I decided to do myself something that so far NOAA has refused to do: give a CONUS average temperature for the United States from the new ‘state of the art’ United States Climate Reference Network (USCRN). After spending millions of dollars to put in this new network from 2002 to 2008, they are still giving us data from the old one when they report a U.S. national average temperature. As readers may recall, I have demonstrated that old COOP/USHCN network used to monitor U.S. climate is a mishmash of urban, semi-urban, rural, airport and non-airport stations, some of which are sited precariously in observers backyards, parking lots, near air conditioner vents, airport tarmac, and in urban heat islands. This is backed up by the 2011 GAO report spurred by my work.
Here is today’s press release from NOAA, “State of the Climate” for July 2012 where they say:
The average temperature for the contiguous U.S. during July was 77.6°F, 3.3°F above the 20th century average, marking the hottest July and the hottest month on record for the nation. The previous warmest July for the nation was July 1936 when the average U.S. temperature was 77.4°F. The warm July temperatures contributed to a record-warm first seven months of the year and the warmest 12-month period the nation has experienced since recordkeeping began in 1895.
OK, that average temperature for the contiguous U.S. during July is easy to replicate and calculate using NOAA’s USCRN network of stations, shown below:
The U.S. Climate Reference Network (USCRN) consists of 114 stations developed, deployed, managed, and maintained by the National Oceanic and Atmospheric Administration (NOAA) in the continental United States for the express purpose of detecting the national signal of climate change. The vision of the USCRN program is to maintain a sustainable high-quality climate observation network that 50 years from now can with the highest degree of confidence answer the question: How has the climate of the nation changed over the past 50 years? These stations were designed with climate science in mind. Three independent measurements of temperature and precipitation are made at each station, insuring continuity of record and maintenance of well-calibrated and highly accurate observations. The stations are placed in pristine environments expected to be free of development for many decades. Stations are monitored and maintained to high standards, and are calibrated on an annual basis. In addition to temperature and precipitation, these stations also measure solar radiation, surface skin temperature, and surface winds, and are being expanded to include triplicate measurements of soil moisture and soil temperature at five depths, as well as atmospheric relative humidity. Experimental stations have been located in Alaska since 2002 and Hawaii since 2005, providing network experience in polar and tropical regions. Deployment of a complete 29 station USCRN network into Alaska began in 2009. This project is managed by NOAA’s National Climatic Data Center and operated in partnership with NOAA’s Atmospheric Turbulence and Diffusion Division.
So clearly, USCRN is an official effort, sanctioned, endorsed, and accepted by NOAA, and is of the highest quality possible. Here is what a typical USCRN station looks like:
A few other points about the USCRN:
- Temperature is measured with triple redundant air aspirated sensors (Platinum Resistance Thermometers) and averaged between all three sensors. The air aspirated shield exposure system is the best available.
- Temperature is measured continuously and logged every 5 minutes, ensuring a true capture of Tmax/Tmin
- All stations were sited per Leroy 1999 siting specs, and are Class 1 or Class 2 stations by that siting standard. (see section 2.2.1 here of the USCRN handbook PDF)
- The data goes through quality control, to ensure an errant sensor hasn’t biased the values, but is otherwise unchanged.
- No stations are near any cities, nor have local biases of any kind that I have observed in any of my visits to them.
- Unlike the COOP/USHCN network where they fought me tooth and nail, NOAA provided station photographs up front to prove the “pristine” nature of the siting environment.
- All data is transmitted digitally via satellite uplink direct from the station.
So this means that:
- There are no observer or transcription errors to correct.
- There is no time of observation bias, nor need for correction of it.
- There is no broad scale missing data, requiring filling in data from potentially bad surrounding stations. (FILNET)
- There are no needs for bias adjustments for equipment types since all equipment is identical.
- There are no need for urbanization adjustments, since all stations are rural and well sited.
- There are no regular sensor errors due to air aspiration and triple redundant lab grade sensors. Any errors detected in one sensor are identified and managed by two others, ensuring quality data.
- Due to the near perfect geospatial distribution of stations in the USA, there isn’t a need for gridding to get a national average temperature.
Knowing this, I wondered why NOAA has never offered a CONUS monthly temperature from this new network. So, I decided that I’d calculate one myself.
The procedure for a CONUS monthly average temperature from USCRN:
- Download each station data set from here: USCRN Quality Controlled Datasets.
- Exclude stations that are part of the USHCN-M (modernized USHCN) or USRCRN-Lite stations which are not part of the 114 station USCRN master set.
- Exclude stations that are not part of the CONUS (HI and AK)
- Load all July USCRN 114 station data into an Excel Spreadsheet, available here: CRN_CONUS_stations_July2012_V1.2
- Note stations that have missing monthly totals data. Three in July 2012, Elgin, AZ, (4 missing days) Avondale, PA,(5 missing days) McClellanville, SC, (7 missing days) and set their data aside to be dealt with separately.
- Do sums and calculate CONUS area averages from the Tmax, Tmin, Tavg and Tmean data provided for each station.
- Do a separate calculation to see how much difference the stations with missing/partial data make for the entire CONUS.
Here are the results:
USA Monthly Mean for July 2012: 75.72°F
(111 stations)
USA Monthly Average for July 2012: 75.51°F
(111 stations)
USA Monthly Mean for July 2012: 75.74°F
(114 stations, 3 w/ partial missing data, difference 0.02)
USA Monthly Average for July 2012: 75.55°F
(114 stations, 3 w/ partial missing data, difference 0.04)
============================
Comparison to NOAA’s announcement today:
Using the old network, NOAA says the USA Average Temperature for July 2012 is: 77.6°F
Using the NOAA USCRN data, the USA Average Temperature for July 2012 is: 75.5°F
The difference between the old problematic network and new USCRN is 2.1°F cooler.
This puts July 2012, according to the best official climate monitoring network in the USA at 1.9°F below the 77.4°F July 1936 USA average temperature in the NOAA press release today, not a record by any measure. Dr. Roy Spencer suggested earlier today that he didn’t think so either, saying:
So, all things considered (including unresolved issues about urban heat island effects and other large corrections made to the USHCN data), I would say July was unusually warm. But the long-term integrity of the USHCN dataset depends upon so many uncertain factors, I would say it’s a stretch to to call July 2012 a “record”.
This result also strongly suggests, that a well sited network of stations, as the USCRN is designed from inception to be, is totally free of the errors, biases, adjustments, siting issues, equipment issues, and UHI effects that plague the older COOP USHCN network that is a mishmash of problems that the new USCRN was designed to solve.
It suggests Watts et al 2012 is on the right track when it comes to pointing out the temperature measurement differences between stations with and without such problems. I don’t suggest that my method is a perfect comparison to the older COOP/USHCN network, but the fact that my numbers come close, within the bounds of the positive temperature bias errors noted in Leroy 1999, and that the more “pristine” USCRN network is cooler for absolute monthly temperatures (as would be expected) suggests my numbers aren’t an unreasonable comparison.
NOAA never mentions this new pristine USCRN network in any press releases on climate records or trends, nor do they calculate and display a CONUS value for it. Now we know why. The new “pristine” data it produces is just way too cool for them.
Look for a regular monthly feature using the USCRN data at WUWT. Perhaps NOAA will then be motivated to produce their own monthly CONUS Tavg values from this new network. They’ve had four years to do so since it was completed.
UPDATE: Some people questioned what is the difference between the mean and average temperature values. In the monthly data files from USCRN, there are these two values:
T_MONTHLY_MEAN
T_MONTHLY_AVG
http://www.ncdc.noaa.gov/crn/qcdatasets.html
The mean is the monthly (max+min)/2, and the average is the average of all the daily averages.
UPDATE2: I’ve just sent this letter to NCDC – to ncdc.info@ncdc.noaa.gov
Hello,
I apologize for not providing a proper name in the salutation, but none was given on the contact section of the referring web page.
I am attempting to replicate the CONUS temperature average of 77.6 degrees Fahrenheit for July 2012, listed in the August 8th 2012, State of the Climate Report here: http://www.ncdc.noaa.gov/sotc/
Pursuant to that, would you please provide the following:
1. The data source of the surface temperature record used.
2. The list of stations used from that surface temperature record, including any exclusions and reasons for exclusions.
3. The method used to determine the CONUS average temperature, such as simple area average, gridded average, altitude corrections, bias corrections, etc. Essentially what I’m requesting is the method that can be used to replicate the resultant 77.6F CONUS average value.
4. A flowchart of the procedures in step 3 if available.
5. Any other information you deem relevant to the replication process.
Thank you sincerely for your consideration.
Best Regards,
Anthony Watts
===================================================
Below is the response I got to the email address provided in the SOTC release, some email addresses redacted to prevent spamming.
===================================================
—–Original Message—–
From: mailer-daemon@xxxx.xxxx.xxx
Date: Thursday, August 09, 2012 3:22 PM
To: awatts@xxxxxxx.xxx
Subject: Undeliverable: request for methods used in SOTC press release
Your message did not reach some or all of the intended recipients.
Sent: Thu, 9 Aug 2012 15:22:43 -0700
Subject: request for methods used in SOTC press release
The following recipient(s) could not be reached:
ncdc.info@ncdc.noaa.gov
Error Type: SMTP
Error Description: No mail servers appear to exists for the recipients address.
Additional information: Please check that you have not misspelled the recipients email address.
hMailServer
===============================
UPDATE3: 8/10/2012. This may put the issue to rest about straight averaging -vs- some corrected method. From http://www.ncdc.noaa.gov/temp-and-precip/us-climate-divisions.php
It seems they are using TCDD (simple average) still. I’ve sent an email to verify…hopefully they get it.
Traditional Climate Divisional Database
Traditionally, climate division values have been computed using the monthly values for all of the Cooperative Observer Network (COOP) stations in each division are averaged to compute divisional monthly temperature and precipitation averages/totals. This is valid for values computed from 1931 to the present. For the 1895-1930 period, statewide values were computed directly from stations within each state. Divisional values for this early period were computed using a regression technique against the statewide values (Guttman and Quayle, 1996). These values make up the traditional climate division database (TCDD).
Gridded Divisional Database
The GHCN-D 5km gridded divisional dataset (GrDD) is based on a similar station inventory as the TCDD however, new methodologies are used to compute temperature, precipitation, and drought for United States climate divisions. These new methodologies include the transition to a grid-based calculation, the inclusion of many more stations from the pre-1930s, and the use of NCDC’s modern array of quality control algorithms. These are expected to improve the data coverage and the quality of the dataset, while maintaining the current product stream.
The GrDD is designed to address the following general issues inherent in the TCDD:
- For the TCDD, each divisional value from 1931-present is simply the arithmetic average of the station data within it, a computational practice that results in a bias when a division is spatially undersampled in a month (e.g., because some stations did not report) or is climatologically inhomogeneous in general (e.g., due to large variations in topography).
- For the TCDD, all divisional values before 1931 stem from state averages published by the U.S. Department of Agriculture (USDA) rather than from actual station observations, producing an artificial discontinuity in both the mean and variance for 1895-1930 (Guttman and Quayle, 1996).
- In the TCDD, many divisions experienced a systematic change in average station location and elevation during the 20th Century, resulting in spurious historical trends in some regions (Keim et al., 2003; Keim et al., 2005; Allard et al., 2009).
- Finally, none of the TCDD’s station-based temperature records contain adjustments for historical changes in observation time, station location, or temperature instrumentation, inhomogeneities which further bias temporal trends (Peterson et al., 1998).
The GrDD’s initial (and more straightforward) improvement is to the underlying network, which now includes additional station records and contemporary bias adjustments (i.e., those used in the U.S. Historical Climatology Network version 2; Menne et al., 2009).
The second (and far more extensive) improvement is to the computational methodology, which now addresses topographic and network variability via climatologically aided interpolation (Willmott and Robeson, 1995). The outcome of these improvements is a new divisional dataset that maintains the strengths of its predecessor while providing more robust estimates of areal averages and long-term trends.
The NCDC’s Climate Monitoring Branch plans to transition from the TCDD to the more modern GrDD by 2013. While this transition will not disrupt the current product stream, some variances in temperature and precipitation values may be observed throughout the data record. For example, in general, climate divisions with extensive topography above the average station elevation will be reflected as cooler climatology. A preliminary assessment of the major imapacts of this transition can be found in Fenimore, et. al, 2011.
Simon says:
The two sets of weather stations are in different places.Therefore the averages are different. Nick has calculated the average altitude of the two sets and the historical network set was on average 178m higher. The NOAA report the historic set average so that it is directly comparable with previous years
If USCRN and USHCN are not comparable because they are two sets of weather stations in different places, then how are USHCN 1936 and USHCN 2012 comparable? They are also two sets of weather stations in different places…
So, based on what wayne is saying, even if temperatures in the 30’s were exactly the same as now, today’s would be recorded at higher because we now can record short duration peaks that would have been missed in the 30s.
Do people agree with this?
If so, this tells me that we simply do not know if we are now warmer or colder than in the 30s, unless there are some stations that maintained the same type of equipment between the 302 and today – are there?
I am told the accuracy of the temp in the part of the record where they used thermometers was +/1 0.5 deg C. Is that right? What is the accuracy now? When were the sensors in the old COOP/USHCN network moved over to the new more accurate sensors.
Sorry that these are likely old questions but I am about to give a talk and want to have these things straight in my mind.
Theoretically, yes, but not likely in the CRN, at least not due to factors of nearby human influence like a brief wind tranporting some a/c heat exchanger exhaust. The response times of the LIG thermometer and the PRT thermometer are likely an order of magnitude difference, with PRT being faster, but IIRC correctly they have a sampling algorithm that brings the response times back in line. I don’t see this as an issue.
G David says:
I ran this past a Warmist and his reply was:
” that’s an oranges / apples comparison. You’re comparing 76-year-old records from all US weather stations with records from a new, specialised climate monitoring network.
That is true. It is also true that NOAA is comparing 76 year old records from the 1936 network against records from a different, newer 2012 network.
“It’d be like measuring the length of a football field with an old fibreglass tape, and comparing it to the measurement made with a high-precision laser rangefinder.”
Actually, it is more like measuring a football field in 1936 with an old kinky metal tape, measuring it again in 2012 with an old frayed fiberglass tape and calling the comparison “good” … and then measuring it again in 2012 with a laser rangefinder and complaining about the comparison.
“Have you adjusted (I believe “homogenised” is the term climate scientists use) the USCRN results to match those from the old temperature series?”
Probably – becuase ‘adjusting’ better data to match worse data is what they tend to do. Can’t imagine that they have forsaken this opportunity.
“Or vice versa?”
Not possible. You can “adjust” inconsistent data to “match” better data all you want. It will still be inconsistent.
” But, given that we’re interested in the trend here, …”
Dutiful regurigitation of the standard warmist talking point, but we are not talking about trend here. We are talking about a rank comparison.
“Or is it your position that, because we didn’t have a super-high-quality climate monitoring network in place, that we should completely ignore any climate data gathered prior to the USCRN being commissioned?”
Completely? No. But we should absolutely ignore it when it is not sufficient to the task at hand. That would include
“Never mind that the USHCN data correlates very well with the satellite data, …”
No it doesnt. The different surface records give different rankings from each other, which are different from the satellite rankings – rankings being what we are talking about now. Of course,they also give different trends …
Tom Harris says:
So, based on what wayne is saying, even if temperatures in the 30′s were exactly the same as now, today’s would be recorded at higher because we now can record short duration peaks that would have been missed in the 30s.
Do people agree with this?
I’m not sure that is a valid argument. The new sensors may have a faster response time, but the response time of the system is determined by the sampling interval. Given that the recording interval is given as 5 minutes, that is likely the sampling interval as well.
So, how does the response time of a max/min LIG thermometer compare to 5 minutes?
There are likely numerous other instrumentation issues that could be affected by transient temp spikes. One of the fundamental deficiencies of the historic networks is the reliance on the faulty Tmax-Tmin/2 – Tmean idea of average temperature. That is very sensitive to transient spikes, and also to more diffuse differences in temp distribution. Everyone knows that this deficiency exists, but no one wants to face it because they want to use those data.
It is very similar to the way that no one faces the fact that we are arguing global heat content in terms of surface temperature…
So NOAA is using “Mean” and Average backwards?
I can sit still for “Average” be the (Min+Max)/2.
the Mean is almost always to meant to be an centroid of all measurements. So when you are making two measurements a day, min and max, ok, I can grudgingly accept mean.
But that is not the convention adopted by NOAA?
As I understand it,
T_MONTHLY_MEAN = (T_MONTHLY_MAX + T_MONTHLY_MIN) / 2
(which really should be written
T_MONTHLY_MEAN = (T_MONTHLY_AVGMAX + T_MONTHLY_AVGMIN) / 2 )
T_MONTHLY_AVG = (Sum of 24*(days in month) AVG (or mean!) temperature readings.)
So it doesn’t apply when all you have is a min max stations? In my book, this is closer to the true meaning of “mean”.
Mean ought to be the integration of all data points in the record, divided by the time frame. It should never have been adopted as mid point of the min-max outliers on any time scale. What’s done is done. This confusing and irregular terminology is another example of poorly the whole system has been set up.
Anthony, very kindly, I have to disagree that this is a non-issue. The reason is looking at the final results and what is actually coming out of the climate system. I have used two sources:
http://w1.weather.gov/data/obhistory/KOKC.html
This is the last three days hourly data. You have to be quick to capture this level of data for it doesn’t seem this data further back is available to the public.
and
http://www.srh.noaa.gov/oun/climate/get_f6.php
For monthly maximum and minimum temperatures with other data.
For August 2012 so far:
This is what is reported and I assume this is what is passed on up stream to create the national climatology data.
Now here is what you would get if you merely took the hourly maximum from the hourly data:
Now from what I can tell so far it is the top version that gets passed along and this must be a maximum small slice of an hour’s maximum.
That is all I wanted someone to realize. I think it is relevant when you are comparing maximum temperatures far back in time when sub-hour measurements were not even being made. How would you ever do you reconcile this except by ignoring these instantaneous temperatures and sticking with the hourly averages?
So I think it is *reported* warmer in 2012 compared to the 1930’s partially due to something this simple. This is not to marginalize what this thread is about but just to add credence to your point.
I still don’t understand.
Let’s say the new thermocouples can pick up temperature heat bursts of, say, 1/10 of a second duration (Does anyone know how short a spike they can resolve?), then, if no filtering was done on the data, a 1/10th second heat spike could make it through into the record of the highest temperature that day.
So, I assume (but don’t know – does anyone?), that they must filter the data so that temperature spikes less than a certain time duration are filtered out. Is this so? If so, how long does a spike have to last before it is accepted into the final data for that station?
If the thermal inertia of a thermometer in the 30s was such that it effectively took an average temp over a, say, 3 min period, then the only way one could compare those readings with today would be if today’s data was filtered so that very short duration spikes were removed and the data averaged over the 3 min, with all the short time duration bursts removed. Do they do that?
If the Stevenson boxes used the Six registering thermometer, it might be interesting to hear how these were reset. I get that they would only register one maximum and one minimum temperature per day – the limits that the liquids were pushed by internal pressures for that period. Still, a Wiki article points out that the thermometer was prone (actually, “notorious”) for a few design flaws:
From article, “Six’s thermometer”:
http://en.wikipedia.org/wiki/Maximum_minimum_thermometer
Beyond any chemistry issues that could affect their function, I can’t help but wonder how human error might have biased a long term record – say, forgetting to shake (or otherwise reset) the thermometer columns back into place every day. I suppose both the same max / min temps would be carried across to the second day, so maybe that’s not such an issue. Just curious.
Tom Harris says:
I still don’t understand.
Let’s say the new thermocouples can pick up temperature heat bursts of, say, 1/10 of a second duration (Does anyone know how short a spike they can resolve?), then, if no filtering was done on the data, a 1/10th second heat spike could make it through into the record of the highest temperature that day.
Your problem is that you are assuming the sampling rate is the same as the thermocouple response time. If the thermocouple can respond to an event of 1/10 second duration, but is only sampled once every 5 minutes then a 1/10 second event is only going to get recorded about 1 in every 3000 times it occurs – i.e. when it happens to occur at the moment a sample is taken.
Above, someone says the recording rate is 1 record every 5 minutes. Not given is the sampling rate, or the method of aggregating sample values into a record, if there is more than 1 sample per record.
FYI, all, Anthony just told me that, when you count the thermal mass of the PRT case holding the device, the response times of LIG and PRT are not very different. So this seems like a non-issue.
JJ says:
August 10, 2012 at 12:55 pm
“Actually, it is more like measuring a football field in 1936 with an old kinky metal tape, measuring it again in 2012 with an old frayed fiberglass tape and calling the comparison “good” … and then measuring it again in 2012 with a laser rangefinder and complaining about the comparison.”
As an old land surveyor, I like to mostly lurk but let me give my two cents worth. Being an old land surveyor, I could measure a football field with the old kinky metal tape (chain) just as accurately as the laser rangefinder. The reason why I say this is because the I looked up the accuracy for a laser rangefinder to find it’s +-10 cm or 0.33 feet.
Real chains, called Gunters chains, were used in the 18th and 19th centuries by surveyors but when the 100 or 200 foot steal tapes were introduced in the early 20th they were still called chains. Surveyors, at least in Kansas, use feet as the basic unit but with a base ten system of tenths and hundreds of feet. This is because most old land deeds use these units so it’s easy to keep it the consistent.
You are right about the use of fiberglass tapes today but we use them for approximate measurements and for something the size of a football field we discovered their accuracy is +-0.5 ft. When I first started in the 70’s we still used chains and I actually did stake out a football field once with a chain and we and our accuracy was +-0.35 ft or almost as accurate as today’s langefinders. Now I know the old kinky chain will have issues but there are techniques used to calibrate it to get an accurate measurement. Even the old frayed fiberglass tape that stretches easily can be calibrated if you know what you’re doing.
A better analogy would be to compare the metal or fiberglass tapes to either a theadolite-electronic distance meter(EDM) or the latest and most accurate GPS geosystems. We are able to get +-0.05 ft./1.5 cm for the EDM and +-0.02 ft./0.5 cm for the GPS.
I’m sure everyone gets your point but I thought I’d educate you a little about taking accurate distance measurements. We are also able to get accurate vertical measurements too with a +-1 cm accuracy for both electronic systems.
@Tom Harris says:
August 10, 2012 at 3:15 pm
“FYI, all, Anthony just told me that, when you count the thermal mass of the PRT case holding the device, the response times of LIG and PRT are not very different. So this seems like a non-issue.”
OK, I’ll buy that for now but it seems most people I know, if they knew what they were really comparing, would care much whether the average of the warmest few minutes, averaged, now were a degree or a fraction of a degree higher than the average of the warmest few minutes were back in the ‘30s.
I seem to have always assumed that these numbers were at least the warmest average ‘hour’ so those fast fluctuations with warm winds were just averaged out of the record but it seems I was incorrect. Learn something every day.
REPLY:
I had looked at the specs on the PRT, and due to it being encased, it has a thermal mass. From the spec sheet:
Time Constant: 63% of thermal response in 13 sec when immersed from 20°C air into 50°C water flowing at 0.2 m/s
http://www1.ncdc.noaa.gov/pub/data/uscrn/documentation/site/sensors/airtemperature/Descriptions/summarycurrentairtempsensor.doc
So it’s not far off the old LIG response time of 10-30 seconds due to its thermal mass. All three PRT’s have to be within 0.3 of each other for it to be a real value that passes QC.
-Anthony
Thank you Anthony. Didn’t mean to raise a meaningless question. I just always considered some thermal mass, to a certain degree, to be good, for that in itself helps in averaging out fast and spurious peaks and troughs in the temperature readings. Seems everyone else (climatologists) tend to like fast thermometers to maintain those fast fluctuations but that does magnify the extremes on both sides. Thanks again for the input. (Also never thought I would even spend a summer with an electronic thermometer outdoors next to me most of the time, gives you a new perspective on these issues)
DCA,
Your $0.02 is appreciated. I routinely use both survey grade GPS and a laser theodolite (total station) in my work. It was that laser range finder that I was thinking of above.
The kinky steel tape I was picturing wouldn’t have been an old surveyor’s chain. You old surveyors tend to appreciate your equipment and care for it a bunch better than some of our field crews. Several tenths here and there doesn’t really affect their work, and the battered remains of a dozen tapes in our storeroom are testament to the fact that they know it. The fiberglass? Good grief. If one of those bedraggeled 100m reels has more than 297 ft left on it, that’s the “good” one.
That is about how I see weather data. The equipment (either the individual instruments or networks of same) may be capable of X level of accuracy, but that isn’t going to be achieved if the operators understand that the goal of the effort is consistent with a lower standard of rigor …
[Snip. Repreated ‘denial’ comments. ~dbs, mod.]
Even if their assertion was ‘accurate’ it is only accurate by +0.2 degree. Ooooh! Scary, scary, scary, and so far inside the bounds of instrument error as to be meaningless. Basically the SAME RESULT as July 1936. In other words, it took 76 years for all that huffing and puffing of supposed AGW to REWARM the planet to the same temperature. And then Nick Stokes gets his knickers in a knot? C’mon, Nick, you need better tweezers to pick fly shytte out of black pepper. What an inane waste of effort. This is the “warmest ever” that all the warmists are bleating about. Let’s see: 0.2/377K=0.053050397878%. This is so bloody ludicrous as to make a person glad that he is old.
[Snip. This is a potholer-free blog. Read the archives to see why. ~dbs, mod.]
The analogue used previously with the tape and laser is rather interesting. It would be akin to saying that the old sailing ships were more efficient than the new technology model because they were wind powered and therefore better. Forgetting about the amount of crew it required to handle it. It has already been stated that the temps taken way back in the early 1900s were random at best, taken at different times at worst. Both those efforts would vary the temps results.
Now we have technology making adjustments using algorithms and the claim stands that this would not make any difference and yet the new system in place is claimed to be affected by elevation, when in fact it still only records the temps in order to record warming or cooling. That entire argument just demonstrates that cherry picking by warmists is a preference and does not really require substantiation as long as it shows their required end result. is demonstrated. It is truly becoming quite a farce.
The Washington Post article on US temperature (Sunday, August 12th) presents a NOAA temperature graph overlaid with a straight line showing a steady increase in temperature from 1900 all the way to 2010. The global cooling betwixt the 40s and 70s, and the flat global temp from about 1998 till now doesn’t show up. Is this a regional issue, or would the better temperature records you are using show this difference?
The Washington Post (August 11th) shows a NOAA temperature graph with an overlaid straight line average which increases steadily from 1900 to 2010. Is it the case that the there is merely a regional discrepancy with global temperatures reported elsewhere, namely the cooling during the 40s to 70s and the straight line temp from about 1998 to 2010?
Forget my (just earlier) query. The new improved stations can’t do anything about the earlier NOAA temp records
Looks as if all 3 of the above can be deleted. My bad. But I did send a link to this site to The Washington Post author, and mentioned the 2 degree discrepancy. He acknowledged, and is investigating. I’d still like to know why the NOAA graph (in the Post) shows a steady increase. Is that a problem with their curve fitting? I can’t believe the US has been showing a temp increase for 15 years when the global temp has been flat. (Also, same issue, what about the 1940s to 1970s ?)
Pardon me if this has been mentioned; I couldn’t wade through all the comments. But I don’t see the big deal here — so, the average of a brand new data set doesn’t match the old data set. Wow! Hold the presses! (And do you think this may be why they aren’t using the new data set yet – to do so would require adjustment, and since that’s a dirty word here, I’m surprised you object.)
Dear climatebeagle says: August 9, 2012 at 7:17 am & Anthony’’s Reply
Where you asked if the 5 minute temperature data was available at NOAA’s site. The technical answer is yes. To get this data:
1) Go to the “Observations” section here: http://www.ncdc.noaa.gov/crn/observations.htm
2) Pick an individual station
3) Under “Station Information” pick “Sensor Data”
4) The Pick “Temperature”
At this point you can see the individual 5-minute sensor readings as well as the calculated value for the site – as a table. You have to manually grab the data and insert it into say excel… so it’s not exactly user friendly and it would take forever to get a month’s worth of data for a single station. But it can, technically, be done.
NOAA also has a price sheet for detailed climate data. See at the bottom of the site here: http://www.ncdc.noaa.gov/crn/qcdatasets.html.
Where NOAA states:
Obviously the data would be a gold mine for those of us interested in TOB issues and any bias that the use of a daily Tmax and Tmin would have (in comparison to simply using the average of the five minute readings). But the price of a full years worth of data for all stations looks to be in the range of $100 and is bit above my level of affordability.
Regards, Kforestcat
Reblogged this on The GOLDEN RULE and commented:
Keeping an eye on another global scam, that of introducing political and social control on the pretext of Catastrophic Anthropogenic Global Warming. As we have come to expect, valuable information from WUWT proving the lack of scientific evidence for the introduction of carbon controls and taxes,