In part 1 of this series ‘Measuring the Surface Air Temperature’ I wrote that James Hansen of NASA’s Goddard Space Institute explains that it is not easy to measure surface air temperature particularly in the presence of vegetation because the temperature above the vegetation may be very different from the temperature below the vegetation.
So, I thought, maybe it is easier to measure the surface temperature where there is not much vegetation, for example, at the Antarctic.
But apparently knowing the average temperatures on Antarctica has its own challenge including the sparseness of ground-based weather stations particularly in the continent’s high altitude interior and the harsh environment also takes its toll on equipment.
So NASA relies on satellites that measure energy radiated from the ice surface and estimate a level of uncertainty in these measurements between 2-3 degree Celsius (read more here).
Given this level of uncertainty I find it extraordinary that NASA can suggest a warming trend of a fraction of a degree over the last 20 years in the following image.
Bill Kininmonth, former head of Australia’s Bureau of Meteorology’s National Climate Centre, recently emailed me that because it is very difficult to assess surface temperature over ice surfaces using satellite radiometers it is more realistic to consider sea surface temperatures and to also exclude regions of seasonal sea ice.
In the same email he provided the following image of the sea surface temperatures.
Bill also explained that the Larsen B ice shelf at the Antarctic shattered rather than melted earlier this year, with the comment “shattering is not related to melting”.
Jennifer Marohasy BSc PhD is a critical thinker with expertise in the scientific method.
Another reason why we mining types don’t accept mainstream explanations for geomorphological adjustments of changing, surficial,thermal states.
Well Bill would say that. And why did it shatter?
http://www.colorado.edu/news/releases/2001/14.html
I suppose the accelerating glaciers in the region are also “shattering”. hmmmmmm….
The model of AGW impacts on Antarctic ice is not one of mass melting but disintegration from undermining ice sheets and also erosion of glacier sea buttresses from warmer waters.
Which is why some scientists think the IPCC sea level rise estimates are underestimates.
“The model of AGW impacts on Antarctic ice is not one of mass melting but disintegration from undermining ice sheets and also erosion of glacier sea buttresses from warmer waters”
1. Mass melting obviously means that the whole iceshelf melts, so that implies a rapidly diminishing ice sheet retreating towards its origins, ( I was thinking of mentioning headwaters but that would have been to geologically insensitive and inappropriate).
2. Undermining of ice sheets: Impossible – UN Treaties, etc. forbid mining in Antarctica.
3.Erosion of Glacier Sea Buttesses from warmer waters. It is an obvious fact that seawater lapping at a glacial buttress must be warmer, for if colder, then glacial buttress would be spilling onto ice.
3a. So, we conclude that glacier ice is colder than sea water. Does, therefore, warmer sea, erode glacial buttress?
3c. YES! IFF buttress is not fed by pre-buttress ice making machine.
3.d Also: What is, to be critical, glacier sea butress; excuse but is this same as mattress sold by capitalist dogs to hard working socialist workers?
When I see the word “anomaly,” I assume that it implies that we have enough data to establish the standard or normal conditions. The metric that the climate community is using doesn’t really make sense to me as a physicist.
In addition, an uncertainty of “2-3 degree Celsius” means that, to establish statistically significant differences, you have to see VERY large deviations from the normal conditions. So, both of the figures in the post are within 1 sigma of the measurement error.
Why are we bothering with AGW anymore? After at least $20 billion in research and modeling, we still can’t distinguish normal variability and measurement uncertainty from any signal that might be there.
http://depriest-mpu.blogspot.com/2008/05/it-doesnt-add-up.html
Russ
“Anomaly”
This is calculated by subtracting the computed yearly mean temp from a climate mean (usually the mean of yearly means from some arbitrary 30 year period).
Put in a crasser mode, they get the mean temp for 1961 to 1990, for example, average it, then use that mean as the bench mark for yearly means before and after.
It really means that the temperature anomaly is another word for the standard deviation about a running mean, and that seems to me to be a statistical nonsense.
Louis,
If that is the definition, then it is statistical and physical nonsense. Basically, they are using a standard deviation (which is always positive) to define a difference from an average temperature. WHAT???
And, I still don’t understand how a global average temperature (whether sea surface or land based) makes any physical sense. Are they using this “temperature” to match either the blackbody wavelength (lambda-max) or energy flux emitted by the earth? Are they measuring either of these things? —> Not in any reasonable way that I have seen.
As a physicist/nuclear engineer, I always assumed that those in the climatology field were legitimate scientists, but that assumption is being severely tested by the silliness of the metrics that have chosen.
Louis,
If that is the definition, then it is statistical and physical nonsense. Basically, they are using a standard deviation (which is always positive) to define a difference from an average temperature. WHAT???
And, I still don’t understand how a global average temperature (whether sea surface or land based) makes any physical sense. Are they using this “temperature” to match either the blackbody wavelength (lambda-max) or energy flux emitted by the earth? Are they measuring either of these things? —> Not in any reasonable way that I have seen.
As a physicist/nuclear engineer, I always assumed that those in the climatology field were legitimate scientists, but that assumption is being severely tested by the silliness of the metrics that have chosen.
“Basically, they are using a standard deviation (which is always positive) to define a difference from an average temperature. ” – did you say you were any engineer? Incredible !
Lucy,
Are you claiming that a standard deviation about the mean can be negative? By definition, the sample standard deviation is
s = SQRT[(1/(n-1))* SUMi[(xi – xmean)*(xi – xmean)]]
In case you still don’t understand the really simple math, the stuff in the square root is ALWAYS positive. Thus, s is also always positive.
You can put error bars on something by adding and subtracting the sample standard deviation, but the value for is positive.
What is truly incredible is that we allow people to continue to use nonsensical metrics to promote policies that will tax us into oblivion.
BTW, I am not an anonymous web poster changing my name when it suits me. Here is my University website:
http://microep.uark.edu/faculty/faculty%20pages/DePriest.html
No I’m claiming you’re a goose that doesn’t know the first thing about anomalies. It’s pretty basic. Nothing to do with S.D.s old trout. You’re up a dry gully. This sort of error well illustrates the breathtaking arrogance of you guys.
If this is the quality of your comments – better become anonymous quickly and avoid further embarrassment to your institution.
And I can see that you’ve decided to kick the science coz you don’t like some of the policy responses. About what we’d expect from engineers.
So, Lucy, you are claiming that we can measure a global average temperature within +/-(the width of a gnat’s a$$) and then pick out a temperature trend that amounts to a small dimple on that same gnat’s a$$. That’s all I need to know about you.
BTW, who is this “we”? The same “we” that goes to work in a car, truck, or bus designed and built by engineers (maybe a bicycle in your case) on roads designed and built by engineers. The same “we” that types idiotic comments on a computer and keyboard designed and built by engineers. Oh, you have electricity to power that computer and heat/cool your home. “We” should probably thank a power distribution engineer as well as the engineer that designed the generation plant that produced the electricity.
Creep pls.
Oh come in spinner on the engineer quip. I’m sorry – yes you’re all very useful aren’t you. The world is so grateful.
How many nuclear engineers does it take to change a light bulb? Seven. One to install the new bulb and six to figure out what to do with the old one.
On anomalies – yes I am saying accurate enough as borne out by legions of papers and diverse lines of evidence. Our high quality local Australian data shows essentially the same pattern. Your ignorance and arrogance is simply breathtaking. Standard deviations indeed ! ROTFL
Funny how the satellite data basically shows the same trends too. But how can this be – you can’t do it !!
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1979/offset:-0.146/mean:12/plot/uah/from:1979/mean:12/plot/rss/from:1979/mean:12/plot/gistemp/from:1979/offset:-0.238/mean:12
Anomalies are pretty simple – add the base period mean back and voila you have the original data. Wow. Nuclear physics. Rocket science. PhDs needed. Nobel prize stuff.
The El Nino phenomenon itself is described in terms of sea surface temperature (SST) anomalies of a few degrees or fractions of a degree. Such a big effect from small SST anomalies. SST anomalies are behind understanding of climate forecasting.
Now go sit somewhere quietly and don’t fiddle with any dials or switches. We’ll call you if needed. Promise.
“About what we’d expect from engineers” ? For starters, Russ probably hasn’t quite left his sheltered world of academia for a life of hard knocks in the field.
When pondering signals a good engineer would know about alternatives to the various temp series as better indicators of our solar energy capture.
Let’s suggest again, mass balance of ice between the poles is reflected in sea level anomalies over much longer time scales. Temporary fog or fury can’t suddenly change the total amount of fresh water left above the briny. Any climate series can be zeroed or ranged against this accumulation given a global mean.
Before I get too far down this path with both Lucy and King, I should follow this sage advice, “Never argue with a moron. They will bring you down to their level and beat your a$$ with their experience.”
In any case, I am not an academic even though I have an office at a university. If you looked at my CV, you would find that I have spent the last 7 years as radiation effects engineer in a U.S. NNSA laboratory. I work to quality nuclear weapon components in radiation fields that have large uncertainties.
My current focus is in the UNCERTAINTY QUANTIFICATION of large multi-physics parallel processing codes. The codes that I work on have real consequences for safety, surety, and reliability of our weapon systems. If the GCM codes are wrong, then you just get bad policy rather than disasters. I can tell you that the GCM codes haven’t even started down the path to understand either the aleatory (random) or epistemic (lack of knowledge) uncertainties. Until they can put error bars on the model calculations with a realistic assessment of each of those uncertainty types, I will assume the variance is infinite.
Well Russ – I’m very worried now. So you ensure nuclear safety eh? mmmmm. And you don’t even understand a basic anomaly.
Don’t try to obfuscate this out into GCM codes – this issue is simply about trends in observations – well actually just data representation.
AlC: There is hope yet. Someone who still uses the word “cute” can be rehabilitated and returned to doing R/L arts n crafts despite his CV missing out with say music like jazz.
Russ: As one who has done a fair bit of practical industrial safety, infrastructure protection and a little nuclear physics, the only working instrument we need is a well tuned imagination plugged in to the project in hand. Building fancy maths round uncertainties and less desirable facts is no way to cope with some unexpected reaction or dilemma.
Listening to the best of Van Morrison again I was reminded of that time when I had an analogue CRO with a very fast rise time and could watch mixed signals while listening to the lab sound gear. Sure we can focus on the base player, the saxophonist, the keyboard or the lead vocalist in turn while listening but what about analyzing the visual display?
Max / min can mean so much in climate debate. In R/F spectrum use the study of energy in waves and pulses creates a whole new field for the imagination to explore. Signal to noise ratio comes after signal capture so I focused on antennas, transducers and other stuff like batteries.
100% pure signals are just an illusion in a chaotic world. BTW both mid range speakers in my old three way Celestions have failed but then my hearing is less bright than it was too.
Wes; we know the internet is not well policed but neither is the sidewalk in Kings Cross on a Saturday night or Sunday morning for that matter.
Russ,
In addition when the SD does go negative, all that means is highly skewed data which need to be normalised before statistics can be applied. This is usually the case with low element concentrations since nothing can be less than zero in physical reality.
As Fred Hoyle once pointed, when the science of something is settled in becomes an engineering problem. But when many scientists, spending huge amounts of money still have disputes about a particular problem, here climate science, it is clear that they are using the wrong theories or ideas. This is generally the case when scientific truth is dependent on consensus – but then it isn’t science. However its practitioners do believe it is science.
Russ – “I can tell you that the GCM codes haven’t even started down the path to understand either the aleatory (random) or epistemic (lack of knowledge) uncertainties. Until they can put error bars on the model calculations with a realistic assessment of each of those uncertainty types, I will assume the variance is infinite.”
Who have you talked to? What was the result from your peer reviewed paper detailing the problems of uncertainty in GCMs? Have you actually examined the scientific papers that result from model runs?
Why don’t you post these things to James Annan or Gavin Schmidt who are active in the field of climate modelling?
Russ: “Lucy,
Are you claiming that a standard deviation about the mean can be negative? By definition, the sample standard deviation is
s = SQRT[(1/(n-1))* SUMi[(xi – xmean)*(xi – xmean)]]
In case you still don’t understand the really simple math, the stuff in the square root is ALWAYS positive. Thus, s is also always positive.
You can put error bars on something by adding and subtracting the sample standard deviation, but the value for is positive.”
Louis:
“Russ,
In addition when the SD does go negative, all that means is highly skewed data….”
Shouldn’t you engineers get together and get a consistent story going? (Sorry, Louis, I’m with Russ on this: the SD is always positive.)
This thread is soooo entertaining.
Peterd
The computation of the SD is always positive, I never said it wasn’t, but half the values are less than a mean, and if the data is highly skewed, the sd gets into negative values for the distribution, which is impossible.
So Russ and I do have it all together, thank you.
Peterd
These are the statistics computed from this data:
1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,3,3,3,4,4,5.
Column A
Number of values 19
Sum 39
Minimum 1
Maximum 5
Mean 2.1
95% confidence interval 0.61
Standard deviation 1.3
Coefficient of variation 0.61781
Skew 0.987
Kurtosis -0.042
Kolmogorov-Smirnov stat 0.27
2 Standard deviations +/- the mean puts it as (2.1 + 2.6) and (2.1 -2.6) or -0.5 < 2.1 <4.5
Russ; ignore creep and ender; the base period ideology is as flawed as AGW is; moving averages, which are the guts of the ‘anomalies’ from the base period, are themselves flawed; they always trail reality, pointing in the opposite direction to any trend.
For example; 11, 12, 13, 14, 15, 16, 15, 14, 13, 12 11, is a sequence of 11 values. Including the number 16 in adding the ist 6 events you have an average of 13.5; after the 15, an average of 14.6, for the 6 events; after 14 an average of 14.5 for 6 events; after the 13, an average still of 14.5. The actual values are falling in a very clear trend, but the moving average is continuing to rise. Having more fun; if we incrementally increase the average over the pool so that for the ist 7 to 15, the av is 13.71, so therefore 15 is +vely anomalous even though the trend is down; for the ist 8 to 14, the av is 13.75, so 14 is still +vely anomalous, and so on.
When we look at the discrepancies for actual base period results, a paper by McLean and Quirk provides a useful reference point:
http://mclean.ch/climate/Aust_temps_alt_view.pdf
This paper looks at a well documented event in the pacific called the Pacific Event (PE). The significance for base periods is that GISS has a base period of 1951-1980, Hadley 1961-1990; the PE occurred in 1976 with a climate lapse period of 5 years during which time temp rose by 1.46C; since GISS has a preponderance of cooler temps prior to the PE, the elevation of trend after 1980 will be greater than from a base period of 1961-1990, and, conversely, the coolness and elevation of trend before 1976 will be less with Hadley, with an overall greater trend over the century for GISS, simply because of their different base period.
A confession: It’s been so long since all those experiments in the physics labs I had to look up “SD is always positive”
Beyond – “Clinically SD is characterized by a mild to severe erythema with irregular shape, whitish or yellowish scales and a greasy appearance, involving the seborrheic skin regions: the scalp, temples, retroauricular folds, outer parts of the ears, eyebrows, eyelids, glabella, nasolabial folds, and the midline areas of the chest and back”(AIDs) etc I found the following link back to school.
http://phoenix.phys.clemson.edu/tutorials/stddev/index.html
The thing is; after many years of technical support to a whole range of disciplines and related sciences I don’t recall using SD again. Maintaining a live signal is far more important than stewing over its accuracy.
With most measurement apparatus its ether working close to spot on or you chuck it and find something better. Freeing up your primary indicator is also very important. Appropriate response to rates of change is another fundamental characteristic that precedes the pursuit of absolutes in measurements of chaotic events.
I recall a chap glimpsing a swollen super heated steam tube in a big furnace. It didn’t take him long to climb several long vertical ladders and screw the steam drum dump valve to the roof wide open. It didn’t take us long to create a spectacular cloud up10-20, 000 ft.
I can’t imagine doing SD on a set of near white hot pressure tubes. Anomalies must be seen in terms of 3D impacts.
C’mon cohenite: This McLean stuff harks back to work with Bob Foster, Ian Castles n Co. Other than this blog and Andrew Bolt it just plopped in the ocean.
You can’t put a beer down on the best fitting slope for fig 4.
Weeelll – I hate to say it but I can see Louis’s point of view. most stats texts say SD is positive. But I have seen positive or negative.
ANYWAY – who cares – it’s irrelevant to the point.
And why are we suddenly talking about moving averages?
Lordy me.
You can pick any base you like – absolute zero – the temperature of the Sun perhaps?
Anomalies are the fodder of climate science. Add the base back on and you have the raw data. Wow ! Rocket science.
In any case check this guy out relavitising it all for us.
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1979/offset:-0.146/mean:12/plot/uah/from:1979/mean:12/plot/rss/from:1979/mean:12/plot/gistemp/from:1979/offset:-0.238/mean:12
Doesn’t make any interpretation difference between data sets. It’s got warmer over the last 100 years – the end. Is that so surprising?
(and yes you do have to be careful with moving averages but also regressions – do we HAVE to go there?? pullease no)
Gavin my old friend – here’s something nice for you and some blog valium. Miles Davis – Human Nature – sums it all up eh? I know you dig it.
Headphones on, S/Nr excellent, video sharp and his music is sublime. What more can I say?
Sigh, the SD is not negative, the class-interval on which the readings are binned to is negative. If Column A in my previous post if ppm Zn, then there is no way that we can have – 0.5 ppm Zn.
And if any one thinks they can then excoriate me for doing statistics on an intensive variable such as ppm, sorry – we in the geosciences make sure that we can do that by making sure that the sample support is uniform for the data collection. It means collecting standard 1metre drilled intersects, it means taking equal volume aliquots or splits from the drilled intercepts.
Climate science seems to be clueless about these sampling protocols, so the statistics they calculate from their raw data are simply specious unless proven otherwise.
gavin; yeah, you’re right; Tamino called the McLean/Quirk paper crackpot; no reasons, just crackpot; so I wrote back and called him Bristlecone, and it never got up. Actually, I think your chronology is a bit out of whack; the paper was done at the end of 2007; weren’t Castles and Foster in their prime a bit earlier?
Creep; why would you have to look up that a SD is always +ve when it is a square? You miss the point about base periods and anomalies; this whole debate is predicated on comparisons; the trends are mirrored between the respective data sources, but some are larger than others, no? Anyway, your WFT graph sure looks like a downward trend to me.
Anomalies are the fodder of climate science – are they now.
Anomalies in geoscience are computed quite differently but these data are not dependent on time, while in climate it is.
However the method in geoscience is to collect data on a 2D grid, East and North, and measure a value say Zn ppm. If the Zn data fit the Gaussian distribution, then basic statistics are calculated, and anomalous data are those with values greater than 2SD above the mean. (In practice we don’t do this but plot the data on probability plots and if this plotting shows two discrete, in a statistical sense, or more sample populations, then the sample population at the upper end is possibly the anomalous one.
Climate science creates anomalies quite differently. It determines a base period of 30 years in which the climate variable is averaged, in this case temperature say from 1961 to 1990.
A statistic is produced but only valid for the base period 1961 to 1990. Temperature anomalies are then calculated for the rest of the data by noting the difference between the calculated mean per year and the previously calculated benchmark, itself a mean as well.
But this is total baloney, for the data outside the benchmark period have no statistical relationship with the data within the benchmakr period.
Cohenite – weeeell – coz the SD might be considered either positive or negative in value because it is calculated as a square root of the variance, which can be either positive or negative. The variance is positive as the constituent residuals are squared. SD is SQRT of variance. Yes?
However negative physical quantities obviously don’t make sense so it’s positive in mainstream use but plus or minus “x” SDs about a normalised mean in common use describing distrubtions. Hence some of the confusion. However, in Googling around on this some learned statistical souls actually state explicitly it can be -ve or +ve which I thought was worth a comment. Little known factoid #17289289298
But all irrelevant.
As for trends – if you start in 1998 or 2002 and do a regression you would get a downward trend. If you picked 2001 – a flattish line perhaps.
Any earlier date and a positive trend.
Higher order polynomials can give you anything you’d like – but do you have a justification for picking one except to bolster one’s personal preferences.
Exactly Louis; the base period is a house of cards; it is what Stewart Franks has been saying; if you have a base period in one IPO period with a particular climate, how can that base period be used to establish deviations in another IPO climate type?
creep; “Any earlier date and a positive trend” How about 1645-1715? This is cracking me up; can’t anomalies be positive or negative?
“Higher order polynomials can give you anything you’d like-but do you have a justification for picking one except to bolster one’s personal preferences.” Perzackerly.
Louis I am utterly amazed for an occasionally seeming intelligent person you can be so wacko on this basic anomaly stuff. Climate science does NOT have to use 30 years. 30 years is simply a WMO arbitrary standard for a “climatology”.
It can be 100 years, 50 years , 37.532 years – whatever.
It’s simply to make things relative. You can simply recover the original data by adding on the base mean. No tricks.
To quote the UK Met Office – “The World Meteorological Organization (WMO) requires the calculation of averages for consecutive periods of 30 years, with the latest covering the 1961-1990 period. However, many WMO members, including the UK, update their averages at the completion of each decade. Thirty years was chosen as a period long enough to eliminate year-to-year variations. ”
If you updated your base mean every new year people would start to get confused about different anomalies for same years in the same data series.
This is an incredibly simple concept – there is no trickery unless you compare GISS and CRU without realising the base periods are different.
GISS – 1951-1980
CRU – 1961-1990
But it is all very arbitrary !!
Watch this clip for a vivid example (without screaming) http://cce.890m.com/part06/
Cohenite – exactly – any trend is relative to a period obviously – which Bob Carter loves to point out – we could go back to the beginning of the world in the extreme. But it’s pretty simple for the time since the industrial revolution – we want to understand the period in which we’re making significant contributions of anthropogenic CO2 to the atmosphere. So what is the temperature trend doing in this period and do we understand why? (Not to say previous periods are of no interest)
A polynomial has no process knowledge – you could make the right hand end of a suitable curve go up or down. Mindless data dredging through iterative curve fitting is not really hypothesis testing.
Indeed the example graphic featured recently on the blog (temp time series with fitted polynomial) trended wrong at the left hand end of the graph compared to measured data. The ongoing trend downwards at the right end was pure mathematical extrapolation. http://www.jennifermarohasy.com/blog/archives/002905.html#comments
Doesn’t the Creep ever work? If so who’s picking up his tab? With all his banter, I’d have a hard time faking job-related activity, which I do attempt, modestly.
Alarmist Creep
Climate is defined sensu-strictu as weather metrics averaged over a 30 year period. If that is the case then the last climate climate projection would be 2008-15 years, 1993.
In any case climate science’s use of the word “anomaly” is quite different to the rest of us and I doubt that it has any statistical meaning ion the first place, although the process by which the raw data is put through is indeed an averaging process – but one thing is clear – add the mean temperature to the anomaly data and the temperature curve flattens out quite appreciably, causing most of us to wonder what all the hub-bub is about rising temperature.
It’s this anomaly method that exaggerates minor fluctuations in the signal, and it’s called chartmanship. It’s mind boggling to see climate scientists become agitated over variations within 1 degree Celsius that is less than instrument resolution.
But elsewhere someone pointed out that James Hansen did his PHd on the atmosphere of Venus and that explains it all. Now I understand why he is obsessed with CO2, probably thinking earth might become like Venus. In this he is quite in error.
But that is another topic which is off thread here.
Weeeelll…
Yes I agree manipulation of graphic axes is standard ruse in deceptive statistics or misrepresentation of data. You can exaggerate or reduce the visual impact for sure.
Yes if you plot the data as absolute Celsius, Fahrenheit or even Kelvin the curve will look very flat. But that in itself is a misrepresentation of the data.
Small differences in sea surface temperatures – 0.5 to 1.5 C produce the El Nino effect (or La Nina) and drastically affect the whole world’s weather bringing droughts to some places and floods to others.
Such a small amount. If you look at a map of absolute sea surface temperatures (SSTs) you won’t see it !!! The effect is hidden
A long term shift of 0.5C is like moving climate boundaries 500km. e.g. Perth becomes more like Geraldton. Coffs Harbour becomes Brisbane’s temperatures.
Small differences like this can affect frosts – which can be needed for vernalisation of things like stone fruit, pome fruit and olives. Small numbers do matter. Which is why olive orchard investors want to know about climate change.
And of course we experience tremendous variation in any day from day to night.
Yes there is an accuracy issue with non-digital (by eye) measurement of thermometers or operator neglect – but we’re not talking about “a” station. We’re talking 1000s of stations. Statistically it works out as valid. Large numbers. Evenly spread error works out over time.
Indeed the satellite temperature which is spatial shows more or less the same trends as the surface records.
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1979/offset:-0.146/mean:12/plot/uah/from:1979/mean:12/plot/rss/from:1979/mean:12/plot/gistemp/from:1979/offset:-0.238/mean:12
Borehole measurements will confirm warming.
Australia’s high quality network has been chosen carefully. Does not include capital cities to avoid heat islands. Similar patterns to the global record.
You can quibble over individual stations but many lines of evidence on large numbers of stations all point to the same overall pattern.
The story is pretty well one way and various lines of evidence concur.
But in the end all this is just an index. 0.5C warming in itself is NOT a problem per se. Global temperature average just a one metric of trends.
Of course it’s sort of meaningless in a strictly physical sense. But it is just an index. And a valid one.
The REAL issue is what, if anything happens, to circulation patterns, droughts, floods, hurricanes, heatwaves, storms, hurricanes, and cold outbreaks. It’s the extreme events that affect humanity (climate change or not) and natural ecosystems.
These numbers are harder. Smaller less frequent. You need decades of data.
30 years 1961-1990 is JUST “a climatology” choice. Not really that magical. Close to present day. And a long enough period to give a “sensible” mean for a base period. But the satellite guys don’t use it. Neither do GISS.
The first question you need to ask when you see any anomaly map or time series is “what’s the base period”.
“Which is why some scientists think the IPCC sea level rise estimates are underestimates.”
Is this also why two papers came out in the last couple years that think the IPCC have the sea level rise a little high??
Here is the article referencing the papers.
http://www.worldclimatereport.com/index.php/2008/05/06/slower-sea-level-rise/
They should have read the latest – http://www.sciencemag.org/cgi/content/abstract/1154580
Adjusting for water held in global dams and reservoirs would make the rate of sea rise constant for the last 80 years. The rise has been reduced by water held in storages around the world.
There is no reason to anticipate a vast acceleration in rate unless terrestrial ice sheets in Greenland and Antarctica collapse/disintegrate.
So this latter point is the reason for the comment that some scientists think the rate is too conservative. They believe these systems can be somewhat undermined. They won’t melt in situ. Whether we are seeing some early signs of this is to early to tell. I’m interested but not alarmed.
Here is another contributor to Glacial and Ice Shelf Loss:
http://pubs.usgs.gov/of/2007/1047/ea/of2007-1047ea031.pdf
http://www.enn.com/climate/article/29658
http://www.sciencedaily.com/releases/2004/05/040527235943.htm
http://www.volcanolive.com/erebus.html
Compare this picture of volcano locations:
http://vulcan.wr.usgs.gov/Volcanoes/Antarctica/Maps/map_antarctica_volcanoes.htm
with the graphics of temp anomaly:
http://wattsupwiththat.files.wordpress.com/2008/01/antarctic_temps_avh1982-2004.jpg
Alarmist Creep,
what does water storage have to do with the IPCC saying the sea level IS rising at over 3mm year and researchers finding it is rising 1-1.5mm oer year??
Please give us an estimate of how much the stored water would affect sea level or reference to someone who has. I keep hearing this claim and seeing no numbers.
Of course, maybe you should suggest that the IPCC start pushing for sea bottom and floating island settlements powered by renewable energy. Excellent chance to start fresh and design a clean, balanced life!!!
I don’t have access to the Paper. Does he estimate the increased evaporation from the extra water surface area exposed to the sun??
Does he take into account any of the other side effects of containment??
It would be quite interesting if the containment is almost exactly balancing extra melt caused by warming from glaciers over 80 years!!
creep; that dam storage nonsense is a furphy; for a start the drainage of aquifers, which is a real environmental problem, unlike AGW, more than compensates for dammed water; the Ogallala aquifer alone is being deplenished by more than 12 billion cubic meteres of water a year; that would do any sea rise. But Nils-Axel Morner doesn’t think there is any sea rise; and the sub-oceanic aquifer which recycles the world’s oceans will have more to do with sea level than any human activity; Craig O’Neill has a piece on this in Australasian Science, Vol 29, no 3.
As to this temp business, Motls has a good piece on the fraud of average global temp at:
http://motls.blogspot.com/2008/05/average-temperature-vs-average.html
More generally I cannot see how CO2 heat increase (if any) is not contained by Wien and Stefan-Boltzmann.
I’m having a look at the World Climate Report Papers – the article ends appallingly – “IPCC certainly seems to be exaggerating the best estimate of sea level rise, and it make us wonder what else they might be exaggerating.” – what a load of crap.
These papers were written long after the latest IPCC report – so how could the IPCC take them into account. One is a local effect issue – sea level rise is not uniform for a start. The other I need to read in detail. And they have made no reference to other research work in this area – e.g. J. A. Church, N. J. White, Geophys. Res. Lett. 2006 – so who says the French guys are right.
And the IPCC do not research themselves – they only review what has been done by the global science community.
A serious critique will do some compare and contrast not just state – “this is right” and the other guys are “sus”.
Typical one eyed job and poor blogging by a very biased World Climate Report.
Back to dams…
I have sent the water reservoir paper via Jen to forward to your email. If you worry about evaporation you’ll also have to work out what precipitates out given overall equilibrium – all of it perhaps?
The water storage paper says there’s about 0.55mm/yr in it. It linearises the last 80 years of expansion into a quite straight trend.
In any event without ice sheet collapse the sea level height increases for 2100 are still modest.
Nils-Axel Morner makes stuff up and has been severely rebuked in the literature. Like the tidal flat tree he mocked up with that was supposedly cut down. ROTFL.
If the aquifers are drained – where’s the water gone – evaporated? And precipitated out back into streams and hence the ocean. At least try to think through your mass balance argument before ranting.
I’ll bet Cohenite has not even read the said paper !
~10,800 cubic kilometers of water has been impounded on land to date, reducing
the magnitude of global sea level (GSL) rise by –30.0 millimeters, at an average rate of –0.55
millimeters per year during the past half century.
If loopy string physicist Motl has “invalidated” the average global temperature he will has with his friendly fire also destroyed the satellite record. Oh dear. What tangled webs we weave. Lubos’s latest drivel would have to go down as one of the craziest rants of all time. Bizarre. LMAO.
He wrong on first opening “Vincent Gray and Alan Siddons have been emphasizing an important point that the (arithmetic) average temperature is not the relevant quantity that should be substituted into various calculations of the heat and energy budget of Earth.” – who says they do !!! the end…
creep; you’re becoming hysterical; I read the abstract; unlike the idle rich I can’t afford the complete paper; I have no idea what your point is about the aquifers; mine is; if they have been drained and not refiled that water must either be in the oceans or in transit to the ocean; if your point is that oceans would be higher but for the dammed water, then surely that conclusion must be mitigated by the water in the ocean from drained aquifers, yes?
What on earth does satellite record have to do with what Motl is describing? If the existing base period for temp has a time taint then Motl is suggesting the anomaly concept also has a regional taint. Motl manifests this by averaging regional Stefan-Boltzmann values; you can’t have it both ways; AGW utilises SB to allegedly prove the heating effect of CO2; Motl is using SB to prove that regional variations and the maintainence of the overall energy budget nullify the significance of any satellite observed (or for that matter, any source of data) increase in global average temp.
“Craziest rants of all time.” Come on, any of Basil Fawlty’s top it.
OK – if you’re mining aquifers that never refill i.e. paleo water fair enough – and how much of these are exploited to depletion I guess is the question. MDB for example is more about pressure than volume. So where’s your numbers? Otherwise hand waving …
Given I’m filthy rich I’ll ask Jen to email you the paper. In any case – it’s simply of interest – not revolutionary – doesn’t add metres.
In the end it’s about mass balance. Inputs and outputs.
“AGW utilises SB to allegedly prove the heating effect of CO2” – does it? Do tell.
All you have is a very simple generalised energy budget which says the world would be much cooler without any greenhouse effect at all.
And so “maintainence of the overall energy budget nullify the significance of any satellite observed (or for that matter, any source of data) increase in global average temp” – wow !! “prove” – Oh well it’s the end of the satellite record too. Keep smoking that hooch.
And of course you have a regional taint – that’s why there are grid boxes, stacked in 3D and land surface schemes in GCMs. It’s a bit more than a few “averages”. These issues are solved explicitly.
The global “average” temperature is simply “a” metric of cumulative climate forcing impact. “A” metric or indicator. Not “the”.
creep; we are at cross purposes; let me express it philosphically;
Russell’s paradox concerns things which do not belong to any class but belong to a class of things which do not belong to any class. The paradox is, if it is a member of itself, it must not possess the defining property of the class, which is not to be a member of itself. If it is not a member of itself, it must possess the defining property of the class, and therefore must be a member of itself. This is a semantic issue resolved in reality by the actual quality of uniqueness. So, with temperature (and other climate paremeters); a base period purports to resolve the paradox of a trend of unique temperatures; but anomalies are still ‘coarse graining’ the reality of each temperature data. Any attempt to establish a trend on the basis of a base period is still compromised by dechoherence because any different base period will produce different anomalies (the Russell paradox). Can this be resolved by statistical significance? No, because any trend has a geographical algorithm as well as a time one. Given that the geographical algorithm is dependent on the time algorithm no level of certainty can mitigate the dechoherent element of the ‘trend’.
“a base period purports to resolve the paradox of a trend of unique temperatures” – it does?
Why is there a paradox. It’s only a simple relative manipulation. A different base will change the anomaly amplitude.
Geographic variation, processing technique or instrument variation (e.g. satellite vs thermometer) is fine – it’s a different methodology/technology. A different sampling of the same issue. A different set of data.
I’m not with you I’m afraid. I don’t see why this is that complex.
Temperature is defined as the thermal state of an object in thermal equilibrium. As the earth isn’t, it can’t have a temperature.
Oops!