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In time series data, seasonality refers to the trends that occur at specific regular intervals less than a year, such as weekly, monthly, or quarterly. Seasonality may be caused by various factors, such as weather, vacation, and holidays [1] and consists of periodic, repetitive, and generally regular and predictable patterns in the levels [2] of a time series.
Season creep was included in the 9th edition of the Collins English Dictionary published in London June 4, 2007. [38] [39] The term was popularized in the media after the report titled "Season Creep: How Global Warming Is Already Affecting The World Around Us" was published by the American environmental organization Clear the Air on March 21, 2006. [40]
The seasonally adjusted annual rate (SAAR) is a rate that is adjusted to take into account typical seasonal fluctuations in data and is expressed as an annual total. SAARs are used for data affected by seasonality , when it could be misleading to directly compare different times of the year.
The solar seasons change at the cross-quarter days, which are about 3–4 weeks earlier than the meteorological seasons and 6–7 weeks earlier than seasons starting at equinoxes and solstices. Thus, the day of greatest insolation is designated "midsummer" as noted in William Shakespeare 's play A Midsummer Night's Dream , which is set on the ...
Climate change is already impacting our seasons in New York and phenology, bolstered by citizen science, is documenting those impacts. Climate change is affecting seasonal indicators. How ...
Climate change is upsetting the regular rhythm of the seasons, making plants and wildlife more susceptible to disease. Climate change: Seasonal shifts causing 'chaos' for UK nature Skip to main ...
Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series. It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components.
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]