GLOBAL COOLING !!!! Return of Arctic ice cap as it grows by 29%


A chilly Arctic summer has left 533,000 more square miles of ocean covered with ice than at the same time last year – an increase of 29 per cent.

The rebound from 2012’s record low comes six years after the BBC reported that global warming would leave the Arctic ice-free in summer by 2013.

Instead, days before the annual autumn re-freeze is due to begin, an unbroken ice sheet more than half the size of Europe already stretches from the Canadian islands to Russia’s northern shores.




ice sheet graphic.jpg



 Since publication of the original version of this article, the US source of the figures – the NASA-funded National Snow and Ice Data Centre (NSIDC) – was discovered to have made a huge error and then quietly corrected the figure without mentioning it.

On September 4, NSIDC, based at the University of Colorado, stated on its website that in August 2013 the Arctic ice cover recovered by a record 2.38 million sq km – 919,000 sq miles – from its 2012 low.

News of this figure was widely reported – including by Mailonline – on September 8. But on September 10, the NSIDC quietly changed it to 1.38 million sq km (533,000 sq miles) – and replaced the original document so the old figure no longer shows up on a main Google search. It can now only be found on an old ‘cached’ page.

The figures in this article have now been corrected.

Prompted by an inquiry from ‘green’ blogger Bob Ward, the NSIDC’s spokeswoman Natasha Vizcarra said the mistake was a ‘typographical error’, telling him: ‘There are no plans to make a statement on the change because it was not an error in the data.’

The Northwest Passage from the Atlantic to the Pacific has remained blocked by pack-ice all year. More than 20 yachts that had planned to sail it have been left ice-bound and a cruise ship attempting the route was forced to turn back.

Some eminent scientists now believe the world is heading for a period of cooling that will not end until the middle of this century – a process that would expose computer forecasts of imminent catastrophic warming as dangerously misleading.

The disclosure comes 11 months after The Mail on Sunday triggered intense political and scientific debate by revealing that global warming has ‘paused’ since the beginning of 1997 – an event that the computer models used by climate experts failed to predict.

In March, this newspaper further revealed that temperatures are about to drop below the level that the models forecast with ‘90 per cent certainty’.

The pause – which has now been accepted as real by every major climate research centre – is important, because the models’ predictions of ever-increasing global temperatures have made many of the world’s economies divert billions of pounds into ‘green’ measures to counter  climate change.

Those predictions now appear gravely flawed.

The continuing furore caused by The Mail on Sunday’s revelations – which will now be amplified by the return of the Arctic ice sheet – has forced the UN’s climate change body to reconsider its position.

The UN Intergovernmental Panel on Climate Change (IPCC) was due in October to start publishing its Fifth Assessment Report – a huge three-volume study issued every six or seven years. It will hold a pre-summit in Stockholm later this month.


Only six years ago, the BBC reported that the Arctic would be ice-free in summer by 2013, citing a scientist in the US who claimed this was a ‘conservative’ forecast. Perhaps it was their confidence that led more than 20 yachts to try to sail the Northwest Passage from the Atlantic to  the Pacific this summer. As of last week, all these vessels were stuck in the ice, some at the eastern end of the passage in Prince Regent Inlet, others further west at Cape Bathurst.

Shipping experts said the only way these vessels were likely to be freed was by the icebreakers of the Canadian coastguard. According to the official Canadian government website, the Northwest Passage has remained ice-bound and impassable  all summer.

The BBC’s 2007 report quoted scientist  Professor Wieslaw Maslowski, who based his views on super-computer models and the fact that ‘we use a high-resolution regional model for the Arctic Ocean and sea ice’.

He was confident his results were ‘much more realistic’ than other projections, which ‘underestimate the amount of heat delivered to the sea ice’. Also quoted was Cambridge University expert

Professor Peter Wadhams. He backed Professor Maslowski, saying his model was ‘more efficient’ than others because it ‘takes account of processes that happen internally in the ice’.

He added: ‘This is not a cycle; not just a fluctuation. In the end, it will all just melt away quite suddenly.’



Leaked documents show that governments which support and finance the IPCC are demanding more than 1,500 changes to the report’s ‘summary for policymakers’. They say its current draft does not properly explain the pause.

At the heart of the row lie two questions: the extent to which temperatures will rise with carbon dioxide levels, as well as how much of the warming over the past 150 years – so far, just 0.8C – is down to human greenhouse gas emissions and how much is due to natural variability.

In its draft report, the IPCC says it is ‘95 per cent confident’ that global warming has been caused by humans – up from 90 per cent in 2007.


This claim is already hotly disputed. US climate expert Professor Judith Curry said last night: ‘In fact, the uncertainty is getting bigger. It’s now clear the models are way too sensitive to carbon dioxide. I cannot see any basis for the IPCC increasing its confidence level.’

She pointed to long-term cycles  in ocean temperature, which have a huge influence on climate and  suggest the world may be approaching a period similar to that from 1965 to 1975, when there was a clear cooling trend. This led some scientists at the time to forecast an imminent ice age.

Professor Anastasios Tsonis, of the University of Wisconsin, was one of the first to investigate the ocean cycles. He said: ‘We are already in a cooling trend, which I think will continue for the next 15 years at least. There is no doubt the warming of the 1980s and 1990s has stopped.

Then... NASA satelite images showing the spread of Artic sea ice 27th August 2012

Then… NASA satellite images showing the spread of Arctic sea ice 27th August 2012


...And now, much bigger: The spread of Artic sea ice on August 15 2013

…And now, much bigger: The same Nasa image taken in 2013



‘The IPCC claims its models show a pause of 15 years can be expected. But that means that after only a very few years more, they will have to admit they are wrong.’


Others are more cautious. Dr Ed Hawkins, of Reading University, drew the graph published by The Mail on Sunday in March showing how far world temperatures have diverged from computer predictions. He admitted the cycles may have caused some of the recorded warming, but insisted that natural variability alone could not explain all of the temperature rise over the past 150 years.

Nonetheless, the belief that summer Arctic ice is about to disappear remains an IPCC tenet, frequently flung in the face of critics who point to the pause.

Yet there is mounting evidence that Arctic ice levels are cyclical. Data uncovered by climate historians show that there was a massive melt in the 1920s and 1930s, followed by intense re-freezes that ended only in 1979 – the year the IPCC says that shrinking began.

Professor Curry said the ice’s behaviour over the next five years would be crucial, both for understanding the climate and for future policy. ‘Arctic sea ice is the indicator to watch,’ she said.


 NOAA shows ‘the pause’ in the U.S. surface temperature record over nearly a decade

After years of waiting, NOAA has finally made a monthly dataset on the U.S. Climate Reference Network available in a user friendly way via their recent web page upgrades. This data is from state-of-the-art ultra-reliable triple redundant weather stations placed on pristine environments. As a result, these temperature data need none of the adjustments that plague the older surface temperature networks, such as USHCN and GHCN, which have been heavily adjusted to attempt corrections for a wide variety of biases. Using NOAA’s own USCRN data, which eliminates all of the squabbles over the accuracy of and the adjustment of temperature data, we can get a clear plot of pristine surface data. It could be argued that a decade is too short and that the data is way too volatile for a reasonable trend analysis, but let’s see if the new state-of-the-art USCRN data shows warming.

A series of graphs from NOAA follow, plotting Average, Maximum, and Minimum surface temperature follow, along with trend analysis and original source data to allow interested parties to replicate it.

First, some background on this new temperature monitoring network, from the network home page:

USCRN Station


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.


As you can see from the map below, the USCRN is well distributed, with good spatial resolution, providing an excellent representivity of the CONUS, Alaska, and Hawaii.


From the Site Description page of the USCRN:


Every USCRN observing site is equipped with a standard set of sensors, a data logger and a satellite communications transmitter, and at least one weighing rain gauge encircled by a wind shield. Off-the-shelf commercial equipment and sensors are selected based on performance, durability, and cost.

Highly accurate measurements and reliable reporting are critical. Deployment includes calibrating the installed sensors and maintenance will include routine replacement of aging sensors. The performance of the network is monitored on a daily basis and problems are addressed as quickly as possible, usually within days.

Many criteria are considered when selecting a location and establishing a USCRN site:

  • Regional and spatial representation: Major nodes of regional climate variability are captured while taking into account large-scale regional topographic factors.
  • Sensitivity to the measurement of climate variability and trends: Locations should be representative of the climate of the region, and not heavily influenced by unique local topographic features and mesoscale or microscale factors.
  • Long term site stability: Consideration is given to whether the area surrounding the site is likely to experience major change within 50 to 100 years. The risk of man made encroachments over time and the chance the site will close due to the sale of the land or other factors are evaluated. Federal, state, and local government land and granted or deeded land with use restrictions (such as that found at colleges) often provide a high stability factor. Population growth patterns are also considered.
  • Naturally occurring risks and variability:
    • Flood plains and locations in the vicinity of orographically induced winds like the Santa Ana and the Chinook are avoided.
    • Locations with above average tornado frequency or having persistent periods of extreme snow depths are avoided.
    • Enclosed locations that may trap air and create unusually high incidents of fog or cold air drainage are avoided.
    • Complex meteorological zones, such as those adjacent to an ocean or to other large bodies of water are avoided.
  • Proximity:
    • Locations near existing or former observing sites with long records of daily precipitation and maximum and minimum temperature are desirable.
    • Locations near similar observing systems operated and maintained by personnel with an understanding of the purpose of climate observing systems are desirable.
    • Endangered species habitats and sensitive historical locations are avoided.
    • A nearby source of power is required. AC power is desirable, but, in some cases, solar panels may be an alternative.
  •  Access: Relatively easy year round access by vehicle for installation and periodic maintenance is desirable.



As you can see, every issue and contingency has been thought out and dealt with. Essentially, the U.S. Climate Reference Network is the best climate monitoring network in the world, and without peer. Besides being in pristine environments away from man-made influences such as urbanization and resultant UHI issues, it is also routinely calibrated and maintained, something that cannot be said for the U.S. Historical Climate Network (USHCN), which is a mishmash of varying equipment (alcohol thermometers in wooden boxes, electronic thermometers on posts, airport ASOS stations placed for aviation), compromised locations, and a near complete lack of regular thermometer testing and calibration.

Having established its equipment homogenity, state of the art triple redundant instrumentation, lack of environmental bias, long term accuracy, calibration, and lack of need for any adjustments, let us examine the data produced for the last decade by the U.S. Climate Reference Network.

First, from NOAA’s own plotter at the National Climatic Data Center in Asheville, NC, this plot they make available to the public showing average temperature for the Contiguous United States by month:


Source: NCDC National Temperature Index time series plotter

To eliminate any claims of “cherry picking” the time period, I selected the range to be from 2004 through 2014, and as you can see, no data exists prior to January 2005. NOAA/NCDC does not make any data from the USCRN available prior to 2005, because there were not enough stations in place yet to be representative of the Contiguous United States. What you see is the USCRN data record in its entirety, with no adjustments, no start and end date selections, and no truncation. The only thing that has been done to the monthly average data is gridding the USCRN stations, so that the plot is representative of the Contiguous United States.

Helpfully, the data for that plot is also made available on the same web page. Here is a comma separated value (CSV) Excel workbook file for that plot above from NOAA:

USCRN_Avg_Temp_time-series (Excel Data File)

Because NOAA/NCDC offers no trend line generation in  their user interface, from that NOAA provided data file, I have plotted the data, and provided a linear trend line using a least-squares curve fitting procedure which is a function in the DPlot program that I use.

Not only is there a pause in the posited temperature rise from man-made global warming, but a clearly evident slight cooling trend in the U.S. Average Temperature over nearly the last decade:


We’ve had a couple of heat waves and we’ve had some cool spells too. In other words, weather.

The NCDC National Temperature Index time series plotter also makes maximum and minimum temperature data plots available. I have downloaded their plots and data, supplemented with my own plots to show the trend line. Read on.


NOAA/NCDC plot of maximum temperature:

USCRN_max_temp_Jan2004-April2014Source of the plot here.

Data from the plot: USCRN_Max_Temp_time-series (Excel Data File)*

My plot with trend line:


As seen by the trend line, there is a slight cooling in maximum temperatures in the Contiguous United States, suggesting that heat wave events (seen in 2006 and 2012) were isolated weather incidents, and not part of the near decadal trend.


NOAA/NCDC plot of minimum temperature:


Source of the plot here.

USCRN_Min_Temp_time-series (Excel Data File)*

The cold winter of 2013 and 2014 is clearly evident in the plot above, with Feb 2013 being -3.04°F nationally.

My plot with trend line:


*I should note that NOAA/NCDC’s links to XML, CSV, and JSON files on their plotter page only provide the average temperature data set, and not the maximum and minimum temperature data sets, which may be a web page bug. However, the correct data appears in the HTML table on display below the plot, and I imported that into Excel and saved it as a data file in workbook format.

The trend line illustrates a cooling trend in the minimum temperatures across the Contiguous United States for nearly a decade. There is some endpoint sensitivity in the plots going on, which is to be expected and can’t be helped, but the fact that all three temperature sets, average, max, and min show a cooling trend is notable.

It is clear there has been no rise in U.S. surface air temperature in the past decade. In fact, a slight cooling is demonstrated, though given the short time frame for the dataset, about all we can do is note it, and watch it to see if it persists.

Likewise, there does not seem to have been any statistically significant warming in the contiguous U.S. since start of the new USCRN data, using the average, maximum or minimum temperature data.

I asked three people who are well versed in data plotting and analysis to review this post before I published it, one, Willis Eschenbach, added his own graph as part of the review feedback, a trend analysis with error bars, shown below.

CRN Mean US temperature anomaly

While we can’t say there has been a statistically significant cooling trend, even though the slope of the trend is downward, we also can’t say there’s been a statistically significant warming trend either.

What we can say, is that this is just one more dataset that indicates a pause in the posited rise of temperature in the Contiguous United States for nearly a decade, as measured by the best surface temperature monitoring network in the world. It is unfortunate that we don’t have similar systems distributed worldwide.


Something has been puzzling me and I don’t have a good answer for the reason behind it, yet.

As Zeke pointed out in comments and also over at Lucia’s, USCRN and USHCN data align nearly perfectly, as seen in this graph. That seems almost too perfect to me. Networks with such huge differences in inhomogeneity, equipment, siting, station continuity, etc. rarely match that well.


Note that there is an important disclosure missing from that NOAA graph, read on.

Dr Roy Spencer shows in this post the difference from USHCN to USCRN:

Spurious Warmth in NOAA’s USHCN from Comparison to USCRN

The results for all seasons combined shows that the USHCN stations are definitely warmer than their “platinum standard” counterparts:
Spencer doesn’t get a match between USHCN and USCRN, so why does the NOAA/NCDC plotter page?

And our research indicates that USHCN as a whole runs warmer that the most pristine stations within it.

In research with our surfacestations metadata, we find that there is quite a separation between the most pristine stations (Class 1/2) and the NOAA final adjusted data for USHCN. This is examining 30 year data from 1979 to 2008 and also 1979 to present. We can’t really go back further because metadata on siting is almost non-existent. Of course, it all exists in the B44 forms and site drawings held in the vaults of NCDC but is not in electronic form, and getting access is about as easy as getting access to the sealed Vatican archives.

By all indications of what we know about siting, the Class 1/2 USHCN stations should be very close, trend wise, to USCRN stations, yet the ENTIRE USHCN dataset, including the hundreds of really bad stations, with poor siting and trends that don’t come close to the most pristine Class 1/2 stations are said to be matching USCRN. But from our own examination of all USHCN data and nearly all stations for siting, we know that is not true.

So, I suppose I should put out a caveat here. I wrote this above:

“What you see is the USCRN data record in its entirety, with no adjustments, no start and end date selections, and no truncation. The only thing that has been done to the monthly average data is gridding the USCRN stations, so that the plot is representative of the Contiguous United States.”

I don’t know that for a fact to be totally true, as I’m going on what has been said about the intents of NCDC in the way they treat and display the USCRN data. They have no code or methodology reference on their plotter web page, so I can’t say with 100% certainty that the output of that web page plotter is 100% adjustment free.  The code is hidden in a web engine black box, and all we know are the requesting parameters. We also don’t know what their gridding process is. All I know is the stated intent that there will be no adjustments like we see in USHCN.

And some important information is missing that should be plainly listed.  NCDC is doing an anomaly calculation on USCRN data, but as we know, there is only 9 years and 4 months of data. So, what period are they using for their baseline data to calculate the anomaly? Unlike other NOAA graphs like this one below, they don’t show the baseline period or baseline temperature on the graph Zeke plotted above.

This one is the entire COOP network, with all its warts, has the baseline info, and it shows a cooling trend as well, albeit greater than USCRN:



Every climate dataset out there that does anomaly calculations shows the baseline information, because without it, you really don’t know what your are looking at. I find it odd that in the graph Zeke got from NOAA, they don’t list this basic information, yet in another part of their website, shown above, they do.

Are they using the baseline from another dataset, such as USHCN, or the entire COOP network to calculate an anomaly for USCRN? It seems to me that would be a no-no if in fact they are doing that. For example, I’m pretty sure I’d get flamed here if I used the GISS baseline to show anomalies for USCRN.

So until we get a full disclosure as to what NCDC is actually doing, and we can see the process from start to finish, I can’t say with 100% certainty that their anomaly output is without any adjustments, all I can say with certainty is that I know that is their intent.

Given that there are some sloppy things on this new NCDC plotter page, like the misspelling of the word Contiguous. They spell it Continguous, in the plotted output graph title and in the actual data file they produce: USCRN_Avg_Temp_time-series (Excel Data file). Then there’s the missing baseline information on the anomaly calc, and the missing outputs of data files for the max and min temperature data sets (I had to manually extract them from the HTML as noted by asterisk above).

All of this makes me wonder if the NCDC plotter output is really true, and if in the process of doing gridding, and anomaly calcs, if the USCRN data is truly adjustment free. I read in the USCRN documentation that one of the goals was to use that data to “dial in” the adjustments for USHCN, at least that is how I interpret this:

The USCRN’s primary goal is to provide future long-term homogeneous temperature and precipitation observations that can be coupled to long-term historical observations for the detection and attribution of present and future climate change. Data from the USCRN is used in operational climate monitoring activities and for placing current climate anomalies into an historical perspective.

So if that is true, and USCRN is being used to “dial in” the messy USHCN adjustments for the final data set, it would explain why USCHN and USCRN match so near perfectly for those 9+ years. I don’t believe it is a simple coincidence that two entirely dissimilar networks, one perfect, the other a heterogeneous train wreck requiring multiple adjustments would match perfectly, unless there was an effort to use the pristine USCRN to “calibrate” the messy USHCN.

Given what we’ve learned from Climategate, I’ll borrow words from Reagan and say: Trust, but verify

That’s not some conspiracy theory thinking like we see from “Steve Goddard”, but a simple need for the right to know, replicate and verify, otherwise known as science. Given his stated viewpoint about such things, I’m sure Mosher will back me up on getting full disclosure of method, code, and output engine for the USCRN anomaly data for the CONUS so that we can do that,and to also determine if USHCN adjustments are being “dialed in” to fit USCRN data.

# # #

UPDATE 2 (Second-party update okayed by Anthony):  I believe the magnitude of the variations and their correlation (0.995) are hiding the differences.  They can be seen by subtracting the USHCN data from the USCRN data:


read more:



Popular Webpage Posts