From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Ecocentrism Ecocentrism (/ˌɛkoʊˈsɛntrɪzəm/; from Greek: οἶκος oikos, 'house' and κέντρον kentron, 'center') is a term used by environmental philosophers and ecologists to denote a nature-centered, as opposed to human-centered (i.e., anthropocentric), system of values. The justification for ecocentrism usually consists in an ontological belief and subsequent ethical claim. The ontological belief denies that there are any existential divisions between human and non-human nature sufficient to claim that humans are either (a) the sole bearers of intrinsic value or (b) possess greater intrinsic value than non-human nature. Thus the subsequent ethical claim is for an equality of intrinsic value across human and non-human nature, or biosphericalegalitarianism.
The ecocentric ethic was conceived by Aldo Leopold
and recognizes that all species, including humans, are the product of a
long evolutionary process and are inter-related in their life
processes. The writings of Aldo Leopold and his idea of the land ethic and good environmental management are a key element to this philosophy.
Ecocentrism focuses on the biotic community as a whole and strives to maintain ecosystem composition and ecological processes. The term also finds expression in the first principle of the deep ecology movement, as formulated by Arne Næss and George Sessions in 1984
which points out that anthropocentrism,
which considers humans as the center of the universe and the pinnacle
of all creation, is a difficult opponent for ecocentrism.
Environmental thought and the various branches of the environmental
movement are often classified into two intellectual camps: those that
are considered anthropocentric, or "human-centred," in orientation and
those considered biocentric, or "life-centred". This division has been
described in other terminology as "shallow" ecology versus "deep"
ecology and as "technocentrism" versus "ecocentrism". Ecocentrism can be seen as one stream of thought within environmentalism,
the political and ethical movement that seeks to protect and improve
the quality of the natural environment through changes to
environmentally harmful human activities by adopting environmentally
benign forms of political, economic, and social organization and through
a reassessment of humanity's relationship with nature. In various ways,
environmentalism claims that non-human organisms and the natural
environment as a whole deserve consideration when appraising the
morality of political, economic, and social policies.
Environmental communication scholars suggest that anthropocentric
ways of being and identities are maintained by various modes of
cultural disciplinary power such as ridiculing, labelling, and
silencing. Accordingly, the transition to more ecocentric ways of being
and identities requires not only legal and economic structural change,
but also the emergence of ecocultural practices that challenge
anthropocentric disciplinary power and lead to the creation of
ecocentric cultural norms.
Ecocentrism is taken by its proponents to constitute a radical challenge to long-standing and deeply rooted anthropocentric
attitudes in Western culture, science, and politics. Anthropocentrism
is alleged to leave the case for the protection of non-human nature
subject to the demands of human utility, and thus never more than
contingent on the demands of human welfare. An ecocentric ethic, by
contrast, is believed to be necessary in order to develop a
non-contingent basis for protecting the natural world. Critics of
ecocentrism have argued that it opens the doors to an anti-humanist
morality that risks sacrificing human well-being for the sake of an
ill-defined 'greater good'. Deep ecologistArne Naess has identified anthropocentrism as a root cause of the ecological crisis, human overpopulation, and the extinctions of many non-human species. Lupinacci also points to anthropocentrism as a root cause of environmental degradation.
Others point to the gradual historical realization that humans are not
the centre of all things, that "A few hundred years ago, with some
reluctance, Western people admitted that the planets, Sun and stars did
not circle around their abode. In short, our thoughts and concepts
though irreducibly anthropomorphic need not be anthropocentric."
Industrocentrism
It
sees all things on earth as resources to be utilized by humans or to be
commodified. This view is the opposite of anthropocentrism and
ecocentrism.
Ecocentrism is also contrasted with technocentrism
(meaning values centred on technology) as two opposing perspectives on
attitudes towards human technology and its ability to affect, control
and even protect the environment. Ecocentrics, including "deep green"
ecologists, see themselves as being subject to nature, rather than in
control of it. They lack faith in modern technology and the bureaucracy
attached to it. Ecocentrics will argue that the natural world should be
respected for its processes and products, and that low impact technology
and self-reliance is more desirable than technological control of
nature.
Technocentrics,
including imperialists, have absolute faith in technology and industry
and firmly believe that humans have control over nature. Although
technocentrics may accept that environmental problems do exist, they do
not see them as problems to be solved by a reduction in industry.
Indeed, technocentrics see that the way forward for developed and
developing countries and the solutions to our environmental problems
today lie in scientific and technological advancement.
The distinction between biocentrism
and ecocentrism is ill-defined. Ecocentrism recognizes Earth's
interactive living and non-living systems rather than just the Earth's
organisms (biocentrism) as central in importance.
The term has been used by those advocating "left biocentrism", combining
deep ecology with an "anti-industrial and anti-capitalist" position (David Orton et al.).
This brain region is involved in a wide range of higher-order cognitive functions, including speech formation (Broca's area), gaze (frontal eye fields), working memory (dorsolateral prefrontal cortex), and risk processing (e.g. ventromedial prefrontal cortex).
The basic activity of this brain region is considered to be
orchestration of thoughts and actions in accordance with internal goals.
Many authors have indicated an integral link between a person's will to
live, personality, and the functions of the prefrontal cortex.
This brain region has been implicated in executive functions, such as planning, decision making, working memory, personality expression, moderating social behavior and controlling certain aspects of speech and language.
Executive function relates to abilities to differentiate among
conflicting thoughts, determine good and bad, better and best, same and
different, future consequences of current activities, working toward a
defined goal, prediction of outcomes, expectation based on actions, and
social "control" (the ability to suppress urges that, if not suppressed,
could lead to socially unacceptable outcomes).
The frontal cortex supports concrete rule learning, with more
anterior regions supporting rule learning at higher levels of
abstraction.
Structure
Definition
There are three possible ways to define the prefrontal cortex:
as that part of the frontal cortex whose electrical stimulation does not evoke movements
Granular frontal cortex
The prefrontal cortex has been defined based on cytoarchitectonics by the presence of a cortical granular layer IV.
It is not entirely clear who first used this criterion. Many of the
early cytoarchitectonic researchers restricted the use of the term
prefrontal to a much smaller region of cortex including the gyrus rectus and the gyrusrostralis (Campbell, 1905; G. E. Smith, 1907; Brodmann, 1909; von Economo and Koskinas, 1925). In 1935, however, Jacobsen used the term prefrontal to distinguish granular prefrontal areas from agranular motor and premotor areas.
In terms of Brodmann areas, the prefrontal cortex traditionally
includes areas 8, 9, 10, 11, 12, 13, 14, 24, 25, 32, 44, 45, 46, and 47, however, not all of these areas are strictly granular – 44 is dysgranular, caudal 11 and orbital 47 are agranular. The main problem with this definition is that it works well only in primates but not in nonprimates, as the latter lack a granular layer IV.
Projection zone
To define the prefrontal cortex as the projection zone of the mediodorsal nucleus of the thalamus builds on the work of Rose and Woolsey,
who showed that this nucleus projects to anterior and ventral parts of
the brain in nonprimates, however, Rose and Woolsey termed this
projection zone "orbitofrontal." It seems to have been Akert, who, for
the first time in 1964, explicitly suggested that this criterion could
be used to define homologues of the prefrontal cortex in primates and
nonprimates. This allowed the establishment of homologies despite the lack of a granular frontal cortex in nonprimates.
The projection zone definition is still widely accepted today (e.g. Fuster), although its usefulness has been questioned.
Modern tract tracing studies have shown that projections of the
mediodorsal nucleus of the thalamus are not restricted to the granular
frontal cortex in primates. As a result, it was suggested to define the
prefrontal cortex as the region of cortex that has stronger reciprocal
connections with the mediodorsal nucleus than with any other thalamic
nucleus. Uylings et al.
acknowledge, however, that even with the application of this criterion,
it might be rather difficult to define the prefrontal cortex
unequivocally.
Electrically silent area of frontal cortex
A
third definition of the prefrontal cortex is the area of frontal cortex
whose electrical stimulation does not lead to observable movements. For
example, in 1890 David Ferrier
used the term in this sense. One complication with this definition is
that the electrically "silent" frontal cortex includes both granular and
non-granular areas.
Subdivisions
According to Striedter, the PFC of humans can be delineated into two functionally, morphologically, and evolutionarily different regions: the ventromedial PFC (vmPFC) consisting of:
the ventral prefrontal cortex (VPFC)
the medial prefrontal cortex present in all mammals (MPFC)
The ventrolateral prefrontal cortex contains BA45 which is part of Broca's area. Some researchers also include BA44 the other part of Broca's area.
Interconnections
The
prefrontal cortex is highly interconnected with much of the brain,
including extensive connections with other cortical, subcortical and
brain stem sites. The dorsal prefrontal cortex is especially interconnected with brain regions involved with attention, cognition and action, while the ventral prefrontal cortex interconnects with brain regions involved with emotion.
The prefrontal cortex also receives inputs from the brainstem arousal
systems, and its function is particularly dependent on its neurochemical
environment. Thus, there is coordination between one's state of arousal and mental state.
The interplay between the prefrontal cortex and socioemotional system
of the brain is relevant for adolescent development, as proposed by the Dual Systems Model.
The medial prefrontal cortex has been implicated in the generation of slow-wave sleep (SWS), and prefrontal atrophy has been linked to decreases in SWS.
Prefrontal atrophy occurs naturally as individuals age, and it has been
demonstrated that older adults experience impairments in memory consolidation as their medial prefrontal cortices degrade. In older adults, instead of being transferred and stored in the neocortex during SWS, memories start to remain in the hippocampus where they were encoded, as evidenced by increased hippocampal activation compared to younger adults during recall tasks, when subjects learned word associations, slept, and then were asked to recall the learned words.
The ventrolateral prefrontal cortex (VLPFC) has been implicated
in various aspects of speech production and language comprehension. The
VLPFC is richly connected to various regions of the brain including the
lateral and medial temporal lobe, the superior temporal cortex, the
infertemporal cortex, the perirhinal cortex, and the parahippoccampal
cortex. These brain areas are implicated in memory retrieval and consolidation, language processing,
and association of emotions. These connections allow the VLPFC to
mediate explicit and implicit memory retrieval and integrate it with
language stimulus to help plan coherent speech. In other words, choosing the correct words and staying "on topic" during conversation come from the VLPFC.
Function
Executive function
The original studies of Fuster and of Goldman-Rakic
emphasized the fundamental ability of the prefrontal cortex to
represent information not currently in the environment, and the central
role of this function in creating the "mental sketch pad". Goldman-Rakic
spoke of how this representational knowledge was used to intelligently
guide thought, action, and emotion, including the inhibition of
inappropriate thoughts, distractions, actions, and feelings.
In this way, working memory can be seen as fundamental to attention and
behavioral inhibition. Fuster speaks of how this prefrontal ability
allows the wedding of past to future, allowing both cross-temporal and
cross-modal associations in the creation of goal-directed,
perception-action cycles. This ability to represent underlies all other higher executive functions.
Shimamura proposed Dynamic Filtering Theory to describe the role of the prefrontal cortex in executive functions.
The prefrontal cortex is presumed to act as a high-level gating or
filtering mechanism that enhances goal-directed activations and inhibits
irrelevant activations. This filtering mechanism enables executive
control at various levels of processing, including selecting,
maintaining, updating, and rerouting activations. It has also been used
to explain emotional regulation.
Miller and Cohen proposed an Integrative Theory of Prefrontal
Cortex Function, that arises from the original work of Goldman-Rakic and
Fuster. The two theorize that "cognitive control stems from the active
maintenance of patterns of activity in the prefrontal cortex that
represents goals and means to achieve them. They provide bias signals to
other brain structures whose net effect is to guide the flow of
activity along neural pathways that establish the proper mappings
between inputs, internal states, and outputs needed to perform a given
task".
In essence, the two theorize that the prefrontal cortex guides the
inputs and connections, which allows for cognitive control of our
actions.
The prefrontal cortex is of significant importance when top-down processing
is needed. Top-down processing by definition is when behavior is guided
by internal states or intentions. According to the two, "The PFC is
critical in situations when the mappings between sensory inputs,
thoughts, and actions either are weakly established relative to other
existing ones or are rapidly changing". An example of this can be portrayed in the Wisconsin Card Sorting Test (WCST).
Subjects engaging in this task are instructed to sort cards according
to the shape, color, or number of symbols appearing on them. The thought
is that any given card can be associated with a number of actions and
no single stimulus-response mapping will work. Human subjects with PFC
damage are able to sort the card in the initial simple tasks, but unable
to do so as the rules of classification change.
Miller and Cohen conclude that the implications of their theory
can explain how much of a role the PFC has in guiding control of
cognitive actions. In the researchers' own words, they claim that,
"depending on their target of influence, representations in the PFC can
function variously as attentional templates, rules, or goals by
providing top-down bias signals to other parts of the brain that guide
the flow of activity along the pathways needed to perform a task".
Experimental data indicate a role for the prefrontal cortex in
mediating normal sleep physiology, dreaming and sleep-deprivation
phenomena.
When analyzing and thinking about attributes of other
individuals, the medial prefrontal cortex is activated, however, it is
not activated when contemplating the characteristics of inanimate
objects.
Studies using fMRI have shown that the medial prefrontal cortex
(mPFC), specifically the anterior medial prefrontal cortex (amPFC), may
modulate mimicry behavior. Neuroscientists are suggesting that social
priming influences activity and processing in the amPFC, and that this
area of the prefrontal cortex modulates mimicry responses and behavior.
As of recent, researchers have used neuroimaging techniques to find that along with the basal ganglia, the prefrontal cortex is involved with learning exemplars, which is part of the exemplar theory,
one of the three main ways our mind categorizes things. The exemplar
theory states that we categorize judgements by comparing it to a similar
past experience within our stored memories.
A 2014 meta-analysis by Professor Nicole P.Yuan from the
University of Arizona found that larger prefrontal cortex volume and
greater PFC cortical thickness were associated with better executive
performance.
Attention and memory
Lebedev et al. experiment that dissociated representation of spatial attention from representation of spatial memory in prefrontal cortex
A widely accepted theory regarding the function of the brain's prefrontal cortex is that it serves as a store of short-term memory.
This idea was first formulated by Jacobsen, who reported in 1936 that
damage to the primate prefrontal cortex caused short-term memory
deficits. Karl Pribram and colleagues (1952) identified the part of the prefrontal cortex responsible for this deficit as area46, also known as the dorsolateral prefrontal cortex (dlPFC). More recently, Goldman-Rakic
and colleagues (1993) evoked short-term memory loss in localized
regions of space by temporary inactivation of portions of the dlPFC. Once the concept of working memory (see also Baddeley's model of working memory) was established in contemporary neuroscience by Alan Baddeley
(1986), these neuropsychological findings contributed to the theory
that the prefrontal cortex implements working memory and, in some
extreme formulations, only working memory.
In the 1990s this theory developed a wide following, and it became the
predominant theory of PF function, especially for nonhuman primates. The
concept of working memory used by proponents of this theory focused
mostly on the short-term maintenance of information, and rather less on
the manipulation or monitoring of such information or on the use of that
information for decisions. Consistent with the idea that the prefrontal
cortex functions predominantly in maintenance memory, delay-period
activity in the PF has often been interpreted as a memory trace. (The
phrase "delay-period activity" applies to neuronal activity that follows
the transient presentation of an instruction cue and persists until a
subsequent "go" or "trigger" signal.)
To explore alternative interpretations of delay-period activity
in the prefrontal cortex, Lebedev et al. (2004) investigated the
discharge rates of single prefrontal neurons as monkeys attended to a
stimulus marking one location while remembering a different, unmarked
location. Both locations served as potential targets of a saccadic eye movement.
Although the task made intensive demands on short-term memory, the
largest proportion of prefrontal neurons represented attended locations,
not remembered ones. These findings showed that short-term memory
functions cannot account for all, or even most, delay-period activity in
the part of the prefrontal cortex explored. The authors suggested that
prefrontal activity during the delay-period contributes more to the
process of attentional selection (and selective attention) than to memory storage.
Speech production and language
Various
areas of the prefrontal cortex have been implicated in a multitude of
critical functions regarding speech production, language comprehension,
and response planning before speaking.
Cognitive neuroscience has shown that the left ventrolateral prefrontal
cortex is vital in the processing of words and sentences.
The right prefrontal cortex has been found to be responsible for
coordinating the retrieval of explicit memory for use in speech, whereas
the deactivation of the left is responsible for mediating implicit
memory retrieval to be used in verb generation.
Recollection of nouns (explicit memory) is impaired in some amnesic
patients with damaged right prefrontal cortices, but verb generation
remains intact because of its reliance on left prefrontal deactivation.
Many researchers now include BA45 in the prefrontal cortex
because together with BA44 it makes up an area of the frontal lobe
called Broca's area. Broca's Area is widely considered the output area of the language production pathway in the brain (as opposed to Wernicke's area
in the medial temporal lobe, which is seen as the language input area).
BA45 has been shown to be implicated for the retrieval of relevant
semantic knowledge to be used in conversation/speech.
The right lateral prefrontal cortex (RLPFC) is implicated in the
planning of complex behavior, and together with bilateral BA45, they act
to maintain focus and coherence during speech production.
However, left BA45 has been shown to be activated significantly while
maintaining speech coherence in young people. Older people have been
shown to recruit the right BA45 more so than their younger counterparts. This aligns with the evidence of decreased lateralization in other brain systems during aging.
In addition, this increase in BA45 and RLPFC activity in
combination of BA47 in older patients has been shown to contribute to
"off-topic utterances." The BA47 area in the prefrontal cortex is
implicated in "stimulus-driven" retrieval of less-salient knowledge than
is required to contribute to a conversation.
In other words, elevated activation of the BA47 together with altered
activity in BA45 and the broader RLPFC has been shown to contribute to
the inclusion of less relevant information and irrelevant tangential
conversational speech patterns in older subjects.
In the last few decades, brain imaging
systems have been used to determine brain region volumes and nerve
linkages. Several studies have indicated that reduced volume and
interconnections of the frontal lobes with other brain regions is
observed in patients diagnosed with mental disorders; those subjected to repeated stressors; those who excessively consume sexually explicit materials; suicides; criminals; sociopaths; those affected by lead poisoning; It is believed that at least some of the human abilities to feel guilt or remorse, and to interpret reality, are dependent on a well-functioning prefrontal cortex. The advanced neurocircuitry and self-regulatory function of the human prefrontal cortex is also associated with the higher sentience and sapience of humans,
as the prefrontal cortex in humans occupies a far larger percentage of
the brain than in any other animal. It is theorized that, as the brain
has tripled in size over five million years of human evolution, the prefrontal cortex has increased in size sixfold.
A review on executive functions in healthy exercising individuals
noted that the left and right halves of the prefrontal cortex, which is
divided by the medial longitudinal fissure, appears to become more interconnected in response to consistent aerobic exercise. Two reviews of structural neuroimaging
research indicate that marked improvements in prefrontal and
hippocampal gray matter volume occur in healthy adults that engage in
medium intensity exercise for several months.
Chronic intake of alcohol
leads to persistent alterations in brain function including altered
decision-making ability. The prefrontal cortex of chronic alcoholics has
been shown to be vulnerable to oxidative DNA damage and neuronal cell death.
History
Perhaps the seminal case in prefrontal cortex function is that of Phineas Gage,
whose left frontal lobe was destroyed when a large iron rod was driven
through his head in an 1848 accident. The standard presentation is that,
although Gage retained normal memory, speech and motor skills, his
personality changed radically: He became irritable, quick-tempered, and
impatient—characteristics he did not previously display — so that
friends described him as "no longer Gage"; and, whereas he had
previously been a capable and efficient worker, afterward he was unable
to complete. However, careful analysis of primary evidence shows that descriptions of Gage's psychological
changes are usually exaggerated when held against the description given
by Gage's doctor, the most striking feature being that changes
described years after Gage's death are far more dramatic than anything
reported while he was alive.
Subsequent studies on patients with prefrontal injuries have
shown that the patients verbalized what the most appropriate social
responses would be under certain circumstances. Yet, when actually
performing, they instead pursued behavior aimed at immediate
gratification, despite knowing the longer-term results would be
self-defeating.
The interpretation of this data indicates that not only are
skills of comparison and understanding of eventual outcomes harbored in
the prefrontal cortex but the prefrontal cortex (when functioning
correctly) controls the mental option to delay immediate gratification
for a better or more rewarding longer-term gratification result. This
ability to wait for a reward is one of the key pieces that define
optimal executive function of the human brain.
There is much current research devoted to understanding the role
of the prefrontal cortex in neurological disorders. Clinical trials have
begun on certain drugs that have been shown to improve prefrontal
cortex function, including guanfacine, which acts through the alpha-2A adrenergic receptor. A downstream target of this drug, the HCN channel, is one of the most recent areas of exploration in prefrontal cortex pharmacology.
Etymology
The term "prefrontal" as describing a part of the brain appears to have been introduced by Richard Owen in 1868.
For him, the prefrontal area was restricted to the anterior-most part
of the frontal lobe (approximately corresponding to the frontal pole).
It has been hypothesized that his choice of the term was based on the prefrontal bone present in most amphibians and reptiles.
Numerical climate models (or climate system models) are mathematical models that can simulate the interactions of important drivers of climate. These drivers are the atmosphere, oceans, land surface and ice. Scientists use climate models to study the dynamics of the climate system and to make projections of future climate and of climate change.
Climate models can also be qualitative (i.e. not numerical) models and
contain narratives, largely descriptive, of possible futures.
Climate models take account of incoming energy from the Sun as well as outgoing energy from Earth. An imbalance results in a change in temperature. The incoming energy from the Sun is in the form of short wave electromagnetic radiation, chiefly visible and short-wave (near) infrared. The outgoing energy is in the form of long wave (far) infrared electromagnetic energy. These processes are part of the greenhouse effect.
Climate models vary in complexity. For example, a simple radiant heat
transfer model treats the Earth as a single point and averages outgoing
energy. This can be expanded vertically (radiative-convective models)
and horizontally. More complex models are the coupled atmosphere–ocean–sea iceglobal climate models. These types of models solve the full equations for mass transfer, energy transfer and radiant exchange. In addition, other types of models can be interlinked. For example Earth System Models include also land use as well as land use changes. This allows researchers to predict the interactions between climate and ecosystems.
Big climate models are essential but they are not perfect. Attention
still needs to be given to the real world (what is happening and why).
The global models are essential to assimilate all the observations,
especially from space (satellites) and produce comprehensive analyses of
what is happening, and then they can be used to make
predictions/projections. Simple models have a role to play that is
widely abused and fails to recognize the simplifications such as not
including a water cycle.
General circulation models (GCMs)
Climate models are systems of differential equations based on the basic laws of physics, fluid motion, and chemistry.
To "run" a model, scientists divide the planet into a 3-dimensional
grid, apply the basic equations, and evaluate the results. Atmospheric
models calculate winds, heat transfer, radiation, relative humidity, and surface hydrology within each grid and evaluate interactions with neighboring points.
Atmospheric GCMs (AGCMs) model the atmosphere and impose sea surface temperatures as boundary conditions. Coupled atmosphere-ocean GCMs (AOGCMs, e.g. HadCM3, EdGCM, GFDL CM2.X, ARPEGE-Climat)
combine the two models. The first general circulation climate model
that combined both oceanic and atmospheric processes was developed in
the late 1960s at the NOAAGeophysical Fluid Dynamics Laboratory
AOGCMs represent the pinnacle of complexity in climate models and
internalise as many processes as possible. However, they are still under
development and uncertainties remain. They may be coupled to models of
other processes, such as the carbon cycle,
so as to better model feedback effects. Such integrated multi-system
models are sometimes referred to as either "earth system models" or
"global climate models."
Simulation
of the climate system in full 3-D space and time was impractical prior
to the establishment of large computational facilities starting in the
1960s. In order to begin to understand which factors may have changed
Earth's paleoclimate
states, the constituent and dimensional complexities of the system
needed to be reduced. A simple quantitative model that balanced
incoming/outgoing energy was first developed for the atmosphere in the
late 19th century. Other EBMs similarly seek an economical description of surface temperatures by applying the conservation of energy constraint to individual columns of the Earth-atmosphere system.
Essential features of EBMs include their relative conceptual simplicity and their ability to sometimes produce analytical solutions.
Some models account for effects of ocean, land, or ice features on the
surface budget. Others include interactions with parts of the water cycle or carbon cycle.
A variety of these and other reduced system models can be useful for
specialized tasks that supplement GCMs, particularly to bridge gaps
between simulation and understanding.
Zero-dimensional models
Zero-dimensional models consider Earth as a point in space, analogous to the pale blue dot viewed by Voyager 1 or an astronomer's view of very distant objects. This dimensionless
view while highly limited is still useful in that the laws of physics
are applicable in a bulk fashion to unknown objects, or in an
appropriate lumped manner if some major properties of the object are
known. For example, astronomers know that most planets in our own
solar system feature some kind of solid/liquid surface surrounded by a
gaseous atmosphere.
is the effective emissivity
of Earth's combined surface and atmosphere (including clouds). It is a
quantity between 0 and 1 that is calculated from the equilibrium to be
about 0.61. For the zero-dimensional treatment it is equivalent to an
average value over all viewing angles.
This very simple model is quite instructive. For example, it shows
the temperature sensitivity to changes in the solar constant, Earth
albedo, or effective Earth emissivity. The effective emissivity also
gauges the strength of the atmospheric greenhouse effect, since it is the ratio of the thermal emissions escaping to space versus those emanating from the surface.
The calculated emissivity can be compared to available data.
Terrestrial surface emissivities are all in the range of 0.96 to 0.99
(except for some small desert areas which may be as low as 0.7).
Clouds, however, which cover about half of the planet's surface, have an
average emissivity of about 0.5
(which must be reduced by the fourth power of the ratio of cloud
absolute temperature to average surface absolute temperature) and an
average cloud temperature of about 258 K (−15 °C; 5 °F).
Taking all this properly into account results in an effective earth
emissivity of about 0.64 (earth average temperature 285 K (12 °C;
53 °F)).
Models with separated surface and atmospheric layers
One-layer EBM with blackbody surface
Dimensionless models have also been constructed with functionally
separated atmospheric layers from the surface. The simplest of these
is the zero-dimensional, one-layer model,
which may be readily extended to an arbitrary number of atmospheric
layers. The surface and atmospheric layer(s) are each characterized by
a corresponding temperature and emissivity value, but no thickness.
Applying radiative equilibrium (i.e conservation of energy) at the
interfaces between layers produces a set of coupled equations which are
solvable.
Layered models produce temperatures that better estimate those observed for Earth's surface and atmospheric levels. They likewise further illustrate the radiative heat transfer
processes which underlie the greenhouse effect. Quantification of this
phenomenon using a version of the one-layer model was first published
by Svante Arrhenius in year 1896.
Radiative-convective models
Water vapor
is a main determinant of the emissivity of Earth's atmosphere. It both
influences the flows of radiation and is influenced by convective flows
of heat in a manner that is consistent with its equilibrium
concentration and temperature as a function of elevation (i.e. relative humidity
distribution). This has been shown by refining the zero dimension
model in the vertical to a one-dimensional radiative-convective model
which considers two processes of energy transport:
upwelling and downwelling radiative transfer through atmospheric layers that both absorb and emit infrared radiation
upward transport of heat by air and vapor convection, which is especially important in the lower troposphere.
Radiative-convective models have advantages over simpler models and also lay a foundation for more complex models.
They can estimate both surface temperature and the temperature
variation with elevation in a more realistic manner. They also simulate
the observed decline in upper atmospheric temperature and rise in
surface temperature when trace amounts of other non-condensible greenhouse gases such as carbon dioxide are included.
Other parameters are sometimes included to simulate localized
effects in other dimensions and to address the factors that move energy
about Earth. For example, the effect of ice-albedo feedback on global climate sensitivity has been investigated using a one-dimensional radiative-convective climate model.
Higher-dimension models
The
zero-dimensional model may be expanded to consider the energy
transported horizontally in the atmosphere. This kind of model may well
be zonally
averaged. This model has the advantage of allowing a rational
dependence of local albedo and emissivity on temperature – the poles can
be allowed to be icy and the equator warm – but the lack of true
dynamics means that horizontal transports have to be specified.
Early examples include research of Mikhail Budyko and William D. Sellers who worked on the Budyko-Sellers model. This work also showed the role of positive feedback in the climate system and has been considered foundational for the energy balance models since its publication in 1969.
Earth systems models of intermediate complexity (EMICs)
Depending on the nature of questions asked and the pertinent time
scales, there are, on the one extreme, conceptual, more inductive
models, and, on the other extreme, general circulation models
operating at the highest spatial and temporal resolution currently
feasible. Models of intermediate complexity bridge the gap. One example
is the Climber-3 model. Its atmosphere is a 2.5-dimensional
statistical-dynamical model with 7.5° × 22.5° resolution and time step
of half a day; the ocean is MOM-3 (Modular Ocean Model) with a 3.75° × 3.75° grid and 24 vertical levels.
Box models
Schematic of a simple box model used to illustrate fluxes in geochemical cycles, showing a source (Q), sink (S) and reservoir (M)
Box models are simplified versions of complex systems, reducing them to boxes (or reservoirs) linked by fluxes. The boxes are assumed to be mixed homogeneously. Within a given box, the concentration of any chemical species
is therefore uniform. However, the abundance of a species within a
given box may vary as a function of time due to the input to (or loss
from) the box or due to the production, consumption or decay of this
species within the box.
Simple box models, i.e. box model with a small number of boxes
whose properties (e.g. their volume) do not change with time, are often
useful to derive analytical formulas describing the dynamics and
steady-state abundance of a species. More complex box models are usually
solved using numerical techniques.
In 1956, Norman Phillips developed a mathematical model that
realistically depicted monthly and seasonal patterns in the troposphere.
This was the first successful climate model. Several groups then began working to create general circulation models.
The first general circulation climate model combined oceanic and
atmospheric processes and was developed in the late 1960s at the Geophysical Fluid Dynamics Laboratory, a component of the U.S. National Oceanic and Atmospheric Administration.
By 1975, Manabe and Wetherald had developed a three-dimensional global climate model that gave a roughly accurate representation of the current climate. Doubling CO2 in the model's atmosphere gave a roughly 2 °C rise in global temperature.
Several other kinds of computer models gave similar results: it was
impossible to make a model that gave something resembling the actual
climate and not have the temperature rise when the CO2 concentration was increased.
By the early 1980s, the U.S. National Center for Atmospheric Research had developed the Community Atmosphere Model (CAM), which can be run by itself or as the atmospheric component of the Community Climate System Model. The latest update (version 3.1) of the standalone CAM was issued on 1 February 2006. In 1986, efforts began to initialize and model soil and vegetation types, resulting in more realistic forecasts. Coupled ocean-atmosphere climate models, such as the Hadley Centre for Climate Prediction and Research's HadCM3 model, are being used as inputs for climate change studies.
Increase of forecasts confidence over time
The pattern correlation between global climate models and observations has improved over sequential CMIP phases 3, 5, and 6.[42]
The Coupled Model Intercomparison Project (CMIP) has been a leading effort to foster improvements in GCMs and climate change understanding since 1995.
The IPCC stated in 2010 it has increased confidence in forecasts coming from climate models:
"There
is considerable confidence that climate models provide credible
quantitative estimates of future climate change, particularly at
continental scales and above. This confidence comes from the foundation
of the models in accepted physical principles and from their ability to
reproduce observed features of current climate and past climate changes.
Confidence in model estimates is higher for some climate variables
(e.g., temperature) than for others (e.g., precipitation). Over several
decades of development, models have consistently provided a robust and
unambiguous picture of significant climate warming in response to
increasing greenhouse gases."
A 2012 U.S. National Research Council report discussed how the large and diverse U.S. climate modeling enterprise could evolve to become more unified.
Efficiencies could be gained by developing a common software
infrastructure shared by all U.S. climate researchers, and holding an
annual climate modeling forum, the report found.
Issues
Electricity consumption
Cloud-resolving climate models are nowadays run on high intensity super-computers which have a high power consumption and thus cause CO2 emissions. They require exascale computing (billion billion – i.e., a quintillion – calculations per second). For example, the Frontier exascale supercomputer consumes 29 MW. It can simulate a year’s worth of climate at cloud resolving scales in a day.
Techniques that could lead to energy savings, include for
example: "reducing floating point precision computation; developing
machine learning algorithms to avoid unnecessary computations; and
creating a new generation of scalable numerical algorithms that would
enable higher throughput in terms of simulated years per wall clock
day."
Parametrization
Parameterization in a weather
or climate model is a method of replacing processes that are too
small-scale or complex to be physically represented in the model by a
simplified process. This can be contrasted with other processes—e.g.,
large-scale flow of the atmosphere—that are explicitly resolved within
the models. Associated with these parameterizations are various parameters
used in the simplified processes. Examples include the descent rate of
raindrops, convective clouds, simplifications of the atmospheric radiative transfer on the basis of atmospheric radiative transfer codes, and cloud microphysics.
Radiative parameterizations are important to both atmospheric and
oceanic modeling alike. Atmospheric emissions from different sources
within individual grid boxes also need to be parameterized to determine
their impact on air quality.
