Occasional Thoughts on Climate Change

[bluewave]

On 4/20/2023 at 7:06 AM, chubbs said:

Note also that many coop stations had big temperature drops from the 1940s to the 1960s or 1970s as stations were modernized. One source of error before modernization is the coop use of mercury  max/min thermometers which were subject to time of day bias. Stations with hourly reporting avoided this error. Fortunately there are many local stations and the coop stations were modernized at different times, so station updates are easily identified and corrected by comparing nearby stations using bias adjustment software.

 

Why Adjust Temperatures?

There are a number of folks who question the need for adjustments at all. Why not just use raw temperatures, they ask, since those are pure and unadulterated? The problem is that (with the exception of the newly created Climate Reference Network), there is really no such thing as a pure and unadulterated temperature record. Temperature stations in the U.S. are mainly operated by volunteer observers (the Cooperative Observer Network, or co-op stations for short). Many of these stations were set up in the late 1800s and early 1900s as part of a national network of weather stations, focused on measuring day-to-day changes in the weather rather than decadal-scale changes in the climate.

Nearly every single station in the network in the network has been moved at least once over the last century, with many having 3 or more distinct moves. Most of the stations have changed from using liquid in glass thermometers (LiG) in Stevenson screens to electronic Minimum Maximum Temperature Systems (MMTS) or Automated Surface Observing Systems (ASOS). Observation times have shifted from afternoon to morning at most stations since 1960, as part of an effort by the National Weather Service to improve precipitation measurements.

All of these changes introduce (non-random) systemic biases into the network. For example, MMTS sensors tend to read maximum daily temperatures about 0.5 C colder than LiG thermometers at the same location. There is a very obvious cooling bias in the record associated with the conversion of most co-op stations from LiG to MMTS in the 1980s, and even folks deeply skeptical of the temperature network like Anthony Watts and his coauthors add an explicit correction for this in their paper.

Time of observation changes from afternoon to morning also can add a cooling bias of up to 0.5 C, affecting maximum and minimum temperatures similarly. The reasons why this occurs, how it is tested, and how we know that documented time of observations are correct (or not) will be discussed in detail in the subsequent post. There are also significant positive minimum temperature biases from urban heat islands that add a trend bias up to 0.2 C nationwide to raw readings.

Because the biases are large and systemic, ignoring them is not a viable option. If some corrections to the data are necessary, there is a need for systems to make these corrections in a way that does not introduce more bias than they remove.

What are the Adjustments?

Two independent groups, the National Climate Data Center (NCDC) and Berkeley Earth (hereafter Berkeley) start with raw data and use differing methods to create a best estimate of global (and U.S.) temperatures. Other groups like NASA Goddard Institute for Space Studies (GISS) and the Climate Research Unit at the University of East Anglia (CRU) take data from NCDC and other sources and perform additional adjustments, like GISS’s nightlight-based urban heat island corrections.

Time of Observation (TOBs) Adjustments

Temperature data is adjusted based on its reported time of observation. Each observer is supposed to report the time at which observations were taken. While some variance of this is expected, as observers won’t reset the instrument at the same time every day, these departures should be mostly random and won’t necessarily introduce systemic bias. The major sources of bias are introduced by system-wide decisions to change observing times, as shown in Figure 3. The gradual network-wide switch from afternoon to morning observation times after 1950 has introduced a CONUS-wide cooling bias of about 0.2 to 0.25 C. The TOBs adjustments are outlined and tested in Karl et al 1986 and Vose et al 2003, and will be explored in more detail in the subsequent post. The impact of TOBs adjustments is shown in Figure 6, below.

Pairwise Homogenization Algorithm (PHA) Adjustments

The Pairwise Homogenization Algorithm was designed as an automated method of detecting and correcting localized temperature biases due to station moves, instrument changes, microsite changes, and meso-scale changes like urban heat islands.

The algorithm (whose code can be downloaded here) is conceptually simple: it assumes that climate change forced by external factors tends to happen regionally rather than locally. If one station is warming rapidly over a period of a decade a few kilometers from a number of stations that are cooling over the same period, the warming station is likely responding to localized effects (instrument changes, station moves, microsite changes, etc.) rather than a real climate signal.

To detect localized biases, the PHA iteratively goes through all the stations in the network and compares each of them to their surrounding neighbors. It calculates difference series between each station and their neighbors (separately for min and max) and looks for breakpoints that show up in the record of one station but none of the surrounding stations. These breakpoints can take the form of both abrupt step-changes and gradual trend-inhomogenities that move a station’s record further away from its neighbors. The figures below show histograms of all the detected breakpoints (and their magnitudes) for both minimum and maximum temperatures.
 

While fairly symmetric in aggregate, there are distinct temporal patterns in the PHA adjustments. The single largest of these are positive adjustments in maximum temperatures to account for transitions from LiG instruments to MMTS and ASOS instruments in the 1980s, 1990s, and 2000s. Other notable PHA-detected adjustments are minimum (and more modest maximum) temperature shifts associated with a widespread move of stations from inner city rooftops to newly-constructed airports or wastewater treatment plants after 1940, as well as gradual corrections of urbanizing sites like Reno, Nevada. The net effect of PHA adjustments is shown in Figure 8, below.

 

The PHA has a large impact on max temperatures post-1980, corresponding to the period of transition to MMTS and ASOS instruments. Max adjustments are fairly modest pre-1980s, and are presumably responding mostly to the effects of station moves. Minimum temperature adjustments are more mixed, with no real century-scale trend impact. These minimum temperature adjustments do seem to remove much of the urban-correlated warming bias in minimum temperatures, even if only rural stations are used in the homogenization process to avoid any incidental aliasing in of urban warming, as discussed in Hausfather et al. 2013.

The PHA can also effectively detect and deal with breakpoints associated with Time of Observation changes. When NCDC’s PHA is run without doing the explicit TOBs adjustment described previously, the results are largely the same (see the discussion of this in Williams et al 2012). Berkeley uses a somewhat analogous relative difference approach to homogenization that also picks up and removes TOBs biases without the need for an explicit adjustment.

With any automated homogenization approach, it is critically important that the algorithm be tested with synthetic data with various types of biases introduced (step changes, trend inhomogenities, sawtooth patterns, etc.), to ensure that the algorithm will identically deal with biases in both directions and not create any new systemic biases when correcting inhomogenities in the record. This was done initially in Williams et al 2012 and Venema et al 2012. There are ongoing efforts to create a standardized set of tests that various groups around the world can submit homogenization algorithms to be evaluated by, as discussed in our recently submitted paper. This process, and other detailed discussion of automated homogenization, will be discussed in more detail in part three of this series of posts.

 

 

 

 

[TheClimateChanger]

I know some people will look at the Smithsonian Institution numbers I've shared from the 19th century, and say "but those are averages of 7 am, 2 pm, and 9 pm" readings and not averages of maximum and minimum temperatures, and my response would be that's there's little difference between the two. First, the times are on local solar time - which for most of Pennsylvania is similar to local standard time. So 7 am and 2 pm are roughly high and low, and 9 pm is roughly in the middle of the two.

For the sake of comparison, let's look at the Pittsburgh readings for 2011.

January was 24.2F. From the LCD, the 7 am (standard) mean was 21, the 2 pm (standard) mean was 28, and the 9 pm (standard) mean was 25F. The Smithsonian mean would be reported as 24.7F, or 0.5F warmer than the true mean.

February was 31.8F. From the LCD, the 7 am (standard) mean was 29F, the 2 pm (standard) mean was 36F, and the 9 pm (standard) mean was 32F. The Smithsonian mean would be reported as 32.3F, or 0.5F warmer than the true mean.

March was 39.2F. From the LCD, the 7 am (standard) mean was 33F, the 2 pm (standard) mean was 45F, and the 9 pm (standard) mean was 39F. The Smithsonian mean would be reported as 39.0F, or 0.2F cooler than the true mean.

April was 53.3F. From the LCD, the 7 am (standard) mean was 48F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 53F. The Smithsonian mean would be reported as 53.3F, or exactly the same as the true mean.

May was 62.9F. From the LCD, the 7 am (standard) mean was 57F, the 2 pm (standard) mean was 70F, and the 9 pm (standard) mean was 63F. The Smithsonian mean would be reported as 63.3F, or 0.4F warmer than the true mean.

June was 70.0F. From the LCD, the 7 am (standard) mean was 65F, the 2 pm (standard) mean was 78F, and the 9 pm (standard) mean was 71F. The Smithsonian mean would be reported as 71.3F, or 1.3F warmer than the true mean.

July was 76.9F. From the LCD, the 7 am (standard) mean was 70F, the 2 pm (standard) mean was 85F, and the 9 pm (standard) mean was 77F. The Smithsonian mean would be reported as 77.3F, or 0.4F warmer than the true mean.

August was 72.8F. From the LCD, the 7 am (standard) mean was 66F, the 2 pm (standard) mean was 81F, and the 9 pm (standard) mean was 72F. The Smithsonian mean would be reported as 73.0F, or 0.2F warmer than the true mean.

September was 65.4F. From the LCD, the 7 am (standard) mean was 60F, the 2 pm (standard) mean was 71F, and the 9 pm (standard) mean was 64F. The Smithsonian mean would be reported as 65.0F, or 0.4F cooler than the true mean.

October was 52.8F. From the LCD, the 7 am (standard) mean was 47F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 52F. The Smithsonian mean would be reported as 52.7F, or 0.1F cooler than the true mean.

November was 46.9F. From the LCD, the 7 am (standard) mean was 42F, the 2 pm (standard) mean was 53F, and the 9 pm (standard) mean was 47F. The Smithsonian mean would be reported as 47.3F, or 0.4F warmer than the true mean.

December was 37.5F. From the LCD, the 7 am (standard) mean was 34F, the 2 pm (standard) mean was 42F, and the 9 pm (standard) mean was 38F. The Smithsonian mean would be reported as 38.0F, or 0.5F warmer than the true mean.

[TheClimateChanger]

Just now, TheClimateChanger said:

I know some people will look at the Smithsonian Institution numbers I've shared from the 19th century, and say "but those are averages of 7 am, 2 pm, and 9 pm" readings and not averages of maximum and minimum temperatures, and my response would be that's there's little difference between the two. First, the times are on local solar time - which for most of Pennsylvania is similar to local standard time. So 7 am and 2 pm are roughly high and low, and 9 pm is roughly in the middle of the two.

For the sake of comparison, let's look at the Pittsburgh readings for 2011.

January was 24.2F. From the LCD, the 7 am (standard) mean was 21, the 2 pm (standard) mean was 28, and the 9 pm (standard) mean was 25F. The Smithsonian mean would be reported as 24.7F, or 0.5F warmer than the true mean.

February was 31.8F. From the LCD, the 7 am (standard) mean was 29F, the 2 pm (standard) mean was 36F, and the 9 pm (standard) mean was 32F. The Smithsonian mean would be reported as 32.3F, or 0.5F warmer than the true mean.

March was 39.2F. From the LCD, the 7 am (standard) mean was 33F, the 2 pm (standard) mean was 45F, and the 9 pm (standard) mean was 39F. The Smithsonian mean would be reported as 39.0F, or 0.2F cooler than the true mean.

April was 53.3F. From the LCD, the 7 am (standard) mean was 48F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 53F. The Smithsonian mean would be reported as 53.3F, or exactly the same as the true mean.

May was 62.9F. From the LCD, the 7 am (standard) mean was 57F, the 2 pm (standard) mean was 70F, and the 9 pm (standard) mean was 63F. The Smithsonian mean would be reported as 63.3F, or 0.4F warmer than the true mean.

June was 70.0F. From the LCD, the 7 am (standard) mean was 65F, the 2 pm (standard) mean was 78F, and the 9 pm (standard) mean was 71F. The Smithsonian mean would be reported as 71.3F, or 1.3F warmer than the true mean.

July was 76.9F. From the LCD, the 7 am (standard) mean was 70F, the 2 pm (standard) mean was 85F, and the 9 pm (standard) mean was 77F. The Smithsonian mean would be reported as 77.3F, or 0.4F warmer than the true mean.

August was 72.8F. From the LCD, the 7 am (standard) mean was 66F, the 2 pm (standard) mean was 81F, and the 9 pm (standard) mean was 72F. The Smithsonian mean would be reported as 73.0F, or 0.2F warmer than the true mean.

September was 65.4F. From the LCD, the 7 am (standard) mean was 60F, the 2 pm (standard) mean was 71F, and the 9 pm (standard) mean was 64F. The Smithsonian mean would be reported as 65.0F, or 0.4F cooler than the true mean.

October was 52.8F. From the LCD, the 7 am (standard) mean was 47F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 52F. The Smithsonian mean would be reported as 52.7F, or 0.1F cooler than the true mean.

November was 46.9F. From the LCD, the 7 am (standard) mean was 42F, the 2 pm (standard) mean was 53F, and the 9 pm (standard) mean was 47F. The Smithsonian mean would be reported as 47.3F, or 0.4F warmer than the true mean.

December was 37.5F. From the LCD, the 7 am (standard) mean was 34F, the 2 pm (standard) mean was 42F, and the 9 pm (standard) mean was 38F. The Smithsonian mean would be reported as 38.0F, or 0.5F warmer than the true mean.

Obviously, to get a better comparison of the Smithsonian Institution means compared to the true means, you would need to look at a longer time frame and more locations. But, in general, the differences are surprisingly small. Remember these Smithsonian people were smart - they may not have had modern technology, but they were resourceful and able to make do with what they had. Generally, there appears to be a slight warm bias in the Smithsonian means - this is particularly the case in the early summer, when the 7 am reading [8 am EDT] would be too late to capture the true minimum temperature. In general, there is already a couple degree rise by that point. This effect is, of course, negligible in the cold season when 7 am EST is around sunrise.

It is worth noting that, a few of these old records, are said to have taken the first reading at sunrise. In those cases, the above effect would not be true and there may even be a slight cool bias in those records. However, the effect again would be very small. The main point is you can look at these old records obtained from three measurements and directly compare them to modern true means without the need for any adjustment since the error is not in one direction, small in degree, and generally a small warm bias. With the small warm bias, the old records are actually underestimating the amount of warming that has occurred.

[TheClimateChanger]

13 minutes ago, TheClimateChanger said:

I know some people will look at the Smithsonian Institution numbers I've shared from the 19th century, and say "but those are averages of 7 am, 2 pm, and 9 pm" readings and not averages of maximum and minimum temperatures, and my response would be that's there's little difference between the two. First, the times are on local solar time - which for most of Pennsylvania is similar to local standard time. So 7 am and 2 pm are roughly high and low, and 9 pm is roughly in the middle of the two.

For the sake of comparison, let's look at the Pittsburgh readings for 2011.

January was 24.2F. From the LCD, the 7 am (standard) mean was 21, the 2 pm (standard) mean was 28, and the 9 pm (standard) mean was 25F. The Smithsonian mean would be reported as 24.7F, or 0.5F warmer than the true mean.

February was 31.8F. From the LCD, the 7 am (standard) mean was 29F, the 2 pm (standard) mean was 36F, and the 9 pm (standard) mean was 32F. The Smithsonian mean would be reported as 32.3F, or 0.5F warmer than the true mean.

March was 39.2F. From the LCD, the 7 am (standard) mean was 33F, the 2 pm (standard) mean was 45F, and the 9 pm (standard) mean was 39F. The Smithsonian mean would be reported as 39.0F, or 0.2F cooler than the true mean.

April was 53.3F. From the LCD, the 7 am (standard) mean was 48F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 53F. The Smithsonian mean would be reported as 53.3F, or exactly the same as the true mean.

May was 62.9F. From the LCD, the 7 am (standard) mean was 57F, the 2 pm (standard) mean was 70F, and the 9 pm (standard) mean was 63F. The Smithsonian mean would be reported as 63.3F, or 0.4F warmer than the true mean.

June was 70.0F. From the LCD, the 7 am (standard) mean was 65F, the 2 pm (standard) mean was 78F, and the 9 pm (standard) mean was 71F. The Smithsonian mean would be reported as 71.3F, or 1.3F warmer than the true mean.

July was 76.9F. From the LCD, the 7 am (standard) mean was 70F, the 2 pm (standard) mean was 85F, and the 9 pm (standard) mean was 77F. The Smithsonian mean would be reported as 77.3F, or 0.4F warmer than the true mean.

August was 72.8F. From the LCD, the 7 am (standard) mean was 66F, the 2 pm (standard) mean was 81F, and the 9 pm (standard) mean was 72F. The Smithsonian mean would be reported as 73.0F, or 0.2F warmer than the true mean.

September was 65.4F. From the LCD, the 7 am (standard) mean was 60F, the 2 pm (standard) mean was 71F, and the 9 pm (standard) mean was 64F. The Smithsonian mean would be reported as 65.0F, or 0.4F cooler than the true mean.

October was 52.8F. From the LCD, the 7 am (standard) mean was 47F, the 2 pm (standard) mean was 59F, and the 9 pm (standard) mean was 52F. The Smithsonian mean would be reported as 52.7F, or 0.1F cooler than the true mean.

November was 46.9F. From the LCD, the 7 am (standard) mean was 42F, the 2 pm (standard) mean was 53F, and the 9 pm (standard) mean was 47F. The Smithsonian mean would be reported as 47.3F, or 0.4F warmer than the true mean.

December was 37.5F. From the LCD, the 7 am (standard) mean was 34F, the 2 pm (standard) mean was 42F, and the 9 pm (standard) mean was 38F. The Smithsonian mean would be reported as 38.0F, or 0.5F warmer than the true mean.

Just for the record, for the year of 2011, the Smithsonian mean for PIT would have been 53.1F, or just 0.3F warmer than the true mean. Like I said, this was an incredible approximation in the absence of a max/min thermometer.

[TheClimateChanger]

On 4/24/2023 at 11:51 PM, TheClimateChanger said:

People have no idea how cold it really used to be. I mean can you imagine any low elevation site in the State of Pennsylvania having a year with an annual mean of 40.0F nowadays?

Compare that to today:

Or even look at the Signal Service records for Pittsburgh. This doesn't look that much cooler than today - but these were taken 500 feet lower than the modern airport records. That's enough of an elevation change to easily account for 2 degrees or more. Even still, there are some doozies mixed in there. 46.9F in 1827, 47.8F in 1856. The modern record cold year (again 500' higher in elevation) is 48.0F in 1976. If there were records at the airport location, it could have been 45 or 46 degrees in those years.

I just don't know how anyone can doubt climate change. Look at the period from October 1836 to April 1837 in the Allegheny Arsenal [Lawrenceville, Pittsburgh] records. And the means of 48.2F and 46.9F aren't far from the coldest in the modern record [48.0F, in 1976]. But these are from a site 500' lower in elevation than the PIT Airport. But look at what a cooler climate, plus a major volcanic eruption in Nicaragua, was capable of doing. I feel like people don't realize how cold it used to be, and how in the natural climate state, we would probably be just several big volcanic eruptions in rapid succession from a new glacial advance.

October 1836: 38.2F [The coldest in the modern record is 45.9F, or 7.7F warmer than this reading!]

November 1836: 30.8F [The coldest in the modern record is 33.1F, or 2.3F warmer than this reading!]

December 1836: 22.4F [Would tie 1963 for 2nd coldest in the modern record]

January 1837: 16.8F [Would be the 2nd coldest in the modern record]

February 1837: 25.6F [Would tie 20th coldest in the modern record]

March 1837: 27.7F [Would be 2nd coldest in the modern record -- current 2nd place at 31.0F]

April 1837: 31.3F [The coldest in the modern record is 43.8F, or 12.5F warmer than this reading!]

Can anyone alive today even imagine an April with a subfreezing mean temperature at the latitude of Pittsburgh today? Unfathomable.

[TheClimateChanger]

It's fascinating to me how close that Smithsonian technique gets to approximating the true mean. I noticed in later years, they doubleweighted the 9 PM reading. So the formula became [7 + 2 + 9 + 9] / 4, where 7, 2 & 9 are the hours of the temperature reading, and that seems to eliminate most of the slight excess.

I looked at Buffalo from 2016, and here's the comparison. True mean is 51.1F, average of 7 AM, 2 PM, 9 PM readings is 51.5F, average of 7 AM, 2 PM, and 9 PM with a doubleweighting of the 9 PM reading is 51.2F.

Maximum	Minimum	Mean		7 AM EST	2 PM EST	9 PM EST	AVERAGE	SPEC. AVG
33.9	19.9	26.9		25	31	27	27.7	27.5
37.7	21.7	29.7		27	34	29	30.0	29.8
48.8	31.0	39.9		35	45	39	39.7	39.5
52.3	33.9	43.1		39	49	43	43.7	43.5
68.8	49.0	58.9		54	66	57	59.0	58.5
77.8	57.4	67.6		64	75	67	68.7	68.3
82.8	65.4	74.1		70	81	73	74.7	74.3
84.6	66.5	75.6		70	83	75	76.0	75.8
76.3	57.6	67.0		61	74	65	66.7	66.3
62.6	46.2	54.4		50	60	53	54.3	54.0
53.1	37.0	45.1		41	51	45	45.7	45.5
36.2	26.1	31.2		30	33	32	31.7	31.8
		51.1					51.5	51.2

[ChescoWx]

20 hours ago, TheClimateChanger said:

I just don't know how anyone can doubt climate change. Look at the period from October 1836 to April 1837 in the Allegheny Arsenal [Lawrenceville, Pittsburgh] records. And the means of 48.2F and 46.9F aren't far from the coldest in the modern record [48.0F, in 1976]. But these are from a site 500' lower in elevation than the PIT Airport. But look at what a cooler climate, plus a major volcanic eruption in Nicaragua, was capable of doing. I feel like people don't realize how cold it used to be, and how in the natural climate state, we would probably be just several big volcanic eruptions in rapid succession from a new glacial advance.

October 1836: 38.2F [The coldest in the modern record is 45.9F, or 7.7F warmer than this reading!]

November 1836: 30.8F [The coldest in the modern record is 33.1F, or 2.3F warmer than this reading!]

December 1836: 22.4F [Would tie 1963 for 2nd coldest in the modern record]

January 1837: 16.8F [Would be the 2nd coldest in the modern record]

February 1837: 25.6F [Would tie 20th coldest in the modern record]

March 1837: 27.7F [Would be 2nd coldest in the modern record -- current 2nd place at 31.0F]

April 1837: 31.3F [The coldest in the modern record is 43.8F, or 12.5F warmer than this reading!]

Can anyone alive today even imagine an April with a subfreezing mean temperature at the latitude of Pittsburgh today? Unfathomable.

100% agreed!!  I don't know how anyone can deny climate change....climate has always and will always be changing (cyclical climate change is real). Now if you believe it will never swing back to a cooler period of time at some point in the future - that we do not know.

[Typhoon Tip]

I realize we have a 'sea ice -related' thread, but this isn't related to sea ice.  It has to do with oceanic temperatures, in general...

A fascinating user interface graphic: https://climatereanalyzer.org/clim/sst_daily/

I'm sure for y'all that pick and probe through the web and research matters this is already known?  either way. 

It's referenced in an article over at Phys.org, that also conveys some weirdness that seems prequel to alarm and criticality - but we'll see on the latter.

https://phys.org/news/2023-04-earth-hot-sudden-ocean-spike.html

[TheClimateChanger]

 

[lee59]

On 4/25/2023 at 10:16 AM, TheClimateChanger said:

I'm still not finding a urban heat island effect. Like this data for Grampian in Clearfield County, has a mean of 45.7F, with individual years ranging from 42.7F [1875] to 48.6F [1878]. If I compare this to the modern records for nearby DuBois, we find a mean of 47.8F. Again, 2.1F doesn't sound like a ton. But it's massive in this context. 45.7F is the third coldest annual mean in the DUJ records dating back to 1963. And DUJ is 400' higher in elevation than this site, and somewhat further north. There are 10 years in this data set that are colder than anything observed at DUJ since 1963. We would need a high-end VEI 8 just to have a chance to experience what is a natural climate in this state for a few years.

I believe there are examples of the UHI all the time. The next time there is a quiet clear night, check the temperature difference between the rural area and the nearest urban city. Having said that both are probably rising at similar rates over the years because our climate in the northeast, at least as far as I am concerned, has gotten milder and wetter.

 

 

[chubbs]

Satellite daily global SST anomaly through April 28. The current SST spike is roughly as large as previous anomaly spikes for an entire nino.  Looks unprecedented in terms of size and short duration.

[bluewave]

 

[chubbs]

 

[bdgwx]

It looks like the global SST excursion peaked at 4.7σ on April 23rd.

 

[Typhoon Tip]

"...To warm the entire planet takes an extraordinary amount of extra energy. Recent research shows we've added the energy of 25 billion nuclear bombs to the Earth system in just the last 50 years ...

  ... But almost all of this energy to date has been taken up by the oceans. It's no wonder we're seeing rapid warming in our oceans..."

Just a few turn of phrase in an interesting perspective summary written here,

https://phys.org/news/2023-05-trillion-tons-greenhouse-gases-billion.html

[chubbs]

 

[Typhoon Tip]

On 5/4/2023 at 6:29 AM, chubbs said:

 

It seems like this is happening to0 close to the objectively observed/realized loss of the -ONI during this mid spring ... which was teetering on ending since mid or late January really, but suddenly accelerated to neutral rather recently... And it wasn't merely the SSTs associated with the ONI .. but the total evaluation considers the thermocline and other llv wind etc etc.  

It's hard the relay between the -ONI to this weird spike has been silently extraordinary.  It almost as a 'rebound' phenomenon

[chubbs]

A less sarcastic take.

 

[Typhoon Tip]

1 hour ago, chubbs said:

A less sarcastic take.

 

That's the aspect and what I'm also waiting out on this ...

     is there some how some way that an instrumentation idiosyncratic error happened. 

I also am wondering if the rather abrupt lost of the -ONI ( La Nina base state) that took place back in Feb into March may have equally abruptly "de-masked" - think 'snap back' where say, 3 years of GW relative suppression in the La Nina sea was suddenly removed, and we gain those three years back all at once

The problem is... it is weird to move the entire planetary oceanic surface mass by 2/10s of a degree C like that... We're talking about many ordera of magnitude in hydrogen bomb ( units, if there is such a thing) energy to do that... and doing so - most importantly - in 30 days.  That's not merely seasonal change doing that.  

a   this is all an instrumentation/systemic calibration glitch...

b   something seriously f'ed just happened at an unprecedented truly historic, and possibly scary implication scale for a plethora of reasons, too vast and too complex to calculate very quickly enough ... due to secondary and tertiary derivatives --> emergent properties via complex interactions in time... All of which is too vast to categorize before any will-be consequences are observed.  

Human kind has always been vastly more proficient at reconstructing disasters and ferreting out the causalities, after the fact ... than they are at predicting the future nearly as adroitly.  If they were ...we wouldn't be in this mess 

[ChescoWx]

The first 4 months of the year have been the warmest on record for Chester County since 1894. During our current cyclical warmer climate phase we have seen 8 of the top 10 warmest starts to the year since just 1990!  However it is important to note that 13 of the Top 25 warmest first 4 months occurred prior to 1960 (see below).

However, for those of us that believe in normal cyclical climate change... some cooler periods are likely in our not too distant future. With the start of the modern grand solar minimum (when solar magnetic field and its magnetic activity will be reduced by 70%) which began in 2020 and will last through about 2053 we should expect to see our temperatures begin to chill as part of the next normal cooling cycle by up to 1.8°F.  This cooling is expected to be most notable during the periods of solar minima between the cycles 25–26 and 26–27 which means we should see some clear cooling starting later this decade and peaking during the 2030's into the 2040's before our next warming cycle looks to begin later in the 2050's.

[chubbs]

The sun has switched from a slight cooling to a slight warming factor in cycle 25.

[bdgwx]

According to Berkeley Earth...

In Feb 2016 the monthly anomaly was 1.32 C. This is highest in their period of record.

In Mar 2023 the monthly anomaly was 1.24 C. 

Using a typical 4 month lag for the ENSO response the 2016/02 value matches up with an ONI of 2.4 and the 2023/03 value matches up with -0.9.

We were only 0.09 C shy of eclipsing the old record, which occurred during a super El Nino, while in the midst of a triple dip La Nina. Yikes!

[Typhoon Tip]

18 hours ago, bdgwx said:

According to Berkeley Earth...

In Feb 2016 the monthly anomaly was 1.32 C. This is highest in their period of record.

In Mar 2023 the monthly anomaly was 1.24 C. 

Using a typical 4 month lag for the ENSO response the 2016/02 value matches up with an ONI of 2.4 and the 2023/03 value matches up with -0.9.

We were only 0.09 C shy of eclipsing the old record, which occurred during a super El Nino, while in the midst of a triple dip La Nina. Yikes!

There are early 'winds' of El Nino claims already. However, I'm not sure the dots can be connected so easily.

As I recently brought to the attention of the forums

                                                   ( https://climatereanalyzer.org/clim/sst_daily/ )

...there is a separate global-scaled phenomenon that has recently taken place with regard to oceanic surface temperatures. And so as usual ... since site above was published the skeptic bugs have been scurrying around for kernels and crumbs of instrumentation suspicion for a variety of usual motivations, ranging from personally seeking an audience, to an agenda to offset the implications as an ongoing effort to evade the truth -

Let's hope they are right this time, because as an aside, ... in order to thermally move the Terrain oceanic en masse upward by 2/10ths of even a single deg C, is something on the order of incomprehensibly large.

Incomprehensibly large usually doesn't end well regardless the type of competition.

The scales are not really tenable to the average Humanity.  ... Not wanting to go down the rabbit whole of denial reasons, the most common one is because the tenability of concepts isn't there. Minds cannot occupy that which is too far beyond dimensionalizing in most cases.

Anyway, I suspect it is likely to be misconstrued and blamed on El Nino.

But of interest to me is that this phenomenon will likely pose challenges to furthering deeper analysis efforts. The entire arc of ENSO monitoring --> relates to the climate forcing, cannot be so readily presumed.  We can spend 10 years gathering data ... formulating hypothesis, testing said hypothesis, and then writing papers to expose the results proving what we already suspect to be true up front:  if the oceans verify as indeed having risen temperature unilaterally like that ... the El Nino physics are concomitantly going to be less effective in forcing the climate.

Something like arithmetic thinking immediately would argue that El Nino is going to be subsumed by that phenomenon - a concept I was just warning about elsewhere on the forum ... So, seeing you muse above ( bold ) ...well?   Yeah.

But it wouldn't be (likely) completely subsumed either.  It's a matter of budgeting gradients in the system.  If the El Nino occurs, but the mid latitude oceans are so warm already ... it does not create the same amount of gradient.  The simplest mechanism that starts the whole ball of wax is how much of A --> B   If B is already large, ... less A --> B.  If less A --> B, that is expressed by less impact.  

That's everything ... air moves on this planet because A --> B.  If A = B... A no longer moves to B, and there's nothin'

 

 

[Typhoon Tip]

https://www.nature.com/articles/s41467-023-37554-1

"...This suggests that everywhere needs to be prepared for a heatwave so extreme it is deemed implausible based on the current observational record..."

[TheClimateChanger]

Climate scientists first laughed at a ‘bizarre’ campaign against the BoM – then came the harassment | Climate science | The Guardian

[chubbs]

Will GISS break a record this year? Odds are increasing. This year trails the the top 2 years 2016+2020 for Jan-Apr, but both of those years cooled in the last 8 months of the year as el nino weakened. Recent years with large ONI increases Jan-->Dec: 2015, 2009 and 2006, all warmed in the last 8 months of the year vs, Jan-April. 2023 sits at 1.01 for Jan-Apr vs 1.02 GISS record;  so back-end of the year warming like either 2015, 2009 or 2006 would produce a record. We'll see.

[chubbs]

 

[bdgwx]

This is getting interesting. My own model using the latest IRI ENSO forecast is now predicting that 2023 will come in 0.05 C above 2016 in the GISS record. I was not expecting a new record in 2023 so this does come as a bit of a surprise. 

Edit: Note that 2016 and 2020 in the GISTEMP dataset are tied.

[bdgwx]

To put this in perspective if (and that is a big IF right now) 2023 is record breaking and ENSO follows the IRI ensemble forecast then a new record will have been achieved with an average 4-month lagged ONI of -0.15. 

[Typhoon Tip]

good luck

 

https://phys.org/news/2023-05-anthropocene-sixth-mass-extinction-event.html