Limits...
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

Matrix of correlogram models (a—all data, b—first threshold) for various taxa at the same locations
© Copyright Policy - OpenAccess
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4555345&req=5

Fig6: Matrix of correlogram models (a—all data, b—first threshold) for various taxa at the same locations

Mentions: On average, correlogram shows a decline for the 3.5 days lag (Alnus—5.2, Betula—2.9, Corylus—3.5). Afterwards, the value kept decreasing steadily. Thus, autocorrelation coefficients reduced to zero after an average of 15.0 days (range 8.2–22.5) (Figs. 5, 6; Table 2). The removal of extreme values increased autocorrelation (0.70 on average) and expanded its range (19.5 and 18.2 days on average) (Tables 2, 3).Fig. 5


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)

Matrix of correlogram models (a—all data, b—first threshold) for various taxa at the same locations
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig6: Matrix of correlogram models (a—all data, b—first threshold) for various taxa at the same locations
Mentions: On average, correlogram shows a decline for the 3.5 days lag (Alnus—5.2, Betula—2.9, Corylus—3.5). Afterwards, the value kept decreasing steadily. Thus, autocorrelation coefficients reduced to zero after an average of 15.0 days (range 8.2–22.5) (Figs. 5, 6; Table 2). The removal of extreme values increased autocorrelation (0.70 on average) and expanded its range (19.5 and 18.2 days on average) (Tables 2, 3).Fig. 5

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