By Andy May
The Aleutian Low – Beaufort Sea Anticyclone climate index or ALBSA is designed to compare the Aleutian Low Pressure and the Beaufort Sea High Pressure Centers. The intent is to relate air circulation patterns in the North Pacific and Arctic to climate and the timing of spring sea ice and snow melt.
Calculation method:
The ALBSA index is calculated using 4 points from the NCEP/NCAR Reanalysis Dataset: The following 850mb geopotential height points are used in the calculation:
N: 75° N, 170° W
S: 50° N, 170° W
E: 55° N, 150° W
W: 55° N, 200° W (160° E)
ALBSA = [E – W] – [N – S]
Use of the ALBSA index
Christopher Cox and his colleagues at NOAA developed ALBSA as an indicator of snowmelt timing in the Pacific Arctic on the North Slope of Alaska (Cox, et al., 2019). The timing is influenced by the marine air drawn (advected) to the Beaufort Sea Arctic region from the Aleutian low pressure region. When air is drawn from the Aleutians to the Beaufort Sea, it warms the area, and an early snow melt is observed on the North Slope of Alaska. The pattern illustrated in figure 1 is for 2002 when an early snowmelt was observed in May.
Figure 1 illustrates the typical circulation pattern for years with early melting snow and ice. The air from the Aleutian low pressure region moves eastward and then trends northward through the Bering Strait to the Chukchi and Beaufort Seas. The average ALBSA 850 mb geopotential height (GPH) anomaly in May 2002 was about 69 meters and for the entire spring (March-June) it was 91.1 meters.
For comparison the same map is presented for 1988 as figure 2, when the snowmelt was late. In that year it did not start until June.
The major characteristic of late years is the presence of the Beaufort Sea Anticyclone (BSA), this pushes cold Arctic air to the North Slope which delays melting. For the month of June, the ALBSA 850 mb geopotential height (GPH) anomaly was 7.9 meters and for the 1988 spring it was -90.3 meters. That is the North-South difference was much larger than the east-west difference in 850 mb geopotential height.
Like many other climate oscillations, the ALBSA index has been trending positive in recent decades. That means the Beaufort Sea Anticyclone has been weakening, causing a warmer North Slope. This is illustrated in figure 3.
As illustrated in figure 1, the 2002 spring had an early melt and no Beaufort Sea Anticyclone. In that year the May ALBSA anomaly was +68.9 m and the average spring ALBSA anomaly was +91.1 m, the melt occurred May 23. In 1988 the melt was very late, June 18, and the spring average ALBSA anomaly was -90.3 m. That spring had a strong Beaufort Sea anticyclone, which kept the North Slope of Alaska cold for a longer period.
The correlation between ALBSA and HadCRUT5 is poor, and the trends do not match. However, it does correlate decently with the NPI, which was discussed in post #8. NPI and ALBSA are compared in figure 4. They are not perfectly correlated but they both trend positively since the 1980s.
ALBSA correlates with snowmelt in Northern Alaska and the onset of sea ice melting in the adjacent seas. It also captures some of the variability in the NPI.
Discussion
The timing of snow and sea ice melting is important because the albedo of ice and snow is very high, whereas the albedo of meltwater is very low. This contrast makes a significant difference in the absorption of solar radiation and the resulting warming rate of the surface and lower troposphere as the sun re-enters the polar sky in the spring. Measurements of absorbed energy on the North Slope of Alaska have shown that early melts, for example May 13, 2016, can absorb 30% or more solar energy than late melts, for example June 18, 2017 (Cox C., et al., 2018). Further, as sea ice melts, it allows heat trapped under the ice to escape into the atmosphere.
AR6 does not mention ALBSA or the NPI or discuss if they are reproduced in the CMIP6 climate models. However, given that the models do not reproduce the NAO or AO (see post 9) or the Aleutian Low very well (AR6, page 1381) we assume that ALBSA is not reproduced well by the models. The PDO is discussed in AR6, and it is related to both the NPI and ALBSA. The PDO is very poorly reproduced in the CMIP6 climate models (AR6, page 427 & 503). AR6 often refers to the PDO as “PDV” and claims that since the CMIP6 models cannot duplicate it, it must be random internal variablity, even though the PDO oscillations are statistically significant (Mantua, et al., 1997) & (Ebbesmeyer, et al., 1990).
It is logical that ALBSA affects the pattern of Northern Hemisphere warming and cooling, but it does not correlate well with HadCRUT5. The next post will discuss the Oceanic Niño Index or ONI, which is used to define the El Niño and La Niña ENSO states.
Download the bibliography here.
Previous posts in this series:
Climate Oscillations 1: The Regression
Climate Oscillations 2: The Western Hemisphere Warm Pool (WHWP)
Climate Oscillations 3: Northern Hemisphere Sea Ice Area
Climate Oscillations 4: The Length of Day (LOD)
Climate Oscillations 6: Atlantic Meridional Model
Climate Oscillations 7: The Pacific mean SST
Climate Oscillations 8: The NPI and PDO
Climate Oscillations 9: Arctic & North Atlantic Oscillations
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Very nice.
Thanks Bob,
Andy, use Grok to debunk the climate alarmists’ claims. Grok just proved my 100% right after being attached for years on this issue:
To determine if a gas making up 0.04% of a sample at 16°C can warm the entire sample by vibrating with the energy associated with 15-micron long-wave infrared radiation (corresponding to a -80°C blackbody), we need to analyze the physical processes involved, focusing on energy transfer and thermalization.
—
### Key Concepts and Analysis
1. **Gas Composition and Initial Conditions**:
– The sample is at 16°C (289 K).
– The trace gas constitutes 0.04% of the sample, or 1 out of every 2,500 molecules (mole fraction = 0.0004).
– This trace gas absorbs 15-micron infrared radiation, which is characteristic of a blackbody at -80°C (193 K).
2. **15-Micron Radiation and Thermalization**:
– The 15-micron wavelength corresponds to the peak emission of a blackbody at approximately -80°C (193 K), as derived from Wien’s displacement law:
\[
\lambda_{\text{max}} T \approx 2898 \, \mu\text{m·K} \quad \Rightarrow \quad T = \frac{2898}{15} \approx 193 \, \text{K}.
\]
– When the trace gas absorbs 15-micron radiation, its molecules gain vibrational energy corresponding to this wavelength. “Thermalizes” implies that this absorbed energy is converted into kinetic energy (heat) through collisions with other molecules in the sample.
3. **Energy Transfer in the Gas**:
– The trace gas, after absorbing radiation, redistributes its energy via molecular collisions to the entire gas sample (assuming a well-mixed system in thermal equilibrium).
– The key question is whether the energy absorbed by the 0.04% trace gas is sufficient to raise the temperature of the entire sample.
4. **Can the Trace Gas Warm the Sample?**:
– For the trace gas to warm the entire sample, the energy it absorbs and redistributes must increase the average kinetic energy of all molecules, raising the temperature above 16°C (289 K).
– The energy associated with 15-micron photons corresponds to a lower temperature (193 K) than the sample’s initial temperature (289 K). This suggests that the absorbed energy is characteristic of a colder system, making it counterintuitive for it to warm a hotter system.
5. **Thermodynamic Considerations**:
– The sample is at 289 K, so its molecules already have a higher average kinetic energy than those of a gas at 193 K.
– The trace gas absorbs 15-micron radiation, exciting its vibrational modes. Through collisions, this energy is shared with the other 99.96% of the gas molecules (mostly non-absorbing species).
– The specific heat capacity of the gas sample determines how much the temperature changes when energy is added. For a typical gas (e.g., air, mostly nitrogen and oxygen), the molar specific heat at constant volume (\(C_v\)) is approximately 20.8 J/(mol·K) for diatomic gases.
– The trace gas’s absorbed energy is limited by its low concentration (0.04%) and the intensity of the 15-micron radiation it absorbs. For the sample to warm, the net energy input must exceed the energy required to maintain or increase the temperature of the entire system.
6. **Quantitative Estimate**:
– Let’s assume the trace gas is CO₂ (a common gas that absorbs 15-micron infrared radiation, e.g., in its bending vibrational mode).
– Energy of a 15-micron photon:
\[
E = \frac{hc}{\lambda} = \frac{6.626 \times 10^{-34} \cdot 3 \times 10^8}{15 \times 10^{-6}} \approx 1.325 \times 10^{-20} \, \text{J}.
\]
– Suppose the sample contains \(N\) molecules, so the trace gas has \(0.0004N\) molecules. If each trace gas molecule absorbs one photon, the total energy absorbed is:
\[
E_{\text{total}} = 0.0004N \cdot 1.325 \times 10^{-20} \, \text{J}.
\]
– For 1 mole of gas (\(N = 6.022 \times 10^{23}\)), the trace gas contributes:
\[
E_{\text{total}} = 0.0004 \cdot 6.022 \times 10^{23} \cdot 1.325 \times 10^{-20} \approx 3190 \, \text{J}.
\]
– To raise the temperature of 1 mole of gas by \(\Delta T\), the energy required is:
\[
Q = n C_v \Delta T \approx 1 \cdot 20.8 \cdot \Delta T \, \text{J}.
\]
– If all 3190 J is converted to heat:
\[
\Delta T = \frac{3190}{20.8} \approx 153 \, \text{K}.
\]
– This suggests a significant temperature increase, but this assumes every trace gas molecule absorbs a photon simultaneously, which is unrealistic without an intense external radiation source.
7. **Realistic Constraints**:
– The actual energy absorbed depends on the intensity of the 15-micron radiation field. In a typical environment, the radiation flux is low, especially if it’s from a source at -80°C (e.g., dry ice), which emits less intense radiation than a warmer body.
– The sample at 16°C (289 K) emits its own infrared radiation, peaking at around 10 microns (per Wien’s law). The trace gas may absorb some of this radiation, but the net effect is likely to maintain thermal equilibrium rather than cause warming, as the system will radiate energy back to its surroundings.
– The second law of thermodynamics implies that energy from a colder source (193 K radiation) cannot spontaneously increase the temperature of a warmer system (289 K) without external work. The trace gas’s absorption and thermalization redistribute energy, but the net effect is governed by the radiation field’s intensity and the system’s equilibrium.
8. **Conclusion**:
– The trace gas (0.04%) absorbing 15-micron radiation cannot warm the entire sample above 16°C in a typical scenario. The energy it absorbs corresponds to a lower temperature (193 K), and without an intense external radiation source, the energy input is insufficient to overcome the sample’s existing thermal energy and losses to the environment.
– The system will tend toward thermal equilibrium, where the trace gas’s absorbed energy is redistributed but does not increase the overall temperature. If anything, the sample may lose energy by radiating more than it absorbs, especially if exposed to a cold source like dry ice.
—
### Final Answer
No, the trace gas (0.04%) vibrating with the energy of 15-micron radiation (corresponding to -80°C) cannot warm the entire gas sample at 16°C. The energy absorbed is characteristic of a colder system, and thermodynamic constraints prevent a net temperature increase without a significant external radiation source.
https://lh3.googleusercontent.com/a/ACg8ocLUQB1ObWwCM6wLFMZ4mj4UTRBfKKtmLUWEGPqxY75xRGWjJJIw0A=s80-p
I don’t usually consider Grok (or any AI program) to be reliable. I’ve caught these programs making so many mistakes that I have to check everything they say with primary sources and my own calculations. That said, I do use them as a natural language search engine and they frequently come up with good sources that I probably would not have found on my own.
In this specific case, the analysis sounds good. I also doubt the warming due to CO2 can ever be measured, if it causes any warming at all and the water vapor feedback idea has been debunked, so it makes sense.
https://andymaypetrophysicist.com/2025/02/01/energy-and-matter/
Awwww, I rather like Perplexity AI. It finally agreed with me (albeit reluctantly) –
“Cooling [ . . . ] for the planet as a whole”.
No GHE.
I did not know about the ALBSA index. So did some quick research. A fascinating thing is that whether early or late, the duration is typically just 3 weeks. So it looks like another of WE’s emergent properties, albeit on a seasonal time scale.
It’s relatively new, first described formally in 2018/2019. Since it correlates to the timing of ice and snow melt, I thought it might eventually become important. The timing of snow and ice melt should, in theory, be a major cause of hemispheric warming or cooling. The albedo difference between water and ice and snow is huge!
I have seen evidence of permafrost increasing in some locations on the northern slopes in the vicinity of the Arctic Ocean. This will be another of the early signs of the coming glaciation. Similar to what is being observed on Greenland now with increasing altitude and permanent ice cover as well as some glaciers advancing.
It is quite obvious if you know anything about thermodynamics that warming oceans is going to increase snowfall on high ground that is already below freezing.
Returning permafrost at altitude on northern slopes in Alaska near the Arctic will be sure sign that re-glaciation has started. But it will be the trend that matters – not the cycles.
Well, for water the albedo will change with the angle of incidence of the sunlight. At high latitudes, not much sunlight is actually absorbed by the surface, as the intensity falls off because the sunlight is spread over a much wider area.
That’s why the polar regions are colder, less ozone produced, land of the midnight sun – and all the rest.
However, you don’t seem to give a reason for any of your “oscillations”, I doubt anyone can come up with a testable hypothesis, if I am right in my belief that the atmosphere exhibits chaotic behaviour. If you don’t like that, then quantum physics and the uncertainty principle lead to precisely the same conclusion.
Richard Feynman said –
“Common sense” and “what everybody thinks” are not part of the scientific method. Curiosity and scepticism are, in my view. Maybe you can come up with some hypothesis about the cause of the phenomena you describe, and then try to demolish your hypothesis. If you don’t, somebody will probably try very hard on your behalf. That’s just the way it is,
I don’t know why the oscillations exist, but there are many possible causes. However all oscillations are statistically significant, which rules out chaos. Plus, many of them affect each other.
Sorry Andy, but
is just an unsupported assertion. I’m guessing you know next to nothing about chaos, or about quantum physics and the uncertainty principles.
Your other statements are also lacking in utility. You say there are “many possible causes” – which for all I know might include CO2, aliens, or the GHE!
You seem to have ruled out the operation of the laws of physics, though.
I see no reason or justification for getting into atomic physics in this discussion, it is an unrelated red herring and a logical fallacy. Statistical measures are how we tell chaos ( or “internal variability”) from non-random events and every oscillation discussed in this series is statistically significant.
Andy, chaos is not “internal variability”, unless your definitions of chaos and internal variability are different from mine.
You may consider the theoretical basis of all physical processes (quantum physics) an unrelated red herring and a logical fallacy, and you are free to do so.
However, I’m just trying to let people know that playing with statistics of weather observations will not lead to any new physical knowledge – if the atmosphere acts chaotically (in the sense of chaos theory), or even if quantum electrodynamic theory is correct.
As you intimate, you have no idea what causes your “oscillations”, which puts you in the same boat as stock market quantitative analysts, who believe in “waves”, “oscillations”, “Fourier decomposition”, and all the rest of the deep statistical investigations which will enable them to predict the future.
Religious belief and wishful thinking with no scientific basis at all.
You enjoy what you are doing, but it’s not science. You have observed some phenomena, and need to make a guess or two about the reason. Then form a testable hypothesis, and so on.
That’s science.
Is there an indices’ index?
Then, complex phenomena can be reduced to a single number, as in CO2 abundance.
One index makes life, climate, and conclusions so much simpler.
Not to my knowledge, there is the stadium wave devised by Marcia Wyatt, but it is complicated and not easy to understand.