Solar neutrino problem

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Solar_neutrino_problem

The solar neutrino problem concerned a large discrepancy between the flux of solar neutrinos as predicted from the Sun's luminosity and as measured directly. The discrepancy was first observed in the mid-1960s and was resolved around 2002.

The flux of neutrinos at Earth is several tens of billions per square centimetre per second, mostly from the Sun's core. They are nevertheless difficult to detect, because they interact very weakly with matter, traversing the whole Earth. Of the three types (flavors) of neutrinos known in the Standard Model of particle physics, the Sun produces only electron neutrinos. When neutrino detectors became sensitive enough to measure the flow of electron neutrinos from the Sun, the number detected was much lower than predicted. In various experiments, the number deficit was between one half and two thirds.

Particle physicists knew that a mechanism, discussed in 1957 by Bruno Pontecorvo, could explain the deficit in electron neutrinos. However, they hesitated to accept it for various reasons, including the fact that it required a modification of the accepted Standard Model. They first pointed at the solar model for adjustment, which was ruled out. Today it is accepted that the neutrinos produced in the Sun are not massless particles as predicted by the Standard Model but rather a superposition of defined-mass eigenstates in different (complex) proportions. That allows a neutrino produced as a pure electron neutrino to change during propagation into a mixture of electron, muon and tau neutrinos, with a reduced probability of being detected by a detector sensitive to only electron neutrinos.

Several neutrino detectors aiming at different flavors, energies, and traveled distance contributed to our present knowledge of neutrinos. In 2002 and 2015, a total of four researchers related to some of these detectors were awarded the Nobel Prize in Physics.

Background

Reactions of proton-proton cycle

The Sun performs nuclear fusion via the proton–proton chain reaction, which converts four protons into alpha particles, neutrinos, positrons, and energy. This energy is released in the form of electromagnetic radiation, as gamma rays, as well as in the form of the kinetic energy of both the charged particles and the neutrinos. The neutrinos travel from the Sun's core to Earth without any appreciable absorption by the Sun's outer layers.

In the late 1960s, Ray Davis and John N. Bahcall's Homestake Experiment was the first to measure the flux of neutrinos from the Sun and detect a deficit. The experiment used a chlorine-based detector. Many subsequent radiochemical and water Cherenkov detectors confirmed the deficit, including the Kamioka Observatory and Sudbury Neutrino Observatory.

The expected number of solar neutrinos was computed using the standard solar model, which Bahcall had helped establish. The model gives a detailed account of the Sun's internal operation.

In 2002, Ray Davis and Masatoshi Koshiba won part of the Nobel Prize in Physics for experimental work which found the number of solar neutrinos to be around a third of the number predicted by the standard solar model.

In recognition of the firm evidence provided by the 1998 and 2001 experiments "for neutrino oscillation", Takaaki Kajita from the Super-Kamiokande Observatory and Arthur McDonald from the Sudbury Neutrino Observatory (SNO) were awarded the 2015 Nobel Prize for Physics. The Nobel Committee for Physics, however, erred in mentioning neutrino oscillations in regard to the SNO Experiment: for the high-energy solar neutrinos observed in that experiment, it is not neutrino oscillations, but rather the Mikheyev–Smirnov–Wolfenstein effect, that produced the observed results. Bruno Pontecorvo was not included in these Nobel prizes since he died in 1993.

Proposed solutions

Early attempts to explain the discrepancy proposed that the models of the Sun were wrong, i.e., the temperature and pressure in the interior of the Sun were substantially different from what was believed. For example, since neutrinos measure the amount of current nuclear fusion, it was suggested that the nuclear processes in the core of the Sun might have temporarily shut down. Since it takes thousands of years for heat energy to move from the core to the surface of the Sun, this would not immediately be apparent.

Advances in helioseismology observations made it possible to infer the interior temperatures of the Sun; these results agreed with the well established standard solar model. Detailed observations of the neutrino spectrum from more advanced neutrino observatories produced results which no adjustment of the solar model could accommodate: while the overall lower neutrino flux (which the Homestake experiment results found) required a reduction in the solar core temperature, details in the energy spectrum of the neutrinos required a higher core temperature. This happens because different nuclear reactions, whose rates have different dependence upon the temperature, produce neutrinos with different energy. Any adjustment to the solar model worsened at least one aspect of the discrepancies.

Resolution

Main articles: Neutrino oscillation and Mikheyev–Smirnov–Wolfenstein effect

The solar neutrino problem was resolved with an improved understanding of the properties of neutrinos. According to the Standard Model of particle physics, there are three flavors of neutrinos: electron neutrinos, muon neutrinos, and tau neutrinos. Electron neutrinos are the ones produced in the Sun and the ones detected by the above-mentioned experiments, in particular the chlorine-detector Homestake Mine experiment.

Through the 1970s, it was widely believed that neutrinos were massless and their flavors were invariant. However, in 1968 Pontecorvo proposed that if neutrinos had mass, then they could change from one flavor to another. Thus, the "missing" solar neutrinos could be electron neutrinos which changed into other flavors along the way to Earth, rendering them invisible to the detectors in the Homestake Mine and contemporary neutrino observatories.

The supernova 1987A indicated that neutrinos might have mass because of the difference in time of arrival of the neutrinos detected at Kamiokande and IMB. However, because very few neutrino events were detected, it was difficult to draw any conclusions with certainty. If Kamiokande and IMB had high-precision timers to measure the travel time of the neutrino burst through the Earth, they could have more definitively established whether or not neutrinos had mass. If neutrinos were massless, they would travel at the speed of light; if they had mass, they would travel at velocities slightly less than that of light. Since the detectors were not intended for supernova neutrino detection, they didn't have precise timing and this could not be done.

Strong evidence for neutrino oscillation came in 1998 from the Super-Kamiokande collaboration in Japan. It produced observations consistent with muon neutrinos (produced in the upper atmosphere by cosmic rays) changing into tau neutrinos within the Earth: Fewer atmospheric neutrinos were detected coming through the Earth than coming directly from above the detector. These observations concerned only muon neutrinos; no tau neutrinos were observed at Super-Kamiokande. The result made it more plausible that the deficit in the electron-flavor neutrinos observed in the (relatively low-energy) Homestake experiment also had to do with neutrino mass and flavor-changing.

One year later, the Sudbury Neutrino Observatory (SNO) started collecting data. That experiment aimed at the ⁸B solar neutrinos, which at around 10 MeV are not much affected by oscillation in both the Sun and the Earth. A large deficit is nevertheless expected due to the Mikheyev–Smirnov–Wolfenstein effect as had been calculated by Alexei Smirnov in 1985. SNO's unique design employing a large quantity of heavy water as the detection medium was proposed by Herb Chen, also in 1985. SNO observed electron neutrinos specifically, and all flavors of neutrinos collectively, hence the fraction of electron neutrinos could be calculated. After extensive statistical analysis, the SNO collaboration determined that fraction to be about 34%, in perfect agreement with prediction. The total number of detected ⁸B neutrinos also agrees with the then-rough predictions from the solar model.

Adenosine triphosphate

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Adenosine_triphosphate 

 

Adenosine triphosphate

Adenosine triphosphate (ATP) is a nucleoside triphosphate that provides energy of approximate 30.5kJ/mol to drive and support many processes in living cells, such as muscle contraction, nerve impulse propagation, and chemical synthesis. Found in all known forms of life, it is often referred to as the "molecular unit of currency" for intracellular energy transfer.

When consumed in a metabolic process, ATP converts either to adenosine diphosphate (ADP) or to adenosine monophosphate (AMP). Other processes regenerate ATP. It is also a precursor to DNA and RNA, and is used as a coenzyme. An average adult human processes around 50 kilograms (about 100 moles) daily.

From the perspective of biochemistry, ATP is classified as a nucleoside triphosphate, which indicates that it consists of three components: a nitrogenous base (adenine), the sugar ribose, and the triphosphate.

Structure

ATP consists of three parts: a sugar, an amine base, and a phosphate group. More specifically, ATP consists of an adenine attached by the #9-nitrogen atom to the 1′ carbon atom of a sugar (ribose), which in turn is attached at the 5' carbon atom of the sugar to a triphosphate group. In its many reactions related to metabolism, the adenine and sugar groups remain unchanged, but the triphosphate is converted to di- and monophosphate, giving respectively the derivatives ADP and AMP. The three phosphoryl groups are labeled as alpha (α), beta (β), and, for the terminal phosphate, gamma (γ).

In neutral solution, ionized ATP exists mostly as ATP⁴⁻, with a small proportion of ATP³⁻.

Metal cation binding

Polyanionic and featuring a potentially chelating polyphosphate group, ATP binds metal cations with high affinity. The binding constant for Mg²⁺ is (9554). The binding of a divalent cation, almost always magnesium, strongly affects the interaction of ATP with various proteins. Due to the strength of the ATP-Mg²⁺ interaction, ATP exists in the cell mostly as a complex with Mg²⁺ bonded to the phosphate oxygen centers.

A second magnesium ion is critical for ATP binding in the kinase domain. The presence of Mg²⁺ regulates kinase activity. It is interesting from an RNA world perspective that ATP can carry a Mg ion which catalyzes RNA polymerization.

Chemical properties

Salts of ATP can be isolated as colorless solids.

The cycles of synthesis and degradation of ATP; 2 and 1 represent input and output of energy, respectively.

ATP is stable in aqueous solutions between pH 6.8 and 7.4 (in the absence of catalysts). At more extreme pH levels, it rapidly hydrolyses to ADP and phosphate. Living cells maintain the ratio of ATP to ADP at a point ten orders of magnitude from equilibrium, with ATP concentrations fivefold higher than the concentration of ADP. In the context of biochemical reactions, the P-O-P bonds are frequently referred to as high-energy bonds.

Reactive aspects

The hydrolysis of ATP into ADP and inorganic phosphate:

ATP⁴⁻ + H₂O ⇌ ADP³⁻ + HPO2−3 + H⁺

releases 20.5 kilojoules per mole (4.9 kcal/mol) of enthalpy. This may differ under physiological conditions if the reactant and products are not exactly in these ionization states. The values of the free energy released by cleaving either a phosphate (P_i) or a pyrophosphate (PP_i) unit from ATP at standard state concentrations of 1 mol/L at pH 7 are:

ATP + H₂O → ADP + P_i   ΔG°' = −30.5 kJ/mol (−7.3 kcal/mol)

ATP + H₂O → AMP + PP_i  ΔG°' = −45.6 kJ/mol (−10.9 kcal/mol)

These abbreviated equations at a pH near 7 can be written more explicitly (R = adenosyl):

[RO−P(O)₂−O−P(O)₂−O−PO₃]⁴⁻ + H₂O → [RO−P(O)₂−O−PO₃]³⁻ + [HPO₄]²⁻ + H⁺

[RO−P(O)₂−O−P(O)₂−O−PO₃]⁴⁻ + H₂O → [RO−PO₃]²⁻ + [HO₃P−O−PO₃]³⁻ + H⁺

At cytoplasmic conditions, where the ADP/ATP ratio is 10 orders of magnitude from equilibrium, the ΔG is around −57 kJ/mol.

Along with pH, the free energy change of ATP hydrolysis is also associated with Mg²⁺ concentration, from ΔG°' = −35.7 kJ/mol at a Mg²⁺ concentration of zero, to ΔG°' = −31 kJ/mol at [Mg²⁺] = 5 mM. Higher concentrations of Mg²⁺ decrease free energy released in the reaction due to binding of Mg²⁺ ions to negatively charged oxygen atoms of ATP at pH 7.

This image shows a 360-degree rotation of a single, gas-phase magnesium-ATP chelate with a charge of −2. The anion was optimized at the UB3LYP/6-311++G(d,p) theoretical level and the atomic connectivity modified by the human optimizer to reflect the probable electronic structure.

Production from AMP and ADP

Production, aerobic conditions

A typical intracellular concentration of ATP is 1–10 μmol per gram of muscle tissue in a variety of eukaryotes. The dephosphorylation of ATP and rephosphorylation of ADP and AMP occur repeatedly in the course of aerobic metabolism.

ATP can be produced by a number of distinct cellular processes; the three main pathways in eukaryotes are (1) glycolysis, (2) the citric acid cycle/oxidative phosphorylation, and (3) beta-oxidation. The overall process of oxidizing glucose to carbon dioxide, the combination of pathways 1 and 2, known as cellular respiration, produces about 30 equivalents of ATP from each molecule of glucose.

ATP production by a non-photosynthetic aerobic eukaryote occurs mainly in the mitochondria, which comprise nearly 25% of the volume of a typical cell.

Glycolysis

Main article: Glycolysis

In glycolysis, glucose and glycerol are metabolized to pyruvate. Glycolysis generates two equivalents of ATP through substrate phosphorylation catalyzed by two enzymes, phosphoglycerate kinase (PGK) and pyruvate kinase. Two equivalents of nicotinamide adenine dinucleotide (NADH) are also produced, which can be oxidized via the electron transport chain and result in the generation of additional ATP by ATP synthase. The pyruvate generated as an end-product of glycolysis is a substrate for the Krebs Cycle.

Glycolysis is viewed as consisting of two phases with five steps each. In phase 1, "the preparatory phase", glucose is converted to 2 d-glyceraldehyde-3-phosphate (g3p). One ATP is invested in Step 1, and another ATP is invested in Step 3. Steps 1 and 3 of glycolysis are referred to as "Priming Steps". In Phase 2, two equivalents of g3p are converted to two pyruvates. In Step 7, two ATP are produced. Also, in Step 10, two further equivalents of ATP are produced. In Steps 7 and 10, ATP is generated from ADP. A net of two ATPs is formed in the glycolysis cycle. The glycolysis pathway is later associated with the Citric Acid Cycle which produces additional equivalents of ATP.

Regulation

In glycolysis, hexokinase is directly inhibited by its product, glucose-6-phosphate, and pyruvate kinase is inhibited by ATP itself. The main control point for the glycolytic pathway is phosphofructokinase (PFK), which is allosterically inhibited by high concentrations of ATP and activated by high concentrations of AMP. The inhibition of PFK by ATP is unusual since ATP is also a substrate in the reaction catalyzed by PFK; the active form of the enzyme is a tetramer that exists in two conformations, only one of which binds the second substrate fructose-6-phosphate (F6P). The protein has two binding sites for ATP – the active site is accessible in either protein conformation, but ATP binding to the inhibitor site stabilizes the conformation that binds F6P poorly. A number of other small molecules can compensate for the ATP-induced shift in equilibrium conformation and reactivate PFK, including cyclic AMP, ammonium ions, inorganic phosphate, and fructose-1,6- and -2,6-biphosphate.

Citric acid cycle

Main articles: Citric acid cycle and Oxidative phosphorylation

In the mitochondrion, pyruvate is oxidized by the pyruvate dehydrogenase complex to the acetyl group, which is fully oxidized to carbon dioxide by the citric acid cycle (also known as the Krebs cycle). Every "turn" of the citric acid cycle produces two molecules of carbon dioxide, one equivalent of ATP guanosine triphosphate (GTP) through substrate-level phosphorylation catalyzed by succinyl-CoA synthetase, as succinyl-CoA is converted to succinate, three equivalents of NADH, and one equivalent of FADH₂. NADH and FADH₂ are recycled (to NAD⁺ and FAD, respectively) by oxidative phosphorylation, generating additional ATP. The oxidation of NADH results in the synthesis of 2–3 equivalents of ATP, and the oxidation of one FADH₂ yields between 1–2 equivalents of ATP. The majority of cellular ATP is generated by this process. Although the citric acid cycle itself does not involve molecular oxygen, it is an obligately aerobic process because O₂ is used to recycle the NADH and FADH₂. In the absence of oxygen, the citric acid cycle ceases.

The generation of ATP by the mitochondrion from cytosolic NADH relies on the malate-aspartate shuttle (and to a lesser extent, the glycerol-phosphate shuttle) because the inner mitochondrial membrane is impermeable to NADH and NAD⁺. Instead of transferring the generated NADH, a malate dehydrogenase enzyme converts oxaloacetate to malate, which is translocated to the mitochondrial matrix. Another malate dehydrogenase-catalyzed reaction occurs in the opposite direction, producing oxaloacetate and NADH from the newly transported malate and the mitochondrion's interior store of NAD⁺. A transaminase converts the oxaloacetate to aspartate for transport back across the membrane and into the intermembrane space.

In oxidative phosphorylation, the passage of electrons from NADH and FADH₂ through the electron transport chain releases the energy to pump protons out of the mitochondrial matrix and into the intermembrane space. This pumping generates a proton motive force that is the net effect of a pH gradient and an electric potential gradient across the inner mitochondrial membrane. Flow of protons down this potential gradient – that is, from the intermembrane space to the matrix – yields ATP by ATP synthase. Three ATP are produced per turn.

Although oxygen consumption appears fundamental for the maintenance of the proton motive force, in the event of oxygen shortage (hypoxia), intracellular acidosis (mediated by enhanced glycolytic rates and ATP hydrolysis), contributes to mitochondrial membrane potential and directly drives ATP synthesis.

Most of the ATP synthesized in the mitochondria will be used for cellular processes in the cytosol; thus it must be exported from its site of synthesis in the mitochondrial matrix. ATP outward movement is favored by the membrane's electrochemical potential because the cytosol has a relatively positive charge compared to the relatively negative matrix. For every ATP transported out, it costs 1 H⁺. Producing one ATP costs about 3 H⁺. Therefore, making and exporting one ATP requires 4H^+. The inner membrane contains an antiporter, the ADP/ATP translocase, which is an integral membrane protein used to exchange newly synthesized ATP in the matrix for ADP in the intermembrane space.

Regulation

The citric acid cycle is regulated mainly by the availability of key substrates, particularly the ratio of NAD⁺ to NADH and the concentrations of calcium, inorganic phosphate, ATP, ADP, and AMP. Citrate – the ion that gives its name to the cycle – is a feedback inhibitor of citrate synthase and also inhibits PFK, providing a direct link between the regulation of the citric acid cycle and glycolysis.

Beta oxidation

Main article: Beta-oxidation

In the presence of air and various cofactors and enzymes, fatty acids are converted to acetyl-CoA. The pathway is called beta-oxidation. Each cycle of beta-oxidation shortens the fatty acid chain by two carbon atoms and produces one equivalent each of acetyl-CoA, NADH, and FADH₂. The acetyl-CoA is metabolized by the citric acid cycle to generate ATP, while the NADH and FADH₂ are used by oxidative phosphorylation to generate ATP. Dozens of ATP equivalents are generated by the beta-oxidation of a single long acyl chain.

Regulation

In oxidative phosphorylation, the key control point is the reaction catalyzed by cytochrome c oxidase, which is regulated by the availability of its substrate – the reduced form of cytochrome c. The amount of reduced cytochrome c available is directly related to the amounts of other substrates:

${\displaystyle \frac{1}{2}\text{NADH}+\text{cyt}{\text{c}}_{\text{ox}}^{}+\text{ADP}+{\text{P}}_{\text{i}}^{}\rightleftharpoons \frac{1}{2}{\text{NAD}}^{+}+\text{cyt}{\text{c}}_{\text{red}}^{}+\text{ATP}}$

which directly implies this equation:

${\displaystyle \frac{[\mathrm{c}\mathrm{y}\mathrm{t}{\mathrm{c}}_{\mathrm{r}\mathrm{e}\mathrm{d}}]}{[\mathrm{c}\mathrm{y}\mathrm{t}{\mathrm{c}}_{\mathrm{o}\mathrm{x}}]}={\left(\frac{[\mathrm{N}\mathrm{A}\mathrm{D}\mathrm{H}]}{[\mathrm{N}\mathrm{A}\mathrm{D}{]}^{+}}\right)}^{\frac{1}{2}}\left(\frac{[\mathrm{A}\mathrm{D}\mathrm{P}][{\mathrm{P}}_{\mathrm{i}}]}{[\mathrm{A}\mathrm{T}\mathrm{P}]}\right)K_{\mathrm{e}\mathrm{q}}}$

Thus, a high ratio of [NADH] to [NAD⁺] or a high ratio of [ADP] [P_i] to [ATP] imply a high amount of reduced cytochrome c and a high level of cytochrome c oxidase activity. An additional level of regulation is introduced by the transport rates of ATP and NADH between the mitochondrial matrix and the cytoplasm.

Ketosis

Main article: Ketone bodies

Ketone bodies can be used as fuels, yielding 22 ATP and 2 GTP molecules per acetoacetate molecule when oxidized in the mitochondria. Ketone bodies are transported from the liver to other tissues, where acetoacetate and beta-hydroxybutyrate can be reconverted to acetyl-CoA to produce reducing equivalents (NADH and FADH₂), via the citric acid cycle. Ketone bodies cannot be used as fuel by the liver, because the liver lacks the enzyme β-ketoacyl-CoA transferase, also called thiolase. Acetoacetate in low concentrations is taken up by the liver and undergoes detoxification through the methylglyoxal pathway which ends with lactate. Acetoacetate in high concentrations is absorbed by cells other than those in the liver and enters a different pathway via 1,2-propanediol. Though the pathway follows a different series of steps requiring ATP, 1,2-propanediol can be turned into pyruvate.

Production, anaerobic conditions

Fermentation is the metabolism of organic compounds in the absence of air. It involves substrate-level phosphorylation in the absence of a respiratory electron transport chain.

The equation for the reaction of glucose to form lactic acid is:

C₆H₁₂O₆ + 2 ADP + 2 P_i → 2 CH₃CH(OH)COOH + 2 ATP + 2 H₂O

Anaerobic respiration is respiration in the absence of O₂. Prokaryotes can utilize a variety of electron acceptors. These include nitrate, sulfate, and carbon dioxide. In anaerobic organisms and prokaryotes, different pathways result in ATP. ATP is produced in the chloroplasts of green plants in a process similar to oxidative phosphorylation, called photophosphorylation.

ATP replenishment by nucleoside diphosphate kinases

ATP can also be synthesized through several so-called "replenishment" reactions catalyzed by the enzyme families of nucleoside diphosphate kinases (NDKs), which use other nucleoside triphosphates as a high-energy phosphate donor, and the ATP:guanido-phosphotransferase family.

ATP production during photosynthesis

In plants, ATP is synthesized in the thylakoid membrane of the chloroplast. The process is called photophosphorylation. The "machinery" is similar to that in mitochondria except that light energy is used to pump protons across a membrane to produce a proton-motive force. ATP synthase then ensues exactly as in oxidative phosphorylation. Some of the ATP produced in the chloroplasts is consumed in the Calvin cycle, which produces triose sugars.

ATP recycling

The total quantity of ATP in the human body is about 0.1 mol/L. The majority of ATP is recycled from ADP by the aforementioned processes. Thus, at any given time, the total amount of ATP + ADP remains fairly constant.

The energy used by human cells in an adult requires the hydrolysis of 100 to 150 mol/L of ATP daily, which means a human will typically use their body weight worth of ATP over the course of the day. Each equivalent of ATP is recycled 1000–1500 times during a single day (150 / 0.1 = 1500), at approximately 9×10²⁰ molecules/s.

An example of the Rossmann fold, a structural domain of a decarboxylase enzyme from the bacterium Staphylococcus epidermidis (PDB: 1G5Q​) with a bound flavin mononucleotide cofactor

Biochemical functions

Cellular energy production

The conversion of ATP to ADP is the principal mechanism for energy supply in biological processes. Energy is produced in cells when the terminal phosphate group in an ATP molecule is removed from the chain to produce adenosine diphosphate (ADP) when water hydrolyzes ATP:

ATP + H₂O → ADP + HPO₄^2- + H⁺ + energy

However, removing a phosphate group from ADP to produce adenosine monophosphate (AMP) also produces extra energy.

Intracellular signaling

ATP is involved in signal transduction by serving as substrate for kinases, enzymes that transfer phosphate groups. Kinases are the most common ATP-binding proteins. They share a small number of common folds. Phosphorylation of a protein by a kinase can activate a cascade such as the mitogen-activated protein kinase cascade.

ATP is also a substrate of adenylate cyclase, most commonly in G protein-coupled receptor signal transduction pathways and is transformed to second messenger, cyclic AMP, which is involved in triggering calcium signals by the release of calcium from intracellular stores.^[35] This form of signal transduction is particularly important in brain function, although it is involved in the regulation of a multitude of other cellular processes.

DNA and RNA synthesis

ATP is one of four monomers required in the synthesis of RNA. The process is promoted by RNA polymerases. A similar process occurs in the formation of DNA, except that ATP is first converted to the deoxyribonucleotide dATP. Like many condensation reactions in nature, DNA replication and DNA transcription also consume ATP.

Amino acid activation in protein synthesis

Main article: Amino acid activation

Aminoacyl-tRNA synthetase enzymes consume ATP in the attachment tRNA to amino acids, forming aminoacyl-tRNA complexes. Aminoacyl transferase binds AMP-amino acid to tRNA. The coupling reaction proceeds in two steps:

1. aa + ATP ⟶ aa-AMP + PP_i
2. aa-AMP + tRNA ⟶ aa-tRNA + AMP

The amino acid is coupled to the penultimate nucleotide at the 3′-end of the tRNA (the A in the sequence CCA) via an ester bond (roll over in illustration).

ATP binding cassette transporter

Transporting chemicals out of a cell against a gradient is often associated with ATP hydrolysis. Transport is mediated by ATP binding cassette transporters. The human genome encodes 48 ABC transporters, that are used for exporting drugs, lipids, and other compounds.

Extracellular signalling and neurotransmission

Cells secrete ATP to communicate with other cells in a process called purinergic signalling. ATP serves as a neurotransmitter in many parts of the nervous system, modulates ciliary beating, affects vascular oxygen supply etc. ATP is either secreted directly across the cell membrane through channel proteins or is pumped into vesicles which then fuse with the membrane. Cells detect ATP using the purinergic receptor proteins P2X and P2Y. ATP has been shown to be a critically important signalling molecule for microglia - neuron interactions in the adult brain, as well as during brain development. Furthermore, tissue-injury induced ATP-signalling is a major factor in rapid microglial phenotype changes.

Muscle contraction

ATP fuels muscle contractions. Muscle contractions are regulated by signaling pathways, although different muscle types being regulated by specific pathways and stimuli based on their particular function. However, in all muscle types, contraction is performed by the proteins actin and myosin.

ATP is initially bound to myosin. When ATPase hydrolyzes the bound ATP into ADP and inorganic phosphate, myosin is positioned in a way that it can bind to actin. Myosin bound by ADP and P_i forms cross-bridges with actin and the subsequent release of ADP and P_i releases energy as the power stroke. The power stroke causes actin filament to slide past the myosin filament, shortening the muscle and causing a contraction. Another ATP molecule can then bind to myosin, releasing it from actin and allowing this process to repeat.

Protein solubility

ATP has recently been proposed to act as a biological hydrotrope and has been shown to affect proteome-wide solubility.

Abiogenic origins

Acetyl phosphate (AcP), a precursor to ATP, can readily be synthesized at modest yields from thioacetate in pH 7 and 20 °C and pH 8 and 50 °C, although acetyl phosphate is less stable in warmer temperatures and alkaline conditions than in cooler and acidic to neutral conditions. It is unable to promote polymerization of ribonucleotides and amino acids and was only capable of phosphorylation of organic compounds. It was shown that it can promote aggregation and stabilization of AMP in the presence of Na⁺, aggregation of nucleotides could promote polymerization above 75 °C in the absence of Na⁺. It is possible that polymerization promoted by AcP could occur at mineral surfaces. It was shown that ADP can only be phosphorylated to ATP by AcP and other nucleoside triphosphates were not phosphorylated by AcP. This might explain why all lifeforms use ATP to drive biochemical reactions.

ATP analogues

Biochemistry laboratories often use in vitro studies to explore ATP-dependent molecular processes. ATP analogs are also used in X-ray crystallography to determine a protein structure in complex with ATP, often together with other substrates.

Enzyme inhibitors of ATP-dependent enzymes such as kinases are needed to examine the binding sites and transition states involved in ATP-dependent reactions.

Most useful ATP analogs cannot be hydrolyzed as ATP would be; instead, they trap the enzyme in a structure closely related to the ATP-bound state. Adenosine 5′-(γ-thiotriphosphate) is an extremely common ATP analog in which one of the gamma-phosphate oxygens is replaced by a sulfur atom; this anion is hydrolyzed at a dramatically slower rate than ATP itself and functions as an inhibitor of ATP-dependent processes. In crystallographic studies, hydrolysis transition states are modeled by the bound vanadate ion.

Caution is warranted in interpreting the results of experiments using ATP analogs, since some enzymes can hydrolyze them at appreciable rates at high concentration.

Medical use

ATP is used intravenously for some heart-related conditions.

History

ATP was discovered in 1929 from muscle tissue by Karl Lohmann [de] and Jendrassik and, independently, by Cyrus Fiske and Yellapragada Subba Rao of Harvard Medical School, both teams competing against each other to find an assay for phosphorus.

It was proposed to be the intermediary between energy-yielding and energy-requiring reactions in cells by Fritz Albert Lipmann in 1941. He played a major role in establishing that ATP is the energy currency of a cell.

It was first synthesized in the laboratory by Alexander Todd in 1948, and he was awarded the Nobel Prize in Chemistry in 1957 partly for this work.

The 1978 Nobel Prize in Chemistry was awarded to Peter Dennis Mitchell for the discovery of the chemiosmotic mechanism of ATP synthesis.

The 1997 Nobel Prize in Chemistry was divided, one half jointly to Paul D. Boyer and John E. Walker "for their elucidation of the enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP)" and the other half to Jens C. Skou "for the first discovery of an ion-transporting enzyme, Na⁺, K⁺ -ATPase."

Climate sensitivity

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Climate_sensitivity 

Diagram of factors that determine climate sensitivity. After increasing CO₂ levels, there is an initial warming. This warming gets amplified by the net effect of climate feedbacks.

Climate sensitivity is a key measure in climate science and describes how much Earth's surface will warm for a doubling in the atmospheric carbon dioxide (CO₂) concentration. Its formal definition is: "The change in the surface temperature in response to a change in the atmospheric carbon dioxide (CO₂) concentration or other radiative forcing." This concept helps scientists understand the extent and magnitude of the effects of climate change.

The Earth's surface warms as a direct consequence of increased atmospheric CO₂, as well as increased concentrations of other greenhouse gases such as nitrous oxide and methane. The increasing temperatures have secondary effects on the climate system. These secondary effects are called climate feedbacks. Self-reinforcing feedbacks include for example the melting of sunlight-reflecting ice as well as higher evapotranspiration. The latter effect increases average atmospheric water vapour, which is itself a greenhouse gas.

Scientists do not know exactly how strong these climate feedbacks are. Therefore, it is difficult to predict the precise amount of warming that will result from a given increase in greenhouse gas concentrations. If climate sensitivity turns out to be on the high side of scientific estimates, the Paris Agreement goal of limiting global warming to below 2 °C (3.6 °F) will be even more difficult to achieve.

There are two main kinds of climate sensitivity: the transient climate response is the initial rise in global temperature when CO₂ levels double, and the equilibrium climate sensitivity is the larger long-term temperature increase after the planet adjusts to the doubling. Climate sensitivity is estimated by several methods: looking directly at temperature and greenhouse gas concentrations since the Industrial Revolution began around the 1750s, using indirect measurements from the Earth's distant past, and simulating the climate.

Fundamentals

The rate at which energy reaches Earth (as sunlight) and leaves Earth (as heat radiation to space) must balance, or the planet will get warmer or cooler. An imbalance between incoming and outgoing radiation energy is called radiative forcing. A warmer planet radiates heat to space faster and so a new balance is eventually reached, with a higher temperature and stored energy content. However, the warming of the planet also has knock-on effects, which create further warming in an exacerbating feedback loop. Climate sensitivity is a measure of how much temperature change a given amount of radiative forcing will cause.

Radiative forcing

Main articles: Radiative forcing and Earth's energy imbalance

Radiative forcings are generally quantified as Watts per square meter (W/m²) and averaged over Earth's uppermost surface defined as the top of the atmosphere. The magnitude of a forcing is specific to the physical driver and is defined relative to an accompanying time span of interest for its application. In the context of a contribution to long-term climate sensitivity from 1750 to 2020, the 50% increase in atmospheric CO
₂ is characterized by a forcing of about +2.1 W/m². In the context of shorter-term contributions to Earth's energy imbalance (i.e. its heating/cooling rate), time intervals of interest may be as short as the interval between measurement or simulation data samplings, and are thus likely to be accompanied by smaller forcing values. Forcings from such investigations have also been analyzed and reported at decadal time scales.

Radiative forcing leads to long-term changes in global temperature. A number of factors contribute radiative forcing: increased downwelling radiation from the greenhouse effect, variability in solar radiation from changes in planetary orbit, changes in solar irradiance, direct and indirect effects caused by aerosols (for example changes in albedo from cloud cover), and changes in land use (deforestation or the loss of reflective ice cover). In contemporary research, radiative forcing by greenhouse gases is well understood. As of 2019, large uncertainties remain for aerosols.

Key numbers

Further information: Carbon dioxide in Earth's atmosphere and Instrumental temperature record

Carbon dioxide (CO₂) levels rose from 280 parts per million (ppm) in the 18th century, when humans in the Industrial Revolution started burning significant amounts of fossil fuel such as coal, to over 415 ppm by 2020. As CO₂ is a greenhouse gas, it hinders heat energy from leaving the Earth's atmosphere. In 2016, atmospheric CO₂ levels had increased by 45% over preindustrial levels, and radiative forcing caused by increased CO₂ was already more than 50% higher than in pre-industrial times because of non-linear effects. Between the 18th-century start of the Industrial Revolution and the year 2020, the Earth's temperature rose by a little over one degree Celsius (about two degrees Fahrenheit).

Societal importance

Because the economics of climate change mitigation depend greatly on how quickly carbon neutrality needs to be achieved, climate sensitivity estimates can have important economic and policy-making implications. One study suggests that halving the uncertainty of the value for transient climate response (TCR) could save trillions of dollars. A higher climate sensitivity would mean more dramatic increases in temperature, which makes it more prudent to take significant climate action. If climate sensitivity turns out to be on the high end of what scientists estimate, the Paris Agreement goal of limiting global warming to well below 2 °C cannot be achieved, and temperature increases will exceed that limit, at least temporarily. One study estimated that emissions cannot be reduced fast enough to meet the 2 °C goal if equilibrium climate sensitivity (the long-term measure) is higher than 3.4 °C (6.1 °F). The more sensitive the climate system is to changes in greenhouse gas concentrations, the more likely it is to have decades when temperatures are much higher or much lower than the longer-term average.

Factors that determine sensitivity

The radiative forcing caused by a doubling of atmospheric CO₂ levels (from the pre-industrial 280 ppm) is approximately 3.7 watts per square meter (W/m²). In the absence of feedbacks, the energy imbalance would eventually result in roughly 1 °C (1.8 °F) of global warming. That figure is straightforward to calculate by using the Stefan–Boltzmann law and is undisputed.

A further contribution arises from climate feedbacks, both self-reinforcing and balancing. The uncertainty in climate sensitivity estimates is mostly from the feedbacks in the climate system, including water vapour feedback, ice–albedo feedback, cloud feedback, and lapse rate feedback. Balancing feedbacks tend to counteract warming by increasing the rate at which energy is radiated to space from a warmer planet. Self-reinfocing feedbacks increase warming; for example, higher temperatures can cause ice to melt, which reduces the ice area and the amount of sunlight the ice reflects, which in turn results in less heat energy being radiated back into space. The reflectiveness of a surface is called albedo. Climate sensitivity depends on the balance between those feedbacks.

Types

Schematic of how different measures of climate sensitivity relate to one another

Depending on the time scale, there are two main ways to define climate sensitivity: the short-term transient climate response (TCR) and the long-term equilibrium climate sensitivity (ECS), both of which incorporate the warming from exacerbating feedback loops. They are not discrete categories, but they overlap. Sensitivity to atmospheric CO₂ increases is measured in the amount of temperature change for doubling in the atmospheric CO₂ concentration.

Although the term "climate sensitivity" is usually used for the sensitivity to radiative forcing caused by rising atmospheric CO₂, it is a general property of the climate system. Other agents can also cause a radiative imbalance. Climate sensitivity is the change in surface air temperature per unit change in radiative forcing, and the climate sensitivity parameter is therefore expressed in units of °C/(W/m²). Climate sensitivity is approximately the same whatever the reason for the radiative forcing (such as from greenhouse gases or solar variation). When climate sensitivity is expressed as the temperature change for a level of atmospheric CO₂ double the pre-industrial level, its units are degrees Celsius (°C).

Transient climate response

Further information: Transient climate response to cumulative carbon emissions

The transient climate response (TCR) is defined as "the change in the global mean surface temperature, averaged over a 20-year period, centered at the time of atmospheric carbon dioxide doubling, in a climate model simulation" in which the atmospheric CO₂ concentration increases at 1% per year. That estimate is generated by using shorter-term simulations. The transient response is lower than the equilibrium climate sensitivity because slower feedbacks, which exacerbate the temperature increase, take more time to respond in full to an increase in the atmospheric CO₂ concentration. For instance, the deep ocean takes many centuries to reach a new steady state after a perturbation during which it continues to serve as heatsink, which cools the upper ocean. The IPCC literature assessment estimates that the TCR likely lies between 1 °C (1.8 °F) and 2.5 °C (4.5 °F).^[30]

A related measure is the transient climate response to cumulative carbon emissions (TCRE), which is the globally averaged surface temperature change after 1000 GtC of CO₂ has been emitted. As such, it includes not only temperature feedbacks to forcing but also the carbon cycle and carbon cycle feedbacks.

Equilibrium climate sensitivity

The equilibrium climate sensitivity (ECS) is the long-term temperature rise (equilibrium global mean near-surface air temperature) that is expected to result from a doubling of the atmospheric CO₂ concentration (ΔT_2×). It is a prediction of the new global mean near-surface air temperature once the CO₂ concentration has stopped increasing, and most of the feedbacks have had time to have their full effect. Reaching an equilibrium temperature can take centuries or even millennia after CO₂ has doubled. ECS is higher than TCR because of the oceans' short-term buffering effects. Computer models are used for estimating the ECS. A comprehensive estimate means that modelling the whole time span during which significant feedbacks continue to change global temperatures in the model, such as fully-equilibrating ocean temperatures, requires running a computer model that covers thousands of years. There are, however, less computing-intensive methods.

The IPCC Sixth Assessment Report (AR6) stated that there is high confidence that ECS is within the range of 2.5 °C to 4 °C, with a best estimate of 3 °C.

The long time scales involved with ECS make it arguably a less relevant measure for policy decisions around climate change.

Effective climate sensitivity

A common approximation to ECS is the effective equilibrium climate sensitivity, is an estimate of equilibrium climate sensitivity by using data from a climate system in model or real-world observations that is not yet in equilibrium. Estimates assume that the net amplification effect of feedbacks, as measured after some period of warming, will remain constant afterwards. That is not necessarily true, as feedbacks can change with time. In many climate models, feedbacks become stronger over time and so the effective climate sensitivity is lower than the real ECS.

Earth system sensitivity

By definition, equilibrium climate sensitivity does not include feedbacks that take millennia to emerge, such as long-term changes in Earth's albedo because of changes in ice sheets and vegetation. It also does not include the slow response of the deep oceans' warming, which takes millennia. Earth system sensitivity (ESS) incorporates the effects of these slower feedback loops, such as the change in Earth's albedo from the melting of large continental ice sheets, which covered much of the Northern Hemisphere during the Last Glacial Maximum and still cover Greenland and Antarctica. Changes in albedo as a result of changes in vegetation, as well as changes in ocean circulation, are also included. The longer-term feedback loops make the ESS larger than the ECS, possibly twice as large. Data from the geological history of Earth is used in estimating ESS. Differences between modern and long-ago climatic conditions mean that estimates of the future ESS are highly uncertain. The carbon cycle is not included in the definition of the ESS, but all other elements of the climate system are included.

Sensitivity to nature of forcing

Different forcing agents, such as greenhouse gases and aerosols, can be compared using their radiative forcing, the initial radiative imbalance averaged over the entire globe. Climate sensitivity is the amount of warming per radiative forcing. To a first approximation, the cause of the radiative imbalance does not matter. However, radiative forcing from sources other than CO₂ can cause slightly more or less surface warming than the same averaged forcing from CO₂. The amount of feedback varies mainly because the forcings are not uniformly distributed over the globe. Forcings that initially warm the Northern Hemisphere, land, or polar regions generate more self-reinforcing feedbacks (such as the ice-albedo feedback) than an equivalent forcing from CO₂, which is more uniformly distributed over the globe. This gives rise to more overall warming. Several studies indicate that human-emitted aerosols are more effective than CO₂ at changing global temperatures, and volcanic forcing is less effective. When climate sensitivity to CO₂ forcing is estimated using historical temperature and forcing (caused by a mix of aerosols and greenhouse gases), and that effect is not taken into account, climate sensitivity is underestimated.

State dependence

Artist impression of a Snowball Earth.

Climate sensitivity has been defined as the short- or long-term temperature change resulting from any doubling of CO₂, but there is evidence that the sensitivity of Earth's climate system is not constant. For instance, the planet has polar ice and high-altitude glaciers. Until the world's ice has completely melted, a self-reinforcing ice–albedo feedback loop makes the system more sensitive overall. Throughout Earth's history, multiple periods are thought to have snow and ice cover almost the entire globe. In most models of "Snowball Earth", parts of the tropics were at least intermittently free of ice cover. As the ice advanced or retreated, climate sensitivity must have been very high, as the large changes in area of ice cover would have made for a very strong ice–albedo feedback. Volcanic atmospheric composition changes are thought to have provided the radiative forcing needed to escape the snowball state.

Equilibrium climate sensitivity can change with climate.

Throughout the Quaternary period (the most recent 2.58 million years), climate has oscillated between glacial periods, the most recent one being the Last Glacial Maximum, and interglacial periods, the most recent one being the current Holocene, but the period's climate sensitivity is difficult to determine. The Paleocene–Eocene Thermal Maximum, about 55.5 million years ago, was unusually warm and may have been characterized by above-average climate sensitivity.

Climate sensitivity may further change if tipping points are crossed. It is unlikely that tipping points will cause short-term changes in climate sensitivity. If a tipping point is crossed, climate sensitivity is expected to change at the time scale of the subsystem that hits its tipping point. Especially if there are multiple interacting tipping points, the transition of climate to a new state may be difficult to reverse.

The two most common definitions of climate sensitivity specify the climate state: the ECS and the TCR are defined for a doubling with respect to the CO₂ levels in the pre-industrial era. Because of potential changes in climate sensitivity, the climate system may warm by a different amount after a second doubling of CO₂ from after a first doubling. The effect of any change in climate sensitivity is expected to be small or negligible in the first century after additional CO₂ is released into the atmosphere.

Estimation

Using Industrial Age (1750–present) data

Climate sensitivity can be estimated using the observed temperature increase, the observed ocean heat uptake, and the modelled or observed radiative forcing. The data are linked through a simple energy-balance model to calculate climate sensitivity. Radiative forcing is often modelled because Earth observation satellites measuring it has existed during only part of the Industrial Age (only since the late 1950s). Estimates of climate sensitivity calculated by using these global energy constraints have consistently been lower than those calculated by using other methods, around 2 °C (3.6 °F) or lower.

Estimates of transient climate response (TCR) that have been calculated from models and observational data can be reconciled if it is taken into account that fewer temperature measurements are taken in the polar regions, which warm more quickly than the Earth as a whole. If only regions for which measurements are available are used in evaluating the model, the differences in TCR estimates are negligible.

A very simple climate model could estimate climate sensitivity from Industrial Age data by waiting for the climate system to reach equilibrium and then by measuring the resulting warming, ΔT_eq (°C). Computation of the equilibrium climate sensitivity, S (°C), using the radiative forcing ΔF (W/m²) and the measured temperature rise, would then be possible. The radiative forcing resulting from a doubling of CO₂, F_2×CO2, is relatively well known, at about 3.7 W/m². Combining that information results in this equation:

${\displaystyle S=\mathrm{\Delta }{T}_{eq}\times F_{2\times C{O}_2}/\mathrm{\Delta }F}$.

However, the climate system is not in equilibrium since the actual warming lags the equilibrium warming, largely because the oceans take up heat and will take centuries or millennia to reach equilibrium. Estimating climate sensitivity from Industrial Age data requires an adjustment to the equation above. The actual forcing felt by the atmosphere is the radiative forcing minus the ocean's heat uptake, H (W/m²) and so climate sensitivity can be estimated:

${\displaystyle S=\mathrm{\Delta }T\times F_{2\times C{O}_2}/(\mathrm{\Delta }F-H).}$

The global temperature increase between the beginning of the Industrial Period, which is (taken as 1750, and 2011 was about 0.85 °C (1.53 °F). In 2011, the radiative forcing from CO₂ and other long-lived greenhouse gases (mainly methane, nitrous oxide, and chlorofluorocarbon) that have been emitted since the 18th century was roughly 2.8 W/m². The climate forcing, ΔF, also contains contributions from solar activity (+0.05 W/m²), aerosols (−0.9 W/m²), ozone (+0.35 W/m²), and other smaller influences, which brings the total forcing over the Industrial Period to 2.2 W/m², according to the best estimate of the IPCC Fifth Assessment Report in 2014, with substantial uncertainty. The ocean heat uptake, estimated by the same report to be 0.42 W/m², yields a value for S of 1.8 °C (3.2 °F).

Other strategies

In theory, Industrial Age temperatures could also be used to determine a time scale for the temperature response of the climate system and thus climate sensitivity: if the effective heat capacity of the climate system is known, and the timescale is estimated using autocorrelation of the measured temperature, an estimate of climate sensitivity can be derived. In practice, however, the simultaneous determination of the time scale and heat capacity is difficult.

Attempts have been made to use the 11-year solar cycle to constrain the transient climate response. Solar irradiance is about 0.9 W/m² higher during a solar maximum than during a solar minimum, and those effect can be observed in measured average global temperatures from 1959 to 2004. Unfortunately, the solar minima in the period coincided with volcanic eruptions, which have a cooling effect on the global temperature. Because the eruptions caused a larger and less well-quantified decrease in radiative forcing than the reduced solar irradiance, it is questionable whether useful quantitative conclusions can be derived from the observed temperature variations.

Observations of volcanic eruptions have also been used to try to estimate climate sensitivity, but as the aerosols from a single eruption last at most a couple of years in the atmosphere, the climate system can never come close to equilibrium, and there is less cooling than there would be if the aerosols stayed in the atmosphere for longer. Therefore, volcanic eruptions give information only about a lower bound on transient climate sensitivity.

Using data from Earth's past

Historical climate sensitivity can be estimated by using reconstructions of Earth's past temperatures and CO₂ levels. Paleoclimatologists have studied different geological periods, such as the warm Pliocene (5.3 to 2.6 million years ago) and the colder Pleistocene (2.6 million to 11,700 years ago), and sought periods that are in some way analogous to or informative about current climate change. Climates further back in Earth's history are more difficult to study because fewer data are available about them. For instance, past CO₂ concentrations can be derived from air trapped in ice cores, but as of 2020, the oldest continuous ice core is less than one million years old. Recent periods, such as the Last Glacial Maximum (LGM) (about 21,000 years ago) and the Mid-Holocene (about 6,000 years ago), are often studied, especially when more information about them becomes available.

A 2007 estimate of sensitivity made using data from the most recent 420 million years is consistent with sensitivities of current climate models and with other determinations. The Paleocene–Eocene Thermal Maximum (about 55.5 million years ago), a 20,000-year period during which massive amount of carbon entered the atmosphere and average global temperatures increased by approximately 6 °C (11 °F), also provides a good opportunity to study the climate system when it was in a warm state. Studies of the last 800,000 years have concluded that climate sensitivity was greater in glacial periods than in interglacial periods.

As the name suggests, the Last Glacial Maximum was much colder than today, and good data on atmospheric CO₂ concentrations and radiative forcing from that period are available. The period's orbital forcing was different from today's but had little effect on mean annual temperatures. Estimating climate sensitivity from the Last Glacial Maximum can be done by several different ways. One way is to use estimates of global radiative forcing and temperature directly. The set of feedback mechanisms active during the period, however, may be different from the feedbacks caused by a present doubling of CO₂, which introduces additional uncertainty. In a different approach, a model of intermediate complexity is used to simulate conditions during the period. Several versions of this single model are run, with different values chosen for uncertain parameters, such that each version has a different ECS. Outcomes that best simulate the LGM's observed cooling probably produce the most realistic ECS values.

Using climate models

Frequency distribution of equilibrium climate sensitivity based on simulations of the doubling of CO₂. Each model simulation has different estimates for processes which scientists do not sufficiently understand. Few of the simulations result in less than 2 °C (3.6 °F) of warming or significantly more than 4 °C (7.2 °F). However, the positive skew, which is also found in other studies, suggests that if carbon dioxide concentrations double, the probability of large or very large increases in temperature is greater than the probability of small increases.

Climate models simulate the CO₂-driven warming of the future as well as the past. They operate on principles similar to those underlying models that predict the weather, but they focus on longer-term processes. Climate models typically begin with a starting state and then apply physical laws and knowledge about biology to predict future states. As with weather modelling, no computer has the power to model the complexity of the entire planet and simplifications are used to reduce that complexity to something manageable. An important simplification divides Earth's atmosphere into model cells. For instance, the atmosphere might be divided into cubes of air ten or one hundred kilometers on each side. Each model cell is treated as if it were homogeneous (uniform). Calculations for model cells are much faster than trying to simulate each molecule of air separately.

A lower model resolution (large model cells and long time steps) takes less computing power but cannot simulate the atmosphere in as much detail. A model cannot simulate processes smaller than the model cells or shorter-term than a single time step. The effects of the smaller-scale and shorter-term processes must therefore be estimated by using other methods. Physical laws contained in the models may also be simplified to speed up calculations. The biosphere must be included in climate models. The effects of the biosphere are estimated by using data on the average behaviour of the average plant assemblage of an area under the modelled conditions. Climate sensitivity is therefore an emergent property of these models; it is not prescribed, but it follows from the interaction of all the modelled processes.

To estimate climate sensitivity, a model is run by using a variety of radiative forcings (doubling quickly, doubling gradually, or following historical emissions) and the temperature results are compared to the forcing applied. Different models give different estimates of climate sensitivity, but they tend to fall within a similar range, as described above.

Testing, comparisons, and climate ensembles

Modelling of the climate system can lead to a wide range of outcomes. Models are often run that use different plausible parameters in their approximation of physical laws and the behaviour of the biosphere, which forms a perturbed physics ensemble, which attempts to model the sensitivity of the climate to different types and amounts of change in each parameter. Alternatively, structurally-different models developed at different institutions are put together, creating an ensemble. By selecting only the simulations that can simulate some part of the historical climate well, a constrained estimate of climate sensitivity can be made. One strategy for obtaining more accurate results is placing more emphasis on climate models that perform well in general.

A model is tested using observations, paleoclimate data, or both to see if it replicates them accurately. If it does not, inaccuracies in the physical model and parametrizations are sought, and the model is modified. For models used to estimate climate sensitivity, specific test metrics that are directly and physically linked to climate sensitivity are sought. Examples of such metrics are the global patterns of warming, the ability of a model to reproduce observed relative humidity in the tropics and subtropics, patterns of heat radiation, and the variability of temperature around long-term historical warming. Ensemble climate models developed at different institutions tend to produce constrained estimates of ECS that are slightly higher than 3 °C (5.4 °F). The models with ECS slightly above 3 °C (5.4 °F) simulate the above situations better than models with a lower climate sensitivity.

Many projects and groups exist to compare and to analyse the results of multiple models. For instance, the Coupled Model Intercomparison Project (CMIP) has been running since the 1990s.

Historical estimates

Svante Arrhenius in the 19th century was the first person to quantify global warming as a consequence of a doubling of the concentration of CO₂. In his first paper on the matter, he estimated that global temperature would rise by around 5 to 6 °C (9.0 to 10.8 °F) if the quantity of CO₂ was doubled. In later work, he revised that estimate to 4 °C (7.2 °F). Arrhenius used Samuel Pierpont Langley's observations of radiation emitted by the full moon to estimate the amount of radiation that was absorbed by water vapour and by CO₂. To account for water vapour feedback, he assumed that relative humidity would stay the same under global warming.

The first calculation of climate sensitivity that used detailed measurements of absorption spectra, as well as the first calculation to use a computer for numerical integration of the radiative transfer through the atmosphere, was performed by Syukuro Manabe and Richard Wetherald in 1967. Assuming constant humidity, they computed an equilibrium climate sensitivity of 2.3 °C per doubling of CO₂, which they rounded to 2 °C, the value most often quoted from their work, in the abstract of the paper. The work has been called "arguably the greatest climate-science paper of all time" and "the most influential study of climate of all time."

A committee on anthropogenic global warming, convened in 1979 by the United States National Academy of Sciences and chaired by Jule Charney, estimated equilibrium climate sensitivity to be 3 °C (5.4 °F), plus or minus 1.5 °C (2.7 °F). The Manabe and Wetherald estimate (2 °C (3.6 °F)), James E. Hansen's estimate of 4 °C (7.2 °F), and Charney's model were the only models available in 1979. According to Manabe, speaking in 2004, "Charney chose 0.5 °C as a reasonable margin of error, subtracted it from Manabe's number, and added it to Hansen's, giving rise to the 1.5 to 4.5 °C (2.7 to 8.1 °F) range of likely climate sensitivity that has appeared in every greenhouse assessment since ...." In 2008, climatologist Stefan Rahmstorf said: "At that time [it was published], the [Charney report estimate's] range [of uncertainty] was on very shaky ground. Since then, many vastly improved models have been developed by a number of climate research centers around the world."

Assessment reports of IPCC

Historical estimates of climate sensitivity from the IPCC assessments. The first three reports gave a qualitative likely range, and the fourth and the fifth assessment report formally quantified the uncertainty. The dark blue range is judged as being more than 66% likely.

Despite considerable progress in the understanding of Earth's climate system, assessments continued to report similar uncertainty ranges for climate sensitivity for some time after the 1979 Charney report. The First Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), published in 1990, estimated that equilibrium climate sensitivity to a doubling of CO₂ lay between 1.5 and 4.5 °C (2.7 and 8.1 °F), with a "best guess in the light of current knowledge" of 2.5 °C (4.5 °F). The report used models with simplified representations of ocean dynamics. The IPCC supplementary report, 1992, which used full-ocean circulation models, saw "no compelling reason to warrant changing" the 1990 estimate; and the IPCC Second Assessment Report stated, "No strong reasons have emerged to change [these estimates]," In the reports, much of the uncertainty around climate sensitivity was attributed to insufficient knowledge of cloud processes. The 2001 IPCC Third Assessment Report also retained this likely range.

Authors of the 2007 IPCC Fourth Assessment Report stated that confidence in estimates of equilibrium climate sensitivity had increased substantially since the Third Annual Report. The IPCC authors concluded that ECS is very likely to be greater than 1.5 °C (2.7 °F) and likely to lie in the range 2 to 4.5 °C (3.6 to 8.1 °F), with a most likely value of about 3 °C (5.4 °F). The IPCC stated that fundamental physical reasons and data limitations prevent a climate sensitivity higher than 4.5 °C (8.1 °F) from being ruled out, but the climate sensitivity estimates in the likely range agreed better with observations and the proxy climate data.

The 2013 IPCC Fifth Assessment Report reverted to the earlier range of 1.5 to 4.5 °C (2.7 to 8.1 °F) (with high confidence), because some estimates using industrial-age data came out low. The report also stated that ECS is extremely unlikely to be less than 1 °C (1.8 °F) (high confidence), and it is very unlikely to be greater than 6 °C (11 °F) (medium confidence). Those values were estimated by combining the available data with expert judgement.

In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models was developed by scientific groups around the world. Across 27 global climate models, estimates of a higher climate sensitivity were produced. The values spanned 1.8 to 5.6 °C (3.2 to 10.1 °F) and exceeded 4.5 °C (8.1 °F) in 10 of them. The estimates for equilibrium climate sensitivity changed from 3.2 °C to 3.7 °C and the estimates for the transient climate response from 1.8 °C, to 2.0 °C. The cause of the increased ECS lies mainly in improved modelling of clouds. Temperature rises are now believed to cause sharper decreases in the number of low clouds, and fewer low clouds means more sunlight is absorbed by the planet and less reflected to space.

Remaining deficiencies in the simulation of clouds may have led to overestimates, as models with the highest ECS values were not consistent with observed warming. A fifth of the models began to 'run hot', predicting that global warming would produce significantly higher temperatures than is considered plausible. According to these models, known as hot models, average global temperatures in the worst-case scenario would rise by more than 5 °C above preindustrial levels by 2100, with a "catastrophic" impact on human society. In comparison, empirical observations combined with physics models indicate that the "very likely" range is between 2.3 and 4.7 °C. Models with a very high climate sensitivity are also known to be poor at reproducing known historical climate trends, such as warming over the 20th century or cooling during the last ice age. For these reasons the predictions of hot models are considered implausible, and have been given less weight by the IPCC in 2022.