Guest post by Jeff Id 
I will leave this alone for another week or two while I wait for a reply to my emails to the BEST group, but there are three primary problems with the Berkeley temperature trends which must be addressed if the result is to be taken seriously. Now by seriously, I don’t mean by the IPCC which takes all alarmist information seriously, but by the thinking person.
Here’s the points:
1 – Chopping of data is excessive. They detect steps in the data, chop the series at the steps and reassemble them. These steps wouldn’t be so problematic if we weren’t worrying about detecting hundredths of a degree of temperature change per year. Considering that a balanced elimination of up and down steps in any algorithm I know of would always detect more steps in the opposite direction of trend, it seems impossible that they haven’t added an additional amount of trend to the result through these methods.
Steve McIntyre discusses this here. At the very least, an examination of the bias this process could have on the result is required.
2 – UHI effect. The Berkeley study not only failed to determine the magnitude of UHI, a known effect on city temperatures that even kids can detect, it failed to detect UHI at all. Instead of treating their own methods with skepticism, they simply claimed that UHI was not detectable using MODIS and therefore not a relevent effect.
This is not statistically consistent with prior estimates, but it does verify that the effect is very small, and almost insignificant on the scale of the observed warming (1.9 ± 0.1 °C/100yr since 1950 in the land average from figure 5A).
This is in direct opposition to Anthony Watts surfacestation project which through greater detail was very much able to detect the ‘insignificant’ effect.
Summary and Discussion
The classification of 82.5% of USHCNv2 stations based on CRN criteria provides a unique opportunity for investigating the impacts of different types of station exposure on temperature trends, allowing us to extend the work initiated in Watts [2009] and Menne et al. [2010].
The comparison of time series of annual temperature records from good and poor exposure sites shows that differences do exist between temperatures and trends calculated from USHCNv2 stations with different exposure characteristics. 550 Unlike Menne et al. [2010], who grouped all USHCNv2 stations into two classes and found that “the unadjusted CONUS minimum temperature trend from good and poor exposure sites … show only slight differences in the unadjusted data”, we found the raw (unadjusted) minimum temperature trend to be significantly larger when estimated from the sites with the poorest exposure sites relative to the sites with the best exposure. These trend differences were present over both the recent NARR overlap period (1979-2008) and the period of record (1895-2009). We find that the partial cancellation Menne et al. [2010] reported between the effects of time of observation bias adjustment and other adjustments on minimum temperature trends is present in CRN 3 and CRN 4 stations but not CRN 5 stations. Conversely, and in agreement with Menne et al. [2010], maximum temperature trends were lower with poor exposure sites than with good exposure sites, and the differences in
trends compared to CRN 1&2 stations were statistically significant for all groups of poorly sited stations except for the CRN 5 stations alone. The magnitudes of the significant trend differences exceeded 0.1°C/decade for the period 1979-2008 and, for minimum temperatures, 0.7°C per century for the period 1895-2009.
The non-detection of UHI by Berkeley is NOT a sign of a good quality result considering the amazing detail that went into Surfacestations by so many people. A skeptical scientist would be naturally concerned by this and it leaves a bad taste in my mouth to say the least that the authors aren’t more concerned with the Berkeley methods. Either surfacestations very detailed, very public results are flat wrong or Berkeley’s black box literal “characterization from space” results are.
Someone needs to show me the middle ground here because I can’t find it.
I sent this in an email to Dr. Curry:
Non-detection of UHI is a sign of problems in method. If I had the time, I would compare the urban/rural BEST sorting with the completed surfacestations project. My guess is that the comparison of methods would result in a non-significant relationship.
3 – Confidence intervals.
The confidence intervals were calculated in this method by eliminating a portion of the temperature stations and looking at the noise that the elimination created. Lubos Motl described the method accurately as intentionally ‘damaging’ the dataset. It is a clever method to identify the sensitivity of the method and result to noise. The problem is that the amount of damage assumed is equal to the percentage of temperature stations which were eliminated. Unfortunately the high variance stations are de-weighted by intent in the processes such that the elimination of 1/8 of the stations is absolutely no guarantee of damaging 1/8 of the noise. The ratio of eliminated noise to change in final result is assumed to be 1/8 and despite some vague discussion of Monte-Carlo verifications, no discussion of this non-linearity was even attempted in the paper.
Prayer to the AGW gods.
All that said, I don’t believe that warming is undetectable or that temperatures haven’t risen this century. I believe that CO2 helps warming along as the most basic physics proves. My objection has always been to the magnitude caused by man, the danger and the literally crazy “solutions”. Despite all of that, this temperature series is statistically speaking, the least impressive on the market. Hopefully, the group will address my confidence interval critiques, McIntyre’s very valid breakpoint detection issues and a more in depth UHI study.
Holding of breath is not advised.
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Max Hugoson,
The MinMax Thermometer was invented in 1782. The same design is still in use today to measure minimum and maximum temperatures at places like schools.
Minimum and maximum temperatures have been measured in the same way since before 1800 thru to the introduction of electronic thermometers in the later part of the 20th century.
The accuracy of measuring minimum and maximum temperatures would have been pretty much unchanged for 150 years.
I see Leif beat me to the minmax thermometer point.
The troposphere is warmed by and from the ground up
Excepting aerosols, which warm the troposphere by absorbing and scattering incoming solar irradiance.
One study from India
http://www.agu.org/pubs/crossref/2011/2011GL046654.shtml
My analysis is now up at the Bishop Hill blog
http://www.bishop-hill.net/blog/2011/11/4/australian-temperatures.html
Friends:
I write to point out a confusion that seems to exist in the minds of several posters to this thread;
i.e. UHI and local anthropogenic effects on temperature are not the same thing.
UHI affects cities and their immediate surroundings. A UHI can provide a temperature of several degrees above the temperature of the surrounding countryside, and this difference between city and surrounding temperatures can be expected to increase with time as the city grows. But cities cover a tiny proportion of the Earth’s surface so the effect of UHI on global average temperature may be undetectable among the other ‘noise’ of the global average.
However, the averaged temperature measurements on land are mostly obtained near sites of human habitation. And human habitation affects local temperature in many ways; e.g. land use changes, proximity of measurement equipment to human devices such as dwellings, machinery, and heating or cooling equipment, and etc..
So, the obtained temperature measurements on land are almost all affected by human activity. And these measurements provide a significant contribution to the estimate of global average temperature. Therefore, local anthroppgenic effects probably provide a significant contribution – i.e. distortion – to the global average although they are mostly not UHI.
Richard
Jeff Id,
Appreciate your post.
What are your thoughts about whether or not a rural farming effect from land use also needs to be evaluated but separately from UHI? Could such an effect have detection issues?
John
Has anyone done a study on what time the minimum temperature is reached? If I heat one pot to 300 F, and another to 400 F, and I set both pots outside overnight, they will both be the same temperature at some point, but the 300 F pot will get there more quickly.
In 1850 how much land world wide had been changed? In 2011 how much land world wide has been changed? It’s not just urbanization, it all land changes man has made to the surface of the earth over the 150 years. In 1970 the land around my house was farmland and dirt roads, 40 years later the farmland is gone replaced with bricks, concrete and bitumen, how can this not have any effect? If the absorption of Solar radiation by the surface of the earth is the means by which the temperature of the earth is determined any change in the absorbing surface will change the temperature achieved, up or down. If concrete and bitumen replace trees and grass the temperature must go up, that’s basic physics.
Just not sure what this statement means, please explain:
Jeff Id “I believe that CO2 helps warming along as the most basic physics proves.”
How?
Why is it that we cannot seem to agree that UHI (which is a well observed fact and easily visible in the data) is different to dUHI and dRural. BEST did not attempt to investigate UHI, they did (possibly rather poorly) attempt to detect the difference betwen dUHI and dRural. They conclude dUHI/dRural shows no divergence but that any long term warming signal is present in both.
I am not happy about quite a bit in the BEST study but I do wish people would stop conflating UHI and dUHI and thereby create Straw Man arguments.
AT LAST – an intelligent analysis of a temperature data set!
This study based upon weather data taken at 3 hourly intervals for 60 years… hopefully there are some data series with ONE HOUR data than can be analysed… and perhaps a study of ONE MINUTE data would show just how INSANE the settle science of (Tmin+Tmax)/2 really is!!!!!!!!!!!!
Don Monfort says:
November 3, 2011 at 10:25 pm
“Did you actually read the BEST UHI paper? They stated they could not use MODIS data to separate urban from rural areas, so they broke areas down into rural, and very rural. […] They state: “Rather than compare urban sites to non-urban, thereby explicitly estimating UHI effects, we split sites into very-rural and not very-rural.”
Looks like the “best” climate science of 2011 still cannot account for the development of UHI over time.
Maybe, if we give them ALL of our money, that’ll suffice so that they can find out how human settlements around temperature stations developed over time.
They could use historic maps.
BEST was obviously an attempt at fabricating a publication with a media campaign attached that they could rush out the door in the run-up to Durban. Rename it to “FASTEST, CHEAPEST AND WORST”.
A “Rural Farming Effect”? (RFE, for those who abbreviate everything…)
Think instead perhaps of a “Rural Forestry Effect” with respect to its affect on overall northern hemisphere albedo during each of the four North Hemisphere!) land-dominated seasons.
And – above all – Don’t get blind-tracked into “winter=snow everywhere either! Consider a real-world snow-line at about 40 degrees north through the eastern US, but further south through the mountain states, a big “hole” in the Great Basin, and high-altitude snow average coverages down the west coast.
Canada, as all ‘Merikins well know, is completely covered in snow all year round…. “Obviously” there has been no changes in forest extent, forest type, or crop type up there. 8<)
Europe? Will vary as well: Not all will be snow covered every winter, but even Spain changes its albedo from season to season. Much of the eastern plains of Europe (north and south of the Carpathians, pretty much all the way through to the southern Russian and Turkish mountains, then the Himalayas through China to Manchuria will also vary greatly from summer to winter. The question again becomes: Has the seasonal albedo changed as more forest grow – in part due to more CO2? Have the European and Ural forest types (pine, deciduous, colors, shades, heights) changed to change albedo the tens of millions of sq km's where no people live and farm?
To consider the change in albedo that may be causing an change in temperature the past 40 years, I believe you must consider is not an albedo changing summer-through-winter, but the change in each season's albedo as North American deciduous forests have re-grown so strongly the past 40 years. In the southern pine forests, much more trees – but they don't drop their leaves in the winter. Then again, south of 40 north latitude, is there wide areas of "snow" on the ground to be reflective, regardless of tree coverage? What is the change in albedo as small farms are abandoned, and crop areas previous plowed in spring, then growing as dark green through the summer, then harvested back to "dirt" in the fall and then laid bare over the winter return to grassland and then to trees and shrubs? The new grass, trees and shrubs will change albedo.
Overseas? I expect a careful check will find that many Russian (fast-growing) forests have re-grown as industrial growth and large-scale industrial farming suddenly ended with the fall of Communism. The Ural Sea is an example of the opposite: massive desertification because of socialist "farming" policies and bad irrigation. But an example of a regional change in albedo none-the-less. What is the change in China's albedo over its new farmlands? Or was there crop use changes since 1990?
European forest/crop changes? I don't know – and welcome your thoughts and contributions.
African forest/crop/savannah/farming changes? Very significant de-forestation as people try desperately to get wood for fires – since the enviro's deny them real fuel. Farming? In many areas, farms are abandoned due to socialist dictatorships and racial warfare burn out farms, and their previously rotated fields return to ???? True – African farm and crop changes are mid-tropic, but what is that change in the albedo where the sun is overhead all year?
India and the nearby island nations? Again, near the equator, but has the crop use changed the past 40 years? The past 20 years? Has it been steady in those very crowded lands? Or has it been steady with respect to albedo BECAUSE they (India and Indonesia) are so crowded?
This is my simple approximation (or perhaps lower limit) for UHI related global temperature increase since 1900:
Spencer has computed a nice graph drawing UHI over population density.for the year 2000.
http://www.drroyspencer.com/wp-content/uploads/ISH-station-warming-vs-pop-density-with-lowest-bin-full.jpg
The curve is close to a logarithmic function, a quadrupling of population density increases UHI by about 0.3-0.4 deg Celcius independant of the initial population. I call this increase in UHI subsequently dUHI. The curve in itself already explains why BEST did not work, as dUHI for a population increase from 10 to 20 is about the same as for an increase from 1 million to 2 million. Very rural and NOT very rural is then no criteria to identify locations with low/strong dUHI.
Now since 1900, the world population has risen from 1.7 to 7 billion. According to Spencer’s curve such an increase in population density would result in an UHI increase dUHI of approx. 0.4 degrees.
2 notes:
1. The graph covers only the USA, it may differ elsewhere..
2. The graph allows only an estimation for an instant population increase in a thought experiment. Other factors contributing over time as well to UHI are not included, such as ever increasing energy consumption, paving of roads, installation of air conditioning, deforestation etc. Most of these factors should further increase UHI.
Leif Svalgaard says:
November 3, 2011 at 9:25 pm
So why do we worry about greenhouse gases, Leif?
Jeff, I agree about UHI, B-est is a total fail on that issue. More on that later.
#1 is a big problem too. A far as I can tell they have done zero assessment of the effects of this splicing technique. They certainly don’t publish any and the only relevant comments in the paper seems to show they think the effects “should be trend neutral”. To my reading that is a fairly honest and clear statement that they have not looked.
So let’s look for them.
Since Dr Muller has chosen to make very public comments about the level of rise since 1950 I looked at how much that result depended on the time scale and start date. I looked at the simple OLS “trend” over a given interval for all possible start dates.
I did not get what I expected.
50y trends:
http://tinypic.com/r/10i5is4/5
Oh, oh! What are those flat bits about? Decade long periods with ZERO trend. That’s not climate.
Let’s check 10y trends:
http://tinypic.com/r/21ophd/5
OK, that’s more like it.
Now let’s look at , say, 12y trends.
http://tinypic.com/r/1449ol/5
WATTSUPWITHTHAT !???
According to BerkeleyEST there was virtually no 12 year period in the last 200 years that had a non zero trend.
This explains why their record shows less variation than other records.
Not only have they removed the noise , they’ve removed half the signal as well.
(I plot the resulting trend against the date of the middle of the range, so “last 50 years” for the most recent last 50 years gets logged at it’s midpoint of 1985)
Careful with that scalpel Doctor !!
While given station location and requirements meeting validity, does anyone know the number of sites that actual that have been checked not guessed as meeting these standards, is important .
Given that two thirds of the planet is water and given that BEST did not cover this at all, you could suggest that when it comes to ‘global temperatures’ the UHI and what is rural is almost side if interesting arguments. Can you really make a claim about ‘global ‘ anything when you don’t cover the majority of the globe?
I thought Jeff Id was a smart guy but this is sounds either wrong or badly expressed.
———
– UHI effect. The Berkeley study not only failed to determine the magnitude of UHI, a known effect on city temperatures that even kids can detect, it failed to detect UHI at all.
———-
There is a distinction between
1. the existence of the UHI which is considered to be measurable by everyone
2. The TREND in the UHI which is commonly positive, but not necessarily always.
3. The effect of the TREND in UHI which may contribute to the trend, and possibly bias, the surface temperature trend.
There are some if buts and maybes around 2 and 3.
As far as I can tell BEST is saying 3 is not turning out as expected here. And confirms previous research.
And gut-feelings don’t count here.
One of the main predictions of climate science is that warming should be fastest at high latitudes. Warming as been very fast in arctic, where UHI is clearly not a factor. I agree with Matt’s analysis. There is a big difference between saying that UHI is not detected and saying that it has a significant effect on world land temperature anomalies. Saying that UHI is not detected is very misleading. Even Anthony’s data, evidently, does not show an effect of UHI on temperature anomalies.
Just seconding the observation made by Richard Courtney upthread about land-use change.
The land has changed dramatically here in Southern Minnesota and Northern Iowa. I blame my father-in-law for that. He owns a D-9 Caterpillar bull-dozer and every time he purchased a new farm over the last few decades, the first thing he would do is level the woodlots and building sites to plant corn and bean.
So how do you measure the effect of transforming a landscaped checker-boarded by green into one that is uniformly black (or near black) for six months of the year?
Also, what exactly defines “urban”. I know, I know population. But seriously, are all urban centers equal? Compare a mature neighborhood shaded by large elms to twenty thousand acres of new suburb. In other words, growing secondary cities are hotter than more established urban centers. How do we account for that?
Even the rural areas are hotter. Our local GHCN station at Zubrota (72644003) is located at a sewage treatment plant that has added a lot of concrete over the last couple decades as well as a new neighborhood – upwind.
So how much warming can be attributed to these factors? .05C? .1C? Does anyone care?
Matt,
“Someone should point out to Jeff that there is a difference between saying “there is no UHI” and saying “there is significant UHI but cities only account for a small fraction of land surface and have only a small impact on global averaged trends”. “
Perhaps you are unaware of this but if you take the time to correctly process satellite LTL data and compare it to ground data, there is a statistically significant difference in trend. i.e. detrend sat data, scale variance, retrend, regress, examine residuals. That is really all the confirmation of UHI that I need. So when a paper is published on non-detection of UHI, it is an example of go home and do it again.
http://youtu.be/4HgUh5bOgbM
Thanks for the tip though.
Another top notch analysis Jeff !!!
Great work !
Steven Mosher says:
November 3, 2011 at 7:57 pm
Are you open to discussion of the upper bound…..?
In broad agreement. I read Steve’s excellent post when there were no comments on it. I haven’t got back to read the comments yet (will do so this evening).The upper bound of 0.1C/decade only goes back to the start of the satelite era and cannot be extrapolated backwards. We should not expect it to be a constant factor anyway. See also my comment here: http://noconsensus.wordpress.com/2011/11/03/considered-critique-of-berkley-temp-series/#comment-57003
I suppose that the fact that BEST were unable to distinguish any different trends between dUHI and dRural can be interpreted another way. We know that trend figures produced from a mixture of dUHI and dRural (the Estimated Global Temperature and its associated trend) differ from trend figures obtained from other sources, i.e. satellites. Perhaps both dUHI and dRural are truely showing the same contamination to the basic signal that their difference from these other sources imply.
Therefore, possibly, this surprising result in identical trends for both dUHI and dRural can be used to determine the magnitude of the different trends between satellite and ground observations.
Marc Morano at Climate Depot headlines today:
Sci-fi writer Jim Laughter: ‘Polar cities no laughing matter’ — ‘Envisions so-called ” polar cities” for future survivors of devastating climate….with link to interview with Laughter, his real name, by the way….
Stephen Rasey says:
November 3, 2011 at 9:56 pm
UHI is cyclic? What’s the period – equal to the rise and decline of the Roman empire? Except the Roman Empire wasn’t cyclic.
Question, re: “UHI” effect –
If we take a time series of temperature measurements, going back to, say 1900, I would think we would need to analyze first which stations were under a UHI effect for each year since the “urban” areas pretty much keep expanding over that time. We’d also have to account for every station that moved either into or away from a UHI effected position. Further, the actual UHI in a given area would vary as well. Every station that at any time was in a UHI would require a slightly different “adjustment” from any other station over that time series. That, and more that I no doubt didn’t mention, would need to be done for each station and the adjustment would need to be “reviewed” for accuracy.
So, my question is, simply, has it been?
Add that to the high number of sites that are not sited properly and are recording information that uniquely requires an individual adjustment for each station, and the question of whether we get a good temperature measurement, let alone a better or “best” one, seems very reasonable to me.
Do we have a group of stations that are not and have not been either in a UHI and are, and continuously have been, properly sited? Assuming they have been properly maintained, what do these, and only these stations show from the 1800’s through today? Heck, what do they show from 1979 through today?
Just wondering.