Today I got a piece of delicious irony and satisfaction in seeing that one of the phantom operated climate blogs, Rabett Run, started using photos from www.surfacestations.org to make a point:
This contrasts to a few months ago when the phantom blog operator maintained that “pictures don’t matter” because, as he put it “they only show a snapshot of time”. Yet he’s using www.surfacestations.org photos to make his point. I’d qualify that as a success in proving the value of photos.
Now this phantom persona “Eli Rabett” is apparently a climate researcher at a major university, but like many other climate blogs, doesn’t use his real name for fear of hurting his tenure/funding/reputation. The exception is RealClimate who does publish the names of the principals. It seems some otherwise honest climate scientists participate in this online game of intellectual charlatanism by not revealing their names when used to make points or to attack others. Why they do it is beyond me, because science is supposed to be about truth. Nobody gets to publish papers in scientific journals anonymously, attend conferences anonymously, or belong to professional organizations anonymously, so why should their conduct online when engaging in science discourse be allowed differently?
By the way, since “Rabett Run” didn’t provide a source, to give proper credit where it is due, the photo of Alma, MI was taken by www.surfacestations.org volunteer Don Kostuch, whom is our most prolific and dedicated volunteer.
I am a groundwater researcher, who has developed VERY large databases, as well as having had to incorporate large amounts of unqualified data. I was always very mindful of quality control issues. From what I have been seeing here and at climateaudit.org, if the standard set by climate “scientists” in collecting/using data was followed by other professions, there would be chaos. So, its a cooling effect… Are there enough of them to outweigh the heating effect, or the “Central Park depopulation” as found at climateaudit? Keep up the good work. Good science is good science – regardless of what the results end up being.
Halpern also posted a photo of farmington ME.
Funny, when I checked the TRENDS at that site versus the TRENDS at nearby sites I saw no RELATIVE cooling.
Both sites tracked each other.
Let Professor Halpern search the database for “cool” stations.
Here will be the outcome.
1. the number of stations by asphalt will be greater than those under shade.
I saw this when we were at 10%.
POINT: microsite bias LIKE UHI BIAS is not equally biased. Microsite BIAS is positive.
2. He will give us a pile of “cool” stations to test our methodolgy on.
3. The Rabbett was the one who defended Detroit Lakes, which led to the Y2K error. Give the bunny enough twine and he will snare him self again.
I like splitting hares.
Anthony/Stephen: Harebrain suggests for every asphalt site there is a shade site. Common sense tells me that relatively speaking asphalt will do a lot more heating than shade will do cooling. Are there any studies enumerating the differences? -lg
Anthony,
I think we have trapped a Bunny with this one.
Comparisons between Alma
Mount pleasant ( in a friggin rock garden) and Owosso Will show that
the “rural” sites are in alignment, while the rock garden at Mount pleaseant rises in temp relative to both.
More later
Didn’t you know that Rabett/Halpern, the folks at Real Climate, etc, are allowed to use double-standards?
So little time, so many baseless assumptions:
1) Eli’s point is that your material is basically self-cancelling within its own terms. If he were using it for any other purpose, you might have an argument. As it is, you don’t.
[MODERATOR NOTE – on #1 I get what he’s trying to say, but we’ll see when its all tallied. So far there does not appear to be a balance as has been suggested.]
2) Eli is a senior scientist (professor) in a hard science, but not climate science. If he used his name on this climate stuff, then e.g. a grants manager at NSF who decided to google his name would find mostly the climate stuff. This is undesirable for obvious reasons. It’s not that hard to find out who he is, BTW, if you really want to know (in contrast to the truly anonymous like the lovely John A. or even the first commenter above).
[NOTE From Moderator – thats really lame, if you are going to regularly author an opinion, stand behind it. ]
3) Steven Mosher: “Funny, when I checked the TRENDS at that site versus the TRENDS at nearby sites I saw no RELATIVE cooling. Both sites tracked each other.”
This is exactly the point. Most of these microsite effects will show absolutely no trend, regardless of whether they have a putative “cooling” or “heating” effect. If they show a trend, the record for that station can be treated appropriately (as is the case now). If they don’t show a trend, they can be ignored. BTW, don’t forget that shadows come from buildings (as are common mext to parking lots) as well as trees.
4) Steven Mosher also refers to a methodology. What methodology? Sounds like vaporware to me. But please do answer Larry’s question.
5) Larry Grimm: “Common sense tells me that relatively speaking asphalt will do a lot more heating than shade will do cooling.”
The air immediately above the asphalt will certainly get relatively hotter, but that’s not where most of the “problem” sensors are. Does common sense tell you that a sensor in an enclosure five feet off the ground and e.g. ten feet away from the asphalt will get significant warming?
Many of these supposedly well vetted, “rural” sites have had many microclimate changes. Some are due to station moves, some to microsite vegetation drift, some to nearby land use changes, and some to equipment substitution.
Each station has its own history, which can effect the “trend”. The MMS NOAA database doesn’t seem to track changes past 1948 and what changes it tracks can be incomplete and questionable (Esp. Lat/Lon translations between deg/sec and deg/decimal potentailly suggesting a location change that didn’t really happen).
Caveat Data (ab)User.
Stephen:
As you look at Alma check the adjustment, I eyeballed it and it looks very large back at the beginning of the record – almost 1C!!
So, two bad sites make good data, wonderful. I don’t like betting my life on crap like this.
Anthony and his volunteers are auditing. They’re waiting for the final results before coming to a conclusion.
I just checked the population of Alma. It should in fact be classified as Rural since its population has never reached 10,000 – the peak being 9652 in 1980 according to the Alma City Master Plan (http://www.ci.alma.mi.us/docs/AlmaMasterPlan10-9-02.pdf). The overall population density also argues against an urban designation – strictly speaking 10000 is the break point for suburban. The basic issue is that the classification scheme by population size to identify UHI and non-UHI effects is problematic to say the least, with much of the data being out of date. If adjustments are made based on this designation then even more issues lie just beneath the surface. ELi’s UHI cooling effect is what the rest of us might call the non-UHI effect!!
All this is said without scrutinizing the actual temperature record.
The Farmington Maine site that is photographed on surfacestations.org is at a new location as of earlier this year. Pictures of the new station will tell you nothing about how microsite changes have affected the temperature trends. The older Farmington site was in place for more than 25 years. The older site wasn’t particularly good. These stations that move around a lot are difficult, perhaps impossible, to use in climate change studies.
I just checked the population of Alma. It should in fact be classified as Rural since its population has never reached 10,000 – the peak being 9652 in 1980 according to the Alma City Master Plan (http://www.ci.alma.mi.us/docs/AlmaMasterPlan10-9-02.pdf). The overall population density also argues against an urban designation – strictly speaking 10000 is the break point for suburban. The basic issue is that the classification scheme by population size to identify UHI and non-UHI effects is problematic to say the least, with much of the data being out of date. If adjustments are made based on this designation then even more issues lie just beneath the surface. ELi’s UHI cooling effect is what the rest of us might call the non-UHI effect!!
All this is said without scrutinizing the actual temperature record.
I don’t believe that the site visits are an audit as much as they are a qualitative survey. Based on the survey interpretation, it should be possible to identify potential hypotheses to evaluate by delving into the details (current and past) of specific sites and potentially applying what’s learned to the other sites. From what I’ve seen, it would be better to focus our attention towards the future to see how all of these predictions turn out.
You know he’s using your bandwidth to link to that picture without permission, and not giving proper accreditations.
Re Jim Bilodeau
Is the photo hot-linked? Rabett should know better than that. It would really be a shame if the owner of surfacestations.org replaced that photo with something more fitting to the occasion. 😉 That mistake is usually only made once.
The reason that trees and buildings are supposed to be kept a distance of 4 times the height of the tree or structure has to do with mixing of the boundry layers. If the wind is blocked at the surface where the sensor is then the heat builds up in that area and introduces a warm bias.
Yep, its hot linked. Sure would be funny to see that picture changed…maybe the rabbit in a pot from “Fatal Attraction”?
Obviously Rabett Run is a weasel operation run by a coward.
Well I gave him a chance, from others comments and his own comments he was aware several hours ago.
I really don’t mind people using the imagery, that is what it is there for. But credit should be given when it’s used. Supposedly this fellow is an academic, and he knows he should attribute others work. The fact that after being advised of such, chose not to do a simple edit speaks to his credibility.
So I changed the photo to a chocolate bunny with an admonition.
On second thought, after a few minutes, I just changed the photo back to the original, but added our logo. Better to push the brand than to pay attention to phantoms lack of courtesy, since they don’t care and won’t do it anyway.
I’m happy to Answer Bloom.
There are several methods for determining homogeneity.Half a dozen or more
Runs test is one taught at Columbia ( hansens) shop.
There are others.
BUT for Bloom, we keep it simple. dirt simple for flowers.
The ALMA site posted by STARTS in 1948. The concern is that the shading, YES THE SHADING documented by our visit, might cool the site.
Actually the trees MAY impair the measurements in two regards. Shading and wind shelter. This is why CRN requires that a site be clear of these kind of obstructions.
SO… lets look at ALMA.
1. Michigan. Been there 18 years done that. The trees in the photo would be leafless sept through March. April is the cruelest month. Shadin is an issue 1/2 of the year.
Still, that is an issue.
2. The shade is in the early morning ( after Tmin) and late afternon, after TMAX. Have a look at
at the Site survey notes. One benefit of visiting a site ( as opposed to night lights) is that you can ASK THE OBSERVER when the temperature guage is in the shade. you can document the time of your visit. this visit was at 930AM. Typically for ALMA TMIN happens right before dawn. Early mrning shade MIGHT ( read carefully) not be an issue.
3. BUT SHADE CAN COOL A SITE! Lets not be microclmate sceptics like Bloom, denying all of the published science about microsite effects.
So, how do we look at this?? Is ALMA cooled by shade?
If the Microsite effects cool this site, then we should see RELATIVE effects when compared to nearby sites.
That is Alma should show a cooling TREND… RELATIVE to nearby sites. Now, HAnsen considers sites within 1200km when he “adjusts” things in his climopractology. I’ll just look at sites a 100km away.
Places I know. Cities I know. Places I’ve been to.
Go to GISS Temp web site.
Select GISS RAW. enter alma.
Get the files for the following
1. Alma.
2. Mount pleaseant
3. Midland
4. Owosso
5. Big Rapids.
Look at data from 1948 onward. WHY 1948? well thats when the ALMA coop site starts.
Now, if ALMA has some radical microsite cooling you will see it diverge from the others.
If ALMA cools more than the others, then that tells us something.
Bloom wont check this. He doesnt know how.
You all have a look.
If you have troubles let me know. I’ll Shoot Watts a file.
Otherwise, let the rabbett dig a hole.
So, mosh, rather than apply some fancy set of algorithms to the site configuration based on the information in the photos, you prefer to compare the data. As you say, it’s just what the scientists do. But since I may have missed it the first time, please do explain to me again exactly how it is you’re using the information in the photos.
I thought the reason for the rabbit hutch was to afford every surface station with constant shade.
By the way I only use an alias out of habit and for continuities sake. There are many people who look at the name “papertiger” and have a feel for what to expect. It wouldn’t be nice of me to start sneaking up on pthem by using the psydonym “Jim”.
Known times of observation from 1977 to present are from 0730-0800. The tree’s shade probably wouldn’t have been much of a factor during that period. Consider, too, the tree’s growth throughout the period of record. Then, there’s the building just east of the CRS. No doubt, there are other human-introduced biases, as well.
He has another image up, btw. Looks like he’ll do one daily. I guess he’s a believer in microsite bias, too.
please do explain to me again exactly how it is you’re using the information in the photos.
From a layman’s perspective, there are a couple things that I noticed about the photo. First, you can’t see how tall the tree is, but it appears to be around 50-75 feet away, and the portion that’s visible doesn’t appear to contain dense folliage. It’s shade effect would only come into play if it were to the south of the monitor, and, even then, probably only at the cooler times of year when the sun is lower in the sky. If the tree is anywhere but to the south of the monitor, it may have no effect at all.
Second, regardless of the orientation of the picture, the bush isn’t likely to provide any more shade than the taller building immediately to the left of it. I can’t imagine the “cooling” effects of the bush and tree in this photo even being measurable.
Stan, the point is that mosh isn’t using the photo information for anything since there are no numerical methods available for that. Developing such methods might be possible, but chances seem slim of being able to do so generically so as to make the photos useful rather than resorting to the difficult and expensive alternative of setting up monitors at each site and running them over a period of time (probably much harder than setting up a separate network from scratch). So, like the scientists, all mosh can do is look at the data and bear in mind that any tangible microsite effects will tend to show up in the data. As in this case, though, most of them don’t amount to much.
Chris D, I guarantee you that this particular site is in shade at that time for at least part of the year due to the substantial hills just to the east. Of course the entire region in which that site is located is famous for having sharply variable micro*climates*, which is a little difficult to know about from photos. OTOH being able to compare and contrast data from a number of other stations around the region probably will indicate something useful about this particular station, which brings us back to the main point.
Bloom writes:
“So, mosh, rather than apply some fancy set of algorithms to the site configuration based on the information in the photos, you prefer to compare the data. ”
The approach is very simple. If you were current on the literature you would get it. But I give you the Middle school version, so your reach can exceed your grasp
1. When the Site survey indicates the potential for an inhomogeneity you have THREE OPTIONS.
A. IGNORE the evidence and ASSUME that microsite BIAS is normally distributed with a mean equal to zero. Basically the Gavin & Bloom ignorance is Bliss approach. The problem here is that cooling bias is asymptotic and warming bias is exponential. simple version. When a site is FULLY shaded… thats the limit. When a site is UHI impaired, people figure a way to put more asphalt, more buildings, more bodies, more heat sources int the same area. Microsite bias is a scale version of UHI bias.
B. DUMP the site as non compliant whether it is a “cooling” site or “warming” site. Mosh Pit
approach. Gavin says we only need 60 sites in the Northern Hemisphere. I like to make him happy. Since 60 sites can be used to sample the NH according to NASA, we volunteer to submit 30 GOOD sites for the US. More than our fair share!! All those shady sites?? Gone. All those asphalt sites???. Gone. Agreed? Thanks Bloom.
Thanks Rabbett! all bad sites are banished. Gavin says we only need 60 in the whole nrthern hemisphere. EMBRACE the consensus. 60 good sites.
wait the US is 2% of the world land mass… figure 5% of the NH.. oh heck 10%.
That means 6 sites in the US. Hey that’s all brazil has. SIX GOOD SITES in the US is all we need. I think we have six good sites in the database. In fact, Surface stations is HELPING gavin, we are ging to test his 6 good sites theory.
C. Try to make some kind of assesment of the contamination and adjust.
There are TWO approaches here.
1. DATA APE & Meat grinder.
2. Focused.
DATA APE thows data at Meat grinder method. See Parkers UHI study.
Focused ( Oke for example) works bottoms up. All relevant data is considered.
So I did an option c2 for you bloom. Even though I prefer the 6 good sites for Gavin!
Anyway….
First it’s not Photos OR data, as you put it.
Photos are data. They can guide our inquiry.
Specifically, if a photo showed SHADING, I would look at TMAX ( max temp recorded for the day)
since shading can impair insolation. Further I would for exponential changes. The literature is clear on this. Simply, the vegetation grows rapidily and then tapers off, This leaves a signal. rapid change follwed by no change. Think logistic curve response.
The type of tree is also important. A CONIFER in won’t lose it needles. A deciduous tree in michigan will lose its leaves. Why does this matter? Well I may start by looking for a signal in TMEAN on an annual basis. Then I realize that maybe the signal is in TMAX… Then I realize that maybe this signal shows up in the spring months and grows into the summer. With the photo of the actual site my apprach to the data can be much more structured, focused. Not data ape.
Photo guides my path.
( PS I didnt even discuss Wind shelter and trees and the importance of leaf type,But Bloom hasnt even read the basic science here )
So, when the photo shows shading you might tailor where you look first.
Now, why photos matter when they show asphalt.
Same with Asphalt and buildings nearby.
1. There is an expectation of insolation amplification. Simply, TMAX can be elevated by multipath reflections.
canyon effects.
2. There is a substantial amount of study showing that these features ALSO impact TMIN. (Simply, for the flower child. )The heat held by anthropomorphic structures release over time and raise the TMIN recordings, narrowing the Dirurnal range.
3. Evapotranspiration impairment.
A good anecdotal example of this is Las Vegas. The max temp has not gone up, but the Minimum has. So, the average goes up….
1. Concrete and asphalt are heat sinks ( think solar house) and they release heat when the air cools, after TMAX…
2. Humans artificially heat the air.
3. Buildings shelter the surface from the cooling efects of wind which can
( under certain conditions) create vertical mixing and cool the surface.
So When I see asphalt and buildings I tend to focus on diurnal range or Tmin.
See Oke. Its not Pictures OR data as bloom suggest.
Its EVIDENCE from the site survey that is used to guide and focus analysis.
To RECAP.
3 options.
1. Ignore the evidence on the assumption of equal bias.
2. Eliminate stations that Violate specs.
3. Estimate the errors of sites.
BLOOM Bloviates:
“As you say, it’s just what the scientists do. But since I may have missed it the first time, please do explain to me again exactly how it is you’re using the information in the photos. ”
The site surveys are not ONLY photos. The site survey verifies the GPS, verifies the elevation, verifies, the instrumentation, documents site compliance with photos. Deviations from compliance are crucial.
For example, Since the 1950s the practice of having climate stations on the rooftops of buildings has been condemned by NOAA.
You would think that NOAA would not have any stations on rooftops. If you looked at station history, like hansen, you would think that no stations are on roof tops.
WRONG!
When you visit sites ( santa rosa, newprt beach) you see that ignorance is bloom, not bliss.
Now, why are these survey validations important.
1. GPS. The sites GPS coordinates are verified by survey. Since Hansen uses a satillite photo to determine the brightness levels of lights “at the site” it is important to verify the GPS. He cant read files from USHCN correctly so why trust him with sharp instruments.
2. Site elevation. Hansen makes adjustements for site elevation ( H99, st. Helena for example)Verifing this has value. In Hansen 99 he says the Laspse rate is “about 6c/km” 6.5 is closer.
3. Instrumentation. over the past NOAA has changed instruments and enclosures.
These changes have caused inhomgeneities. Adjustments have been made for SOME of these documented changes. Verifying the instrumentation has value.
Also, some enclosures show signs of damage or contamination ( missing slats, light bulbs inside, mold on radiation sheilds)
data is good Bloom.
4. Operator interviews. When An operator indicates ( see big rapids, mich) that certain months have anomaly issues, then that is good information. Also, operators can provide site history. ” I planted that tree last year” ” that Air conditioner is never used”
etc etc.
5. PHOTOS.
photos are one piece. To be a quality site in the NEW CRN ( google CRN NOAA)
a new climate network that hansen supports, you need a site survey. You need photos. The photos allow researchers to classify sites using the Leroy scale.
1. No bias
2. No bias
3. 1C Bias
4. 1-3C bias
5. 5C bias
Then decide how you want to proceed.
1. Use Junk sites.
2. Dump Junk Sites.
3. Nip Tuck.
So, Bloom. You decide.
1. Use junk sites withut adjustment.
2. Dispse of them
3. Nip Tuck?
My goodness, what a lot of hand-waving. Let me ask you, mosh:
Can you link to even one paper showing a procedure for adjusting data based on photos?
How about a paper discussing under which of the circumstances you describe all data from a given site should be “junked” without looking at the data itself to see if the problem actually appears there? Got one of those?
If not, I’d say it’s time for you and your associates to put your nose to the grindstone and write those papers. Oh, none of you have the needed skill set? I guess it’s back to hand-waving in that case.
I’ve been reading this blog and others for some time now, and I’m finally compelled to comment thanks to Mr. Bloom.
Mr. Bloom, you seem to be nothing but negative, and a colossal waster of time for all concerned. I read some of the things you posted on the Climate Science blog, and now you are here with odiferous commentary on this one. It is too bad that one closed, it was well written and insightful.
But sir, kindly, STFU (with my apologies in advance to the blog operator) and let these people do the work. THEN you can criticize the results. People whom criticize a project or idea before it is completed when they have nothing to contribute themselves, are the lowest form of critics.
I suggest this – get out there and do something yourself to disprove the idea rather than try to shoot everyone down to ground level.
Critics are lazy. From what I’ve read, I say Mr. Bloom is too lazy to do any useful science himself He is simple blog FOD dropping bits and pieces on the runway hoping to get sucked into the idea engine to do damage.
Thanks, Marsalis! It’s seldom that I hear such a deeply felt compliment. Was the irony unintentional?
Steve Bloom, the peer-reviewed literature and scientific consensus is that eliminating micro-site influences is important and part of the professional standards to be adhered to for surface sites.
When climatologists ignore their own peer-reviewed literature as to siting, and violate their own professionals standards as to siting, it is natural that the validity of their data will be questioned.
“Posted by: Steve Bloom
My goodness, what a lot of hand-waving. Let me ask you, mosh:
Can you link to even one paper showing a procedure for adjusting data based on photos?
How about a paper discussing under which of the circumstances you describe all data from a given site should be “junked” without looking at the data itself to see if the problem actually appears there? Got one of those?
If not, I’d say it’s time for you and your associates to put your nose to the grindstone and write those papers. Oh, none of you have the needed skill set? I guess it’s back to hand-waving in that case.”
Maybe we don’t have the necessary “skill set” to write the papers you suggest.
That’s why we depend on the “scientists” (like Al Gore) to give us the facts.
Thats why we depend on the “experts” (like Hansen, et al) to give us the information, data, and methods they used to adjust the raw data.
There have been 2 papers written describing how siting can bias the results (in Colo and Indiana). This is why surfacestations was started: to see how many of the 2000 or so U.S. sites do not meet world standards.
If the original installation had been photographed, these problems would have been found already.
Bloom writes:
“Can you link to even one paper showing a procedure for adjusting data based on photos? ”
Yes Hansen99 and Hansen2001
These papers used nightlights, a satillite photo to adjust sites based on the rural/urban distinctin that nightlights “established”
essentially you have a strawman argument. No one suggests what you imput here. The photos are a guide. For example, the photos could be used to classify sites into two groups Class1-3 and class 4-5. Then, these grups could be compared.
Bloom continues:
“How about a paper discussing under which of the circumstances you describe all data from a given site should be “junked” without looking at the data itself to see if the problem actually appears there? Got one of those?”
Oke.
Intuition, experience, and review of
classic microclimatic case studies (e.g., Geiger 1965)
suggests to us that the net impact of the most common
changes (compaction due to trampling, increased paving,
tree growth, removal or soiling of snow cover, construction
of buildings and introduction of irrigation)
lead to alteration of nocturnal controls on the surface
heat balance (thermal admittance, sky view factor and
roughness and shelter) in ways that reduce nocturnal
cooling and consequently increase the minimum temperature.
Removal of trees and desiccation will act in
the opposite direction. Are the environments of climate
stations preferentially modified during the inexorable
process of development in a way that leads to net thermal
impacts? We suspect they are, but the question
deserves attention and objective analysis.
The technique here is also relevant to the identification
and assessment of thermal changes at larger scales
and of larger magnitude, such as urban heat islands.
Such effects have managed to gain the attention of
those constructing data banks used to quantify trends
and spatial patterns of air temperature over long periods
and at scales up to those of the globe. Here again
the potential biases of microclimatic site influences are
commonly underappreciated because the focus of the
work is on larger scales (Peterson 2003; Oke 2004) or
the researcher only relies on available electronic databases
of population, night-lights, NDVI or similar indirect
signs of potential site disturbance by humans. Since
seemingly minor microscale alterations to the environment
of a temperature screen are capable of rendering
series inhomogeneous, it has to raise skepticism about
the criteria used to accept stations into some global
datasets. Even the most well-regarded sets accept stations
based on evidence as loose as having no more
than a few tens of thousands of people living nearby, or
the lack of bright lights in the area, or pixels with low
NDVI. Such criteria fail to recognize the possibility that
the immediate microscale environment of the screen is
critical. Such evidence can only be gained from a visit to
the site or a detailed metadata file.
Plus as Gavin has pointed out, referencing shen98, the whole Northern Hemisphere can be sampled with 60 high quality sites.
60. on an area basis that would mean less than 6 sites in the US. So, I believe Gavin and NASA. 60 good sites in the NH.. The photos will help us screen out the potentially bad ones.
Marsalis,
Thanks for reading and following the effort. Don’t trouble yourself too much with the flower child. His responses are canned. Like the chatty Cathy doll, pull his string and the same canned speach comes out. We WANT people to see his style of thought. He’s the Miss South Carolina of AGW.
I think the best assessment of the historical observation was authored by James Hansen.
http://books.nap.edu/openbook.php?isbn=0309063906
Some fun with climate scientist James Hansen. His words:
NOAA, DOD, and the FAA also operate a network of
approximately 1,000 automated observing sites, mostly
at airport locations, that measure hourly temperature,
precipitation, humidity, winds, and other variables.
With some exceptions, these sites have become only marginally useful for documenting
climate variability and change over the last decades because of problems
with changes in location, instrument technology, data handling systems,
and operating procedures. These changes occurred without consideration of
multi-decadal climate monitoring. In particular, the automated systems
replaced manual observatories without sufficient overlap in operations
to relate the data characteristics from the two methods of observation.
However, with adequate sensitivity to their future operations, many of
these sites have the potential to build a very useful climate record for the future.
At the present time USGCRP agencies lack the capability to routinely assess and, therefore, expeditiously correct problems related to multi-decadal climate and weather monitoring. These agencies operate a large number of observing and data management systems used by the scientific community, but no agency has the mission or assumes responsibility to assess routinely the adequacy of these data for analyzing decadal climate changes and variability.
Unfortunately, at a time when major policy decisions regarding climate change issues are being made, the ability to observe the climate is disorganized and declining. Figures 1-4 show the decline in the data sets for the Historical Climatology Network (HCN), both global and national; the Comprehensive Aerological Reference Data Set (CARDS); and the Comprehensive Ocean/ Atmosphere Data Set (COADS).
http://books.nap.edu/openbook.php?record_id=6424&page=20
http://books.nap.edu/openbook.php?record_id=6424&page=25
Read the whole thing. You will find that Hansen slams the very observing system that he uses. When he SCORES the system according to Karls Ten principles, he gives it a 5. 5 out of ten. That like a D+/C-
So, Hansen Condemns the system he uses. and when Anthony takes pictures f these failing sites, when Anthony VERIFIES Hansen’s concerns about the climate measuring system, the Skeptics like Bloom, disregard what Hansen has written.
So, When Hansen criticized the USHCN was he right? or was he wrong like Bloom assumes.
I love the Irony of Bloom denying the science of climate science. Hansen rules. He’s right, the existing system is inadequate.
Hansen’s pledge to open science. Hey Bloom, tell Hansen to free the code
Hansen:
http://books.nap.edu/openbook.php?record_id=6424&page=42
All parties, ………, shall: 1(g) Promote and cooperate in scientific, technological, technical, socioeconomic and other research, systematic observation and development of data archives related to the climate system and intended to further the understanding and to reduce or eliminate the remaining uncertainties regarding the causes, effects, magnitude and timing of climate change and the economic and social consequences of various response strategies; and
1(h) Promote and cooperate in the full, open and prompt exchange of relevant scientific, technological, technical, socioeconomic and legal information related to the climate system and climate change, and to the economic and social consequences of various response strategies.
Free the Code
mosh, you have a fanboy! Likely kind of an old, grizzled fanboy, but you have to take what you can get. Treat him good…
On the photos:
Not sat photos, the direct site photos you guys seem to think are so valuable.
And Oke says to then do what with the site and data? I didn’t see anything there about junking the data.
Oke’s and similar research are what led up to the decision to build the CRN (and similar networks in other countries). Note again that it did not lead to a decision to try to fix prior microsite problems.
Regarding Bloom,
Bloom’s speciality is circular arguments just to make people do busy work to address his complaints. Of course no answer is sufficient, so he just complains more. Hence the circular nature. Pielke’s workload which gave rise to his decision to end his blog was in no small part related to Bloom and others like him that keep repeating the same old circular complaints in an effort to bog down the process. I’d say they succeeded. Pielke just got tired of it, and I don’t blame him.
So, with the questions on this thread having been asked and answered; this thread is closed. We all have better things to do.
I have to run a business, raise a family, conduct the surfacestations research, keep the CA server running, and moderate a blog. Since my business has suffered this summer because I gave way too much time to blogging and research, and since blogging and research is actually taking money out of my pocket because I’m funding a website, travel for surveys, conference costs, Stevenson Screens, dataloggers, and other equipment, something has to give. And that is this blog.
The best way for me to keep the blog open is to not get bogged down in circular arguments like Blooms. So that means throttling it back so I don’t waste time (like with this post) dealing with it. Since the blog engine provided by our local newspaper, the Enterprise Record, (Moveable Type) is broken and will no longer send comments to email for single click approval, I have to drill down into the website several times daily to read all the comments. Failure to do so and to read each and every comment completely can get me into some trouble as we had happen with the Green Man debacle.
So choosing between a lot of extra work, stopping the blog completely, or simply applying a throttle, I choose the throttle to prevent circular arguments.
If that upsets a few people, so be it. But as moderator I get to choose the way it is and is going to be. There are plenty of other blogspots where you can get into circular arguments. Knock yourself out.
The point everybody needs to keep in mind is that winning a blog argument doesn’t matter. Research and publication is what matters. I’m focused on that.
So, don’t feed the Trolls. Don’t even throw breadcrumbs, because like raccoons, once you start feeding them they show up at your back door again and again, and eventually you get bitten.
I’ve posted 1998 and 2007 images of Alma, trees have sure grown a lot in 9 years!
I can’t identify the exact location of the station, but following the rabbet trail, if trees are growing and cooling the site, then there should have been a cooling trend in the data over the last 9 years, not the warming trend (?) in the data?
Looks like there’s been constuction since 1998 also. Once again, Anthropogenic Landscape Beautification!
“1. Use Junk sites.
2. Dump Junk Sites.
3. Nip Tuck.”
All three, surely!
[P.S., but give SB full non-pseudonym credits.]
Does common sense tell you that a sensor in an enclosure five feet off the ground and e.g. ten feet away from the asphalt will get significant warming?
Mmm. No.
The CRN tells us that.