radan huth institute of atmospheric physics, prague, czech republic
DESCRIPTION
Synoptic-climatological evaluation of COST733 circulation classifications: Principles and first results. Radan HUTH Institute of Atmospheric Physics, Prague, Czech Republic. GOAL. assess the synoptic-climatological applicability of classifications - PowerPoint PPT PresentationTRANSCRIPT
Synoptic-climatological evaluation of COST733 circulation classifications:
Principles and first results
Radan HUTH
Institute of Atmospheric Physics,
Prague, Czech Republic
GOAL
• assess the synoptic-climatological applicability of classifications
• i.e., how well they stratify surface weather (climate) conditions
TOOL• 2-sample Kolmogorov-Smirnov test
• equality of distributions of the climate element under one type against under all the other types
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
x
- 1 0 - 5 0 5 1 0 1 5 2 0 2 54 0
4 5
5 0
5 5
6 0
TOOL
• at each station
• classes for which the K-S test rejects the equality of distributions are counted
• the larger the count, the better the stratification, the better the synoptic-climatological applicability
EXAMPLE
• 20 objective class’s over domain 00 (whole Europe)
• + 6 subjective (and objectivized) catalogues (not assigned to any domain)
• from the v1.0 release of COST733 database
EXAMPLE
• winter (DJF)
• maximum temperature
• 97 European stations (ECA&D database)
• Jan 1958 – Feb 1993
Hess&Brez. – individual types
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
W A
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5W Z
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5W S
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5W W
Note geographical coherence of regions of acceptance / rejection of the hypothesis
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
S W Z
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5N W Z
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5H M
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5T M
Hess&Brez. – individual types
Hess&Brez. – individual types
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
H N A
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5H N Z
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5T B
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5T R W
Summary over types: %age of test rejections
subjective + objectivized catalogues
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
H E S S & B R E Z O W S K Y 2 9
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
P E C Z E L Y ( H U ) 1 3
H E S S & B R E Z O W S K Y - o b j . 2 9
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
S C H U E P P ( C H ) 4 0
-20 -10 0 10 20 30 4035
40
45
50
55
60
65
70
75
H&B subj x obj
blue = subj betterred = obj better
x
100 %
85-99 %
70-84 %
<70 %
Summary over types: %age of test rejections
objective catalogues I.
x
100 %
85-99 %
70-84 %
<70 %
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
E N K E & S P E K A T 1 0
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
E R P I C U M S L P 1 0 t y p e s 1 0
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
B E C K 1 8
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
L U N D 1 0
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
J E N K I N S O N - C O L L I S O N 2 6
Summary over types: %age of test rejections
objective catalogues II.
x
100 %
85-99 %
70-84 %
<70 %
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
P 2 7 ( K R U I Z I N G A ) 2 7
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
K - M E A N S N O I T E R ' S 1 7
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
S A N D R A 1 8
- 2 0 - 1 0 0 1 0 2 0 3 0 4 03 5
4 0
4 5
5 0
5 5
6 0
6 5
7 0
7 5
T - M O D E P C A 1 2
BRIEF SUMMARY• considerable differences between class’s, but several
common features• are they season- & variable-specific or more general ?• bad stratification at edges (but not all) of the domain
– SW (W Iberian Peninsula)– SE (Balkans)– NE (N Norway)– E (W Russian border)
• good stratification in – central Europe (N of the Alps)– W Europe (incl. Ireland and whole France)– S & central Scandinavia– Baltic countries (EE, LV, LT)– Iceland (!!!)
• Verona – bad stratification for almost all class’s likely data problem
RANKING OF CLASS’S
• methods ranked by the %age of rejected K-S tests (= well separated classes) at all stations individually
• higher %age better lower rank• ranks averaged over stations for each
classification• area mean rank ranking of the
classification
RANKING OF CLASS’S
• dependence on no. of classes• lower number larger class sizes smaller
difference necessary for significance more (higher %age) of rejections better stratification
Enke&Spekat 10 1 Jenk-Coll 26 10 k-means with iter’s 17 19 T-PCA 7 7 2 Sandra seq. 22 11 Schüepp 40 20 Beck 18 3 k-means no iter’s 17 12 Petisco 14 21 T-PCA var. 12 4 Erpicum SLP 10 10 13 Erpicum Z500 10 10 22 Peczely 13 5 Perret 31 14 DWD 37 23 Hess&Brez obj. 29 6 P-27 (Kruizinga) 27 15 Erpicum Z500 30 29 24 Lund 10 7 Litynski adv. 9 16 ZAMG 42 25 Hess&Brez 29 8 Litynski full 27 17 Erpicum SLP 30 30 26 Sandra 18 9 Ward 11 18
RANKING OF CLASS’Slow number of classes (7 to 14)Enke&Spekat 10 1 T-PCA 7 7 2 T-PCA var. 12 4 Peczely 13 5 Lund 10 7 Erpicum SLP 10 10 13 Litynski adv. 9 16 Ward 11 18 Petisco 14 21 Erpicum Z500 10 10 22
RANKING OF CLASS’Smoderate number of classes (17
to 22)
Beck 18 3 Sandra 18 9 Sandra seq. 22 11 k-means no iter’s 17 12 k-means with iter’s 17 19
RANKING OF CLASS’Shigh number of classes (26 to 42)
Hess&Brez obj. 29 6 Hess&Brez 29 8 Jenkinson&Collison 26 10 Perret 31 14 P-27 (Kruizinga) 27 15 Litynski full 27 17 Schüepp 40 20 DWD 37 23 Erpicum Z500 30 29 24 ZAMG 42 25 Erpicum SLP 30 30 26
PRELIMINARY CONCLUSIONS
• synoptic-climatological applicability widely differs among class’s
• synoptic (& objectivized) catalogues compete successfully with objective methods (although not originally designed for the large domain)
• objectivized Hess-Brezowsky slightly better than original subjective catalogue
• Hess-Brezowsky outperforms all objective methods with comparable no. of types
PRELIMINARY CONCLUSIONS
• tentatively recommendable class’s:– Enke & Spekat– Beck– T-mode PCA– objectivized Hess & Brezowsky– SANDRA
• but: other seasons & other climate elements may lead to different results
task for near future