Post on 04-Jan-2016
description
Homogenization of monthly Benchmark temperature series of network no. 3 – using ProClimDB software
COST Benchmark meeting in Zürich 13-14 September 2010 – Lars
Andresen
Norwegian Meteorological Institute met.no
Software package
– AnClim• Homogeneity analysis (using txt-files)
– ProClimDB• Automating the homogenization procedure
(using mainly dbf-files)
• Petr Štěpánek
Norwegian Meteorological Institute met.no
Normal homogenization procedure
Original Data
Quality control
Reconstruction of series
Homogeneity testing
Adjusting Data
Reference series (40 years, 10 years overlap) from correl. / weights
SNHT (Alexandersson test) Assessment of hom. results
Standardization to base station (AVG/STD)
Stations within 10 km Demands on data coverage
Merging of different series
Iteration process
Reference series (10 years around inhomogeneity) from distances
Standardization to base station (AVG/STD)
Smoothing monthly adjustments / Demands on corr. after adjustm.
Rank of monthly values Comparing with neighbours
Replacing suspicious valuesDist. / Stand. to alt. / Outliers
Norwegian Meteorological Institute met.no
Detecting breaks of network 3 (15 series)
• Outliers removed from manipulated series– 10 outliers from 8 stations
• Testing settings of ProClimDB – 40 year periods, 10 years overlap versus 20
years– Excluding breaks closer than 4 years to edge of
series or to nearest break– Finding the more distinct breaks before the less
distinct ones
Norwegian Meteorological Institute met.no
Removing outliers
Station 01400
Value of 5/1978 changed from 14.8°C (outlier) to 10.8°C (true)
1976, 14.3/14.3
1977, 11.5/11.5
1978, 10.8/14.8
1979, 13.2/13.2
1980, 8.8/8.8
Norwegian Meteorological Institute met.no
Consequences by changing overlap years – A case study, using SNHT method
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Years from edge of series
%
FaultNo sign. breaksNearly approvedApproved
0
10
20
30
40
50
60
70
80
90
100
%
FaultNo sign. breaksNearly approvedApproved
0.3° 0.5° 0.7°
• Single shift of +/- 0.5°
• 2, 4, 9, 19 years from edge of a homogeneous temperature series of 40 years
• Single shift of +/- 0.3, 0.5, 0.7°
• Each pair 9 and 19 years from edge of the series
Norwegian Meteorological Institute met.no
Criteria for detection
• Approved– Correct year (two years involved, both correct)– Adjustment within ± 0.1 degrees, e.g. 0.5 ± 0.1– T0 ≥ 8.1 (40 years – significance level 95%)
• Nearly approved– Correct year, T0 ≥ 8.1, Adj = 0.5 ± 0.3 degrees
– Correct year ± 1, T0 ≥ 8.1, Adj = 0.5 ± 0.2
– Correct year, T0 ≥ 7.0 (s.l.90%), Adj = 0.5 ± 0.1
• Fault– Significant break not approved or nearly approved
Norwegian Meteorological Institute met.no
Network 3 – comparing 46 breaks
B: Breaks detected , M: Missing detection , F: Fault detection
After 0 1 2 iterations
05
101520253035
B M F
05
101520253035
B M F
05
101520253035
B M F
Overlap
10 years
20 years
05
101520253035
B M F
05
101520253035
B M F
05
101520253035
B M F
Y_Poss ≥30
Y_Poss ≥25
Y_Poss ≥20
Norwegian Meteorological Institute met.no
Left: ”Official result” (46 breaks)
Y_Poss ≥15, no iteration
05
101520253035
B M FY_Poss ≥30, 25 and 20, 2
iterations
Case study
05
10152025303540
B M F
Norwegian Meteorological Institute met.no
Discussion – 1Homogeneity analysis
Reference series for finding breaks• Using correlations• Using distances• Weighting of neighbour values (0.5 or 1.0?)• Period (40 years) / Overlap (10 or 20 years?)
Processing of results• Method (SNHT alone or in combination with others?)• Finding most probable breaks (Y_POSSIBLE). How?• Weighting of month, season, year (1, 2, 5)• Metadata (improving?)• Nearness to begin/end/other breaks (2 or 4 years?)
Norwegian Meteorological Institute met.no
Discussion – 2Adjustments of the series
Reference series for making adjustments• Using distance alone (limitation on distance)• Using distance and correlation (limitations on distance
and correlation)
Smoothing monthly adjustments• Gauss filter (0~no smoothing, 2~period of 5 values is
recommended, other?)
Checking correlation after adjustments• Keep smoothed adjustment if correlation improvement
between candidate and neighbours (Corr+value) ≥ 0.005 or ≥ 0.000 ?
Norwegian Meteorological Institute met.no
Discussion – 3
Iterations
• Using adjusted file for new analysis• How finding most probable breaks
– More stringent criteria when automating procedure (depends on metadata and Y_POSSIBLE)?
Norwegian Meteorological Institute met.no
Conclusion
• It is reason for concern about the high number of fault detections
• Use of metadata is necessary in homogenization! Using metadata allows lower values of Y_Possible
• It’s important to find the optimal conditions of a procedure before comparing methods
• Homogenization has no correct answer !