Met Officeโ€™s Amber Warning Turned Out To Be Aย Dud

That amber warning turned out to be a bit of a damp squib.

From NOT A LOT OF PEOPLE KNOW THAT

By Paul Homewood

That amber warning turned out to be a bit of a damp squib.

Despite some hysterical reporting, the best the Met Office could come up with was 45.2mm for the day at Charlwood:

Far from the apocalyptic warnings of 100 mm!

The Emergence of Emergence

So thatโ€™s the idea. Of course, I wasnโ€™t interested in camping, but in climate. In particular, I wanted to find out more about my theory that emergent thermoregulatory climate phenomena are central to the surprising stability of global temperatures.

From Watts Up With That?

Guest Post by Willis Eschenbach

Iโ€™ve been exploring the abilities of Artificial Intelligence, which I described in a previous post as โ€œThe Worldโ€™s Dumbest Genius Librarianโ€œ. I read a curious suggestion as to how to use AI, which was what they called the โ€œblank lineโ€ technique. This is where you give the AI (in my caseย perplexity.ai) a list of things with a blank line โ€œ______โ€ at the end, and it fills in the blank. The example they gave in the suggestion I read was something like โ€œIโ€™m going camping, and Iโ€™m taking a tent, a sleeping bag, a hatchet, and ___โ€. So, I tried it. Here, let me try it again right now so you can see what I mean. Hang on โ€ฆ OK, hereโ€™s what I got:

Me:

โ€œIโ€™m going camping, and Iโ€™m taking a tent, a sleeping bag, a hatchet, and ___โ€

Perplexity:

โ€œBased on your camping listโ€”tent, sleeping bag, hatchetโ€”the next logical and essential item to bring would be a flashlight. A flashlight is crucial for safety and convenience in the outdoors, especially after dark, making it a natural addition to your camping essentials.โ€

So thatโ€™s the idea. Of course, I wasnโ€™t interested in camping, but in climate. In particular, I wanted to find out more about my theory that emergent thermoregulatory climate phenomena are central to the surprising stability of global temperatures.

And what is an emergent phenomenon when it is at home? Here are the characteristics that differentiate emergent climate phenomena from other kinds of critters:

  • They are flow systems far from equilibrium that arise spontaneously, often upon crossing a critical threshold that is temperature-based.
  • Their properties are not predictable from the properties of the condition they emerge from. Thereโ€™s nothing in the nature of atoms of water and air that would predict that they could spontaneously create lightning.
  • They move and act unpredictably.
  • They are often associated with phase changes.
  • They often exhibit โ€œovershootโ€ (hysteresis).
  • They have a lifespan from their initiation to their dissolution.
  • Their patterns arise from many small interactions of their component parts.

So I used that blank line technique to find out more about emergent climate phenomena.

Me:

Among the emergent weather phenomena that help thermoregulate the temperature are thunderstorms, cirrus cloud fields, the Rayleigh-Benard overturning of the lower atmosphere and the upper ocean, cyclones, the Nino/Nina phenomena, tornadoes, dust devils, and _____

The first answer I got was:

Perplexity:

Among the emergent weather phenomena that help thermoregulate the temperatureโ€”such as thunderstorms, cirrus cloud fields, Rayleigh-Bรฉnard overturning in the lower atmosphere and upper ocean, cyclones, the Niรฑo/Niรฑa phenomena, tornadoes, and dust devilsโ€”another significant process is volcanic eruptions.

BZZZT! Wrong, sez I! So I followed that with:

Nope. Volcanoes are 1) not an emergent phenomenon, and 2) not thermoregulatory in nature in that they act regardless of the temperature. Try again.

Perplexity:

Based on the context of emergent, temperature-triggered weather phenomena that actively help thermoregulate Earthโ€™s climate, the most fitting completion for your list is cumulus cloud fields or cumulus convection.

Cumulus clouds, like thunderstorms, form when surface heating reaches a critical threshold, leading to vigorous upward convection. This process increases cloud cover and enhances the reflection of incoming solar radiation, thereby cooling the surface and stabilizing temperatures. This mechanism is described as a classic emergent thermoregulatory processโ€”appearing spontaneously when local temperatures rise above a certain point, and acting to limit further warming

That showed me that perplexity had gotten the underlying idea. So I said that was a good answer, find me another example. It gave me another. I only asked perplexity for one at a time, because AI does better with single questions.

I repeated that a whole bunch of times, getting answers Iโ€™d thought of before, and answers it had given me upthread in a different form, and answers that were a total surprise to me.

I then asked perplexity to read through the whole thread, select the unique, distinct answers, and say why they are emergent phenomena rather than some other kind of phenomena, what their thermoregulatory action is, and how they are distinct from the other phenomena on the list. Below is what I got, unedited. And while I might quibble about some parts of the descriptions, overall it was a fascinating list.


Comprehensive Synopsis of Emergent Thermoregulatory Weather Phenomena

Thunderstorms

  • Emergence: These form spontaneously when surface heating creates convective instability that crosses critical temperature and humidity thresholds. The process is nonlinear, with small changes in conditions triggering explosive growth beyond predictable models.
  • Thermoregulatory Function: They vertically transport heat through updrafts and downdrafts while increasing planetary albedo via anvil clouds. Additionally, rainfall induces evaporative cooling at the surface, disrupting localized heat buildup.
  • Distinctiveness: Unlike planetary-scale oscillations, thunderstorms are short-lived, highly localized convective events driven by surface heating rather than large-scale wind patterns.

Cirrus Cloud Fields

  • Emergence: Self-organizing ice crystal structures arise from wave-induced humidity fluctuations in the upper troposphere. Their formation depends on nonlinear ice-nucleation dynamics that defy simple prediction.
  • Thermoregulatory Function: These clouds trap outgoing longwave radiation (warming) while reflecting sunlight (cooling), creating a context-dependent net effect. They modulate radiative balance across regional scales without producing precipitation.
  • Distinctiveness: Their wispy, high-altitude structure contrasts sharply with low marine stratocumulus decks, functioning more as radiative modulators than convective triggers.

Rayleigh-Bรฉnard Overturning

  • Emergence: Convection cells emerge spontaneously when surface heating exceeds critical buoyancy thresholds in fluid layers. This self-organization stems from nonlinear feedback between temperature gradients and fluid viscosity.
  • Thermoregulatory Function: Cells vertically mix heat in atmospheric/oceanic boundary layers, preventing extreme surface temperatures. They maintain stability by continuously redistributing energy from heated surfaces to cooler layers.
  • Distinctiveness: As a universal fluid dynamic process, it operates in both oceans and atmosphere, unlike event-driven phenomena like haboobs or derechos.

Cyclones

  • Emergence: These large-scale vortices self-organize when wind shear, humidity, and sea-surface temperatures cross instability thresholds. Their structure emerges from nonlinear ocean-atmosphere coupling.
  • Thermoregulatory Function: Cyclones redistribute equatorial heat poleward via winds and induce evaporative cooling through heavy rainfall. They act as planetary-scale heat engines, balancing latitudinal temperature gradients.
  • Distinctiveness: Their synoptic scale and multi-day lifespan differ from mesoscale phenomena like bow echoes or gust fronts.

El Niรฑo-Southern Oscillation (ENSO)

  • Emergence: This pattern arises nonlinearly from coupled ocean-atmosphere feedbacks in the tropical Pacific. Threshold-crossing events trigger phase transitions between warm and cold states.
  • Thermoregulatory Function: ENSO modulates global heat distribution by altering ocean currents, upwelling, and atmospheric circulation. It regulates equatorial Pacific temperatures over multi-year timescales.
  • Distinctiveness: Its interannual pacing contrasts sharply with diurnal processes like sea breezes or nocturnal boundary layer mixing.

Tornadoes

  • Emergence: These form spontaneously when supercell thunderstorms interact with wind shear and convective instability. Their rotation emerges from nonlinear vorticity dynamics.
  • Thermoregulatory Function: Tornadoes rapidly mix warm surface air with cooler upper-level air, disrupting heat buildup. Their intense updrafts/downdrafts enhance local heat redistribution.
  • Distinctiveness: Their small-scale, violently rotating structure differs from non-rotational density currents like gust fronts.

Dust Devils

  • Emergence: Self-organizing vortices arise when intense surface heating creates localized thermal instability. Their formation depends on nonlinear interactions between hot surface layers and cooler air.
  • Thermoregulatory Function: They lift hot surface air upward, replacing it with cooler air and enhancing vertical mixing. This process disrupts near-surface heat accumulation in arid regions.
  • Distinctiveness: As dry, warm-core vortices, they lack the moisture-driven dynamics of thunderstorms or monsoons.

Cumulus Convection

  • Emergence: Fluffy clouds self-assemble when surface heating exceeds convective initiation thresholds. Their growth is a nonlinear response to boundary layer instability.
  • Thermoregulatory Function: Cumulus clouds increase albedo to limit surface heating and promote cooling through shade and latent heat release. They act as precursors to deeper convective systems.
  • Distinctiveness: This represents an early convective phase distinct from mature mesoscale complexes or anvil-topped thunderstorms.

Madden-Julian Oscillation (MJO)

  • Emergence: Spontaneous convection clusters propagate eastward via wind-moisture feedbacks in the tropics. Its emergence stems from collective atmospheric interactions crossing organizational thresholds.
  • Thermoregulatory Function: The MJO modulates tropical heat buildup through cyclic cloud/rain development. It redistributes moisture and energy across ocean basins over 30โ€“60 day periods.
  • Distinctiveness: As a planetary-scale traveling system, it differs from stationary monsoons or localized convective events.

Monsoon Circulation

  • Emergence: This system self-organizes when land-sea thermal contrasts exceed seasonal thresholds. Its onset involves nonlinear feedback between precipitation and atmospheric heating.
  • Thermoregulatory Function: Monsoons cool land surfaces via cloud cover and rainfall while exporting heat to the upper troposphere. They reset regional energy imbalances annually.
  • Distinctiveness: Their seasonally reversing winds contrast with diurnal coastal breezes or persistent trade winds.

Sea Breeze Circulation

  • Emergence: Forms spontaneously when land-sea temperature gradients overcome atmospheric resistance. The circulation emerges from nonlinear pressure adjustments.
  • Thermoregulatory Function: It transports cool marine air inland to moderate coastal temperatures and triggers convective clouds for additional cooling. The nightly reversal prevents excessive cooling.
  • Distinctiveness: This diurnal, coastal-scale process differs from continental-scale cyclones or monsoons.

Stratocumulus Cloud Decks

  • Emergence: Self-organizing cloud blankets form under stable marine boundary layers with strong inversions. Their persistence arises from turbulence-radiation feedback loops.
  • Thermoregulatory Function: These decks dramatically increase albedo to cool subtropical oceans. They suppress surface warming through persistent solar reflection.
  • Distinctiveness: Their uniform, low-altitude structure contrasts with transient cumulus or deep convective clouds.

Reflective Tropical Cloud Shields

  • Emergence: Spontaneously form when sea-surface temperatures exceed critical convection thresholds. Their development is a nonlinear response to oceanic heating.
  • Thermoregulatory Function: These shields limit solar heating via high albedo and often precede thunderstorm development. They act as a tropical thermostat constraining maximum temperatures.
  • Distinctiveness: Their thermodynamic triggering differs from dynamically driven systems like the ITCZ.

Intertropical Convergence Zone (ITCZ)

  • Emergence: Self-organizing convection bands arise from trade-wind convergence and SST gradients. Position emerges from hemisphere-scale energy imbalances.
  • Thermoregulatory Function: The ITCZ cools tropics through cloud albedo and latent heat export. Its seasonal migration balances interhemispheric energy.
  • Distinctiveness: As an equatorial migratory belt, it differs from off-equatorial systems like the MJO.

Mesoscale Convective Systems (MCSs)

  • Emergence: Thunderstorms self-aggregate into complexes via cold-pool interactions. Their structure emerges from nonlinear storm-scale feedbacks.
  • Thermoregulatory Function: MCSs increase albedo with expansive cloud shields and induce evaporative cooling via rainfall. They redistribute heat over regions spanning hundreds of kilometers.
  • Distinctiveness: Their organized cluster structure differs from isolated thunderstorms or synoptic-scale cyclones.

Hadley Cell Expansion

  • Emergence: Intensifies nonlinearly from tropical heating and eddy feedbacks. Poleward expansion emerges when thermal gradients cross critical thresholds.
  • Thermoregulatory Function: The cell exports heat poleward and modulates subtropical aridity. Its widening redistributes energy across hemispheres.
  • Distinctiveness: As a zonal-mean circulation, it contrasts with longitudinal phenomena like the MJO.

Polar Vortex Dynamics

  • Emergence: Self-amplifies from temperature/pressure gradients at high latitudes. Disruptions emerge from stratosphere-troposphere coupling.
  • Thermoregulatory Function: Contains frigid air; breakdowns export cold to mid-latitudes. This stabilizes polar temperatures while balancing hemispheric extremes.
  • Distinctiveness: Its stratospheric coupling differs from surface-driven phenomena like dust devils.

Cumulus-to-Cumulonimbus Transition

  • Emergence: Explosive vertical growth triggers when convective instability thresholds are crossed. This phase shift is a nonlinear atmospheric response.
  • Thermoregulatory Function: Rapid downdrafts and rain evaporation cool surfaces immediately. The process resets local instability by exporting heat vertically.
  • Distinctiveness: Represents a cloud life-cycle phase change unlike stable stratocumulus regimes.

Tropical Sky Clearing

  • Emergence: Spontaneous cloud suppression occurs when temperatures fall below convection thresholds. Emergence depends on humidity-temperature hysteresis.
  • Thermoregulatory Function: Clearing allows solar heating to counterbalance cool conditions. This negative feedback prevents prolonged cooling periods.
  • Distinctiveness: Functions as the inverse of cloud-forming systems like MCSs or ITCZ convection.

Atmospheric Blocking

  • Emergence: Self-sustaining highs form from Rossby wave resonance. Persistence emerges from nonlinear energy trapping.
  • Thermoregulatory Function: Blocks redistribute heat/cold via meridional flow and prolong temperature extremes regionally. They modulate zonal heat transport efficiency.
  • Distinctiveness: Their quasi-stationary synoptic scale differs from traveling cyclones.

Open/Closed-Cell Stratocumulus

  • Emergence: Cellular patterns form spontaneously from turbulence-radiation feedbacks. Transitions exhibit hysteresis and critical thresholds.
  • Thermoregulatory Function: Open cells enhance infrared cooling; closed cells increase solar reflection. This dynamic optimizes local energy balance.
  • Distinctiveness: Pattern transitions differ from uniform decks or cumulus evolution.

Synoptic-Scale Air Advection

  • Emergence: Warm/cold surges arise from jet stream meanders. Their onset depends on pressure-anomaly interactions crossing instability thresholds.
  • Thermoregulatory Function: Advection rapidly redistributes air masses across continents. It prevents persistent regional temperature anomalies.
  • Distinctiveness: Driven by continental-scale dynamics unlike local convection.

Heat Bursts

  • Emergence: Downdrafts compress and warm adiabatically during thunderstorm collapse. Emergence requires specific vertical humidity/temperature profiles.
  • Thermoregulatory Function: Bursts mix elevated warm air downward, disrupting cold pools. They abruptly reset nocturnal surface temperatures.
  • Distinctiveness: Nocturnal, hyper-localized spikes differ from diurnal sea breezes.

Haboobs

  • Emergence: Thunderstorm outflow self-organizes into dust-laden density currents. Dust integration amplifies through particle-fluid feedbacks.
  • Thermoregulatory Function: Dust clouds increase albedo while cold pools enhance surface cooling. They rapidly export heat via dry convection.
  • Distinctiveness: Dust-integrated structure differs from precipitation-driven outflows.

Chinook/Foehn Winds

  • Emergence: Self-amplifying downslope winds form from mountain-wave dynamics. Warming emerges via nonlinear compressional heating.
  • Thermoregulatory Function: Winds rapidly warm leeward slopes, reducing cold extremes and melting snow. They ventilate valleys by exporting stagnant air.
  • Distinctiveness: Orographic triggering differs from flat-terrain wind systems.

Quasi-Resonant Amplification (QRA)

  • Emergence: Rossby waves resonate from jet stream instabilities and topography. Persistence emerges from atmospheric wave trapping.
  • Thermoregulatory Function: QRA locks heat/cold into semi-permanent regional patterns. This prolongs temperature redistribution during extremes.
  • Distinctiveness: Resonance-driven persistence differs from transient easterly waves.

Tropical Easterly Waves

  • Emergence: Self-generate from trade-wind shear and convective feedbacks. Wave organization crosses critical moisture convergence thresholds.
  • Thermoregulatory Function: Waves organize cloud clusters to modulate tropical heating. They propagate moisture imbalances westward.
  • Distinctiveness: Westward propagation contrasts with eastward-moving MJO systems.

Atmospheric Rivers

  • Emergence: Filamentary moisture plumes self-focus from wind convergence. Narrowing emerges via vapor-condensation feedbacks.
  • Thermoregulatory Function: Rivers redistribute latent heat globally and induce cooling via orographic precipitation. They prevent continental overheating during droughts.
  • Distinctiveness: Filamentary structure differs from broad monsoonal flows.

Derechos

  • Emergence: Squall lines self-organize into bows via cold pool-wind shear interactions. Bow echoes emerge from nonlinear storm-scale dynamics.
  • Thermoregulatory Function: Straight-line winds drive large-scale mixing and surface cooling. Their cold pools disrupt regional heat domes.
  • Distinctiveness: Non-rotational windstorms differ from tornadoes or cyclones.

Virga

  • Emergence: Precipitation evaporates spontaneously in dry subcloud layers. Phase-change thresholds govern fallstreak formation.
  • Thermoregulatory Function: Evaporative cooling lowers surface temperatures without rainfall. This provides โ€œdryโ€ heat redistribution in arid zones.
  • Distinctiveness: Evaporation-dominated process differs from rain-cooling in thunderstorms.

Cold-Air Pool Formation

  • Emergence: Cold air self-traps in topography when radiative cooling exceeds mixing thresholds. Pooling emerges from nonlinear density stratification.
  • Thermoregulatory Function: Pools insulate valleys from extreme cold and delay daytime warming. Their eventual mixing exports cold air regionally.
  • Distinctiveness: Topographic confinement differs from open-terrain radiative cooling.

Bow Echoes

  • Emergence: Spontaneous bowing develops from rear-inflow jet dynamics. Acceleration emerges via pressure-perturbation feedbacks.
  • Thermoregulatory Function: Focused downdrafts intensify surface cooling. The bowed structure enhances wind-driven mixing efficiency.
  • Distinctiveness: Mesoscale bow geometry differs from linear squall lines.

Gust Fronts

  • Emergence: Density currents self-propagate from thunderstorm downdraft spreading. Frontogenesis depends on outflow-environment density contrasts.
  • Thermoregulatory Function: Gust fronts induce rapid cold-air advection to disrupt heat buildups. They often trigger secondary convection for additional cooling.
  • Distinctiveness: Leading-edge dynamics differ from parent storm mechanisms.

Fair-Weather Gale (California)

  • Emergence: Intense inland heating draws marine air through coastal gaps nonlinearly. Gale strength emerges from terrain-channeled acceleration.
  • Thermoregulatory Function: Persistently cools interior valleys via onshore flow. Prevents extreme heat buildup in Mediterranean climates.
  • Distinctiveness: Non-storm coastal wind differs from synoptic systems.

Diablo Winds

  • Emergence: Downslope warming self-accelerates from pressure-topography feedbacks. Wind intensity emerges via dry adiabatic compression.
  • Thermoregulatory Function: Rapidly warms coastal zones by breaking cold pools and fog. Exports interior heat seaward during autumn.
  • Distinctiveness: Northern California variant differs from Southern Californiaโ€™s Santa Anas.

Oceanic Bรฉnard Cells

  • Emergence: Hexagonal convection forms spontaneously during surface cooling events. Cell geometry emerges from salt-fingering instabilities.
  • Thermoregulatory Function: Upwells warmer water to limit sea-ice formation. Enhances ocean-atmosphere heat exchange during cold outbreaks.
  • Distinctiveness: Salinity-driven convection differs from atmospheric overturning.

Synthesis of Thermoregulatory Networks

Earthโ€™s climate stability arises from interconnected emergent phenomena operating across scales. Each process exhibits nonlinear threshold behavior, where small forcings trigger disproportional responses that redistribute heat. This networkโ€”from microscale dust devils to planetary-scale ENSOโ€”forms a self-regulating system where local interactions constrain global temperature extremes through complementary cooling/warming feedbacks. The diversity of mechanisms (radiative, convective, advective) ensures resilience, as the suppression of one process activates compensatory phenomena elsewhere in the system.


Dang, sez I, who knew? Certainly not me โ€ฆ most fascinating. I hadnโ€™t realized that a number of those were emergent thermoregulatory phenomena, but yes, they are. And while I had not asked for a synthesis of thermoregulatory networks at the end, thatโ€™s a pretty good one.

Iโ€™m gonna leave it at that for people to ponder, with just one last thought.

Many of those important thermoregulatory phenomena either do not emerge spontaneously in climate models or are not even considered because they are sub-grid-scale in size.

My best regards to all,

w.

As usual โ€ฆ when you comment QUOTE THE EXACT WORDS YOU ARE DISCUSSING. It avoids heaps of problems.

PSโ€”I wonโ€™t be around for about six hours, starting about half an hour after this goes live. Iโ€™m going to the Russian River Rodeo with the kids and grandkids. Hey, I grew up on a cattle ranch, the local rodeo was the highlight of the year in my youth, what can I say? So play nice, no eye gouging, donโ€™t go all Tyson on your opponentโ€™s ear, and Iโ€™ll get back to you when I return.

My Hypothesis Re-Emerges

I wanted to download all of my WUWT posts so I could make them into ebooks on various subjects. Of course, to do that I need to review some of my earliest posts. Bear in mind, this current analysis is the 1,051st post Iโ€™ve put up on WUWT, so itโ€™s not surprising to me that Iโ€™ve totally forgotten writing some of them. This makes for an interesting journey into the past. Some of them made theoretical conjectures of mine that at the time I didnโ€™t have the data and the computer skills and specialized functions that I have now to both do and display a whole host of data analyses in the computer language โ€œRโ€.

From Watts Up With That?

Guest Post by Willis Eschenbach

Iโ€™ve been on a most curious quest this last week.

I wanted to download all of my WUWT posts so I could make them into ebooks on various subjects. Of course, to do that I need to review some of my earliest posts. Bear in mind, this current analysis is the 1,051st post Iโ€™ve put up on WUWT, so itโ€™s not surprising to me that Iโ€™ve totally forgotten writing some of them. This makes for an interesting journey into the past. Some of them made theoretical conjectures of mine that at the time I didnโ€™t have the data and the computer skills and specialized functions that I have now to both do and display a whole host of data analyses in the computer language โ€œRโ€.

My first post for WUWT was The Thermostat Hypothesis. A version of it was later published as a journal article named โ€ The Thunderstorm Thermostat Hypothesis: How Clouds And Thunderstorms Control The Earthโ€™s Temperature.โ€

Itโ€™s available here, just say no thanks to the offers to join. In that post and journal article, I laid out my thoughts about how tropical thunderstorms and cumulus cloud fields worked to thermoregulate the tropical and thus the global temperature. In succeeding years, I realized that this was my first glimpse of what, down the line, I came to see as a much larger variety of individual overlapping โ€œemergentโ€ climate phenomena acting to oppose temperature variations.

And what is an โ€œemergentโ€ phenomenon when itโ€™s at home? Let me auto-plagiarize from my post โ€œEmergent Climate Phenomenaโ€œ, which I encourage you to take a moment to read.

One common property of emergent phenomena is that they are flow systems that are far from equilibrium. As a result, they need to evolve and change in order to survive. They are mobile and mutable, not fixed and unchanging. And locally (but of course not globally), they can reverse entropy (organize the local environment). Indeed, another name for emergent phenomena is โ€œself-organized phenomenaโ€.

Another key to recognizing emergent phenomena is that they arise spontaneously when conditions are right. They donโ€™t have to be artificially generated. They emerge from the background in response to local conditions (temperature, humidity, etc.) passing some threshold.

Next, they often have a lifespan. By a โ€œlifespanโ€, I mean that they come into existence at a certain time and place, generally when some local natural threshold is exceeded. Thereafter, they are in continuous existence for a certain length of time, and at the end of that time, they dissipate and disappear. Clouds are an excellent example, as is our finite lifespan.

Another characteristic of emergent phenomena is that they are not cyclical, or are at best pseudo-cyclical. They do not repeat or move in any regular or ordered or repetitive fashion. Often, they can move about independently, and when they can do so, their movements can be very hard to predict. Predictions of a hurricane track are an example.

Another feature of emergent phenomena is that they are often temperature threshold-based, with the threshold being a certain local temperature difference. By that, I mean that they rarely emerge below that threshold, but above it, their numbers can increase very rapidly.

Another attribute of emergent systems is that they are often associated with phase changes in the relevant fluids, e.g. clouds occur with a phase change of water.

One final attribute of threshold-based emergent systems is crucial to this discussionโ€”they exhibit โ€œovershootโ€ or hysteresis. In the Rayleigh-Bรฉnard circulation shown below, it takes a certain threshold temperature difference from top to bottom to cause the emergence of the circulation pattern. But once that circulation is established, it will persist even though you turn the heat down far below the initiation threshold temperature. And this kind of โ€œovershootโ€ hysteresis is a requirement for successful regulation of lagged systems, system where the response to a change in inputs or conditions doesnโ€™t occur immediately.

So those are some of the characteristic features of emergent phenomena.

โ€ข They are flow systems far from equilibrium that arise spontaneously, often upon crossing a critical threshold that is temperature-based.

โ€ข Their properties are not predictable from the properties of the condition they emerge from. Thereโ€™s nothing in the atoms of water and air that would predict that they could spontaneously create lightning.

โ€ข They move and act unpredictably

โ€ข They are often associated with phase changes, and

โ€ข They often exhibit โ€œovershootโ€ (hysteresis)

โ€ข They have a lifespan from their initiation to their dissolution

โ€ข Their patterns arise from many small interactions

To me, this is a two-fold explanation of why modern state-of-the-art weather models are only reliable a few days out. First, weโ€™re dealing with emergent phenomena, and by their very nature, their future actions canโ€™t be reliably predicted. And second, modern weather and climate models donโ€™t feature spontaneously emerging tropical thunderstorms. Theyโ€™re short on spontaneous emergence of any kind.

And that leaves them analyzing something that doesnโ€™t exist, a world without emergent phenomena. And to attempt that analysis, they are using methods unsuited for the world that does exist, a world dominated by emergent phenomena. See my post The Details Are In The Devil for why this simply wonโ€™t work.

But I digress โ€ฆ reading some of these early posts, I realized that I now could further test the accuracy and understanding of the claims I made there about clouds and thunderstorms. My hypothesis back then was that clouds act to oppose both upwards and downward swings of the temperature. I said that they are a governor rather than a simple feedback.

Climate scientists talk about โ€œcloud feedbackโ€. But what clouds do is not just simple linear feedback of the type discussed by the IPCC scientists. For example, negative feedback just opposes warmingโ€”the warmer it gets, the more it opposes the warming.

But clouds are not like that. Clouds and thunderstorms function as a thermoregulatory governor. They donโ€™t just slow down warming. Instead, they warm the surface when itโ€™s cold, and they cool the surface when itโ€™s warm.

And the reason for this post is that today I thought of another way to show that is true. Let me explain.

The CERES dataset has gridded 1ยฐ longitude by 1ยฐ latitude data of the โ€œSurface Cloud Radiative Effectโ€, or โ€œSurface CREโ€, hereinafter just โ€œCREโ€. The CRE is the difference in radiation hitting the surface between when the clouds are or arenโ€™t present. There are two kinds of cloud radiative effects, shortwave (solar radiation) and longwave (thermal radiation from the atmosphere). The net of the two is the total effect of the clouds, which depending on conditions and type of clouds can either be cooling or warming of the surface..

A negative CRE value in a given area indicates that the presence of clouds cools that part of the planet, and a positive value means the presence of clouds warms the surface.

Let me start with a global look at the surface cloud radiative effect, to determine where clouds warm or cool the surface and by how much.

Figure 1. Global surface cloud radiative effect (net of longwave and shortwave radiation). Negative is cooling, positive is warming.

This shows the net cooling effect of about -19 W/m2. But what it doesnโ€™t show is how the surface net cloud radiative effect varies when the temperature in any location gets warmer or cooler than the average temperature for that area. Thatโ€™s what the IPCC calls โ€œcloud feedbackโ€. They claim it is positive, meaning that when the surface warms, the clouds change to increase that warming. Me, Iโ€™ve always thought that claim was highly improbable for several reasons.

For my new way to show how clouds change with temperature, I looked by latitude at the difference between the seasonal CRE (winter and summer) and the annual average CRE. I took the global maps of mid-summer and mid-winter CRE, and from each of those I subtracted the map shown in Figure 1 above. Then I took averages by each 1ยฐ latitude band. The result is below.

Figure 2. Latitudinal by 1ยฐ bands of the difference between mid-summer/mid-winter surface CRE and the average CRE for that given latitude.

For me, the greatest joy in science is the moment of seeing graphically the result of some new, unknown analysis method. And in this case, I didnโ€™t expect the outcome. The difference in cloud radiative effect is large, regular, and stark. The difference between mid-summer and mid-winter CRE is up to 110 W/m2 in the northern hemisphere and 160 W/m2 in the southern hemisphere.

In addition, in mid-summer in both latitudes the clouds on average cool the entire summer hemisphere compared to average conditions, pole to Equator. And the opposite is true. In mid-winter, clouds in the entire winter hemisphere show increased warming compared to annual averages.

In other words, compared to the local annual average values, when it is warmer than usual, clouds cool the surface, and when it is cooler than usual, clouds warm the surface.

Encouraged by this finding, I decided to look at those summer/winter changes versus annual averages as maps of the earth.

Figure 3. As in Figure 2, showing summer and winter changes from the average conditions.

This gives us another view of how the surface cloud radiative effect changes with the seasons. In winter it gives extra warming, and in the summer it gives extra cooling.

The scientific test of a hypothesis is whether it makes successful, testable predictions. The figures above verify exactly the testable prediction based on what I hypothesized fifteen years ago, that clouds and thunderstorms warm the earth when it is cool and cool it when it is warm โ€ฆ whatโ€™s not to like?

My best to all, and please โ€ฆ no personal attacks.

w.

As Iโ€™ve said before โ€ฆ when you comment, please quote the exact words you are discussing. It avoids endless misunderstandings and disputes.