Whistle blowing on Global Warming

[MORAY37]

again with the problems you seem to have comprehending ............ the defenciency in either paper is that they rely on GISS data to support their conclusions............... GISS data is clearly cherry picked data..... they dont even try to hide that fact.... it says VERY clearly on their website in their methodology for acquiring the data that it is cherry picked.......... they simply try to sugar coat it by saying "we are scientists and we believe this will work"

source citations: GISS (even you should be able to find this one, would it help if I offer you a dollar?)

I suppose you are talking about this site?  I don't know, since you refuse to give a source. It is not in comprehension, sir. It is upon you to cite your references in a debate, not upon me to provide you with them.

http://data.giss.nasa.gov/gistemp/

GISS Surface Temperature Analysis
Updates to Analysis

Graphs and tables are updated around the 10th of every month using the current GHCN and SCAR files. The new files incorporate reports for the previous month and late reports and corrections for earlier months. NOAA updates the USHCN data at a slower, less regular frequency. We will switch to a later version, as soon as a new complete year is available.

Several minor updates to the analysis have been made since its last published description by Hansen et al. (2001). After a testing period they were incorporated at the time of the next routine update. The only change having a detectable influence on analyzed temperature was the 7 August 2007 change to correct a discontinuity in 2000 at many stations in the United States. This flaw affected temperatures in 2000 and later years by ~0.15°C averaged over the United States and ~0.003°C on global average. Contrary to reports in the media, this minor flaw did not alter the years of record temperature, as shown by comparison here of results with the data flaw ('old analysis') and with the correction ('new analysis').

August 2003: A longer version of Hohenpeissenberg station data was made available to GISS and added to the GHCN record. This had no noticeable impact on the global analyses.

March 2005:SCAR data were added to the analysis. This increased data coverage over Antarctica, as evident in the global maps of temperature anomalies.

April 2006:HadISST ocean temperatures are now used only for regions that are identified as ice-free in both the NOAA and HadISST records. This change effects a small number of gridboxes in which HadISST has sea ice while NOAA has open water. The prior approach damped temperature change at these gridboxes because of specification of a fixed temperature in sea ice regions. The new approach still yields a conservative estimate of surface air temperature change, as surface air temperature usually changes markedly when sea ice is replaced by open water or vice versa. Because of the small area of these gridboxes the effect on global temperature change was negligible.

Aug. 7, 2007:A discontinuity in station records in the U.S. was discovered and corrected (GHCN data for 2000 and later years were inadvertently appended to USHCN data for prior years without including the adjustments at these stations that had been defined by the NOAA National Climate Data Center). This had a small impact on the U.S. average temperature, about 0.15°C, for 2000 and later years, and a negligible effect on global temperature, as is shown here.

This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the insignificance of the effect. Further discussions of the curious misinformation are provided by Dr. Hansen on his personal webpage (e.g., his post on "The Real Deal: Usufruct & the Gorilla").

Sep. 10, 2007: The year 2000 version of USHCN data was replaced by the current version (with data through 2005). In this newer version, NOAA removed or corrected a number of station records before year 2000. Since these changes included most of the records that failed our quality control checks, we no longer remove any USHCN records. The effect of station removal on analyzed global temperature is very small, as shown by graphs and maps available here.

Mar. 1, 2008: Starting with our next update, USHCN data will be taken from NOAA's ftp site — the original source for that file — rather than from CDIAC's web site; this way we get the most recent publicly available version. Whereas CDIAC's copy currently ends in 12/2005, NOAA's file extends through 5/2007. Note: New updates usually also include changes to data from previous years. Whereas the GHCN and SCAR data are updated every month, updates to the USHCN data occur at irregular intervals.

The publicly available source codes were modified to automatically adjust if new years are added.

June 9, 2008:Effective June 9, 2008, our analysis moved from a 15-year-old machine (soon to be decommissioned) to a newer machine. This will affect some results, though insignificantly. Some sorting routines were modified to minimize such machine dependence in the future.

A typo was discovered and corrected in the program that dealt with a potential discontinuity in the Lihue station record and some errors were noticed on www.antarctica.ac.uk/met/READER/temperature.html (set of stations not included in Met READER) that were not present before August 2007. We replaced those outliers with the originally reported values.

Those two changes had about the same impact on the results as switching machines (in each case the 1880-2007 change was affected by 0.002°C). See graph and maps.

Aug. 11, 2008: Nick Barnes and staff at Ravenbrook Limited have generously offered to reprogram the GISTEMP analysis using Python only, to make it clearer to a general audience. In the process, they have discovered in the routine that converts USHCN data from hundredths of °F to tenths of °C an unintended dropping of the hundredths of °F before the conversion and rounding to the nearest tenth of °C. This did not significantly change any results since the final rounding dominated the unintended truncation. The corrected code has been used for the current update and is now part of the publicly available source.

Sep. 10, 2008: Comments were added to the homogeneization program (PApars.f) and a line was changed to make the code compiler independent. (Thanks to Nick Barnes who noticed that some compilers may create an infinite loop due to roundoff errors.) These changes had no effect on any results.

Feb. 11, 2009:Two bugs in STEP0 programs were corrected before they had a chance to affect any results. Thanks to Mr. Peter O'Neill for discovering and reporting them to us.

SCAR corrected some errors in their data files; this had no effect on our work since we noticed and corrected most of them a few months ago (see 6/9/2008) and the others concerned stations whose records were too short to be included in our analysis. The analysis description was extended to describe the place where stations with short records are dropped.

May 2009:The sea ice mask adopted in April 2006 was slightly extended to include all ocean northward of 75N, since in that region in the winter months ice was present, particularly at the beginning of our data period, making water temperatures a bad proxy for air temperatures. This has no effect on our analysis, but it removes some odd discontinuities in some trend maps. The gridding tool on our ftp site was changed correspondingly. In addition, the last argument in that tool (mkTsMap.f) was changed to make it easier to use.

September 11, 2009: NOAA NCDC provided an updated file on 9 September of the GHCN data used in our analysis. The new file has increased data quality checks in the tropics. Beginning 11 September the GISS analysis uses the new NOAA data set. The change affects mainly part of South Africa.

November 13, 2009: NOAA is no longer updating the original version of the USHCN data; it ended in May 2007. The new version 2 currently extends to July 2009. Starting today, these newer data will be used in our analysis. Documentation and programs will be updated correspondingly.

December 3, 2009: Nick Barnes and staff at Ravenbrook Limited, while continuing reprogramming the whole GISS analysis, discovered a bug in a program used in STEP5; it was fixed and a rerun of the analysis showed that not a single number posted on this web site was affected by that correction. The public source code was modified correspondingly.

At no point do I see "we are scientists and we believe this will work".

[Anaxogoras]

So NASA is cherrypicking data to support the AGW hoax?

[MORAY37]

So NASA is cherrypicking data to support the AGW hoax?

Says the typical American Denialist where all things revolve around the dollar..."I bet they will now though!  They just lost the shuttle, Constellation and Orion...."   

[MORAY37]

Your posting crap now.

Irony.

“Ignorant people think it's the noise which fighting cats make that is so aggravating, but it ain't so; it's the sickening grammar they use”

 Mark Twain quotes (American Humorist, Writer and Lecturer. 1835-1910)

[CAP1]

So NASA is cherrypicking data to support the AGW hoax?

i think there was some sort of errors pointed out in nasa;s stuff concerning this about 1 or 2 years ago.

[batch]

So NASA is cherrypicking data to support the AGW hoax?

this guy wins the prize............ although moray should share it for actually finding the GISS website

now that you have found the site..... and youre so keen on methodology...... locate the parts where it explains theirs in deriving data........

then please explain to me (since Im obviously not a scientist and have no concept of what Im talking about) how using a 1200Km (approx 750 miles) radius from a SINGLE station as the average temperature for an entire area can possibly be anywhere close to accurate ......... this would imply that the average temperature in Amarillo, TX  and Denver, CO are the same......... I guess its possible so maybe we should go with it

[Widewing]

I've never regarded the hybrid push as being substantive in the short term.  After all, when you have 4 million electric cars.... it still takes gas or coal to produce all that electricity, so the footprint is still there.

It makes some "feel" better though.  

Long term, it may reduce effect somewhat, but I wonder if it would be substantive.

What I find interesting about vehicles like the Wrangler and Hummer is that they reduce the carbon footprint by sharing components and engineering. Adding to the low energy consumption is that Wranglers, for example, stay on the road for an average of 18 years or about 300,000 miles. Gas mileage (I get 17/25) isn't unreasonable, but still almost half of what the Prius gets. I found it fascinating the the Nickel used in the Prius' batteries must make four trans-oceanic and four railroad transits before it ends up at Toyota's battery factory. What makes long-term ownership of the car troublesome is the huge bill associated with battery replacement. This is killing resale of high mileage hybrids. No one wants to buy a Prius that will soon require more than $3,000 to replace the batteries. I've read and believe it to be true, that the Prius (and hybrids in general) will find their way into scrap yards far sooner than conventionally powered vehicles. Two major reasons. The rapid evolution of hybrid technology and the major expense of replacing worn components. Dealers don't want to take high mileage hybrids as trade-ins. They recognize that they risk much if they offer any kind of reasonable warranty. Should the batteries go belly up, they know it will cost them big money to replace them.

In comparison, the Wranglers retain 92% of their sticker price value after two years on the road. Even 10 years down the road, they can still command 40% or more of their original value. Few if any other vehicles can match this.

So, if being "green" is a legitimate goal, buying a Wrangler is one option that defies common, albeit incorrect, reasoning. Of course, when I bought mine, I never even considered that it was a true "green" vehicle.


My regards,

Widewing

[MORAY37]

this guy wins the prize............ although moray should share it for actually finding the GISS website

now that you have found the site..... and youre so keen on methodology...... locate the parts where it explains theirs in deriving data........

then please explain to me (since Im obviously not a scientist and have no concept of what Im talking about) how using a 1200Km (approx 750 miles) radius from a SINGLE station as the average temperature for an entire area can possibly be anywhere close to accurate ......... this would imply that the average temperature in Amarillo, TX  and Denver, CO are the same......... I guess its possible so maybe we should go with it

It's not implying that those areas have the same temperature....  It's implying they have similar climate effects upon that temperature. The specific temperature has very little to do with the actual analysis, besides a numerical base.

IE, if it's a cold winter in New York, statistically within one standard deviation,  it's going to be a cold winter in Philadelphia. (about the same area as the study)

If you can show a specific 5 degree by 5 degree area of the planet that does not conform to this, please share it with Mr. Hansen and NASA.  They will be interested, I assure you.

[MORAY37]

What I find interesting about vehicles like the Wrangler and Hummer is that they reduce the carbon footprint by sharing components and engineering. Adding to the low energy consumption is that Wranglers, for example, stay on the road for an average of 18 years or about 300,000 miles. Gas mileage (I get 17/25) isn't unreasonable, but still almost half of what the Prius gets. I found it fascinating the the Nickel used in the Prius' batteries must make four trans-oceanic and four railroad transits before it ends up at Toyota's battery factory. What makes long-term ownership of the car troublesome is the huge bill associated with battery replacement. This is killing resale of high mileage hybrids. No one wants to buy a Prius that will soon require more than $3,000 to replace the batteries. I've read and believe it to be true, that the Prius (and hybrids in general) will find their way into scrap yards far sooner than conventionally powered vehicles. Two major reasons. The rapid evolution of hybrid technology and the major expense of replacing worn components. Dealers don't want to take high mileage hybrids as trade-ins. They recognize that they risk much if they offer any kind of reasonable warranty. Should the batteries go belly up, they know it will cost them big money to replace them.

In comparison, the Wranglers retain 92% of their sticker price value after two years on the road. Even 10 years down the road, they can still command 40% or more of their original value. Few if any other vehicles can match this.

So, if being "green" is a legitimate goal, buying a Wrangler is one option that defies common, albeit incorrect, reasoning. Of course, when I bought mine, I never even considered that it was a true "green" vehicle.


My regards,

Widewing

I miss mine so much.    Gas was killing me a few years ago, and the mileage sucked.... but I loved her.  Sold my 1999 Wranglerat very nice price, though.

Fuel cells would alleviate much of this discussion, but then again, putting a million potential bombs (what a fuel cell is in reality)  on the road, driven by chicks doing makeup and reading proposals while texting and late for work.........<shudder>

I'll take climate change.  I'd think all the explosions from traffic accidents would far outweigh the reduction in CO₂ footprint.

[batch]

so then your conclusion would be that specific temperatures play no part in global warming? if its cold somewhere then it stands to reason that its cold somewhere nearby? this is the answer to decreasing data station useage?

if its cold in St Louis then it must be cold in Kirksville since its only a couple hundred miles away.......... so we will just use the temperature in St Louis (even though its 6 degrees warmer) to represent both places.... after all cold is cold right?

[MORAY37]

so then your conclusion would be that specific temperatures play no part in global warming? if its cold somewhere then it stands to reason that its cold somewhere nearby? this is the answer to decreasing data station useage?

if its cold in St Louis then it must be cold in Kirksville since its only a couple hundred miles away.......... so we will just use the temperature in St Louis (even though its 6 degrees warmer) to represent both places.... after all cold is cold right?

Don't you get it?  They take a set area.  They take a set amount of measurements within that area.  They reason that if there is a trend, that the trend will show within that area, which is not hinged upon the individual temperatures of all the represented stations.  

Over time, if a trend develops and matches, the other stations don't matter.  

It's like taking a frying pan and dividing it up into 100 1 inch squares. (HEAT IT, COOL it, WHATEVER !!!!)  
 In each 1 inch square you take three measurements at different points inside the square ( Points A, B, C).  Even though the different 1 inch squares will have a different overall temp, and will heat differently, you can get the overall amount of heating within each 1 inch square, through each of the  measurements taken within the square.

You can imply, that since A, B, C are all all within X amount of distance, that they are undergoing very similar radiative heating.  Therefore D through infinity stations within that 1 inch square can be inferred to have similar properties.

 Once you do this for all the squares on the frying pan, you can get the overall picture, and don't need to study the heating of each atom of iron within the frying pan, as you are implying needs to be done for climate.

A, B, C stations within all 100 of those squares comprise very little of the actual area of the pan.  But, they do illustrate the heating trend within that pan nicely.

The actual temperature within each means nothing.  THE CHANGE in temperature over time,  DOES.

WEATHER AND CLIMATE, AGAIN

[batch]

so your belief is that a trend sampled 3-6 decades ago is representative enough to derive an accurate SPECIFIC TEMPERATURE for an entire continent in order to average in with other global "trended" temperatures and state 2009 as 'tied for warmest in recorded history'...........

I liked your explanation (it made no sense logically) but it was thought out....... we arent talking about estimates based on trends....... we are talking about specific temperatures in comparison to other specific temperatures............ and those specific temperatures are being cherry picked to give the desired results

you cannot with ANY degree of fact say that 2009 temperatures were any warmer than <insert year here> without comparing temperatures from the same stations ...... this is NOT what they are doing............ they are taking temperatures from specific known warmer stations and comparing them to previous data from a larger set which contained cooler stations and saying the averages are rising

if you want to display changes in 'averages' then you must use the same original dataset in every calculation........

unless you are willing to submit that these "trends" are unchanging? and if you say the "trends" are unchanging then you by proxy must admit that its not possible for temperature variations outside of those trends............ which of course would mean given that we (according to popular concensus) have been in a cooling trend recently and this cannot change therefore global warming cannot exist

[CAP1]

Don't you get it?  They take a set area.  They take a set amount of measurements within that area.  They reason that if there is a trend, that the trend will show within that area, which is not hinged upon the individual temperatures of all the represented stations.  first off.....sorry for butchering into your post this way.....it's just a little easier for me here.
 now.....if i were to diagnose a computer problem on a car using the above methods, i'd spend days just trying to figure out something as simple as a non-functional turnsignal.
 you of all people should realize that in science(just as in electronics diagnosis), one cannot assume anything.

Over time, if a trend develops and matches, the other stations don't matter.  yes, they do, simply due to the fact that they may show that what is assumed to be a trend is not one after all.

It's like taking a frying pan and dividing it up into 100 1 inch squares. (HEAT IT, COOL it, WHATEVER !!!!)  
 In each 1 inch square you take three measurements at different points inside the square ( Points A, B, C).  Even though the different 1 inch squares will have a different overall temp, and will heat differently, you can get the overall amount of heating within each 1 inch square, through each of the  measurements taken within the square.again, you know as well as the rest of us that it isn't that simple. add in air currents, wind, changing barometric pressure, etc, and that will all change.

You can imply, that since A, B, C are all all within X amount of distance, that they are undergoing very similar radiative heating.  Therefore D through infinity stations within that 1 inch square can be inferred to have similar properties.

 Once you do this for all the squares on the frying pan, you can get the overall picture, and don't need to study the heating of each atom of iron within the frying pan, as you are implying needs to be done for climate.

A, B, C stations within all 100 of those squares comprise very little of the actual area of the pan.  But, they do illustrate the heating trend within that pan nicely.

The actual temperature within each means nothing.  THE CHANGE in temperature over time,  DOES.this almost seems like a contradiction? as the temperature is necessary to show any change. but to see it accuratly, there needs to be unfiltered untouched data, from all sources. the only reason i keep saying this, is because batch is correct. in the example he chose, they could pick their stations, to make things appear as they wish, whereas those against global warming could pick stations within that very same region, and make things appear as they wish.
 try it like this.
you and i both go to the cherry hill mall. we both are going to do a survey. one question. that one question can be simple. "is it cold outside right now?"(bearing in mind it's about 29F at the moment). we each get to ask 100 people this question. where i think it's cold(to me anything below 55F is cold), you think it's comfortable.
 i can pretty much guarantee you that when we sit down in the bar to see each others results, i will have proven that the majority of people surveyed think it is cold outside, while you have proven just the opposite.
 how? we each "cherry picked" the people we asked, and we did this in such a way as to skew our results.
 therefore, the only way to find the true answer, is to ask everyone.
 
 

WEATHER AND CLIMATE, AGAIN

 now, the weather/climate thing.

 saying that the weather is not the climate, is like me telling you that the tires on your car are not a part of it. saying the weather doesn't effect the climate is like saying that flattening those tires will not effect your car.

 i truly do respect you, and your opinions, and truly appreciate that you put so darn much info in your posts........
 one final thing.... calling us "denialists" i think is somewhat bad. 

[Anaxogoras]

they are taking temperatures from specific known warmer stations and comparing them to previous data from a larger set which contained cooler stations and saying the averages are rising

What's your evidence for this claim?  It's rather provocative.  You're not merely accusing them of incompetence, so I think you owe us more than the bald claim by itself.

[Vulcan]

Also, yes they could, but the resulting data would need to be cleaned and fine toothed relentlessly, while not lowering the inherent error probability.  

  Also, you add in the possibility of multiple corruption of the data due to inaccuracy at each individual station, as they are all not uniform.  By using a base area and then randomly using a number of station geographically in that area, you control the amount of error and bias within that data set, as long as that initial postulate (an area X degrees by Y degrees will show trendline) isn't disproved.

moray, sorry but where did you learn data analysis? Because you put on some wierd arguments.

Stats 101: the more data you sample the less influence errors have.