{"id":512,"date":"2026-07-21T16:24:28","date_gmt":"2026-07-21T16:24:28","guid":{"rendered":"http:\/\/77.42.80.226\/?p=512"},"modified":"2026-07-21T16:34:50","modified_gmt":"2026-07-21T16:34:50","slug":"why-spring-no-longer-begins-when-the-calendar-says-it-should","status":"publish","type":"post","link":"https:\/\/climatess.org\/index.php\/2026\/07\/21\/why-spring-no-longer-begins-when-the-calendar-says-it-should\/","title":{"rendered":"Why Spring No Longer Begins When the Calendar Says It Should"},"content":{"rendered":"\n
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SEASONALITY MATTERS \u00b7 6 MIN READ<\/p>\n\n\n\n

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We are used to thinking of seasons as fixed blocks in the calendar. Spring begins in March, summer in June, autumn in September and winter in December. This system is simple and useful, but the atmosphere does not follow our calendar.<\/p>\n\n\n\n

A warm spell may arrive weeks before the official beginning of spring. Summer-like conditions can persist well into September. A cold period may return after plants have already started growing. As the climate changes, the difference between calendar seasons and the conditions we actually experience is becoming increasingly important.<\/p>\n\n\n\n

So how can we identify when one season truly gives way to another?<\/p>\n\n\n\n

Reading the rhythm of the atmosphere<\/h2>\n\n\n\n

In our study, published in the International Journal of Climatology<\/em>, we explored a different way of tracking seasons. Instead of assigning them fixed dates, we used a meteorological index called the Normalised Daily Temperature Range<\/strong>, or NDTR<\/strong>.<\/p>\n\n\n\n

NDTR is calculated from three routine observations: the daily maximum, minimum and average air temperature. Together, they describe more than whether a day was simply warm or cold. They also reflect how the atmosphere heats during the day and cools at night\u2014a rhythm influenced by sunlight, clouds, humidity, soil, vegetation and atmospheric mixing.<\/p>\n\n\n\n

When NDTR is followed throughout the year, a recognisable pattern emerges. Winter has a relatively stable cold-season regime. Spring is marked by rapid atmospheric reorganisation. Summer forms a warmer and more stable period, while autumn records the transition back towards the cold regime. By analysing the peaks, stable sections and inflection points of the annual NDTR curve, we can identify seasonal boundaries from the behaviour of the atmosphere itself.<\/p>\n\n\n\n

Seasons are transitions, not dates<\/h2>\n\n\n\n

This approach changes the central question. Instead of asking, \u201cWhich month are we in?\u201d, we ask, \u201cWhich atmospheric regime are we experiencing?\u201d<\/p>\n\n\n\n

That distinction matters because fixed calendar seasons often place very different weather conditions inside the same three-month block. Early March and late May, for example, may both be labelled spring even though their atmospheric behaviour is completely different.<\/p>\n\n\n\n

Across the sites examined in the study, NDTR-defined seasons were more internally coherent than calendar seasons. Variability in air temperature and dew-point temperature within seasons was reduced by approximately 12\u201314%<\/strong>, while improvements during the rapidly changing spring and autumn periods reached up to 28%<\/strong>. In other words, the NDTR boundaries separated atmospheric regimes more clearly than fixed calendar dates.<\/p>\n\n\n\n

The atmosphere changes first\u2014and ecosystems respond<\/h2>\n\n\n\n

Plants are valuable biological sensors of seasonal change. Their leaves emerge, canopies develop and colours change in response to environmental conditions. We therefore compared atmospheric transitions derived from NDTR with satellite observations of vegetation and with ground-based phenological records.<\/p>\n\n\n\n

The comparison revealed a close relationship, particularly in spring, but not perfect synchronisation. At low elevations, the NDTR-derived start of the growing season occurred about 10 days later<\/strong> than observed plant development. At middle elevations, the difference decreased to approximately 3\u20134 days<\/strong>.<\/p>\n\n\n\n

This does not mean that one of the signals is wrong. They describe different parts of the same process. Vegetation can react to an early warm spell, while NDTR identifies the point at which a more stable seasonal atmospheric regime has become established.<\/p>\n\n\n\n

The difference was larger in autumn. Vegetation may remain green even after its physiological activity has declined, while the atmosphere has already begun its transition towards the cold season. The NDTR-based end of the growing season therefore tended to occur earlier than the observed vegetation signal, with a typical difference ranging from about 12 days at higher sites to 22.8 days at low elevations<\/strong>.<\/p>\n\n\n\n

This distinction is essential: NDTR does not use plants to define the seasons. It identifies atmospheric transitions, while vegetation shows how ecosystems respond to them.<\/p>\n\n\n\n

A changing seasonal map of Europe<\/h2>\n\n\n\n

We applied the method to ERA5-Land climate data across the Euro-Mediterranean region. The results revealed clear geographic patterns shaped by latitude, elevation, continentality and proximity to the sea.<\/p>\n\n\n\n

Winter lasted more than 200 days in parts of northern and northeastern Europe, but fewer than 100 days in many southern and Mediterranean areas. Summer showed the opposite pattern, exceeding 200 days in parts of the Mediterranean while remaining shorter than 100 days in the north.<\/p>\n\n\n\n

Comparing recent decades also showed a broad redistribution of the year. Depending on the climate region, winter shortened by approximately 6\u201321 days<\/strong>, while summer lengthened by about 4\u201312 days<\/strong>. Spring and autumn did not change uniformly: in some regions they expanded as winter contracted, while in others a longer summer reduced the duration of autumn.<\/p>\n\n\n\n

Climate change is therefore not simply making every season shift by the same number of days. It is reorganising the annual cycle differently across regions.<\/p>\n\n\n\n

Why dynamic seasons matter<\/h2>\n\n\n\n

A season definition based on atmospheric behaviour can support much more than climate research. Agricultural planning depends on realistic windows for planting, crop protection and harvest. Tourism, energy demand, pollen exposure and heat-health services also depend on the actual duration of seasonal conditions\u2014not merely on the date printed on a calendar.<\/p>\n\n\n\n

Because NDTR uses routinely available temperature data, it can be calculated for many locations and potentially incorporated into monitoring and forecasting systems. It offers a continuous and comparable way to follow seasonal dynamics without relying on a fixed temperature threshold or on a particular type of vegetation.<\/p>\n\n\n\n

The calendar remains useful. But in a changing climate, it can no longer tell the whole seasonal story. To understand when spring, summer, autumn or winter truly begins, we need to listen to the rhythm of the atmosphere.<\/p>\n\n\n\n

\n\n\n\n

Based on the research article:<\/strong>
Lalic, B. and Firanj Sremac, A. (2026). \u201cTracking Seasonal Transitions Using a Meteorological Seasonality Index.\u201d International Journal of Climatology<\/em>. https:\/\/doi.org\/10.1002\/joc.70447<\/p>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

SEASONALITY MATTERS \u00b7 6 MIN READ We are used to thinking of seasons as fixed blocks in the calendar. Spring begins in March, summer in June, autumn in September and winter in December. This system is simple and useful, but the atmosphere does not follow our calendar. A warm spell may arrive weeks before the […]<\/p>\n","protected":false},"author":1,"featured_media":12,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-512","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-seasonality-matters"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/posts\/512","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/comments?post=512"}],"version-history":[{"count":3,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/posts\/512\/revisions"}],"predecessor-version":[{"id":516,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/posts\/512\/revisions\/516"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/media\/12"}],"wp:attachment":[{"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/media?parent=512"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/categories?post=512"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/climatess.org\/index.php\/wp-json\/wp\/v2\/tags?post=512"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}