Mole Hills

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The cottage industry that has sprung up to examine the daily sea ice numbers or the monthly analyses of surface and satellite temperatures, has certainly increased the number of eyes and that is generally for the good. But unlike in other fields of citizen-science astronomy or phenology spring to mind , the motivation for the temperature observers is heavily weighted towards wanting to find something wrong.

Thus when mistakes occur and with science being a human endeavour, they always will the exuberance of the response can be breathtaking — and quite telling. Imaginary GISS only puts out press releases on the temperature analysis at the end of the year. The headlines trumpeting this result? No heads will roll, no congressional investigations will be launched, no politicians with one possible exception will take note.

This will undoubtedly be disappointing to many, but they should comfort themselves with the thought that the chances of this error happening again has now been diminished. Which is good, right? In contrast to this molehill, there is an excellent story about how the scientific community really deals with serious mismatches between theory, models and data. An initial analysis of a new data source the Argo float network had revealed a dramatic short term cooling of the oceans over only 3 years. Nonetheless, the paper was published somewhat undermining claims that the peer-review system is irretrievably biased to great acclaim in sections of the blogosphere, and to more muted puzzlement elsewhere.

It took a couple of years for these things to fully work themselves out, but the most recent analyses show far fewer of the artifacts that had plagued the ocean heat content analyses in the past. A classic example in fact, of science moving forward on the back of apparent mismatches. Unfortunately, the resolution ended up favoring the models over the initial data reports, and so the whole story is horribly disappointing to some.

Which brings me to my last point, the role of models.


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It is clear that many of the temperature watchers are doing so in order to show that the IPCC-class models are wrong in their projections. However, the direct approach of downloading those models, running them and looking for flaws is clearly either too onerous or too boring. Even downloading the output from here or here is eschewed in favour of firing off Freedom of Information Act requests for data already publicly available — very odd. For another example, despite a few comments about the lack of sufficient comments in the GISS ModelE code a complaint I also often make , I am unaware of anyone actually independently finding any errors in the publicly available Feb version and I know there are a few.

The October anomaly was originally documented as 0. Good for the quick fix. Watts up with that is seriously fixated on the temperature record, though it is clearly not the only evidence of real and rapid warming. I tried my hand at a response to his recent UHI in Reno post, here and visited his comment section, but got no satisfying response to my challenge about the lack of correlation between urbanization and warming anomaly. True, the story may be greatly overblown. There are some things I noticed following what was happening that caused me to go HUH?

The enormous dark red blotch this Oct in Eurasia is due to a data error. There is a similar red blotch in the western Antarctic in Sept that I would question. I would think that any obviously abnormal anomaly warm or cold would be more thoroughly investigated.

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There was a similar 3 degree C jump in north western Europe around That appears to be a real temperature change, not data error. I have yet to see a good paper that jump in temperature. Each abnormal anomaly should offer a learning opportunity. Whether improving data management, improving programming or improving our understanding of weather. Anomalies cold and warm in the range of multiple degrees C are not that unusual.

At the global level, and if you look at whole years, they smooth out, but at local spatial and short time scales these kinds of anomalies are ubiquitous. It appears that there are systemic errors in Russian data collection that results in significantly overstating the ST anomaly by several degrees C warmer for an extended period of time. The October data are counter intuitive and contradicted by UAH troposphere temperatures and Arctic ice extent increases during October. I find your explanation as implausible as Russian October ST. But when the prediction of sea ice turn to be wrong it was because it disappear much faster.

I just hope not to wake up tomorrow and not to hear that CO2 or CH4 are going high and none know why. Behind this there is an important general point: if results are as expected they are less likely to be rigorously cross-checked. The Climate Science community in general has had greater scrutiny over the last decade, largely due to the internet.


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  4. This was an unusual case where large numbers of anomolous data was easily detected due to posted values not jiving with reality. How many other similar issues have gone un-noticed and un-corrected? If the Climate Science community is ever to get buy in from AGW-ers and skeptics alike, then there must be complete transparency and less condescending tones, from both sides. Ruffled feathers of those who have felt the sting of academic critisisms, are getting more shrill and closing ranks. Otherwise, things will continue ad nauseum.

    There is instead a spectrum of confidence that the IPCC tries hard to quantify moderately successfully. For a moment I thought this actually was some groundbreaking news by the way it was presented and commented upon at WUWT. Thank you, RC, for the quick article on this anomaly. After all, when you are looking at all of Russia being Finding comfort in the fact that people, whose motives you detest, find your bugs after publishing calculated results is simply wrong. Additionally, all the motives you list are presumptive assumptions on your part; naked strawmen.

    Some people just want to use anything that happens to push their agenda. Leaves one wondering about errors that lead to underestimating global warming, and whether they might be significant. That would be the real concern, not slightly underestimating it in non-sig ways, or even in sig.

    Just to be clear — is the number of stations in a single corrupt data file, which is one of several such files? Seems surprisingly low, if the latter. This month stations were reported by Nov 10 for October. The number of stations that will report eventually is about Of those stations, 90 had this oddity — which is a significantly higher percentage than one would expect.

    That demonstrates rather poor quality control…something that I think is important when monitoring the global temperature record. That being said, it is good to see RealClimate quickly responding to this issue and addressing the error. Let me guess … is that politician Rodney Hide , recently elected in a change of shoes election result in New Zealand?

    Reference response to 4. Agreed, but if they plateau and persist for a decade or so I find that unusual. I am still trying to decipher Tsonis, but his approach is unique and I feel of value. BTW the only modeling errors that stands out in my lay opinion is that Hansen used 4 degrees for CO2 doubling.

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    I believe he himself said that may lead to an over estimate. Since you feel that you know of other errors, perhaps you would discuss. It is in the interest of science. Our current model has a sensitivity of 2. Well put Gavin. The combination of quick reactions through quality controls and the rare correct findings if outsiders has been beneficial in fixing the glitch quickly. The OLR emitted by carbon dioxide is calculated using the kinetic temperature of the atmosphere, but CO2 emits at its vibrational temperature. The greenhouse effect is due to CO2 absorbing more radiation than it absorbs as was shown by Tyndall and later by Koch.

    This error is common to all models, and has partly arisen because it it believed that planets maintain their top of the atmosphere TOA radiation balance by altering their outgoing long wave radiation OLR , whereas in fact the balance is brought about by changes in incoming shortwave radiation ISR due to clouds. Watts, exaggerates every finding he has, even when there is actual cause for concern; he also is trying to discredit every weather station in the country, as if no other data exists and suddenly every thermometer is impproperly placed and is not calibrated…funny really, and many people follow him as if he is the best bet to discredit AGW.

    I agree with Eyal, I wish this were all not true, however, scientists and science itself is not incompetent in this day and age to be wrong; should we feel good the science is good enough to offer warning or angry that it is correct and so little is being done? I would think that the scientists involved in this field would be very appreciative to those that check the data and the processes used to model the data.

    Thank you for addressing this. Perhaps this is an opportunity to find 2 points of agreement: 1. Finding and fixing errors is a good thing. Giving credit where credit is due is a good thing. As Goetz writes :. The NOAA.

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    The error should have been picked up by normal quality and data handling procedures. It reduces confidence in GISS and opens the door to the possibility of other major errors not being revealed.

    That means that the analysis gets done initially without much supervision. Subsequently a much wider circle of people look at it and if anything seems awry it will be brought up. This is true for sea ice measurements, sateliite temperatures and the surface analysis. I believe John S and the others who noted the anomalies and took the time to determine the cause are due thanks.

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