data..

Of course, this is ALL horseshit because the HEADLINE is about a 0.05degC whooptidoo difference between being tied for 1st and placing 3rd as handicapped by the politcos at NOAA.

Step 2 ---- As IanC says -- keep an eye on the NOAA set. Because just like the cooked and stewed UNEMPLOYMENT NUMBERS --- there will be a revision when no one is looking to put everything back to agree with the Satellite record. It's only purpose was to make the news cycle and keep the jackhammers going. A year from now, that 0.05degC slope to the disagreement will STILL BE THERE -- but the numbers will be pulled down to correct the longer stats of the record.

 

[flacaltenn]

Hey.. How come none of you robed warmers can go fetch the previous Aprils from NOAA so that they can be compared to the sat record?? Might learn a thing or two...

It's already been established UAH has a cool bias, and it's an outlier even among satellite data sets. Cherrypicking the outlier is usually not regarded as good science.

UAH has had to make many corrections over the years, most to fix part of the cool bias. And before each correction, Spencer and Christy would be swearing there was no problem. Those two don't have a good track record.

Oh, it's also odd that someone would ask to compare surface and satellite temps, as that's kind of apples and oranges.

Mamooth doesn't even know that RSS is the lowest dataset right now.

Doubt he knows what the choices are..

Point is --- NOAA pisses it's integrity right down drain everytime they make one of these headlines WITHOUT MENTIONING the other measurement systems and data sets. That's not SCIENCE in the public interest. That's SCIENCE to SWAY the public interest. We EXPECT that horsecrap with all the OTHER Washington numbers they manipulate, and they are using the tactics here....

 

[mamooth]

Big news is that the 2014 reading is the 2nd largest DISAGREEMENT with satellite data in the decade. And that when you subtract the two data vectors -- the resultant trend line SHOULD BE a flat line. It is not. The NOAA 15,000 thermometer and cooked data has about a 0.05degC/decade RISE compared to SAT data..

So the satellite data has problems. Which everyone already knows.

But hey, if cherrypicking the outlier and declaring everything else is a fraud is all you've got, I guess you have to run with it. Makes for a good conspiracy, right?

 

[IanC]

Such certainty that that data do not show what NOAA/NCDC says it shows must be based on evidence. Let's see it.

I personally have given many many examples of large changes made to the records. You, and most of the other posters here just ignore the subject.

That the records have been changed is not evidence that they have been falsified. But that's been the charge.

Most of the changes are pretty arbitrary. And some adjustments like UHI are ridiculously small. I wish I could believe they are unbiased as to result but I fear they are not.

 

[mamooth]

Most of the changes are pretty arbitrary. And some adjustments like UHI are ridiculously small. I wish I could believe they are unbiased as to result but I fear they are not.

Do you have the evidence that the adjustments are "arbitrary"? Remember that anything from Goddard, McIntyre or Watts is almost certainly an illustration of GIGO. That is, they botch their data processing and then, based on the garbage output they've created, they declare a grand conspiracy.

Now, if you're going to accuse fraud, you better be an expert in the field, and have the facts down cold. So let's talk about some corrections. Do you know what each correction on this graph means, and why it trends the way it does? Let's just start with the first. Do you know what TOBS is, and why the data is crazily biased if it doesn't get that correction?

To show how the junk looks in comparison, this one comes from Goddard via Watts. I don't know if you've used it here, but others have. And it's nonsense. GIGO. A giant failure in data processing. Completley wrong, yet the whole denier world has been using it to declare proof of a conspiracy.

 

[flacaltenn]

Yeah.. That looks arbitrary to me. Asshat...

those single point anomalies sometimes DO get published. But regardless the general shape of the corrections, ESPECIALLY back into the 30s and 40s, have an agenda attached to them......

Much less spatial and temporal fiddling with a single sat sensor. Thats why NASA HATES satellites..

 

[mamooth]

Yeah.. That looks arbitrary to me. Asshat...

Oh well, that settles it. Flac says it "looks arbitrary". No need for any further discussion.

those single point anomalies sometimes DO get published. But regardless the general shape of the corrections, ESPECIALLY back into the 30s and 40s, have an agenda attached to them......

Lacking there would be any evidence for the conspiracy theory, other than your usual "My feelings tell me it must be so."

Much less spatial and temporal fiddling with a single sat sensor. Thats why NASA HATES satellites..

Which is why they launch them, because they hate them.

And poor Flac here seems to have little idea of just how much fiddling goes on with that satellite data.

 

[IanC]

Most of the changes are pretty arbitrary. And some adjustments like UHI are ridiculously small. I wish I could believe they are unbiased as to result but I fear they are not.

Do you have the evidence that the adjustments are "arbitrary"? Remember that anything from Goddard, McIntyre or Watts is almost certainly an illustration of GIGO. That is, they botch their data processing and then, based on the garbage output they've created, they declare a grand conspiracy.

Now, if you're going to accuse fraud, you better be an expert in the field, and have the facts down cold. So let's talk about some corrections. Do you know what each correction on this graph means, and why it trends the way it does? Let's just start with the first. Do you know what TOBS is, and why the data is crazily biased if it doesn't get that correction?

To show how the junk looks in comparison, this one comes from Goddard via Watts. I don't know if you've used it here, but others have. And it's nonsense. GIGO. A giant failure in data processing. Completley wrong, yet the whole denier world has been using it to declare proof of a conspiracy.

OK I'll bite. the main component of time of observation bias is that if the actual reading of the thermometers is near the daily minimum then the average will be lower over a long period. likewise if the reading is near the daily max then the average temp will be higher. the reason is that the lower (or higher) reading gets counted twice. the best way to get around this is to read the thermometers at a time other than dawn or late afternoon.

looking at your graph it appears that something happened just after both World Wars that affected the timing of the readings, and hence the TOBS adjustments. I have a coupla questions for you. where is the documentation showing the gradual switchover from afternoon readings to morning readings, as is suggested by the graph from 1950-2000? second, is the TOBS adjustment calibrated to mean average temperature calculated from all possible reading times? or did it just 'happen' to be closer to the highest one?

here is data from Pittsburgh 2006-07 to show the difference reading times make. it is in Fahrenheit.

0:00 51.84
1:00 51.74
2:00 51.67
3:00 51.57
4:00 51.45
5:00 51.27
6:00 51.11
7:00 50.97
8:00 50.90
9:00 51.06
10:00 51.26
11:00 51.51
12:00 51.74
13:00 51.89
14:00 52.10
15:00 52.37
16:00 52.61
17:00 52.78
18:00 52.81
19:00 52.69
20:00 52.44
21:00 52.22
22:00 52.06
23:00 51.94

Oh, and as for Goddard's graph. he used a simple average of all available stations. the reason for the jump at the end is because there were rural stations that had not reported yet. isnt it amazing that a quite small number of rural stations would make that big of a difference. and yet the NOAA adjustments for UHI are less than a tenth of a degree Fahrenheit for the whole 20th century.

 

[IanC]

all I could find is this reprint of a 1995 paper. that would make it contemporary with the graph you linked.

Monthly averages within a climatic division have been calculated by giving equal weight to stations reporting both temperature and precipitation within a division. In the U.S., observers at cooperative stations often take one observation per day, and the ending time of the climatological day at any station can vary from station-to-station as well as year-to-year. Differences of the 24-hour period over which each observer reports his or her maximum and minimum temperature as well as the average temperature [(max + min)/2] affects the calculated monthly mean temperature. Karl, et al. (1986), describe the biases that this introduces. These potential biases were rectified by adjusting for these varying observation times. The model described by Karl, et al. (1986), was used to adjust the climate division averages such that all stations end their climatological day at midnight; i.e., climatological day coincides with calendar day. The time of observation was determined at each station within a climate division during January of the years 1931, 1941, 1951, 1965, 1975, and 1984 for the states of California, Colorado, Illinois, Indiana, New York, North Carolina, and Washington. The fraction of observers recording at various hours of the day was calculated and interpolated for intervening years (extrapolated for subsequent years). For these seven states, the ending time of observation was grouped into three categories: AM, PM, and MD. The AM category included observers who ended their climatological day between 3 AM and 11 AM; the PM category between noon and 9 PM; and the MD category between 10 PM and 2 AM; all local standard time. The fraction of observers in these categories was calculated, and it was assumed the 7 AM observation time best represented the AM category; the 5 PM observation time, the PM category; and midnight for the MD category. The reason for the simplification was to test if a faster method, requiring significantly less bookkeeping and keypunching, could not provide nearly as good results as calculating the fraction of observers at each of the 24 hours of the day.
The time of observation bias model was run by using the latitude and longitude of each of the centroids of the climate divisions. The output from the model was the time of observation bias, with respect to a midnight-to- midnight climatological day, for each of the possible ending hours of the climatological day. Each climate division's monthly average was then adjusted by weighting the bias at any given hour by the fraction of stations within the climate division observing at that hour, and subtracting the result for the reported monthly mean temperature.
Differences of the biases were small (LT 0.3 Deg. F.) for those calculated by categorizing the ending time of observation into three categories compared to those obtained from calculating the fraction of stations with observation times at each of the 24 hours of the day. This is attributed to the preponderance of AM observation times falling between 6 AM and 9 AM, and PM observation times falling between 4 PM and 7 PM. As a result, by assuming 7 AM observation for all AM stations and 5 PM for all PM stations, a good estimate of the median bias is obtained for all AM or PM observations. Furthermore, nearly all the MD stations observed at midnight.

hmmm....not exactly rigorous, is it?


ESRL : PSD : US climate divisions dataset description

 

[Crick]

Not exactly conspiratorial lies either.

 

[IanC]

Not exactly conspiratorial lies either.

hahahahahahaha. things didnt really pick up on the whole 'noble cause' issue until AR3, did they? Hansen was still producing half decent papers back before 2000. although the Reudy UHI one was the beginning of the end I think.

 

[LoneLaugher]

And yet, the historical record...well the one that Hansen and company haven't screwed with that is, shows the 1930's to be the warmest decade in recorded US history.

[MENTION=23239]westwall[/MENTION]

All liberal democrats argue that climate scientists are wrong.

 

[flacaltenn]

And yet, the historical record...well the one that Hansen and company haven't screwed with that is, shows the 1930's to be the warmest decade in recorded US history.

[MENTION=23239]westwall[/MENTION]

All liberal democrats argue that climate scientists are wrong.

I'm sorry. Is that a legal requirement? That means I wasted a lot of time studying the issue and discussing it. Should have known that all you needed was a declaration on your voter registration..

 

[LoneLaugher]

And yet, the historical record...well the one that Hansen and company haven't screwed with that is, shows the 1930's to be the warmest decade in recorded US history.

[MENTION=23239]westwall[/MENTION]

All liberal democrats argue that climate scientists are wrong.

I'm sorry. Is that a legal requirement? That means I wasted a lot of time studying the issue and discussing it. Should have known that all you needed was a declaration on your voter registration..

Why yes. It is a legal requirement. Didn't you know?

 

[westwall]

And yet, the historical record...well the one that Hansen and company haven't screwed with that is, shows the 1930's to be the warmest decade in recorded US history.

[MENTION=23239]westwall[/MENTION]

All liberal democrats argue that climate scientists are wrong.

No. SCIENTISTS do. At least those that haven't been bought by the Goldman Sachs Board of Directors. Once again you seem to prefer blindlessly following the edicts of your masters than thinking for yourself.

I hate to tell you but that's not liberal. That's STUPID!

 

[Crick]

Whether or not this April was the warmest in the historical record is not particularly important. This is just another thread in which to have arguments and insult each other.

 

[mamooth]

OK I'll bite. the main component of time of observation bias is that if the actual reading of the thermometers is near the daily minimum then the average will be lower over a long period. likewise if the reading is near the daily max then the average temp will be higher. the reason is that the lower (or higher) reading gets counted twice. the best way to get around this is to read the thermometers at a time other than dawn or late afternoon.

Yes. And the readings were done by volunteers, often in that warm afternoon, which led to past temps looking higher than they were.

looking at your graph it appears that something happened just after both World Wars that affected the timing of the readings, and hence the TOBS adjustments. I have a coupla questions for you. where is the documentation showing the gradual switchover from afternoon readings to morning readings, as is suggested by the graph from 1950-2000? second, is the TOBS adjustment calibrated to mean average temperature calculated from all possible reading times? or did it just 'happen' to be closer to the highest one?

Vose et al 2003 is sort of the guide here, and gives more details, saying they took it from a database of such hourly readings. Instructions given to the station volunteers about when to check have varied over the years, which is probably what accounts for those bumps. Past 1960, you start getting the automated stations replacing manual stations.

onlinelibrary.wiley.com/doi/10.1029/2003GL018111/pdf

Oh, and as for Goddard's graph. he used a simple average of all available stations. the reason for the jump at the end is because there were rural stations that had not reported yet. isnt it amazing that a quite small number of rural stations would make that big of a difference. and yet the NOAA adjustments for UHI are less than a tenth of a degree Fahrenheit for the whole 20th century.

It wasn't a small number. It was like 25% of the total stations missing. It was an artifact of not using the same time sets. Goddard's missing raw data came at the end of April, when temps were rising. That depressed the raw data average a lot, meaning the final-minus-raw plot spiked. If he'd run the same analysis in November, it would have shown a huge downward spike.

 

[IanC]

OK I'll bite. the main component of time of observation bias is that if the actual reading of the thermometers is near the daily minimum then the average will be lower over a long period. likewise if the reading is near the daily max then the average temp will be higher. the reason is that the lower (or higher) reading gets counted twice. the best way to get around this is to read the thermometers at a time other than dawn or late afternoon.

Yes. And the readings were done by volunteers, often in that warm afternoon, which led to past temps looking higher than they were.

looking at your graph it appears that something happened just after both World Wars that affected the timing of the readings, and hence the TOBS adjustments. I have a coupla questions for you. where is the documentation showing the gradual switchover from afternoon readings to morning readings, as is suggested by the graph from 1950-2000? second, is the TOBS adjustment calibrated to mean average temperature calculated from all possible reading times? or did it just 'happen' to be closer to the highest one?

Vose et al 2003 is sort of the guide here, and gives more details, saying they took it from a database of such hourly readings. Instructions given to the station volunteers about when to check have varied over the years, which is probably what accounts for those bumps. Past 1960, you start getting the automated stations replacing manual stations.

onlinelibrary.wiley.com/doi/10.1029/2003GL018111/pdf

Oh, and as for Goddard's graph. he used a simple average of all available stations. the reason for the jump at the end is because there were rural stations that had not reported yet. isnt it amazing that a quite small number of rural stations would make that big of a difference. and yet the NOAA adjustments for UHI are less than a tenth of a degree Fahrenheit for the whole 20th century.

It wasn't a small number. It was like 25% of the total stations missing. It was an artifact of not using the same time sets. Goddard's missing raw data came at the end of April, when temps were rising. That depressed the raw data average a lot, meaning the final-minus-raw plot spiked. If he'd run the same analysis in November, it would have shown a huge downward spike.

thanks for the link. I have read lots of papers on TOB correction. the problem isnt that it needs to be corrected for, the problem is that it doesnt seem to be following the method that they state is used for correcting. every (sorry, most of the) time you actually look at a station it doesnt match the adjustments that you would expect from their explanation of their methods.

as for Goddard....it seems absurd that any temp data compiler would be declaring April the warmest Apr eeeevah!!! if so much data was missing. because I am sure that the rest of the world is sooooooo much more responsible than the american network.

 

[Crick]

Does anyone here, on other side of this argument, care whether or not this April was the warmest ever? I find it more concerning that this decade was the warmest ever. I find it more concerning that temperatures worldwide continue to climb. I find it more concerning that we're about to go into the Grandfather of all El Ninos. And I find it more concerning that there are still as many people as stupid about all this as the lot of deniers we find here. And, you know what? As hard as this may be to believe, I'm certain these aren't actually the stupidest of the lot.