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Modified, threshold-based circulation type classification for Central Europe, on the basis of Lityński’s classification

Kinga Kulesza
Kinga Kulesza
   | 31 gen 2019
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Pubblicato online: 31 gen 2019
Pagine: 53 - 62
Ricevuto: 24 apr 2018
Accettato: 11 ott 2018
DOI: https://doi.org/10.2478/mgrsd-2018-0033
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© 2019 Kinga Kulesza, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1

Example of a spatial domain for the Lityński-based circulation type classification.Source: own elaboration.
Example of a spatial domain for the Lityński-based circulation type classification.Source: own elaboration.

Figure 2

The thresholds for the classes of the indices Wp (a), Ws (b) and Cp (c) for 16 January 1948-2015. ORG_u – the upper threshold for the ORG classification; NEW_u – the upper threshold for the NEW classification; MOD20_u – the upper threshold for the MOD20 classification; ORG_I – the lower threshold for the ORG classification; NEW_I – the lower threshold for the NEW classification; and MOD20_I – the lower threshold for the MOD20 classification.Source: own elaboration.
The thresholds for the classes of the indices Wp (a), Ws (b) and Cp (c) for 16 January 1948-2015. ORG_u – the upper threshold for the ORG classification; NEW_u – the upper threshold for the NEW classification; MOD20_u – the upper threshold for the MOD20 classification; ORG_I – the lower threshold for the ORG classification; NEW_I – the lower threshold for the NEW classification; and MOD20_I – the lower threshold for the MOD20 classification.Source: own elaboration.

Figure 3

The value distribution of the Wp, Ws, and Cp indices for January (JAN), April (APR), July (JUL), and October (OCT) 1986-2015. Vertical dashed lines denote the class thresholds according to the formula x̄ ±0.433σ (the NEW1 variant); vertical continuous lines denote the class thresholds according to the percentiles 33 and 67 (the MOD30 variant). Variant names are explained in the text.Source: own elaboration.
The value distribution of the Wp, Ws, and Cp indices for January (JAN), April (APR), July (JUL), and October (OCT) 1986-2015. Vertical dashed lines denote the class thresholds according to the formula x̄ ±0.433σ (the NEW1 variant); vertical continuous lines denote the class thresholds according to the percentiles 33 and 67 (the MOD30 variant). Variant names are explained in the text.Source: own elaboration.

Figure 4

Deviations (%) of the frequencies of individual classes for the indices Wp (a), Ws (b), and Cp (c) from the theoretical equally-likely frequency (where the frequency of each class equals 33.33%), in individual classification variants. Variant names are explained in the text.Source: own elaboration.
Deviations (%) of the frequencies of individual classes for the indices Wp (a), Ws (b), and Cp (c) from the theoretical equally-likely frequency (where the frequency of each class equals 33.33%), in individual classification variants. Variant names are explained in the text.Source: own elaboration.

Figure 5

Mean absolute error (MAE) for the sub-variants MOD5, MOD10, MOD15, MOD20, MOD25, MOD30, and MOD35 at different periods of time on which the class thresholds are calculated. Variant names are explained in the text.Source: own elaboration.
Mean absolute error (MAE) for the sub-variants MOD5, MOD10, MOD15, MOD20, MOD25, MOD30, and MOD35 at different periods of time on which the class thresholds are calculated. Variant names are explained in the text.Source: own elaboration.

Figure 6

Atmospheric circulation types determined using the ORG and MOD20 classifications in comparison with synoptic charts for selected days at 12:00 UTC. Variant names are explained in the text.Source: own work on the basis of synoptic charts obtained from: Koninklijk Nederlands Meteorologisch Instituut 2018.
Atmospheric circulation types determined using the ORG and MOD20 classifications in comparison with synoptic charts for selected days at 12:00 UTC. Variant names are explained in the text.Source: own work on the basis of synoptic charts obtained from: Koninklijk Nederlands Meteorologisch Instituut 2018.

Mean absolute error (MAE) for the different variants of the classification algorithm. Variant names are explained in the text.

VariantORGNEWNEW1MOD30
MAB (pp)1.821.051.010.74

The matrix of agreement between the results of individual classification schemes (%). Variant names are explained in the text.

ORG
89.3NEW
88.095.6NEW1
84.991.193.0MOD30
80.986.387.689.2MOD20
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