Climate changeIn common usage, climate change describes global warming—the ongoing increase in global average temperature—and its effects on Earth's climate system. Climate change in a broader sense also includes previous long-term changes to Earth's climate. The current rise in global average temperature is more rapid than previous changes, and is primarily caused by humans burning fossil fuels. Fossil fuel use, deforestation, and some agricultural and industrial practices increase greenhouse gases, notably carbon dioxide and methane.
Climate change denialClimate change denial or global warming denial is dismissal or unwarranted doubt that contradicts the scientific consensus on climate change. Those promoting denial commonly use rhetorical tactics to give the appearance of a scientific controversy where there is none. Climate change denial includes doubts to the extent of how much climate change is caused by humans, its effects on nature and human society, and the potential of adaptation to global warming by human actions.
Climate change adaptationClimate change adaptation is the process of adjusting to the effects of climate change. These can be both current or expected impacts. Adaptation aims to moderate or avoid harm for people. It also aims to exploit opportunities. Humans may also intervene to help adjustment for natural systems. There are many adaptation strategies or options.They can help manage impacts and risks to people and nature. We can classify adaptation actions in four ways. These are infrastructural and technological; institutional; behavioural and cultural; and nature-based options.
Generalized extreme value distributionIn probability theory and statistics, the generalized extreme value (GEV) distribution is a family of continuous probability distributions developed within extreme value theory to combine the Gumbel, Fréchet and Weibull families also known as type I, II and III extreme value distributions. By the extreme value theorem the GEV distribution is the only possible limit distribution of properly normalized maxima of a sequence of independent and identically distributed random variables.
StatisticsStatistics (from German: Statistik, () "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal".
Statistical inferenceStatistical inference is the process of using data analysis to infer properties of an underlying distribution of probability. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population.
Scientific methodThe scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century (with notable practitioners in previous centuries; see the article history of scientific method for additional detail.) It involves careful observation, applying rigorous skepticism about what is observed, given that cognitive assumptions can distort how one interprets the observation.
Scientific realismScientific realism is the view that the universe described by science is real regardless of how it may be interpreted. Within philosophy of science, this view is often an answer to the question "how is the success of science to be explained?" The discussion on the success of science in this context centers primarily on the status of unobservable entities apparently talked about by scientific theories. Generally, those who are scientific realists assert that one can make valid claims about unobservables (viz.
Gumbel distributionIn probability theory and statistics, the Gumbel distribution (also known as the type-I generalized extreme value distribution) is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions. This distribution might be used to represent the distribution of the maximum level of a river in a particular year if there was a list of maximum values for the past ten years. It is useful in predicting the chance that an extreme earthquake, flood or other natural disaster will occur.
Scientific RevolutionThe Scientific Revolution was a series of events that marked the emergence of modern science during the early modern period, when developments in mathematics, physics, astronomy, biology (including human anatomy) and chemistry transformed the views of society about nature. The Scientific Revolution took place in Europe in the second half of the Renaissance period, with the 1543 Nicolaus Copernicus publication De revolutionibus orbium coelestium (On the Revolutions of the Heavenly Spheres) often cited as its beginning.
Sequential analysisIn statistics, sequential analysis or sequential hypothesis testing is statistical analysis where the sample size is not fixed in advance. Instead data are evaluated as they are collected, and further sampling is stopped in accordance with a pre-defined stopping rule as soon as significant results are observed. Thus a conclusion may sometimes be reached at a much earlier stage than would be possible with more classical hypothesis testing or estimation, at consequently lower financial and/or human cost.
Extreme weatherExtreme weather includes unexpected, unusual, severe, or unseasonal weather; weather at the extremes of the historical distribution—the range that has been seen in the past. Extreme events are based on a location's recorded weather history. They are defined as lying in the most unusual ten percent (10th or 90th percentile of a probability density function). The main types of extreme weather include heat waves, cold waves and heavy precipitation or storm events, such as tropical cyclones.
Scientific theoryA scientific theory is an explanation of an aspect of the natural world and universe that can be (or a fortiori, that has been) repeatedly tested and corroborated in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, theories are tested under controlled conditions in an experiment. In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning.
Heavy-tailed distributionIn probability theory, heavy-tailed distributions are probability distributions whose tails are not exponentially bounded: that is, they have heavier tails than the exponential distribution. In many applications it is the right tail of the distribution that is of interest, but a distribution may have a heavy left tail, or both tails may be heavy. There are three important subclasses of heavy-tailed distributions: the fat-tailed distributions, the long-tailed distributions, and the subexponential distributions.
Fréchet distributionThe Fréchet distribution, also known as inverse Weibull distribution, is a special case of the generalized extreme value distribution. It has the cumulative distribution function where α > 0 is a shape parameter. It can be generalised to include a location parameter m (the minimum) and a scale parameter s > 0 with the cumulative distribution function Named for Maurice Fréchet who wrote a related paper in 1927, further work was done by Fisher and Tippett in 1928 and by Gumbel in 1958.
Politics of climate changeThe politics of climate change results from different perspectives on how to respond to climate change. Global warming is driven largely by the emissions of greenhouse gases due to human economic activity, especially the burning of fossil fuels, certain industries like cement and steel production, and land use for agriculture and forestry. Since the Industrial Revolution, fossil fuels have provided the main source of energy for economic and technological development.
Analysis of varianceAnalysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation.
Climate change mitigationClimate change mitigation is action to limit climate change by reducing emissions of greenhouse gases or removing those gases from the atmosphere. The recent rise in global average temperature is mostly due to emissions from burning fossil fuels such as coal, oil, and natural gas. Mitigation can reduce emissions by transitioning to sustainable energy sources, conserving energy, and increasing efficiency. It is possible to remove carbon dioxide () from the atmosphere by enlarging forests, restoring wetlands and using other natural and technical processes.
Effects of climate changeClimate change affects the physical environment, ecosystems and human societies. Changes in the climate system include an overall warming trend, more extreme weather and rising sea levels. These in turn impact nature and wildlife, as well as human settlements and societies. The effects of human-caused climate change are broad and far-reaching, especially if significant climate action is not taken. The projected and observed negative impacts of climate change are sometimes referred to as the climate crisis.
Attribution of recent climate changeEfforts to scientifically ascertain and attribute mechanisms responsible for recent global warming and related climate changes on Earth have found that the main driver is elevated levels of greenhouse gases produced by human activities, with natural forces adding variability. The likely range of human-induced surface-level air warming by 2010–2019 compared to levels in 1850–1900 is 0.8 °C to 1.3 °C, with a best estimate of 1.07 °C. This is close to the observed overall warming during that time of 0.9 °C to 1.
