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Climate variability and change
Climate variability and change
Climate variability and change
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Climate variability includes all the variations in the climate that last longer than individual weather events, whereas the term climate change only refers to those variations that persist for a longer period of time, typically decades or more. Climate change may refer to any time in Earth's history, but the term is now commonly used to describe contemporary climate change, often popularly referred to as global warming. Since the Industrial Revolution, the climate has increasingly been affected by human activities.[1]

The climate system receives nearly all of its energy from the sun and radiates energy to outer space. The balance of incoming and outgoing energy and the passage of the energy through the climate system is Earth's energy budget. When the incoming energy is greater than the outgoing energy, Earth's energy budget is positive and the climate system is warming. If more energy goes out, the energy budget is negative and Earth experiences cooling.

The energy moving through Earth's climate system finds expression in weather, varying on geographic scales and time. Long-term averages and variability of weather in a region constitute the region's climate. Such changes can be the result of "internal variability", when natural processes inherent to the various parts of the climate system alter the distribution of energy. Examples include variability in ocean basins such as the Pacific decadal oscillation and Atlantic multidecadal oscillation. Climate variability can also result from external forcing, when events outside of the climate system's components produce changes within the system. Examples include changes in solar output and volcanism.

Climate variability has consequences for sea level changes, plant life, and mass extinctions; it also affects human societies.

Terminology

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Climate variability is the term to describe variations in the mean state and other characteristics of climate (such as chances or possibility of extreme weather, etc.) "on all spatial and temporal scales beyond that of individual weather events." Some of the variability does not appear to be caused by known systems and occurs at seemingly random times. Such variability is called random variability or noise. On the other hand, periodic variability occurs relatively regularly and in distinct modes of variability or climate patterns.[2]

The term climate change is often used to refer specifically to anthropogenic climate change. Anthropogenic climate change is caused by human activity, as opposed to changes in climate that may have resulted as part of Earth's natural processes.[3] Global warming became the dominant popular term in 1988, but within scientific journals global warming refers to surface temperature increases while climate change includes global warming and everything else that increasing greenhouse gas levels affect.[4]

A related term, climatic change, was proposed by the World Meteorological Organization (WMO) in 1966 to encompass all forms of climatic variability on time-scales longer than 10 years, but regardless of cause. During the 1970s, the term climate change replaced climatic change to focus on anthropogenic causes, as it became clear that human activities had a potential to drastically alter the climate.[5] Climate change was incorporated in the title of the Intergovernmental Panel on Climate Change (IPCC) and the UN Framework Convention on Climate Change (UNFCCC). Climate change is now used as both a technical description of the process, as well as a noun used to describe the problem.[5]

Causes

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On the broadest scale, the rate at which energy is received from the Sun and the rate at which it is lost to space determine the equilibrium temperature and climate of Earth. This energy is distributed around the globe by winds, ocean currents,[6][7] and other mechanisms to affect the climates of different regions.[8]

Factors that can shape climate are called climate forcings or "forcing mechanisms".[9] These include processes such as variations in solar radiation, variations in the Earth's orbit, variations in the albedo or reflectivity of the continents, atmosphere, and oceans, mountain-building and continental drift and changes in greenhouse gas concentrations. External forcing can be either anthropogenic (e.g. increased emissions of greenhouse gases and dust) or natural (e.g., changes in solar output, the Earth's orbit, volcano eruptions).[10] There are a variety of climate change feedbacks that can either amplify or diminish the initial forcing. There are also key thresholds which when exceeded can produce rapid or irreversible change.

Some parts of the climate system, such as the oceans and ice caps, respond more slowly in reaction to climate forcings, while others respond more quickly. An example of fast change is the atmospheric cooling after a volcanic eruption, when volcanic ash reflects sunlight. Thermal expansion of ocean water after atmospheric warming is slow, and can take thousands of years. A combination is also possible, e.g., sudden loss of albedo in the Arctic Ocean as sea ice melts, followed by more gradual thermal expansion of the water.

Climate variability can also occur due to internal processes. Internal unforced processes often involve changes in the distribution of energy in the ocean and atmosphere, for instance, changes in the thermohaline circulation.

Internal variability

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There is seasonal variability in how new high temperature records have outpaced new low temperature records.[11]

Climatic changes due to internal variability sometimes occur in cycles or oscillations. For other types of natural climatic change, we cannot predict when it happens; the change is called random or stochastic.[12] From a climate perspective, the weather can be considered random.[13] If there are little clouds in a particular year, there is an energy imbalance and extra heat can be absorbed by the oceans. Due to climate inertia, this signal can be 'stored' in the ocean and be expressed as variability on longer time scales than the original weather disturbances.[14] If the weather disturbances are completely random, occurring as white noise, the inertia of glaciers or oceans can transform this into climate changes where longer-duration oscillations are also larger oscillations, a phenomenon called red noise.[15] Many climate changes have a random aspect and a cyclical aspect. This behavior is dubbed stochastic resonance.[15] Half of the 2021 Nobel prize on physics was awarded for this work to Klaus Hasselmann jointly with Syukuro Manabe for related work on climate modelling. While Giorgio Parisi who with collaborators introduced[16] the concept of stochastic resonance was awarded the other half but mainly for work on theoretical physics.

Ocean-atmosphere variability

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The ocean and atmosphere can work together to spontaneously generate internal climate variability that can persist for years to decades at a time.[17][18] These variations can affect global average surface temperature by redistributing heat between the deep ocean and the atmosphere[19][20] and/or by altering the cloud/water vapor/sea ice distribution which can affect the total energy budget of the Earth.[21][22]

Oscillations and cycles

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Colored bars show how El Niño years (red, regional warming) and La Niña years (blue, regional cooling) relate to overall global warming. The El Niño–Southern Oscillation has been linked to variability in longer-term global average temperature increase.

A climate oscillation or climate cycle is any recurring cyclical oscillation within global or regional climate. They are quasiperiodic (not perfectly periodic), so a Fourier analysis of the data does not have sharp peaks in the spectrum. Many oscillations on different time-scales have been found or hypothesized:[23]

  • the El Niño–Southern Oscillation (ENSO) – A large scale pattern of warmer (El Niño) and colder (La Niña) tropical sea surface temperatures in the Pacific Ocean with worldwide effects. It is a self-sustaining oscillation, whose mechanisms are well-studied.[24] ENSO is the most prominent known source of inter-annual variability in weather and climate around the world. The cycle occurs every two to seven years, with El Niño lasting nine months to two years within the longer term cycle.[25] The cold tongue of the equatorial Pacific Ocean is not warming as fast as the rest of the ocean, due to increased upwelling of cold waters off the west coast of South America.[26][27]
  • the Madden–Julian oscillation (MJO) – An eastward moving pattern of increased rainfall over the tropics with a period of 30 to 60 days, observed mainly over the Indian and Pacific Oceans.[28]
  • the North Atlantic oscillation (NAO) – Indices of the NAO are based on the difference of normalized sea-level pressure (SLP) between Ponta Delgada, Azores and Stykkishólmur/Reykjavík, Iceland. Positive values of the index indicate stronger-than-average westerlies over the middle latitudes.[29]
  • the Quasi-biennial oscillation – a well-understood oscillation in wind patterns in the stratosphere around the equator. Over a period of 28 months the dominant wind changes from easterly to westerly and back.[30]
  • Pacific Centennial Oscillation - a climate oscillation predicted by some climate models
  • the Pacific decadal oscillation – The dominant pattern of sea surface variability in the North Pacific on a decadal scale. During a "warm", or "positive", phase, the west Pacific becomes cool and part of the eastern ocean warms; during a "cool" or "negative" phase, the opposite pattern occurs. It is thought not as a single phenomenon, but instead a combination of different physical processes.[31]
  • the Interdecadal Pacific oscillation (IPO) – Basin wide variability in the Pacific Ocean with a period between 20 and 30 years.[32]
  • the Atlantic multidecadal oscillation – A pattern of variability in the North Atlantic of about 55 to 70 years, with effects on rainfall, droughts and hurricane frequency and intensity.[33]
  • North African climate cycles – climate variation driven by the North African Monsoon, with a period of tens of thousands of years.[34]
  • the Arctic oscillation (AO) and Antarctic oscillation (AAO) – The annular modes are naturally occurring, hemispheric-wide patterns of climate variability. On timescales of weeks to months they explain 20–30% of the variability in their respective hemispheres. The Northern Annular Mode or Arctic oscillation (AO) in the Northern Hemisphere, and the Southern Annular Mode or Antarctic oscillation (AAO) in the southern hemisphere. The annular modes have a strong influence on the temperature and precipitation of mid-to-high latitude land masses, such as Europe and Australia, by altering the average paths of storms. The NAO can be considered a regional index of the AO/NAM.[35] They are defined as the first EOF of sea level pressure or geopotential height from 20°N to 90°N (NAM) or 20°S to 90°S (SAM).
  • Dansgaard–Oeschger cycles – occurring on roughly 1,500-year cycles during the Last Glacial Maximum

Ocean current changes

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See also: Thermohaline circulation
A schematic of modern thermohaline circulation. Tens of millions of years ago, continental-plate movement formed a land-free gap around Antarctica, allowing the formation of the ACC, which keeps warm waters away from Antarctica.

The oceanic aspects of climate variability can generate variability on centennial timescales due to the ocean having hundreds of times more mass than in the atmosphere, and thus very high thermal inertia. For example, alterations to ocean processes such as thermohaline circulation play a key role in redistributing heat in the world's oceans.

Ocean currents transport a lot of energy from the warm tropical regions to the colder polar regions. Changes occurring around the last ice age (in technical terms, the last glacial period) show that the circulation in the North Atlantic can change suddenly and substantially, leading to global climate changes, even though the total amount of energy coming into the climate system did not change much. These large changes may have come from so called Heinrich events where internal instability of ice sheets caused huge ice bergs to be released into the ocean. When the ice sheet melts, the resulting water is very low in salt and cold, driving changes in circulation.[36]

Life

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Life affects climate through its role in the carbon and water cycles and through such mechanisms as albedo, evapotranspiration, cloud formation, and weathering.[37][38][39] Examples of how life may have affected past climate include:

External climate forcing

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Greenhouse gases

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Main article: Greenhouse gas
CO2 concentrations over the last 800,000 years as measured from ice cores (blue/green) and directly (black)

Whereas greenhouse gases released by the biosphere is often seen as a feedback or internal climate process, greenhouse gases emitted from volcanoes are typically classified as external by climatologists.[50] Greenhouse gases, such as CO2, methane and nitrous oxide, heat the climate system by trapping infrared light. Volcanoes are also part of the extended carbon cycle. Over very long (geological) time periods, they release carbon dioxide from the Earth's crust and mantle, counteracting the uptake by sedimentary rocks and other geological carbon dioxide sinks.

Since the Industrial Revolution, humanity has been adding to greenhouse gases by emitting CO2 from fossil fuel combustion, changing land use through deforestation, and has further altered the climate with aerosols (particulate matter in the atmosphere),[51] release of trace gases (e.g. nitrogen oxides, carbon monoxide, or methane).[52] Other factors, including land use, ozone depletion, animal husbandry (ruminant animals such as cattle produce methane[53]), and deforestation, also play a role.[54]

The US Geological Survey estimates are that volcanic emissions are at a much lower level than the effects of current human activities, which generate 100–300 times the amount of carbon dioxide emitted by volcanoes.[55] The annual amount put out by human activities may be greater than the amount released by supereruptions, the most recent of which was the Toba eruption in Indonesia 74,000 years ago.[56]

Orbital variations

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Milankovitch cycles from 800,000 years ago in the past to 800,000 years in the future.

Slight variations in Earth's motion lead to changes in the seasonal distribution of sunlight reaching the Earth's surface and how it is distributed across the globe. There is very little change to the area-averaged annually averaged sunshine; but there can be strong changes in the geographical and seasonal distribution. The three types of kinematic change are variations in Earth's eccentricity, changes in the tilt angle of Earth's axis of rotation, and precession of Earth's axis. Combined, these produce Milankovitch cycles which affect climate and are notable for their correlation to glacial and interglacial periods,[57] their correlation with the advance and retreat of the Sahara,[57] and for their appearance in the stratigraphic record.[58][59]

During the glacial cycles, there was a high correlation between CO2 concentrations and temperatures. Early studies indicated that CO2 concentrations lagged temperatures, but it has become clear that this is not always the case.[60] When ocean temperatures increase, the solubility of CO2 decreases so that it is released from the ocean. The exchange of CO2 between the air and the ocean can also be impacted by further aspects of climatic change.[61] These and other self-reinforcing processes allow small changes in Earth's motion to have a large effect on climate.[60]

Solar output

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Variations in solar activity during the last several centuries based on observations of sunspots and beryllium isotopes. The period of extraordinarily few sunspots in the late 17th century was the Maunder minimum.

The Sun is the predominant source of energy input to the Earth's climate system. Other sources include geothermal energy from the Earth's core, tidal energy from the Moon and heat from the decay of radioactive compounds. Both long term variations in solar intensity are known to affect global climate.[62] Solar output varies on shorter time scales, including the 11-year solar cycle[63] and longer-term modulations.[64] Correlation between sunspots and climate and tenuous at best.[62]

Three to four billion years ago, the Sun emitted only 75% as much power as it does today.[65] If the atmospheric composition had been the same as today, liquid water should not have existed on the Earth's surface. However, there is evidence for the presence of water on the early Earth, in the Hadean[66][67] and Archean[68][66] eons, leading to what is known as the faint young Sun paradox.[69] Hypothesized solutions to this paradox include a vastly different atmosphere, with much higher concentrations of greenhouse gases than currently exist.[70] Over the following approximately 4 billion years, the energy output of the Sun increased. Over the next five billion years, the Sun's ultimate death as it becomes a red giant and then a white dwarf will have large effects on climate, with the red giant phase possibly ending any life on Earth that survives until that time.[71]

Volcanism

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In atmospheric temperature from 1979 to 2010, determined by MSU NASA satellites, effects appear from aerosols released by major volcanic eruptions (El Chichón and Pinatubo). El Niño is a separate event, from ocean variability.

The volcanic eruptions considered to be large enough to affect the Earth's climate on a scale of more than 1 year are the ones that inject over 100,000 tons of SO2 into the stratosphere.[72] This is due to the optical properties of SO2 and sulfate aerosols, which strongly absorb or scatter solar radiation, creating a global layer of sulfuric acid haze.[73] On average, such eruptions occur several times per century, and cause cooling (by partially blocking the transmission of solar radiation to the Earth's surface) for a period of several years. Although volcanoes are technically part of the lithosphere, which itself is part of the climate system, the IPCC explicitly defines volcanism as an external forcing agent.[74]

Notable eruptions in the historical records are the 1991 eruption of Mount Pinatubo which lowered global temperatures by about 0.5 °C (0.9 °F) for up to three years,[75][76] and the 1815 eruption of Mount Tambora causing the Year Without a Summer.[77]

At a larger scale—a few times every 50 million to 100 million years—the eruption of large igneous provinces brings large quantities of igneous rock from the mantle and lithosphere to the Earth's surface. Carbon dioxide in the rock is then released into the atmosphere.[78] [79] Small eruptions, with injections of less than 0.1 Mt of sulfur dioxide into the stratosphere, affect the atmosphere only subtly, as temperature changes are comparable with natural variability. However, because smaller eruptions occur at a much higher frequency, they too significantly affect Earth's atmosphere.[72][80]

Plate tectonics

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Main article: Plate tectonics

Over the course of millions of years, the motion of tectonic plates reconfigures global land and ocean areas and generates topography. This can affect both global and local patterns of climate and atmosphere-ocean circulation.[81]

The position of the continents determines the geometry of the oceans and therefore influences patterns of ocean circulation. The locations of the seas are important in controlling the transfer of heat and moisture across the globe, and therefore, in determining global climate. A recent example of tectonic control on ocean circulation is the formation of the Isthmus of Panama about 5 million years ago, which shut off direct mixing between the Atlantic and Pacific Oceans. This strongly affected the ocean dynamics of what is now the Gulf Stream and may have led to Northern Hemisphere ice cover.[82][83] During the Carboniferous period, about 300 to 360 million years ago, plate tectonics may have triggered large-scale storage of carbon and increased glaciation.[84] Geologic evidence points to a "megamonsoonal" circulation pattern during the time of the supercontinent Pangaea, and climate modeling suggests that the existence of the supercontinent was conducive to the establishment of monsoons.[85]

The size of continents is also important. Because of the stabilizing effect of the oceans on temperature, yearly temperature variations are generally lower in coastal areas than they are inland. A larger supercontinent will therefore have more area in which climate is strongly seasonal than will several smaller continents or islands.

Other mechanisms

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It has been postulated that ionized particles known as cosmic rays could impact cloud cover and thereby the climate. As the sun shields the Earth from these particles, changes in solar activity were hypothesized to influence climate indirectly as well. To test the hypothesis, CERN designed the CLOUD experiment, which showed the effect of cosmic rays is too weak to influence climate noticeably.[86][87]

Evidence exists that the Chicxulub asteroid impact some 66 million years ago had severely affected the Earth's climate. Large quantities of sulfate aerosols were kicked up into the atmosphere, decreasing global temperatures by up to 26 °C and producing sub-freezing temperatures for a period of 3–16 years. The recovery time for this event took more than 30 years.[88] The large-scale use of nuclear weapons has also been investigated for its impact on the climate. The hypothesis is that soot released by large-scale fires blocks a significant fraction of sunlight for as much as a year, leading to a sharp drop in temperatures for a few years. This possible event is described as nuclear winter.[89]

Humans' use of land impact how much sunlight the surface reflects and the concentration of dust. Cloud formation is not only influenced by how much water is in the air and the temperature, but also by the amount of aerosols in the air such as dust.[90] Globally, more dust is available if there are many regions with dry soils, little vegetation and strong winds.[91]

Evidence and measurement of climate changes

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Paleoclimatology is the study of changes in climate through the entire history of Earth. It uses a variety of proxy methods from the Earth and life sciences to obtain data preserved within things such as rocks, sediments, ice sheets, tree rings, corals, shells, and microfossils. It then uses the records to determine the past states of the Earth's various climate regions and its atmospheric system. Direct measurements give a more complete overview of climate variability.

Direct measurements

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Climate changes that occurred after the widespread deployment of measuring devices can be observed directly. Reasonably complete global records of surface temperature are available beginning from the mid-late 19th century. Further observations are derived indirectly from historical documents. Satellite cloud and precipitation data has been available since the 1970s.[92]

Historical climatology is the study of historical changes in climate and their effect on human history and development. The primary sources include written records such as sagas, chronicles, maps and local history literature as well as pictorial representations such as paintings, drawings and even rock art. Climate variability in the recent past may be derived from changes in settlement and agricultural patterns.[93] Archaeological evidence, oral history and historical documents can offer insights into past changes in the climate. Changes in climate have been linked to the rise[94] and the collapse of various civilizations.[93]

Proxy measurements

[edit]
Variations in CO2, temperature and dust from the Vostok ice core over the last 450,000 years.

Various archives of past climate are present in rocks, trees and fossils. From these archives, indirect measures of climate, so-called proxies, can be derived. Quantification of climatological variation of precipitation in prior centuries and epochs is less complete but approximated using proxies such as marine sediments, ice cores, cave stalagmites, and tree rings.[95] Stress, too little precipitation or unsuitable temperatures, can alter the growth rate of trees, which allows scientists to infer climate trends by analyzing the growth rate of tree rings. This branch of science studying this called dendroclimatology.[96] Glaciers leave behind moraines that contain a wealth of material—including organic matter, quartz, and potassium that may be dated—recording the periods in which a glacier advanced and retreated.

Analysis of ice in cores drilled from an ice sheet such as the Antarctic ice sheet, can be used to show a link between temperature and global sea level variations. The air trapped in bubbles in the ice can also reveal the CO2 variations of the atmosphere from the distant past, well before modern environmental influences. The study of these ice cores has been a significant indicator of the changes in CO2 over many millennia, and continues to provide valuable information about the differences between ancient and modern atmospheric conditions. The 18O/16O ratio in calcite and ice core samples used to deduce ocean temperature in the distant past is an example of a temperature proxy method.

The remnants of plants, and specifically pollen, are also used to study climatic change. Plant distributions vary under different climate conditions. Different groups of plants have pollen with distinctive shapes and surface textures, and since the outer surface of pollen is composed of a very resilient material, they resist decay. Changes in the type of pollen found in different layers of sediment indicate changes in plant communities. These changes are often a sign of a changing climate.[97][98] As an example, pollen studies have been used to track changing vegetation patterns throughout the Quaternary glaciations[99] and especially since the last glacial maximum.[100] Remains of beetles are common in freshwater and land sediments. Different species of beetles tend to be found under different climatic conditions. Given the extensive lineage of beetles whose genetic makeup has not altered significantly over the millennia, knowledge of the present climatic range of the different species, and the age of the sediments in which remains are found, past climatic conditions may be inferred.[101]

Analysis and uncertainties

[edit]

One difficulty in detecting climate cycles is that the Earth's climate has been changing in non-cyclic ways over most paleoclimatological timescales. Currently we are in a period of anthropogenic global warming. In a larger timeframe, the Earth is emerging from the latest ice age, cooling from the Holocene climatic optimum and warming from the "Little Ice Age", which means that climate has been constantly changing over the last 15,000 years or so. During warm periods, temperature fluctuations are often of a lesser amplitude. The Pleistocene period, dominated by repeated glaciations, developed out of more stable conditions in the Miocene and Pliocene climate. Holocene climate has been relatively stable. All of these changes complicate the task of looking for cyclical behavior in the climate.

Positive feedback, negative feedback, and ecological inertia from the land-ocean-atmosphere system often attenuate or reverse smaller effects, whether from orbital forcings, solar variations or changes in concentrations of greenhouse gases. Certain feedbacks involving processes such as clouds are also uncertain; for contrails, natural cirrus clouds, oceanic dimethyl sulfide and a land-based equivalent, competing theories exist concerning effects on climatic temperatures, for example contrasting the Iris hypothesis and CLAW hypothesis.

Impacts

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Life

[edit]
Top: Arid ice age climate
Middle: Atlantic Period, warm and wet
Bottom: Potential vegetation in climate now if not for human effects like agriculture.[102]

Vegetation

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A change in the type, distribution and coverage of vegetation may occur given a change in the climate. Some changes in climate may result in increased precipitation and warmth, resulting in improved plant growth and the subsequent sequestration of airborne CO2. Though an increase in CO2 may benefit plants, some factors can diminish this increase. If there is an environmental change such as drought, increased CO2 concentrations will not benefit the plant.[103] So even though climate change does increase CO2 emissions, plants will often not use this increase as other environmental stresses put pressure on them.[104] However, sequestration of CO2 is expected to affect the rate of many natural cycles like plant litter decomposition rates.[105] A gradual increase in warmth in a region will lead to earlier flowering and fruiting times, driving a change in the timing of life cycles of dependent organisms. Conversely, cold will cause plant bio-cycles to lag.[106]

Larger, faster or more radical changes, however, may result in vegetation stress, rapid plant loss and desertification in certain circumstances.[107][108][109] An example of this occurred during the Carboniferous Rainforest Collapse (CRC), an extinction event 300 million years ago. At this time vast rainforests covered the equatorial region of Europe and America. Climate change devastated these tropical rainforests, abruptly fragmenting the habitat into isolated 'islands' and causing the extinction of many plant and animal species.[107]

Wildlife

[edit]

One of the most important ways animals can deal with climatic change is migration to warmer or colder regions.[110] On a longer timescale, evolution makes ecosystems including animals better adapted to a new climate.[111] Rapid or large climate change can cause mass extinctions when creatures are stretched too far to be able to adapt.[112]

Humanity

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Collapses of past civilizations such as the Maya may be related to cycles of precipitation, especially drought, that in this example also correlates to the Western Hemisphere Warm Pool. Around 70 000 years ago the Toba supervolcano eruption created an especially cold period during the ice age, leading to a possible genetic bottleneck in human populations.

Changes in the cryosphere

[edit]

Glaciers and ice sheets

[edit]

Glaciers are considered among the most sensitive indicators of a changing climate.[113] Their size is determined by a mass balance between snow input and melt output. As temperatures increase, glaciers retreat unless snow precipitation increases to make up for the additional melt. Glaciers grow and shrink due both to natural variability and external forcings. Variability in temperature, precipitation and hydrology can strongly determine the evolution of a glacier in a particular season.

The most significant climate processes since the middle to late Pliocene (approximately 3 million years ago) are the glacial and interglacial cycles. The present interglacial period (the Holocene) has lasted about 11,700 years.[114] Shaped by orbital variations, responses such as the rise and fall of continental ice sheets and significant sea-level changes helped create the climate. Other changes, including Heinrich events, Dansgaard–Oeschger events and the Younger Dryas, however, illustrate how glacial variations may also influence climate without the orbital forcing.

Sea level change

[edit]

During the Last Glacial Maximum, some 25,000 years ago, sea levels were roughly 130 m lower than today. The deglaciation afterwards was characterized by rapid sea level change.[115] In the early Pliocene, global temperatures were 1–2˚C warmer than the present temperature, yet sea level was 15–25 meters higher than today.[116]

Sea ice

[edit]

Sea ice plays an important role in Earth's climate as it affects the total amount of sunlight that is reflected away from the Earth.[117] In the past, the Earth's oceans have been almost entirely covered by sea ice on a number of occasions, when the Earth was in a so-called Snowball Earth state,[118] and completely ice-free in periods of warm climate.[119] When there is a lot of sea ice present globally, especially in the tropics and subtropics, the climate is more sensitive to forcings as the ice–albedo feedback is very strong.[120]

Climate history

[edit]
See also: List of periods and events in climate history and Paleoclimatology

Various climate forcings are typically in flux throughout geologic time, and some processes of the Earth's temperature may be self-regulating. For example, during the Snowball Earth period, large glacial ice sheets spanned to Earth's equator, covering nearly its entire surface, and very high albedo created extremely low temperatures, while the accumulation of snow and ice likely removed carbon dioxide through atmospheric deposition. However, the absence of plant cover to absorb atmospheric CO2 emitted by volcanoes meant that the greenhouse gas could accumulate in the atmosphere. There was also an absence of exposed silicate rocks, which use CO2 when they undergo weathering. This created a warming that later melted the ice and brought Earth's temperature back up.

Paleo-eocene thermal maximum

[edit]
Climate changes over the past 65 million years, using proxy data including Oxygen-18 ratios from foraminifera.

The Paleocene–Eocene Thermal Maximum (PETM) was a time period with more than 5–8 °C global average temperature rise across the event.[121] This climate event occurred at the time boundary of the Paleocene and Eocene geological epochs.[122] During the event large amounts of methane was released, a potent greenhouse gas.[123] The PETM represents a "case study" for modern climate change as in the greenhouse gases were released in a geologically relatively short amount of time.[121] During the PETM, a mass extinction of organisms in the deep ocean took place.[124]

The Cenozoic

[edit]

Throughout the Cenozoic, multiple climate forcings led to warming and cooling of the atmosphere, which led to the early formation of the Antarctic ice sheet, subsequent melting, and its later reglaciation. The temperature changes occurred somewhat suddenly, at carbon dioxide concentrations of about 600–760 ppm and temperatures approximately 4 °C warmer than today. During the Pleistocene, cycles of glaciations and interglacials occurred on cycles of roughly 100,000 years, but may stay longer within an interglacial when orbital eccentricity approaches zero, as during the current interglacial. Previous interglacials such as the Eemian phase created temperatures higher than today, higher sea levels, and some partial melting of the West Antarctic ice sheet.

Climatological temperatures substantially affect cloud cover and precipitation. At lower temperatures, air can hold less water vapour, which can lead to decreased precipitation.[125] During the Last Glacial Maximum of 18,000 years ago, thermal-driven evaporation from the oceans onto continental landmasses was low, causing large areas of extreme desert, including polar deserts (cold but with low rates of cloud cover and precipitation).[102] In contrast, the world's climate was cloudier and wetter than today near the start of the warm Atlantic Period of 8000 years ago.[102]

The Holocene

[edit]
Temperature change over the past 12 000 years, from various sources. The thick black curve is an average.

The Holocene is characterized by a long-term cooling starting after the Holocene Optimum, when temperatures were probably only just below current temperatures (second decade of the 21st century),[126] and a strong African Monsoon created grassland conditions in the Sahara during the Neolithic Subpluvial. Since that time, several cooling events have occurred, including:

In contrast, several warm periods have also taken place, and they include but are not limited to:

Certain effects have occurred during these cycles. For example, during the Medieval Warm Period, the American Midwest was in drought, including the Sand Hills of Nebraska which were active sand dunes. The black death plague of Yersinia pestis also occurred during Medieval temperature fluctuations, and may be related to changing climates.

Solar activity may have contributed to part of the modern warming that peaked in the 1930s. However, solar cycles fail to account for warming observed since the 1980s to the present day.[citation needed] Events such as the opening of the Northwest Passage and recent record low ice minima of the modern Arctic shrinkage have not taken place for at least several centuries, as early explorers were all unable to make an Arctic crossing, even in summer. Shifts in biomes and habitat ranges are also unprecedented, occurring at rates that do not coincide with known climate oscillations [citation needed].

Modern climate change and global warming

[edit]
Main article: Climate change

As a consequence of humans emitting greenhouse gases, global surface temperatures have started rising. Global warming is an aspect of modern climate change, a term that also includes the observed changes in precipitation, storm tracks and cloudiness. As a consequence, glaciers worldwide have been found to be shrinking significantly.[127][128] Land ice sheets in both Antarctica and Greenland have been losing mass since 2002 and have seen an acceleration of ice mass loss since 2009.[129] Global sea levels have been rising as a consequence of thermal expansion and ice melt. The decline in Arctic sea ice, both in extent and thickness, over the last several decades is further evidence for rapid climate change.[130]

Variability between regions

[edit]
Examples of regional climate variability
  • Land-ocean. Surface air temperatures over land masses have been increasing faster than those over the ocean, the ocean absorbing about 90% of excess heat.
    Land-ocean. Surface air temperatures over land masses have been increasing faster than those over the ocean,[131] the ocean absorbing about 90% of excess heat.[132]
  • Hemispheres. The Hemispheres' average temperature changes have diverged because of the North's greater percentage of landmass, and due to global ocean currents.
    Hemispheres. The Hemispheres' average temperature changes[133] have diverged because of the North's greater percentage of landmass, and due to global ocean currents.[134]
  • Latitude bands. Three latitude bands that respectively cover 30, 40 and 30 percent of the global surface area show mutually distinct temperature growth patterns in recent decades.
    Latitude bands. Three latitude bands that respectively cover 30, 40 and 30 percent of the global surface area show mutually distinct temperature growth patterns in recent decades.[135]
  • Altitude. A warming stripes graphic (blues denote cool, reds denote warm) shows how the greenhouse effect traps heat in the lower atmosphere and oceans, so that the upper atmosphere, receiving less reflected energy, cools.
    Altitude. A warming stripes graphic (blues denote cool, reds denote warm) shows how the greenhouse effect traps heat in the lower atmosphere and oceans, so that the upper atmosphere, receiving less reflected energy, cools.[136][137]
  • Global versus regional. For geographical and statistical reasons, larger year-to-year variations are expected for localized geographic regions (e.g., the Caribbean) than for global averages.
    Global versus regional. For geographical and statistical reasons, larger year-to-year variations are expected[138] for localized geographic regions (e.g., the Caribbean) than for global averages.[139]
  • Relative deviation. Though northern America has warmed more than its tropics, the tropics have more clearly departed from normal historical variability (colored bands: 1σ, 2σ standard deviations).
    Relative deviation. Though northern America has warmed more than its tropics, the tropics have more clearly departed from normal historical variability (colored bands: 1σ, 2σ standard deviations).[140]
Global warming has varied substantially by latitude, with the northernmost latitude zones experiencing the largest temperature increases.

In addition to global climate variability and global climate change over time, numerous climatic variations occur contemporaneously across different physical regions.

The oceans' absorption of about 90% of excess heat has helped to cause land surface temperatures to grow more rapidly than sea surface temperatures.[132] The Northern Hemisphere, having a larger landmass-to-ocean ratio than the Southern Hemisphere, shows greater average temperature increases.[134] Variations across different latitude bands also reflect this divergence in average temperature increase, with the temperature increase of northern extratropics exceeding that of the tropics, which in turn exceeds that of the southern extratropics.[135]

Upper regions of the atmosphere have been cooling contemporaneously with a warming in the lower atmosphere, confirming the action of the greenhouse effect and ozone depletion.[137]

Observed regional climatic variations confirm predictions concerning ongoing changes, for example, by contrasting (smoother) year-to-year global variations with (more volatile) year-to-year variations in localized regions.[138] Conversely, comparing different regions' warming patterns to their respective historical variabilities, allows the raw magnitudes of temperature changes to be placed in the perspective of what is normal variability for each region.[140]

Regional variability observations permit study of regionalized climate tipping points such as rainforest loss, ice sheet and sea ice melt, and permafrost thawing.[141] Such distinctions underlie research into a possible global cascade of tipping points.[141]

See also

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Notes

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References

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Climate variability and change

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Climate variability and change refer to fluctuations in climate elements such as temperature, precipitation, and wind patterns that deviate from long-term averages, as well as persistent shifts in those averages, occurring over timescales from seasons to millennia due to internal atmospheric-ocean dynamics and external forcings including solar variations, volcanic eruptions, orbital changes, and anthropogenic greenhouse gas emissions. Natural variability dominates shorter-term changes, exemplified by oscillations like the El Niño-Southern Oscillation (ENSO) that redistribute heat globally, while longer cycles such as Milankovitch orbital forcings have orchestrated alternations over 100,000-year periods by altering solar insolation distribution. Instrumental records indicate global average surface temperatures have increased by about 1.1°C since 1850, with roughly two-thirds of this rise post-1975, corroborated across datasets like HadCRUT and Berkeley Earth, though effects and data homogenization methods introduce uncertainties in precise quantification. Anthropogenic CO2 emissions, rising from pre-industrial ~280 ppm to over 420 ppm, enhance the by trapping outgoing infrared radiation, as evidenced by satellite spectral measurements, yet the net to doubled CO2—estimated at 1.5–4.5°C in mainstream models—remains empirically contested, with observed warming rates falling below many projections and natural factors like solar activity and ocean cycles contributing substantially to recent trends. Controversies persist over attribution, as institutional narratives often emphasize human dominance while downplaying natural variability's role and discrepancies between model hindcasts and satellite-era observations, underscoring the need for skepticism toward sources with evident incentives for alarmist framing.

Terminology and Concepts

Definitions of Variability and Change

variability encompasses fluctuations in statistics, such as averages, extremes, and probabilities of , , and other elements, occurring over timescales from seasons to several decades, distinct from individual events. These variations arise primarily from internal atmospheric and oceanic processes, including phenomena like the El Niño-Southern Oscillation (ENSO), which redistribute heat and moisture globally, leading to temporary deviations from long-term norms without implying a permanent alteration in the 's baseline state. For instance, ENSO events can cause widespread or flooding on interannual scales, but they typically revert toward the mean over time. In contrast, climate change denotes a long-term, statistically detectable shift in the mean state of the climate or its variability, persisting for periods of decades or longer, identifiable through methods like or statistical tests. This definition, as articulated by the (IPCC), encompasses changes attributable to both natural external forcings—such as variations or volcanic eruptions—and anthropogenic factors, including alterations to atmospheric composition from human emissions. Unlike variability, which oscillates around a stable reference mean, climate change involves directional trends, such as sustained increases in global mean surface temperature observed since the late , exceeding natural variability thresholds in multiple datasets. The demarcation between variability and change hinges on duration, persistence, and : short-term anomalies (e.g., multi-year ENSO cycles) represent variability if they do not alter the underlying distribution, whereas prolonged shifts, like the warming or recent anthropogenic warming, qualify as change when they exceed historical ranges or demonstrate non-reverting trends. This distinction is crucial for attribution studies, as natural variability can modulate or mask underlying change signals, requiring separation via modeling and paleoclimate proxies to discern causal drivers. Sources emphasizing only human-induced aspects of change, such as certain policy-oriented reports, may understate natural precedents, but empirical records confirm has undergone multiple natural shifts over millennia, independent of human influence.

Key Metrics and Indicators

anomalies serve as a primary indicator of climate variability and change, with datasets from and NOAA showing the 2024 annual average at approximately 1.28°C above the 20th-century baseline, marking it as the warmest year on record. This warming is modulated by natural oscillations like El Niño-Southern Oscillation (ENSO), which contributed to elevated temperatures in 2023-2024, though the long-term trend since 1880 reflects a rise of about 1.1°C. For 2025 through August, global temperatures ranked second highest, trailing only 2024, amid a transition to neutral ENSO conditions. Atmospheric carbon dioxide (CO₂) concentrations, measured at , reached a monthly average of 425.48 ppm in 2025, continuing an upward trajectory from 315 ppm in 1958, with annual increases accelerating due to anthropogenic emissions. The May 2025 peak hit 430.2 ppm, the second-largest year-over-year jump in the 67-year record, underscoring persistent despite natural sinks absorbing roughly half of emissions. Global mean has risen at an average rate of 3.4 mm per year since 1993, as tracked by satellite altimetry, totaling 8-9 inches (21-24 cm) since 1880, driven by and land ice melt. In 2024, the rate accelerated beyond expectations, linked to extreme warming, reaching a record high of 101.4 mm above 1993 levels by year-end. Upper heat content has increased steadily since the 1970s, absorbing over 90% of Earth's excess energy, with the top 2000 meters gaining heat at rates exceeding prior decades, as evidenced by float and ship-based measurements. This accumulation, equivalent to roughly four bombs per second in recent years, reflects both radiative imbalance and ocean circulation changes. Arctic sea ice minimum extent reached 4.60 million square kilometers in September 2025, tying for the 10th lowest in the satellite era (since 1979), with a long-term decline of 12.2% per decade amid reduced summer melt onset and extent. Variability from weather patterns and ENSO influences annual minima, but the trend indicates diminished ice volume and thickness. Other indicators include shifts in precipitation extremes and drought indices, such as the U.S. Climate Extremes Index, which tracks departures in , , and drought, showing increased frequency of extremes in recent decades, though regional patterns vary due to internal variability. These metrics, derived from instrumental records and proxies, quantify changes against natural baselines but require accounting for data adjustments and urban heat effects in surface observations.

Natural Drivers

Internal Climate Variability


Internal climate variability refers to natural fluctuations in the arising from chaotic internal dynamics and interactions among components such as the atmosphere, oceans, land surface, and , without requiring external forcings. These processes generate preferred spatial patterns of variability, known as modes, that operate on timescales from intraseasonal to multidecadal and contribute substantially to climate predictability on subseasonal to decadal horizons. Internal variability is generally larger in the extratropics than and stronger in winter than summer, influencing regional patterns and masking forced trends in short-term observations. The El Niño-Southern Oscillation (ENSO) represents a dominant interannual mode, with cycles typically lasting 2-7 years, driven by coupled ocean-atmosphere interactions in the tropical Pacific. During El Niño phases, enhanced easterly weaken, leading to warmer sea surface temperatures (SSTs) in the central-eastern Pacific, which shift circulation and generate global teleconnections affecting and temperature; for instance, El Niño events have been linked to increased hurricane activity in the Pacific and droughts in . La Niña phases, conversely, feature cooler SSTs and strengthened trades, often resulting in opposite impacts, such as floods in and drier conditions in the southern U.S. ENSO variability accounts for much of the year-to-year global temperature fluctuations, with strong events capable of altering annual averages by up to 0.15°C. Decadal to multidecadal modes include the (PDO), characterized by SST anomalies in the North Pacific north of 20°N, with phases shifting roughly every 20-30 years. Positive PDO phases feature cooling in the central North Pacific and warming along the coasts, impacting marine ecosystems, such as reduced salmon catches during cool phases, and modulating n precipitation patterns. The PDO enhances El Niño teleconnections to during positive phases, amplifying winter precipitation in the southwestern U.S. and diminishing La Niña effects. The Atlantic Multidecadal Oscillation (AMO) exhibits SST variability in the North Atlantic on 60-80 year cycles, with warm phases since the mid-1990s linked to heightened frequency and intensified multidecadal ENSO variability through alterations in the annual cycle. AMO warm periods increase risk in the U.S. Southwest and north-central regions, while also influencing Sahel rainfall; for example, the positive AMO phase correlates with stronger Pacific ITCZ variability. These oscillations arise from internal ocean circulation changes, such as variations in the Atlantic Meridional Overturning Circulation, rather than direct . Internal modes like ENSO, PDO, and AMO introduce substantial uncertainty in attributing regional climate changes, as their amplitudes can rival anthropogenic forcing on decadal scales, particularly over land areas where variability is amplified. For instance, natural decadal variations may equal global warming-induced surface air temperature changes in magnitude for regional predictions. While models simulate these modes, debates persist on their exact internal origins versus subtle external influences, with some analyses questioning robust multidecadal oscillations in unforced simulations. Nonetheless, observational and modeling evidence confirms their role in generating low-frequency variability that overlays long-term trends.

External Natural Forcings

External natural forcings encompass variations in solar output, volcanic aerosol emissions, and Earth's orbital parameters that alter the planetary energy balance independently of internal climate dynamics. These factors have driven significant climate shifts across geological timescales, with solar and volcanic influences affecting decadal to centennial variability, while orbital changes operate on millennial scales. Empirical reconstructions indicate their radiative forcings are typically small in the compared to pre-industrial baselines but have modulated past s through direct energetic imbalances. Solar irradiance variations, tracked via sunspot cycles and proxy records, impose a of about ±0.17 W/m² over the 11-year Schwabe cycle, stemming from a 0.1% fluctuation in total . This equates to global temperature responses of roughly 0.1°C, as observed in measurements since 1978 showing no net upward trend in irradiance amid rising temperatures. Longer-term solar minima, such as the (1645–1715), correlated with cooler European winters, but reconstructions attribute only modest of 0.1–0.3°C, underscoring limited efficacy for explaining centennial-scale changes without amplification mechanisms like cosmic ray-induced cloud cover, which remain debated. Orbital forcings, formalized by Milankovitch, arise from eccentricity (100,000-year cycle modulating perihelion distance), obliquity (41,000-year axial tilt variation affecting seasonal contrast), and (23,000-year wobble shifting solstice timing). These redistribute insolation, with high-latitude summer peaks driving glacial terminations; for instance, obliquity maxima increase insolation by up to 50 W/m² at 65°N, initiating deglaciations as seen in oxygen records from ice cores. In the , declining obliquity has favored a gradual cooling trajectory, projecting multi-millennial declines of 0.5–1°C per 5,000 years absent countervailing influences, incompatible with 20th-century warming patterns. Volcanic forcings occur via stratospheric aerosol veils from sulfur-rich eruptions, scattering incoming shortwave and yielding negative forcings of 1–5 W/m² for 1–3 years. The 1991 eruption exemplifies this, injecting 20 million tons of SO₂ and inducing 0.5°C detectable in surface temperatures. Larger historical events, like the 1815 Tambora blast, amplified aerosol lifetimes through self-lofting, but aggregate volcanic forcing over the nets near-zero due to episodic nature, contributing to short-term dips amid longer trends rather than sustained directional change.

Anthropogenic Factors

Greenhouse Gas Contributions

Anthropogenic arise predominantly from combustion, industrial processes, agriculture, waste management, and land-use changes such as . These activities have elevated atmospheric concentrations of long-lived es, with (CO2), methane (CH4), and nitrous oxide (N2O) comprising the majority. , though minor in volume, possess high global warming potentials. Global anthropogenic GHG emissions reached 52.9 GtCO2e in 2023, reflecting a 62% increase since 1990. CO2 accounts for approximately 74-76% of total anthropogenic GHG emissions in CO2-equivalent terms, primarily from fossil fuel oxidation in production, transportation, and industry, supplemented by cement manufacturing and net land-use emissions. -related CO2 emissions totaled about 37 Gt in 2023, with coal, oil, and as key contributors; land-use changes, including , added roughly 4-5 GtCO2 annually in recent years, though net land sinks partially offset this.
Greenhouse GasApproximate Share of Total Anthropogenic Emissions (CO2e, %)Primary Anthropogenic Sources
CO274.5 (fossil) + land-use contributionsFossil fuel combustion, production,
CH417.9 in livestock, rice cultivation, fossil fuel extraction and leaks, landfills
N2O4Agricultural (fertilizers), ,
Fluorinated gases~2-3
Methane emissions, equivalent to about 18% of total GHGs, originate largely from biological processes in (roughly 40% of CH4) and systems (30-35%), with the from decomposition. , contributing around 4-6%, is chiefly from application and , enhancing emissions. These breakdowns, derived from inventories like those in IPCC AR6 and , underscore and as dominant sectors, though data uncertainties persist in land-use fluxes and emissions.

Other Human Influences

Anthropogenic aerosols, primarily from industrial emissions, biomass burning, and transportation, exert a net cooling effect on the through direct of solar radiation and indirect modification of cloud properties, with effective estimated at -1.1 W/m² (range -1.7 to -0.4 W/m²) from 1750 to 2019. This forcing offsets a substantial portion of warming, particularly in the , and contributes to regional patterns such as dimming in aerosol-heavy areas like . The spatial distribution of absorbing aerosols, such as , can amplify warming in specific locations like the by reducing surface upon deposition on snow and ice. Land use and land cover changes, including , agricultural expansion, and , alter surface , , and roughness, generating a of approximately -0.2 to -0.5 W/m² globally since pre-industrial times, with stronger regional effects in deforested where reduced lowers flux and enhances sensible heating. These modifications have contributed to amplified warming over land relative to oceans, as bare and crops reflect more than forests, though in some areas provides a counteracting cooling via increased . Peer-reviewed assessments indicate that such changes explain part of the divergence in hemispheric temperature trends, with land alterations exacerbating local variability. The urban heat island effect, arising from impervious surfaces, reduced vegetation, and anthropogenic heat emissions in cities, elevates local temperatures by 1-3°C on average compared to rural surroundings, but its influence on global mean surface temperature trends is minimal, contributing less than 0.1°C to century-scale records due to sparse urban station coverage and data homogenization procedures. Analyses of station metadata and rural comparisons confirm that adjustments for urbanization bias account for potential overestimation, with ocean and remote land data—unaffected by UHI—dominating global averages. Some estimates suggest UHI may explain up to 25% of land-based trends in certain datasets, though this remains contested and does not alter the overall anthropogenic signal. Other influences, such as tropospheric increases from precursors like oxides, add a warming forcing of about 0.4 W/m² since 1750, while stratospheric induces slight cooling, and contrails enhance cover for transient positive forcing. These short-lived climate forcers collectively rival impacts on patterns and regional variability, underscoring the multifaceted nature of human perturbations beyond long-lived gases.

Observational Data

Instrumental Measurements

Instrumental measurements of climate variables, particularly surface air temperature, precipitation, and , provide direct quantitative data on recent climate variability and change, with systematic records emerging in the for localized regions. The longest continuous series, the record, dates to 1659, capturing regional fluctuations driven by natural patterns. Global-scale instrumental data, however, rely on networks of land stations, ship logs, and buoys, achieving sufficient coverage for hemispheric estimates around 1850, though early records were biased toward the Northern Hemisphere's land areas, limiting precision for global averages. These measurements reveal decadal-scale oscillations, such as the early 20th-century warming and mid-century plateau, alongside a net rise of approximately 1.1°C from the 1850–1900 baseline to 2020, as compiled in independent datasets. Major surface temperature datasets include NOAAGlobalTemp, GISTEMP (NASA), and HadCRUT5 (UK Met Office), each integrating thousands of station readings with sea surface temperatures from buckets and engine intakes pre-1940s, transitioning to buoys and satellites later. These records indicate an accelerated warming rate of about 0.06°C per decade since 1850, intensifying to 0.2°C per decade post-1970, though spatial gaps in polar and oceanic regions require infilling via statistical methods, introducing uncertainties estimated at ±0.05°C for annual global means. Data homogenization adjusts for non-climatic biases like station relocations, instrument changes, and time-of-observation shifts, which raw data analyses show would otherwise underestimate recent warming by 10–20% in some periods; however, critics contend that iterative adjustments, often cooling pre-1950 records more than warming post-1950 ones, amplify trends beyond raw observations, particularly in datasets reliant on urban stations. Urban heat island effects, where concrete and asphalt elevate local readings by 1–2°C in cities, contribute up to 22% of observed U.S. warming in raw data, with mainstream adjustments claiming near-complete mitigation via rural baselines, though residual biases persist in global composites due to increasing station urbanization. Satellite-based microwave sounding units (MSU/AMSU), operational since December 1978, measure lower tropospheric temperatures over land and , offering uniform global coverage without surface-specific biases. The (UAH) dataset reports a warming trend of 0.14°C per through 2024, while Remote Sensing Systems () shows 0.21°C per , both lower than surface estimates due to adjustments for , sensor drift, and diurnal drift, with UAH emphasizing lower tropospheric homogeneity. These records highlight tropospheric amplification of surface warming in the but divergences, such as slower polar trends, challenging models expecting uniform vertical profiles under forcing. Ocean heat content measurements advanced with the array of over 3,800 profiling floats deployed since 2000, providing and temperature profiles to 2,000 meters with 0.002°C accuracy, revealing upper- warming of 0.1–0.2°C since 2004 and absorbing over 90% of excess heat inferred from surface trends. Pre-ARGO ship-based , prone to warming biases, underestimated uptake, but ARGO's near-real-time confirm accelerating heat storage below 700 meters, though coverage gaps in marginal seas and deep persist. records, from gauges since the , show increased variability with 1–2% per decade global rise since 1950, but inhomogeneities from gauge undercatch in wind and siting changes complicate attribution. Overall, 's strength lies in empirical directness, yet reliance on adjusted composites underscores the need for transparency to resolve ongoing debates over trend magnitudes.

Proxy Records

Proxy records consist of natural archives that indirectly preserve evidence of past environmental conditions, enabling reconstruction of variability prior to instrumental observations. These proxies include tree rings, s, sediment layers, coral skeletons, and speleothems, each responding to climatic variables such as , , and atmospheric composition through physical, chemical, or biological mechanisms. Reconstructions derive from calibrating proxy signals against modern data where overlapping periods exist, often using statistical models to infer quantitative estimates. Ice cores from and provide high-resolution records extending back hundreds of thousands of years. Oxygen isotope ratios (δ¹⁸O) and deuterium (δD) in ice reflect past temperatures, with the Vostok core documenting orbital-scale cycles where interglacial warmth exceeded glacial minima by 8–10°C in , accompanied by CO₂ variations from 180 ppm to 280 ppm trapped in bubbles. cores reveal abrupt shifts, such as Dansgaard-Oeschger events with warming of 5–10°C over decades during the (circa 115,000–11,700 years ago). These records highlight rapid variability superimposed on longer-term trends driven by orbital forcings. Tree rings offer annual resolution for the past millennium or more, primarily in temperate and boreal zones. Ring width and maximum latewood density correlate with summer temperatures and drought stress; networks reconstruct hemispheric averages showing cooler conditions during the (circa 1450–1850 CE) by 0.5–1°C relative to the 20th century in some datasets. However, species-specific responses, such as divergence in recent decades where ring growth fails to track warming, introduce calibration challenges. Marine and lake sediments extend records to millions of years, using microfossils like for sea surface temperatures via Mg/Ca ratios or alkenone indices, and for terrestrial vegetation shifts indicative of or . Ocean sediment cores confirm mid-Holocene warmth (circa 9,000–5,000 years ago) exceeding current levels in subtropical regions by 1–2°C, linked to orbital enhancing summer insolation. Varved lake sediments preserve seasonal layers for decadal variability. Corals and speleothems provide tropical and cave-based proxies; δ¹⁸O records El Niño-Southern Oscillation variability over centuries, while growth rates and isotopes track strength. These subtropical records show asynchronous regional responses, such as enhanced Indian during the early . Uncertainties in proxy records arise from dating imprecision (e.g., radiocarbon errors beyond 50,000 years), proxy-specific sensitivities to non-climatic factors like biological in trees or effects in isotopes, and sparse global coverage leading to regional biases in syntheses. Multi-proxy ensembles mitigate single-record limitations but require assumptions in weighting and error propagation, with pre-1850 global temperature estimates carrying uncertainties of ±0.5°C or more.

Data Quality and Adjustments

Adjustments to instrumental temperature records aim to correct for non-climatic influences such as changes in times, station relocations, instrument upgrades, and local land-use effects, using algorithms like pairwise homogenization to detect and mitigate discontinuities. These processes, applied by agencies including NOAA and the UK Met Office for HadCRUT, seek to produce homogeneous series reflecting true climatic signals, but their validity depends on accurate break detection and correction direction. Raw surface data often exhibits biases from poor station siting; a comprehensive survey of the U.S. Historical Climatology Network (USHCN) found approximately 70% of stations classified as poorly sited (CRN classes 3-5), located near asphalt, air conditioning exhausts, or urban infrastructure, which can inflate readings via localized heating. Such exposure correlates with increased temperature variance and potentially overstated warming trends, with one analysis estimating a 32% upward bias in raw U.S. trends from substandard siting alone. Homogenization adjustments frequently cool pre-1950 more than recent ones, amplifying post-industrial warming trends; for example, NOAA's methods have been shown to increase the apparent U.S. warming rate by correcting for time-of-observation biases (e.g., shifts from afternoon to morning readings, which artificially lower later minima in ). Globally, versus adjusted comparisons in HadCRUT-like datasets indicate adjustments boost the 1950-2016 warming rate by roughly 10%, though proponents argue this aligns with pristine references like the U.S. Climate Reference Network (USCRN). Critiques highlight inconsistencies in adjustment efficacy; a peer-reviewed of NOAA's Global Historical Climatology Network (GHCN) European subset revealed frequent errors in break identification, with over half of corrections applying the wrong sign, resulting in trends up to 50% higher than unadjusted data in some regions. (UHI) effects, inadequately filtered in global land records, may contribute 20-25% to observed trends, as rural-pristine subsets show subdued warming compared to urban-influenced series. Satellite-derived records (e.g., UAH, microwave sounding units) bypass surface siting issues but require their own and adjustments, yielding lower tropospheric trends of 0.13-0.17°C per decade since 1979, versus 0.18°C per decade in adjusted surface datasets, underscoring unresolved discrepancies between measurement domains. Pristine networks like USCRN, operational since with ideal siting, report U.S. trends approximately half those of adjusted USHCN historical data, suggesting potential overestimation in homogenized long-term series from legacy biases.

Historical Climate Variations

Paleoclimate Evidence

Paleoclimate evidence, derived from natural archives such as ice cores, marine sediments, tree rings, and corals, documents substantial climate variability over millions of years, including repeated glacial-interglacial cycles and shifts between icehouse and greenhouse states, primarily driven by orbital forcings, tectonic changes, and solar variations. These proxies preserve chemical, isotopic, and physical indicators of past temperatures, precipitation, and atmospheric composition, enabling reconstructions of global and regional conditions with varying resolutions from decadal to millennial scales. Ice cores from and provide high-resolution records extending back hundreds of thousands of years, revealing synchronous variations in temperature and greenhouse gases during Quaternary glacial-interglacial transitions. The Vostok ice core, spanning 420,000 years, records eight such cycles with deuterium isotope temperatures fluctuating by 8–10°C and atmospheric CO₂ concentrations ranging from 180 to 300 ppm, while varied between 320 and 790 ppb. The longer EPICA Dome C core extends this to 800,000 years, confirming CO₂ levels remained below 300 ppm throughout, with no excursions approaching modern values of over 420 ppm until the Industrial era. In these records, temperature proxies consistently lead CO₂ increases by 800–1,300 years at the onset of deglaciations, suggesting initial orbital-driven warming mobilizes carbon from oceans and , with subsequent CO₂ release amplifying the temperature rise through feedback effects. This lag underscores the role of —variations in Earth's (period ~100,000 years), axial tilt (obliquity, ~41,000 years), and (~23,000 years)—as primary pacemakers of cycles, modulating seasonal insolation contrasts that build or erode continental ice sheets. Spectral analysis of oxygen ratios in benthic from ocean sediments aligns closely with these orbital periodicities, providing robust evidence for their causal influence on global ice volume changes. Over longer timescales, cores and proxies indicate more extreme variability, such as during the Eocene epoch (56–34 million years ago), when global mean temperatures exceeded modern levels by 10–15°C, polar regions supported temperate forests without permanent ice caps, and deep ocean temperatures reached 12°C, associated with CO₂ concentrations estimated above 1,000 ppm from stomatal indices and boron isotopes. The Paleocene-Eocene Thermal Maximum (PETM) at ~56 million years ago exemplifies rapid natural warming, with a 5–8°C global increase over ~10,000–20,000 years linked to massive carbon releases from volcanic or methane hydrate sources, disrupting ocean circulation and ecosystems as evidenced by benthic foraminiferal extinctions and carbon isotope excursions in sediments. Tree-ring chronologies and speleothems extend high-resolution evidence into the and , capturing regional variability such as the and , with records from the White Mountains showing cooler conditions during the compared to the 20th, independent of anthropogenic influences. Coral growth bands and lake sediment varves further corroborate decadal to centennial fluctuations in tropical sea surface temperatures and monsoon intensity, highlighting internal variability amplified by ocean-atmosphere interactions like El Niño-Southern Oscillation analogs in the past. Collectively, these proxies demonstrate that Earth's exhibits inherent , with natural forcings capable of producing changes comparable to or exceeding 20th-century warming rates in specific intervals, though without the unprecedented atmospheric CO₂ rise observed since 1850.

Holocene and Recent Pre-Industrial Changes

The Holocene epoch commenced approximately 11,700 years before present, succeeding the Younger Dryas cold interval and initiating a period of relative climatic stability following the last glacial maximum. Proxy-based reconstructions from ice cores, tree rings, lake sediments, and speleothems reveal an initial rapid warming in the early Holocene, driven primarily by retreating ice sheets and rising atmospheric CO2 levels from ~260 ppm to ~280 ppm, with global mean surface temperatures (GMST) increasing by about 4-5°C from glacial lows. This warming culminated in the Holocene Climatic Optimum (HCO), spanning roughly 9,500 to 5,500 years BP, during which multi-proxy GMST estimates indicate peak warmth around 7,000 years BP, approximately 0.5°C above late-Holocene levels but comparable to or slightly exceeding pre-industrial averages in some hemispheric reconstructions. Following the HCO, proxy data document a gradual cooling trend across the mid- to late , often termed the Neoglacial period, with GMST declining by 0.5-1°C over millennia, attributed to decreasing summer insolation from Milankovitch orbital cycles and amplified by feedback mechanisms like alpine glacier advances. This long-term cooling featured centennial-scale fluctuations, including the 4.2 ka event—a abrupt and cooling episode linked to weakening—and regional expressions of the 8.2 ka cooling from glacial meltwater pulses. Empirical reconstructions highlight spatial variability, with land areas showing more pronounced seasonality, where summer temperatures peaked earlier than annual means, resolving some discrepancies between proxy data and model simulations that predict orbital-driven warming. Volcanic eruptions and variations contributed to short-term perturbations, but internal ocean-atmosphere dynamics, such as shifts, played key roles in regional anomalies. In the recent pre-industrial era, spanning the last millennium before 1850, climate exhibited notable variability superimposed on the Holocene cooling trajectory, including the Medieval Warm Period (MWP, ~950-1250 CE) and Little Ice Age (LIA, ~1450-1850 CE). Northern Hemisphere reconstructions indicate MWP temperatures ~0.2-0.5°C above the subsequent LIA baseline, with evidence of broader synchrony in proxy networks suggesting a modest global signal, though amplitudes varied regionally due to land-ocean contrasts. The LIA featured cooling of ~0.5-1°C in hemispheric means relative to pre-industrial norms, correlated with clustered volcanic activity—such as sulfate spikes in ice cores—and low solar irradiance during grand minima like the Maunder Minimum (1645-1715 CE), which reduced total solar forcing by ~0.1-0.2 W/m². These forcings induced stratospheric aerosol cooling and altered tropospheric circulation, with volcanic impacts persisting 2-3 years per event and solar changes modulating decadal modes, while excluding significant anthropogenic influence prior to widespread fossil fuel use. Overall pre-industrial variability remained within ~1°C of GMST excursions, underscoring natural drivers' dominance absent modern greenhouse gas rises.

Observed Changes Since 1850

Instrumental records of global surface air temperature, beginning around 1850 from stations and marine observations, show an overall increase of approximately 1.1°C relative to the 1850–1900 baseline through 2024. This warming has not been uniform, with about two-thirds occurring since 1975 and surfaces warming faster than s, the latter absorbing roughly 90% of excess . temperatures have risen more than in the , attributable to greater coverage and ocean circulation patterns. Atmospheric concentrations, reconstructed from cores and direct measurements, have risen from about 280 ppm around 1850 to over 420 ppm by 2024, with the increase accelerating post-1950 via data. Other greenhouse gases, such as , have also increased, from roughly 700 ppb in the mid-19th century to 1900 ppb today. Global mean sea level, measured by tide gauges since the late and augmented by altimetry since 1993, has risen 21–24 cm since 1880, with rates increasing from about 1.5 mm/year historically to 3.7 mm/year recently. glaciers worldwide have retreated since the mid-, with cumulative ice loss accelerating across decades; for instance, many European and North American glaciers have lost 30–50% of their volume since 1850. and Antarctic ice sheets have experienced net mass loss, contributing to , though Antarctic trends show regional variability with some gains in . Ocean heat content in the upper 2000 meters has increased steadily since the 1950s, confirmed by float arrays deployed from 2000 onward, indicating uptake of excess energy consistent with surface warming trends. sea ice extent has declined, particularly in summer minima, at 12% per decade since satellite records began in 1979, though pre-satellite proxy data suggest declines predating this period. These changes exhibit variability influenced by natural oscillations like El Niño-Southern Oscillation, with decadal pauses or slowdowns in surface warming observed, such as from the 1940s to 1970s.

Natural vs. Human Attribution Debates

Detection and attribution analyses seek to apportion observed climate changes between anthropogenic forcings, such as elevated concentrations, and natural drivers including fluctuations, volcanic aerosols, and internal variability from ocean-atmosphere oscillations. Mainstream assessments assert that human activities account for approximately 1.0–1.2°C of the observed ~1.1°C global surface warming since 1850–1900, with natural forcings contributing negligibly or slightly negative over that period. These conclusions derive from optimal fingerprinting techniques, which match spatial patterns of change—such as stratospheric cooling juxtaposed with tropospheric warming—to model ensembles incorporating anthropogenic while excluding it yields divergence from observations. Critics contend that attribution methodologies systematically undervalue natural variability by relying on models that inadequately simulate multidecadal oscillations and regional patterns, leading to overattribution to human causes. A analysis of global mean surface records identified synchronized transitions in major climate indices around 1910–1920, 1940, 1960, 1976–1980, and 2000, suggesting that internal variability, rather than monotonic external forcing, underpins the non-linear 20th-century warming trajectory. Such critiques highlight methodological flaws in optimal fingerprinting, including assumptions of Gaussian error distributions that fail under non-stationary conditions and neglect of unresolved forcings like land-use changes or indirect effects. Solar activity variations, proxied by sunspot numbers and cosmogenic isotopes, exhibit correlations with hemispheric temperatures over centuries, with recent studies quantifying a potential role in modulating total (TSI), ultraviolet output, and flux influencing . Empirical reconstructions indicate TSI changes of ~0.1–0.3 W/m² over 11-year cycles and longer grand solar minima, sufficient to explain portions of early 20th-century warming (1900–1940) when anthropogenic emissions were lower. However, post-1950 —declining solar activity amid rising temperatures—prompts mainstream dismissal of direct TSI dominance, though indirect mechanisms like solar-modulated galactic s enhancing low-cloud could reconcile discrepancies, with sensitivity estimates up to 0.5–1.0 W/m² effective forcing. Internal ocean-atmosphere modes, including the (PDO), (AMO), and El Niño-Southern Oscillation (ENSO), imprint multidecadal temperature fluctuations on global scales, with positive PDO phases (e.g., 1925–1946, 1977–1998) aligning with accelerated warming epochs and contributing ~0.1–0.2°C to mid-20th-century trends via altered heat redistribution. The AMO's warm phase since the 1990s has amplified North Atlantic and Eurasian temperatures, while ENSO episodes account for ~20–30% of interannual variance, masking or amplifying underlying trends. Detractors of dominant natural attribution argue these modes are oscillatory and net zero over centuries, incapable of sustaining directional warming without external forcing, yet empirical deconstructions reveal their role in explaining ~50% of 20th-century variance when phased with solar signals. Persistent uncertainties stem from equilibrium climate sensitivity (ECS) estimates spanning 1.5–4.5°C per CO₂ doubling, with observational constraints favoring lower values (~1.5–2.5°C) inconsistent with high-end model projections, and discrepancies like subdued tropospheric warming over the challenging fingerprint predictions. These gaps fuel debate, as attribution hinges on imperfect models exhibiting overestimated historical hindcasts and underestimated natural internal variability at decadal-to-centennial scales. While peer-reviewed consensus leans anthropogenic, dissenting analyses grounded in empirical underscore unresolved contributions from natural processes, urging caution in policy presumptions of near-exclusive human causality.

Modeling and Predictions

Climate Model Mechanics

Climate models simulate the Earth's by numerically solving a set of partial differential equations derived from fundamental physical laws, including conservation of momentum, mass, energy, and . These equations, often referred to as the , approximate the behavior of fluids in the atmosphere and oceans using the Navier-Stokes equations adapted for large-scale geophysical flows, incorporating terms for gradients, Coriolis forces, , and diabatic heating from and release. General circulation models (GCMs), the core of most climate simulations, discretize the globe into a three-dimensional grid—typically with horizontal resolutions of 50 to 300 kilometers and 20 to 100 vertical levels—to compute state variables such as , wind velocity, humidity, and at discrete points and time steps. Numerical methods employed include finite difference schemes for spatial derivatives and time-stepping algorithms like leapfrog or Runge-Kutta integrators to advance solutions forward in time, ensuring stability through constraints such as the Courant-Friedrichs-Lewy condition, which limits time steps to prevent information propagation exceeding grid speeds. Spectral methods, transforming variables into wavenumber space via Fourier or spherical harmonics, offer efficiency for global domains by exploiting periodicity but require additional handling for non-linear terms and topography. Radiation schemes solve the radiative transfer equation to compute shortwave and longwave fluxes, accounting for absorption, scattering, and emission by gases like CO2, water vapor, and ozone, often using band models or correlated-k approximations for computational tractability. Sub-grid scale processes, unresolved by the grid, necessitate parameterization schemes that empirically or theoretically represent their average effects, such as convective triggered when grid-scale moisture exceeds thresholds, or turbulent mixing via eddy diffusivity closures. microphysics and macrophysics are particularly challenging, with parameterizations estimating formation, evolution, and radiative impacts based on simplified assumptions about droplet/ice processes and feedbacks, introducing uncertainties due to the multi-scale nature of and aerosols. Land surface models parameterize dynamics, vegetation transpiration, and variations, while ocean components solve similar with added and sea-ice . Fully coupled Earth system models integrate atmospheric, oceanic, land, ice-sheet, and biogeochemical modules, exchanging fluxes like heat, momentum, and freshwater at interfaces to simulate interactions such as ocean heat uptake or feedbacks. Initialization often draws from reanalysis datasets or spin-up runs to equilibrium, with forcing from observed or projected gases, aerosols, and solar variability; ensemble simulations perturb initial conditions or parameters to quantify internal variability. High computational demands—requiring supercomputers for simulations spanning centuries—stem from the need for fine resolutions and iterative solver convergence, limiting explicit resolution of processes below ~10 km scales.

Validation Against Observations

Climate models undergo validation through hindcasting, wherein simulations of historical climate forcings are compared against observations, records, and reanalysis datasets to assess fidelity in reproducing trends and variability. This process evaluates key variables such as surface air temperatures, upper-air temperatures, sea surface temperatures, and patterns. While models capture the broad 20th-century global warming signal, systematic biases emerge upon detailed scrutiny, particularly in the magnitude and spatial patterns of change. Surface temperature hindcasts in ensembles like CMIP5 and CMIP6 often exceed observed warming rates; for example, CMIP5 simulations warmed approximately 16% faster than global surface observations since 1970, with about 40% of the divergence attributable to internal variability and the remainder to model errors in forced response. Over the past 50 years, nearly all computerized climate models have projected stronger global warming than the empirically measured rate from datasets like HadCRUT and UAH. These overestimations persist even after accounting for volcanic aerosols and solar variability, suggesting inflated equilibrium climate sensitivity in many models. Tropospheric temperatures provide a stringent test, as models predict enhanced warming in the tropical mid-to-upper due to moist amplification—a "hot spot" signature largely absent in satellite (e.g., UAH, ) and data. Coupled model simulations have shown roughly twice the tropical tropospheric warming relative to satellite observations since 1979, with discrepancies amplified by internal variability and forcing mismatches rather than observational artifacts. Recent analyses confirm that CMIP6 models continue to overestimate these trends, undermining confidence in projections of future amplification. Beyond temperatures, validations reveal mismatches in extent and ocean dynamics; CMIP6 models exhibit biases in September sea ice concentration linked to erroneous atmospheric and oceanic circulations, failing to replicate observed decline rates accurately. trends in regions like the central U.S. also diverge, with models simulating patterns inconsistent with gauge observations due to deficiencies in simulating low-level . These persistent discrepancies highlight limitations in representing natural variability and cloud feedbacks, prompting ongoing refinements but also caution in extrapolating unvalidated projections. Despite some successes in broad-scale energy balance, the prevalence of overpredictions underscores that models tuned to high-sensitivity scenarios do not uniformly align with empirical records.

Projection Uncertainties

Climate projections for future global warming depend on coupled atmosphere-ocean general circulation models (GCMs) integrated over specified emission scenarios, yet these projections are beset by multifaceted uncertainties that span structural model deficiencies, parametric choices, forcing estimates, and internal variability. The IPCC's Sixth Assessment Report (AR6) quantifies global surface air temperature increases of 1.0–1.8°C by 2081–2100 relative to 1850–1900 under low-emission scenarios (SSP1-1.9 to SSP1-2.6), escalating to 3.3–5.7°C under high-emission SSP5-8.5, with 90% confidence intervals reflecting irreducible spreads across model ensembles like CMIP6. These ranges arise partly from equilibrium climate sensitivity (ECS), defined as the long-term temperature response to doubled atmospheric CO₂, assessed at a likely range of 2.5–4.0°C in AR6, narrower than the 1.5–4.5°C of prior reports but still encompassing a factor-of-two spread due to incomplete observational constraints on paleoclimate and process-level feedbacks. A dominant source of projection divergence stems from cloud radiative feedbacks, where low-level marine stratocumulus and mixed-phase may either enhance warming through reduced or mitigate it via increased reflectivity, with CMIP6 models exhibiting a feedback spread of approximately ±0.35 /m²/°C at 90% confidence. Observational constraints, such as satellite-derived responses in clean marine environments, suggest positive feedbacks amplifying sensitivity, rendering low-ECS values (below 2°C) extremely unlikely, yet model biases in schemes and microphysics perpetuate structural . radiative forcing introduces further ambiguity, as anthropogenic sulfates and organics have exerted a cooling effect estimated at -0.9 to -0.1 /m² since pre-industrial times, with the largest inter-model spread among all forcings; future declines under air quality regulations could unmask additional warming, but vertical distribution and interactions remain poorly resolved, contributing up to 0.5°C in transient warming projections. Scenario dependencies compound these issues, as socioeconomic pathways (SSPs) embed assumptions about , , and that diverge sharply—e.g., SSP3-7.0 implies sustained high emissions versus SSP1-1.9's aggressive —yielding non-overlapping warming outcomes despite identical physical models. Internal variability, including decadal oscillations like the , adds noise equivalent to 0.1–0.2°C on multi-decadal scales, while heat uptake efficiency varies across models, delaying peak warming by centuries in some cases. Evaluations of historical projections indicate GCMs have captured global mean warming trends with reasonable skill since the , tracking observed rates of ~0.18°C/decade, but overestimate tropical Pacific warming patterns and changes, highlighting limitations in regional fidelity that amplify for impacts like extremes. Despite advances in resolution and process representation, persistent biases—such as excessive ECS in ~50% of CMIP6 models relative to updated observational inferences—underscore the need for emergent constraints from paleodata and satellites to refine ranges, though consensus views in AR6 reflect averaged model outputs rather than fully reconciled physics.

Potential Impacts

Environmental and Ecological Effects

Rising atmospheric CO2 concentrations have driven a measurable of Earth's vegetated lands, with satellite data from 1982 to 2015 indicating that 25 to 50 percent of global vegetated areas experienced significant greening, 70 percent of which is attributable to CO2 fertilization enhancing and growth. This effect has been particularly pronounced in and agricultural regions, countering some expectations of uniform ecological decline and demonstrating CO2's role as a under elevated levels. However, localized events, such as those observed in the Amazon and European mountains, have been linked to compounded stressors including and insect outbreaks intensified by warmer conditions, though pathogens often play a primary role rather than alone. Species distributions have shifted in response to climatic variability, with empirical observations documenting poleward migrations averaging 17 kilometers per decade for terrestrial species and upslope movements of approximately 11 meters per decade in mountainous regions since the late . These redistributions reflect adaptations to changing thermal niches but can disrupt ecosystems, as evidenced by increased tropicalization of temperate marine communities where warmer waters favor herbivorous , reducing extent. Nonetheless, such changes occur amid dominant anthropogenic pressures like , which exceed climate's current influence on in assessments of imperiled species. In marine environments, warming has triggered mass events, such as the 2014-2017 global episode where sea surface temperatures exceeded thresholds by 1°C for extended periods, expelling symbiotic algae and causing mortality in up to 30 percent of surveyed reefs, though recovery has occurred in less severe cases through larval . Concurrent , with surface declining by 0.1 units since pre-industrial times due to CO2 absorption, impairs in organisms like pteropod mollusks and some corals, potentially altering food webs, yet laboratory and field studies reveal variable resilience among , with non-calcifying often unaffected or benefiting from higher CO2. Overall, while variability contributes to ecological shifts, its role remains secondary to land-use changes and direct exploitation in driving contemporary declines.

Societal and Economic Consequences

Climate variability and change influence societal structures through impacts on health, migration, and inequality, while economic consequences span agriculture, infrastructure, and GDP growth. Empirical assessments indicate that while certain regions face heightened risks from extreme events, human adaptation—such as improved infrastructure and early warning systems—has substantially mitigated adverse outcomes. For instance, global temperature-related deaths have declined by approximately 650,000 annually since the 1990s, driven primarily by reductions in cold-related mortality outpacing increases in heat-related deaths, alongside broader socioeconomic improvements like access to air conditioning and healthcare. Adaptation measures, including resilient building codes and flood defenses, have further reduced vulnerability; in the U.S., the temperature-mortality relationship weakened markedly over the 20th century, with hot days becoming less lethal in warmer regions due to acclimatization and technology. In agriculture, elevated atmospheric CO2 concentrations provide a fertilization effect that enhances crop yields, counteracting some warming-induced stresses. Studies estimate that CO2 fertilization boosted yields of C3 crops like and by 7.1% from 1961 to 2017, contributing to overall global production gains amid . However, this benefit varies by crop type and region; C4 crops such as exhibit smaller responses, and combined with variable patterns, net effects on yields remain regionally heterogeneous, with potential reductions in tropical areas offset by expansions in higher latitudes. Economic analyses suggest that without accounting for CO2 benefits, projected yield losses from warming are overstated, though pests, droughts, and heatwaves pose ongoing risks mitigated by and genetically modified varieties. Extreme weather events, including floods and storms, impose significant economic costs, with U.S. billion-dollar disasters totaling over $2.6 trillion (CPI-adjusted) from 1980 to 2024, though and normalized losses have not escalated proportionally due to and growth in exposed areas. Globally, such events cost an estimated $2 trillion over the past decade, but investments—such as sea walls and —yield high returns, with every $1 spent generating over $10 in avoided damages over a decade. Macroeconomic models project impacts could reduce global GDP by 1-4% by 2100 under moderate warming scenarios, disproportionately affecting developing economies through reduced and , yet historical data show resilience via technological progress and market adjustments. Societal disruptions like migration and conflict arise from variability, with empirical links to reduced increasing displacement in arid regions, though country-specific factors like dominate. Inequality may widen, as extremes regressively impact lower-income groups with limited , exacerbating within-country disparities. Nonetheless, positive historical precedents exist, where past variability prompted societal innovations that enhanced stability, underscoring 's role over deterministic collapse narratives. Overall, integrated assessment models highlight that benefits from milder winters and CO2 effects partially offset costs, with policy emphasizing cost-effective rather than solely to minimize net economic burdens.

Controversies and Critiques

Scientific Debates

Equilibrium climate sensitivity (ECS), the expected long-term global surface air temperature rise from doubled atmospheric CO₂, constitutes a core debate, with estimates varying substantially across methods. Comprehensive general circulation models and paleoclimate reconstructions informing IPCC AR6 yield a likely ECS range of 2.5–4.0°C, emphasizing strong positive feedbacks from and . In contrast, energy budget approaches using satellite-era observations of radiative fluxes, ocean heat uptake, and aerosols derive medians around 2.0°C, with 95% ranges of 1.2–2.9°C, attributing differences to overstated cloud amplification in models. Recent syntheses combining records, paleo constraints, and emergent constraints further support ECS below 3°C, challenging higher model-derived values as inconsistent with observed historical warming. The vertical structure of atmospheric warming, especially the tropical tropospheric "," highlights another discrepancy between theory, models, and data. Moist adiabatic theory and coupled models predict surface warming amplification by factors of 1.5–2.0 in the mid-to-upper tropical (200–300 hPa levels), a of greenhouse forcing via enhanced convection. networks and MSU/AMSU records from 1979–2020, however, show amplification near or below 1.0, with trends statistically inconsistent with multi-model means at >99% confidence in some analyses. While proponents cite reanalysis adjustments or natural variability to reconcile data, critics maintain the mismatch signals model errors in convective mixing and relative humidity, undermining attribution confidence. Model-observation comparisons reveal further tensions in simulating decadal trends and internal variability. CMIP5/6 ensembles broadly match global surface warming since 1850 but diverge on upper-air profiles, rates, and extremes, often simulating excessive tropospheric warming over land and underestimating stratospheric cooling influences. Structural inconsistencies, such as in microphysics and aerosol-cloud interactions, propagate uncertainties, with some ensembles running "hot" relative to post-2000 observations when accounting for multi-decadal oscillations like the AMO. These gaps persist despite tuning, prompting calls for better constraint via emergent relationships and paleoclimate analogs, though mainstream assessments deem overall skill sufficient for projections.

Policy and Alarmism Critiques

Critics of climate alarmism contend that exaggerated claims of imminent catastrophe have historically failed to align with empirical observations, fostering public hysteria rather than measured responses. For example, predictions around the first in 1970 included assertions of widespread famines and by 2000 due to and environmental collapse, none of which occurred as forecasted. Similarly, claims of an ice-free by 2013, as suggested by some models and popularized in media, have not materialized, with summer persisting despite reductions. These discrepancies highlight a pattern where alarmist projections, often amplified by mainstream outlets, overestimate short-term extremes while underemphasizing natural variability and human adaptability. Economist argues in (2020) that such rhetoric drives policies with disproportionate costs relative to benefits, estimating that aggressive mitigation efforts like the would cost $819–$1,890 billion annually through 2100 while averting only about 0.17°C of warming by century's end. 's cost-benefit analyses, drawing on integrated assessment models, indicate that the is often overstated in alarmist narratives, with benefits from CO2 fertilization—such as enhanced global greening and crop yields—offsetting a portion of projected damages. He critiques the focus on emission cuts over innovation, noting that trillions spent on subsidies for intermittent renewables yield minimal emission reductions compared to targeted R&D in nuclear or fusion technologies. Net-zero policies, mandating near-elimination of by mid-century, face scrutiny for their economic toll. In the , pursuit of net zero has correlated with energy prices rising 2–3 times faster than in peers since 2010, contributing to industrial closures and household fuel affecting millions. Global estimates suggest achieving net zero could require $27 trillion annually in redirected spending, imposing opportunity costs by diverting funds from alleviation, , or in developing nations, where climate impacts are often less severe than immediate needs. Critics like Lomborg emphasize that measures—such as resilient —deliver higher returns; for instance, investing in sea walls or drought-resistant crops could mitigate and agricultural risks at fractions of costs. These critiques extend to institutional biases, where summaries from bodies like the IPCC are accused of prioritizing worst-case scenarios to justify expansive interventions, despite underlying data showing moderated projections upon scrutiny. Empirical reviews find no robust evidence linking recent warming to surges in like hurricanes or tornadoes, countering alarmist attributions that drive regulatory overreach. Proponents of rational advocate prioritizing high-impact, low-cost strategies like accelerating green through market incentives, arguing that alarmism erodes credibility and hinders pragmatic solutions.

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