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The Top Weather/Climate Events of 2015 (wunderground.com)
Layzej writes: With only a few stations left to report, 2015 is virtually certain to beat 2014's record as the planet's warmest year since record keeping began in 1880. The new record was caused by the long-term warming of the planet due to human-caused emissions of heat-trapping gases like carbon dioxide, combined with a extra bump in temperature due to the strongest El Niño event ever recorded in the Eastern Pacific. Record warm ocean temperatures in the tropics in 2015 led to a global coral bleaching event, which is expected to cause a loss of 10 — 20% of all coral worldwide. Weather Underground recounts several other records that accompanied the heat including the most intense hurricane ever observed in the Western Hemisphere, the ongoing agricultural fires in Indonesia — the most expensive disaster in Indonesia's history estimated at $16 billion in damages, flooding in America and India, and record central pacific hurricane activity.
The average of the instrumental record ... just like last year, and the year before that. The thing that you're missing is that it's reasonable to do this to account for the fact that you've added additional stations to the dataset, which would alter the raw average.
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Satellite data put it at least in the top 3 years. Oh, and there's no "hiatus" any more.
So you take the most powerful hurricane ever to be evidence AGAINST a prediction of super hurricanes?
Every time there's anything about climate change, there are tons and tons more AC posts than usual, and of course, a large majority of them are making fun of the idea that humankind can change our climate. I wonder if it's just a few nutters, or a team of people paid by the oil industry to do this...
I don't respond to AC's.
also note that what he states is This makes 2015 the third warmest year globally (+0.27 deg C) in the satellite record (since 1979).
this is not at all contradictory or mutually exclusive. the flaws or inadequacies of the satellite data are well known, and its completely possible to be only 3rd warmest in one flawed data set, and warmest in another more complete dataset.
But congratulations on mastering how to lie with statistics 101 and moving onto 102 methods.
That's progress, albeit not the kind honest people like to see.
The guy who said the election was rigged won the presidency with the second-most votes.
Stations sample at a point. Adding more stations is adding more sample points. The distribution of the locations of the stations is no longer the same and that skews the sample, i.e. it's representation of the entire planet is different so you have to change the weightings so you aren't giving more weight to areas that have a different station density.
Very often, people confuse simple with simplistic. The nuance is lost on most. - Clement Mok
I'm kinda sick of fuck-sticks who accept all (so called) science as fact w/o question then brow beat those who may be a little more cautious
No shit! Can you imagine how bad the world be if every single uneducated prick wasn't seen as being as capable of understanding incredibly complex issues on equal footing as those who have studied these issues for decades? I mean, let's face it, your opinion should be every bit as valid as these experts because we all know your gut feeling is without question far more valuable than mountains of accumulated data.
By the way, should you be stricken with cancer, you might shun those very same scientists and make up your own cure based on your beliefs. I'm sure the rest of us here would broadly support your efforts.
Here's the data.
If you look through the data you'll see these are the ten coldest years after 1849, coolest first:
1911, 1909, 1904, 1908, 1862, 1910, 1903, 1864, 1917, 1893.
These are the ten hottest years prior to 2015, hottest first:
2014, **2010, *2005, ***/++1998, **2003, *2006, **2009, **2002, *2007, 2013.
I've also noted El Niño years with stars and La Niña with plusses:
* = weak El Niño year
** = moderate El Niño year
***/++ = 1998 started as a very strong El Niño and ended as a moderate La Niña.
2015 is an El Niño year (which tend to be hot), but is not in this dataset yet. Note that 8/10 of the top 10 years have an El Niño component, except 2013 and 2014, which were "ordinary" but very warm years.
I didn't note the ENSO (El Niño / Southern oscillation) status for the coldest years, because all ten of the coldest years are before 1912 and there is no reliable ENSO data for before 1950 so far as I know. However it's a safe bet that many of these were La Niñas, which tend to be colder than average. The last colder-than-average year was 1985, which was a La Niña; all six La Niña years since have been warmer than the 1850-2014 average. The last "ordinary" (non-ENSO) year that was colder than average was 1970.
Here is the average temperature anomaly by decade: // partial, obviously
Decade Anomaly
1850 -0.3174
1860 -0.3296
1870 -0.2548
1880 -0.3
1890 -0.3623
1900 -0.4099
1918 -0.2494
1930 -0.1182
1940 -0.0036
1950 -0.061
1960 -0.0535
1970 -0.0769
1980 +0.0943
1990 +0.274
2000 +0.4622
2010 +0.4998
Note that all the decades up to the 70s are colder than the "average" year because "average" is dominated by the acceleration of warming from the 90s to present.
I hope this helps.
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You could, but you'd get a less precise tracking of changes in recent years.
You basically have three choices here:
(1) Limit yourself to in instruments and stations in use in 1850.
(2) Add new stations and technologies but ignore their effect on the average.
(3) Add new stations and technologies then use statistical techniques to find the approximation that best fits the datapoints you have.
Simply limiting yourself to the instruments you had in place in 1850 is bound to *overestimate* the amount of warming. That's because the land-based instruments are likely to be overwhelmed by waste heat generated by urban sprawl. Instruments that were in quiet rural suburbs are now in the center of cities with hard, heat-catching surfaces like asphalt and concrete, surrounded by buildings heated with what by 1850 standards are vast amounts of energy. So even if you tried approach 1 you'd still have to adjust the figures (in this case discounting some of the spurious "warming" you're seeing) to get a reasonable estimate of change.
The instrumental "global average temperature" is an artificial construct in any case. We know there must *be* a global average temperature, but we can't measure it directly, short of measuring the temperature continuously over very point on the surface of the Earth. All we have are discrete measurements taken from a finite number of stations. You need some kind of model for how representative you think those measurements you do have are of the whole.
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Here is the "adjustment" you're referring to:
http://cdn.arstechnica.net/wp-...
The recent correction is the difference between the black line and the red line. The temperature rise between 1959 and 2014 is about 0.9C. The adjustment, in the last two years, is just barely large enough to see, about 0.05C. Over the full period analyzed, the new global analysis changed the observed rate of warming from 0.065C/decade to 0.068C/decade, less than the noise.
Really, I need to point out that analyzing data sets is what science does. But, if you actually look at the data, even if you throw out the new corrections entirely, it doesn't make a difference. The corrections didn't change whether warming exists or not.
That image is from this article: http://arstechnica.com/science...
For reference, here is the paper with the adjustments explained: http://www.sciencemag.org/cont...
(Karl, et al., "Possible artifacts of data biases in the recent global surface warming hiatus," Science Vol. 348 no. 6242, 26 June 2015: pp. 1469-1472
DOI: 10.1126/science.aaa5632)
http://www.geoffreylandis.com