Spring index

The spring index shows the time of vegetation development in the spring compared to the long-time average from 1981-2010. The phenological spring phases are summarized in the annually determined index. Since the temperature is vital for plant development, the spring index is a suitable parameter to measure the effects of climate change on vegetation.

The spring index is considered a statistical parameter. It is determined by means of the first ten phenological spring phases of the year and updated at the end of May. The observations documented by means of sufficiently long data series in the corresponding year at nearly 80 stations of the phenological measurement network are incorporated in it.

The spring of 2016

In spring 2016 the vegetation developed earlier than normal. At the beginning of the year, the full flowering of hazel was observed as early as hardly ever before and in February coltsfoot was also flowering very early. In January and February the vegetation had an advance of three to four weeks. Colder weather was reducing this advance in March and April to about a week and in May the development of the vegetation was about in the mean of the period 1981-2010.

Calculating the spring index

The following ten phenological phases are used to characterise the phenological spring as a whole; they occur between January and May:

• Blooming of the hazel bush
• Blooming of the coltsfoot
•  Blooming of the wood anemone
• Blooming of the cherry tree
• New leaf formation of the horse chestnut tree
• New leaf formation of the hazel bush
• New needle formation of the larch
• Blooming of the dandelion
• Blooming of the lady’s smock
• New leaf formation of the beech tree

The deviation from the average occurrence date is determined by means of a principal component analysis. This method is practical for structuring, simplifying and visualising complex data sets. In addition, it can be used to filter spatial and chronological dependencies. One result of this analysis, the 1st main component, is suitable to illustrate the year-over-year variability.

Further information