Do we need to be preparing for Arctic cruising strategies because of Global Cooling

[Reefmagnet]

Originally Posted by SailOar

Newly Discovered Bacteria Could Worsen Climate Change | Mythological World News

A paper from researchers at Georgia Institute of Cultism, and published in the journal Naturopathy, has discovered a bacteria capable of making dead zones deader by depleting the amount of nitrogen in oxygen minimum zones.

3rd day is gunna eat this one for breakfast lol.

[Reefmagnet]

Originally Posted by SailOar

This Chart Shows Why Insurers Are Climate-Change Believers | Poverty Unlimited

I think those later figures may be "inflated" or perhaps some of the earlier figures are somewhat "under populated".

[jackdale]

Originally Posted by GoingWalkabout

No explanation was given as to why this serious fault in test samoling? Why did the measure takers discard 80% to 93% of the data collected? What biases came into play in their decision making into which data sets to keep and which to not use? If course no answer was even touched upon.

Straw man

Other researchers collected data from various sources. They added to the data set; they did not discard other sources.

Muller amalgamated many data sets to get his results.

[SV THIRD DAY]

Originally Posted by jackdale

Muller amalgamated many data sets to get his results.

In the Scientific Community we call that messaging the Data.

[SV THIRD DAY]

Originally Posted by SailOar

Newly Discovered Bacteria Could Worsen Climate Change | Mythological World News

A paper from researchers at Georgia Institute of Cultism, and published in the journal Naturopathy, has discovered a bacteria capable of making dead zones deader by depleting the amount of nitrogen in oxygen minimum zones.

Mythological news....Cultism....folks you can't make this **** up?
Even when I try to be over the top for a Joke, the MMGWC Rises to the occasion and tops me in the lunacy.

[jackdale]

Originally Posted by GoingWalkabout

No explanation was given as to why this serious fault in test samoling (sic)? Why did the measure takers discard 80% to 93% of the data collected? What biases came into play in their decision making into which data sets to keep and which to not use? If course no answer was even touched upon.

Had you bothered to read the BEST study you would find:

In this paper we present results for the Earth’s land surface
temperature only, based on analysis of monthly averages at each
station. We gathered and merged monthly and daily thermometer
measurements from 14 databases to arrive at a collection of 14.4
million mean monthly temperature observations from 44,455 sites.
During this process duplicate stations present in the 14 databases were
detected and eliminated. These data have now been posted online in
a uniform format at Berkeley Earth, along with a description
of the merging and duplicate removal method. For stations that
report only daily data (and not their own monthly average) we
performed the average. We removed only short records (less than 1
year) and records from sites with missing or highly uncertain location
metadata; that left 36,866 stations that we used in our analysis.

http://www.scitechnol.com/2327-4581/2327-4581-1-101.pdf

But then that does not fit with your bizarre conspiracy theory.

[newhaul]

Originally Posted by SailOar

This Chart Shows Why Insurers Are Climate-Change Believers | Poverty Unlimited

This chart only shows that more has been paid out in recent years for damages caused by major weather events. I can almost tell you by this data what weather event happened. All it actually shows is that people are building more in areas subject to major weather events.
Guaranteed the year that topped 120 billion was due to hurricane Katrina.
The year that was just over 70 bil was due to hurricane sandy.

[GoingWalkabout]

Originally Posted by jackdale

Straw man

Other researchers collected data from various sources. They added to the data set; they did not discard other sources.

Muller amalgamated many data sets to get his results.

It is not a straw dog at all. Each person/collection point collected data. 80% to 97% were selectively discarded by each data collector. The Professor did not investigate what criteria was used to discard the non used data. This is worse than sloppy. It undermines his whole model and makes his conclusions fraudulent.

To understand your last statement you need to understand what you mean by data "sets". Is a data set a set of data from each individual data collector/recorder in a particular geographic place. Or is the data set as you refer to the collection of all data from each particular geographic place? So in either case yes his model was built on collection from numerous geographic regions with numerous individuals collecting each data point and then he amalgamated these data points into his model.

This does not change the fact that garbage in equals garbage out. Flawed data collection without strict verification and collection protocols makes a mockery of science. This Professor is not doing anyone any favors by being so sloppy.

I actually love science. Always have. One thing that irks me the most is illogical conclusions drawn from impure and untrusted data.

If the AGW people where diligent about the practice of ethical and sound science then I would pay more attention to their "findings" It is poorly based and even fraudulently concocted figures that keep me skeptical. Become real scientists without the fraud and I may then be able to accept the conclusions wherever they may fall.

In the meantime the politically corrupted scientific community needs to police itself. Go back to questioning all foundational data points and be once again skeptical scientists in the search of truth. If we are indeed going to see 200m rise in sea levels I would certainly like to know. In the meantime no such "predictions" can be relied upon or believed. And the reason why is because of the tardiness of the so called politically funded "scientists".

I am for real climate science. Period.

[jackdale]

Originally Posted by GoingWalkabout

It is not a straw dog (sic) at all. Each person/collection point collected data. 80% to 97% were selectively discarded by each data collector. The Professor did not investigate what criteria was used to discard the non used data. This is worse than sloppy. It undermines his whole model and makes his conclusions fraudulent.


In the meantime the politically corrupted scientific community needs to police itself. Go back to questioning all foundational data points and be once again skeptical scientists in the search of truth.

Muller did go back and used 14 different data sets and explained his methodology.

[GoingWalkabout]

Originally Posted by jackdale

Muller did go back and used 14 different data sets and explained his methodology.

Jackdale. I will go back and review his written work. Nonetheless he said what he said on video which admits a tardiness which is scientifically unacceptable.

Cheers.

[jackdale]

Originally Posted by GoingWalkabout

Jackdale. I will go back and review his written work. Nonetheless he said what he said on video which admits a tardiness (sic) which is scientifically unacceptable.

Cheers.

Are you also hearing impaired?

What he says on the video at 1:40:

"Every other team was using less than 20% of the data, in some cases about 7% of the data." Other teams were using their own data sets.

He does not say "80% to 97% of the collected data was not used" by the BEST study.

Here is Figure 5.7 from AR5. The graphs use about 20 different data sets.

[jimbunyard]

Finally, the Skeptics give us an agenda. (Thanks, SailOar)

Climate Change Deniers Present Graphic Description Of What Earth Must Look Like For Them To Believe - The Union - America's News Source

[conachair]

Interesting piece on why raw data isn't much good..

Thorough, not thoroughly fabricated: The truth about global temperature data | Ars Technica

[Reefmagnet]

Originally Posted by jimbunyard

Finally, the Skeptics give us an agenda. (Thanks, SailOar)

Climate Change Deniers Present Graphic Description Of What Earth Must Look Like For Them To Believe - The Union - America's News Source

You do know you've quoted from The Onion, right?

[GoingWalkabout]

Originally Posted by conachair

Interesting piece on why raw data isn't much good..

Thorough, not thoroughly fabricated: The truth about global temperature data | Ars Technica

If you read the article san he self serving excuses and flimsy conclusions it does a good job in explaining the unreliability of source temperature data collected around the world. it doesn't deal with the mess of ocean temperature data collection. That is another amazing discussion in and of itself.

From the linked article:
Some weather station changes are pretty straight-forward. The desire for weather information at new airports around the 1940s led to station moves. Some of these stations had been set up on the roofs of post office buildings and later found themselves in an open environment on the edge of town. Looking at the temperature records, you might see a sudden and consistent drop in temperatures by a couple of degrees.

Equipment has changed, too, like the installation of a housing to shield thermometers from sunshine or the switch from mercury thermometers to electronic ones. By running them side-by-side, scientists have learned that the two types of thermometers record slightly different low and high temperatures. And because the electronic thermometers necessitated running electricity to the station, some of the stations were moved closer to buildings at the same time.

And while the impact isn’t immediately obvious, changing the time of day that the weather station data is recorded is actually a big deal. Most weather stations didn’t automatically log measurements, especially in the days of mercury thermometers. Instead, special thermometers were designed to mark the minimum and maximum temperatures that were reached. When someone checked the station to note those measurements, they reset the markers.

Imagine that you reset the thermometer at 4:00pm on a hot summer afternoon. The maximum marker is going to immediately return to its previous temperature. Even if the following day is considerably cooler, you will return to see the same high temperature on the thermometer—yesterday’s warmth is accidentally going to be double-counted. The same goes for minimum temperatures recorded in the morning.

As far as long-term trends are concerned, luckily this doesn’t really matter, provided you always check the station at the same time of day. But if you switch from a routine of evening measurements to morning measurements, for example, you’ll suddenly be less likely to double-count high temperatures, but much more likely to double-count low temperatures. This is known as “time of observation bias.”

In most of the world, the effect of all these non-climatic factors is neutral. Changes that raised temperatures have been balanced by changes that lowered them. The US, however, is different. Here, weather stations are run by volunteers who report to the National Weather Service. Compared to other countries, the US has more stations but less uniformity among those stations.

At times, guidelines for the volunteers in the US have changed, with new equipment or procedures gradually spreading through the network of stations. Around 1960, the guidelines changed from late afternoon observations to morning observations. That kicked in over time (many stations didn’t change until a new volunteer took over) (and there’s a substantial cooling bias over that time period as a result.) (says who - where is the evidence of this claim) In the 1980s, the National Weather Service asked volunteers to switch to electronic thermometers, adding another cooling bias.