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Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland.

Nowosad J, Stach A, Kasprzyk I, Grewling Ł, Latałowa M, Puc M, Myszkowska D, Weryszko-Chmielewska E, Piotrowska-Weryszko K, Chłopek K, Majkowska-Wojciechowska B, Uruska A - Aerobiologia (Bologna) (2014)

Bottom Line: The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions.The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back.These results can help to improve the quality of forecasting models.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Dzięgielowa 27, 61-680 Poznań, Poland.

ABSTRACT

The aim of the study was to determine the characteristics of temporal and space-time autocorrelation of pollen counts of Alnus, Betula, and Corylus in the air of eight cities in Poland. Daily average pollen concentrations were monitored over 8 years (2001-2005 and 2009-2011) using Hirst-designed volumetric spore traps. The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions. The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back. The study revealed an association between temporal variations in Alnus, Betula, and Corylus pollen counts in Poland and three main groups of factors such as: (1) air mass exchange after the passage of a single weather front (30-40 % of pollen count variation); (2) long-lasting factors (50-60 %); and (3) random factors, including diurnal variations and measurements errors (10 %). These results can help to improve the quality of forecasting models.

No MeSH data available.


Related in: MedlinePlus

Diagrams of Betula cross-correlation between locations with lead (left branch) and lag (right branch) time using all the data. The cross shows the synchronous correlation value (lag/lead = 0 days). A comparison of these charts allows capturing the asymmetric relationship of time-predominant leads or delays. Cross-correlograms are labelled by class number (see Fig. 3 and description on page 5)
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Fig10: Diagrams of Betula cross-correlation between locations with lead (left branch) and lag (right branch) time using all the data. The cross shows the synchronous correlation value (lag/lead = 0 days). A comparison of these charts allows capturing the asymmetric relationship of time-predominant leads or delays. Cross-correlograms are labelled by class number (see Fig. 3 and description on page 5)

Mentions: Figures 9, 10, 11 show cross-correlograms of Alnus, Betula, and Corylus pollen counts in Poland. Cross-correlograms of alder were the most homogeneous, with symmetric and simple shapes. Moreover, the temporal range of pollen counts was the shortest, in most cases it did not exceed 10 days. Most of birch and hazel cross-correlograms had an asymmetrical shape, often with a few oscillations. Its range was generally longer, sometimes even more than 20 days. Furthermore, correlation rose along with a 1- to 5-day lag/lead in numerous pairs of monitoring sites. The strongest variation was seen in the case of Gdańsk. Most of its cross-correlograms were asymmetric and showed considerable variation.


Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland.

Nowosad J, Stach A, Kasprzyk I, Grewling Ł, Latałowa M, Puc M, Myszkowska D, Weryszko-Chmielewska E, Piotrowska-Weryszko K, Chłopek K, Majkowska-Wojciechowska B, Uruska A - Aerobiologia (Bologna) (2014)

Diagrams of Betula cross-correlation between locations with lead (left branch) and lag (right branch) time using all the data. The cross shows the synchronous correlation value (lag/lead = 0 days). A comparison of these charts allows capturing the asymmetric relationship of time-predominant leads or delays. Cross-correlograms are labelled by class number (see Fig. 3 and description on page 5)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4555345&req=5

Fig10: Diagrams of Betula cross-correlation between locations with lead (left branch) and lag (right branch) time using all the data. The cross shows the synchronous correlation value (lag/lead = 0 days). A comparison of these charts allows capturing the asymmetric relationship of time-predominant leads or delays. Cross-correlograms are labelled by class number (see Fig. 3 and description on page 5)
Mentions: Figures 9, 10, 11 show cross-correlograms of Alnus, Betula, and Corylus pollen counts in Poland. Cross-correlograms of alder were the most homogeneous, with symmetric and simple shapes. Moreover, the temporal range of pollen counts was the shortest, in most cases it did not exceed 10 days. Most of birch and hazel cross-correlograms had an asymmetrical shape, often with a few oscillations. Its range was generally longer, sometimes even more than 20 days. Furthermore, correlation rose along with a 1- to 5-day lag/lead in numerous pairs of monitoring sites. The strongest variation was seen in the case of Gdańsk. Most of its cross-correlograms were asymmetric and showed considerable variation.

Bottom Line: The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions.The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back.These results can help to improve the quality of forecasting models.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Dzięgielowa 27, 61-680 Poznań, Poland.

ABSTRACT

The aim of the study was to determine the characteristics of temporal and space-time autocorrelation of pollen counts of Alnus, Betula, and Corylus in the air of eight cities in Poland. Daily average pollen concentrations were monitored over 8 years (2001-2005 and 2009-2011) using Hirst-designed volumetric spore traps. The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions. The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back. The study revealed an association between temporal variations in Alnus, Betula, and Corylus pollen counts in Poland and three main groups of factors such as: (1) air mass exchange after the passage of a single weather front (30-40 % of pollen count variation); (2) long-lasting factors (50-60 %); and (3) random factors, including diurnal variations and measurements errors (10 %). These results can help to improve the quality of forecasting models.

No MeSH data available.


Related in: MedlinePlus