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VI Seminar Homogenization, Budapest 2008. “Characterization of data sets for the assessment of inhomogeneities of climate data series, resulting from the automation of the observing network in Mainland Portugal. M.Mendes, J.Neto, A.Silva, L.Nunes , P.Viterbo Instituto de Meteorologia, Portugal. - PowerPoint PPT Presentation
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VI Seminar
Homogenization,
Budapest 2008
VI Seminar Homogenization, Budapest 2008
M.Mendes, J.Neto, A.Silva, L.Nunes, P.Viterbo
Instituto de Meteorologia, Portugal
“Characterization of data sets for the assessment of inhomogeneities of climate data
series, resulting from the automation of the observing network in Mainland Portugal
VI Seminar
Homogenization,
Budapest 2008
Current IM network withoverlapping observations
• 30 sites with Automatic Weather Stations (AWS) and Conventional Stations (CS)
• 2 sites also with Present Weather Sensors (WW)
VI Seminar
Homogenization,
Budapest 2008
The problem: continuation of conventional dataseries with data from Automatic Weather Station?
BRAGANÇA MONTHLY MEAN MAXIMUM TEMPERATURE
0
5
10
15
20
25
30
35
1998
1998
1999
1999
1999
1999
1999
1999
2000
2000
2000
2000
2000
2000
2001
2001
2001
2001
2001
2001
2002
2002
2002
2002
2002
2002
2003
2003
2003
2003
2003
2003
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
CS
AWS
BRAGANÇA MONTHLY MEAN MAXIMUM TEMPERATURE
0
5
10
15
20
25
30
35
19
41
19
42
19
43
19
44
19
45
19
46
19
48
19
49
19
50
19
51
19
52
19
53
19
55
19
56
19
57
19
58
19
59
19
60
19
62
19
63
19
64
19
65
19
66
19
67
19
69
19
70
19
71
19
72
19
73
19
74
19
76
19
77
19
78
19
79
19
80
19
81
19
83
19
84
19
85
19
86
19
87
19
88
19
90
19
91
19
92
19
93
19
94
19
95
19
97
19
98
19
99
20
00
20
01
20
02
20
04
20
05
20
06
CS
AWS
BRAGANÇA DAILY MAXIMUM TEMPERATURE
-5,0
0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
40,0
19
41
19
42
19
43
19
44
19
45
19
46
19
47
19
49
19
50
19
51
19
52
19
53
19
54
19
55
19
57
19
58
19
59
19
60
19
61
19
62
19
64
19
65
19
66
19
67
19
68
19
69
19
70
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
88
19
89
19
90
19
91
19
92
19
93
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
03
20
04
20
05
20
06
CS
AWS
BRAGANÇA DAILY MAXIMUM TEMPERATURE
-5,0
0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
40,0
1998
1998
1998
1998
1999
1999
1999
1999
1999
2000
2000
2000
2000
2000
2000
2001
2001
2001
2001
2001
2002
2002
2002
2002
2002
2003
2003
2003
2003
2003
2003
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
CS
AWS
VI Seminar
Homogenization,
Budapest 2008
Nr. CS Start CS End531 01-07-1922 ...535 01-01-1836 ...541 01-11-1988 ...543 01-07-1969 28-02-2006548 01-04-1995 ...551 21-11-2005 ...557 01-01-1869 ...558 01-04-1995 ...560 01-04-1991 ...562 01-01-1873 30-04-2004567 01-02-1992 ...568 01-01-1931 ...570 01-05-1985 ...571 01-01-1932 ...575 01-03-1931 ...579 01-01-1982 ...605 01-08-1967 ...611 01-01-1879 ...619 01-01-1980 ...632 01-01-1924 ...635 01-01-1932 31-12-2001685 01-01-1954 31-08-2002702 01-10-1980 ...744 01-05-1977 ...770 01-01-1924 ...783 01-11-1933 ...812 01-01-1948 ...835 01-01-1927 ...850 01-05-1963 ...864 01-06-1982
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
OVERLAPPING PERIODS OF AWS AND CS DATA
VI Seminar
Homogenization,
Budapest 2008
Station Features
Automatic Weather Stations
Type I - AWS1 (15) Type II – AWS2 (15)
• Temperature (air,ground)• Humidity• Wind• Global radiation• Pressure• Precipitation• Interactive terminal (TIC)• 10 minute records
• Temperature (air, ground)• Humidity• Wind• Global radiation• Precipitation• 10 minute records
Conventional Stations
Principal – CS1 (15) Simple – CS2 (15)
• Temperat.(air, ground)• Humidity• Wind• Sunshine duration• Pressure• Precipitation• Visual parameters (cloud cover, cloud type, present & past weather, horiz. visibility)• Daily records• 1,2 hourly records/day• Profissional Observers
• Temperature (air & ground)• Wind• Sunshine duration• Precipitation• Visual parameters (cloud cover, present & past weather, horizontal visibility,...)• Daily records• 1,2 hourly records/day• Volunteers
Present Weather Systems (2)•Precipitation sensor•Horizontal visibility sensor
VI Seminar
Homogenization,
Budapest 2008
Conventional Observationsand Instruments
Piranómetro
Radiation screen
Thermometers
Thermo-hygrograph
Rain gauge
Sunshine-recorder
Evaporation pan
Mercury Baromet
erVisual observations
VI Seminar
Homogenization,
Budapest 2008
Automatic weather station sensors and equipments
Wind vane and anemometer
Pyranometer
Rain detector
Radiation shield with
temp. & hum. sensors
Rain gauge
AWS with solar panel
GSM Antena
Data acquisition system
VI Seminar
Homogenization,
Budapest 2008
Data records/failures AWS vs CS(10 years data)
AIR TEMPERATURE
Code Parameter
T009 Air temperature at 09 UTC
T015 Air temperature at 15 UTC
T018 Air temperature at 18 UTC
Tmax
Maximum temperature (09-09 UTC)•AWS – 144 consecutive 10 minute records and/or 24 consecutive hour records *•CS – 1 record
Tmin
Minimum temperature (09-09 UTC)•AWS – 144 consecutive 10 minute records and/or 24 consecutive hour records *•CS – 1 record
Tmn1
Maximum temperature (09-18 UTC)•AWS – 60 consecutive 10 minute records and/or 10 consecutive hour records *•CS – 1 record
Tmx1
Minimum temperature (00-10 UTC)•AWS – 66 consecutive 10 minute records and/or 11 consecutive hour records *•CS – 1 record
AWS - % FAILURE DAYS
Nr. NDays T009 T015 T018 Tmax Tmin Tmn1 Tmx1531 3471 4.6 4.4 4.4 12.0 12.1 9.3 8.7535 2771 0.8 0.8 0.6 4.8 4.9 2.7 3.6541 3471 1.5 1.8 1.6 7.2 7.2 4.6 5.3543 2830 1.0 0.9 0.9 1.9 2.0 1.5 1.7
548 3136 1.7 1.3 1.1 5.2 5.2 3.9 4.1551 306 12.7 11.8 11.4 19.9 19.9 18.0 17.3
557 1826 6.6 6.6 6.6 7.3 7.3 7.1 7.2558 3501 2.3 2.3 2.1 5.7 5.7 3.4 4.2560 3501 4.7 5.1 5.0 10.9 10.9 5.2 9.0562 2496 1.6 1.8 1.7 4.9 4.9 3.3 3.9567 3501 1.4 1.2 1.3 3.0 3.0 2.3 2.3
568 3287 3.1 3.0 3.1 9.8 9.8 7.2 7.9570 3167 1.7 1.5 1.6 6.9 6.9 4.3 4.8571 3501 2.8 2.8 2.8 6.2 6.2 4.7 4.9575 3136 1.9 1.3 1.4 5.7 5.8 4.5 5.1579 3501 3.0 3.0 3.2 12.8 12.8 8.2 8.7605 3136 16.1 10.2 13.7 34.5 34.5 30.4 27.5611 2557 7.4 6.8 7.3 19.2 19.2 13.9 14.7619 3106 12.6 14.9 12.3 24.9 24.9 20.6 22.0
632 2557 14.6 9.6 11.4 29.8 29.9 24.9 23.5635 731 7.0 6.7 6.9 15.1 15.2 11.6 12.1685 1553 8.1 7.6 8.0 16.3 16.3 13.3 12.9702 3106 3.8 3.3 3.5 15.4 15.4 10.1 10.1744 3501 9.1 8.4 8.2 17.5 17.5 14.9 14.4
770 3501 11.2 8.6 10.1 24.9 25.0 18.9 20.6783 3501 7.6 6.4 6.7 18.8 18.8 15.7 13.5812 2557 11.9 7.1 8.9 24.6 24.7 23.0 18.7835 3501 8.6 7.8 9.3 17.7 17.7 15.3 14.0850 3501 20.4 10.6 12.9 46.9 47.1 44.0 32.6
864 2771 5.4 5.7 5.5 12.1 12.1 9.1 9.4
CS - % FAILURE DAYS
Nr Ndays T009 T015 T018 Tmax Tmin530 3471 0.07 0.07 0.61 0.42
535 2771 0.01 0.33 0.00 0.00541 3471 0.39 0.41 0.39 0.39543 2830 0.00 0.00 0.00 0.00
548 3136 0.00 0.00 0.00 0.00551 306 0.05 0.10 0.05 0.05
557 1826 0.04 0.06 0.04558 3501 0.28 0.29 0.29 0.28560 3501 0.00 0.02 0.00 0.00562 2496 0.25 0.73 0.31 0.25 0.25567 3501 0.01 0.03 0.01 0.01
568 3287 0.08 0.59 0.12 0.12570 3167 0.00 0.00 0.00 0.00571 3501 0.01 0.02 0.01 0.00
575 3136 0.02 0.06 0.02 0.02579 3501 0.00 0.02 0.00 0.00
5 3136 0.05 0.12 0.05 0.0511 2557 0.04 0.04 0.0419 3106 0.00 0.00 0.00 0.00
32 2557 0.15 0.44 0.16 0.2535 731 0.21 0.24 0.22 0.22
85 1553 0.17 0.20 0.17 0.17102 3106 0.03 0.02 0.08144 3501 0.00 0.34 0.00 0.00
170 3501 0.00 0.00 0.00183 3501 0.34 0.34 0.35 0.35
212 2557 0.00 0.00 0.16 0.00235 3501 0.02 0.30 0.02 0.02250 3501 0.16 0.16 0.16
264 2771 0.29 0.37 0.29 0.29
VI Seminar Homogeniza
tion, Budapest
2008
Bias results for air temperature(Differences between observations AWS-CS)
BIAS 531 535 541 543 548 551 557 558 560 562 567 568 570 571 575 579 605 611 619 632 635 685 702 744 770 783 812 835 850 864
T009 0.19 0.42 0.17 0.56 0.23 -0.05 1.56 0.10 0.04 0.39 -0.03 -0.03 0.54 0.35 0.51 0.08 -0.39 -0.29 -0.20 -0.27 0.61 0.40 0.21 -0.93 0.42 -0.67 1.03 -0.68 0.84 0.37
T015 0.30 0.34 -0.01 -0.27 -2.10 0.38 0.30 -0.17 2.18 0.45 0.23
T018 -0.13 -0.27 -0.08 -0.62 0.01 -0.19 -0.23 -0.27 -0.36 -0.46 -0.30 -0.63 -0.15 -0.28 -0.02 -1.72 -0.61 0.06
Tmin 0.29 -0.12 -0.23 -0.23 -0.38 -0.18 0.12 -0.21 -0.22 -0.25 -0.36 -0.11 -0.01 -0.05 -0.05 -0.19 -0.17 0.01 1.05 0.44 -0.09 1.45 0.02 -0.49 -0.59 0.12 0.59 0.11 -0.23 0.02
Tmn1 0.33 -0.10 -0.21 -0.21 -0.37 -0.14 0.12 -0.20 -0.20 -0.24 -0.35 -0.03 0.00 -0.02 -0.04 -0.18 -0.16 0.03 1.08 0.44 -0.09 1.42 0.03 -0.48 -0.54 0.15 0.60 0.12 -0.23 0.04
Tmax -0.14 0.52 0.19 0.45 0.49 0.06 1.95 0.34 -0.21 0.01 -0.07 -0.05 0.15 0.22 0.14 0.21 -0.21 -0.70 -0.94 -0.51 -0.12 -1.38 -0.01 -0.02 0.31 0.07 0.24 -0.46 0.00 -0.04
Tmx1 -0.15 0.52 0.19 0.44 0.48 0.03 1.95 0.34 -0.23 0.01 -0.08 -0.08 0.14 0.21 0.13 0.20 -0.22 -0.71 -0.98 -0.49 -0.13 -1.39 -0.02 -0.03 0.31 0.06 0.24 -0.46 0.01 -0.04
<-0.25-0.25 to +0.25>+0.25
-> 11 cases for T09, 21 cases for Tmin, 19 cases for Tmax
VI Seminar Homogeniza
tion, Budapest
2008
Spatial distribution ofBias results for air temperature (AWS-CS)
VI Seminar Homogeniza
tion, Budapest
2008
Bias monthly results for air temperature
Tmax Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec5 -0.46 -0.34 -0.22 -0.21 -0.06 -0.11 -0.02 -0.12 -0.31 -0.4 -0.25 -0.28
11 -1.16 -0.98 -0.79 -1.01 -0.56 -0.36 -0.47 -0.19 -0.35 -0.78 -1.17 -0.97
19 -1.21 -0.98 -0.81 -0.83 -0.52 -0.22 -0.66 -0.52 -0.84 -1.03 -1.51 -1.64
32 -1.19 -0.34 0.01 -0.45 -0.05 -0.62 -0.55 -0.54 -0.27 -0.83 -0.43 -1.31
35 -0.28 -0.45 -0.31 -0.14 -0.03 -0.04 0.09 0.06 -0.09 -0.02 -0.12 -0.06
85 -1.67 -1.66 -1.74 -1.4 -0.9 -1.33 -0.71 -1.12 -1.27 -0.61 -1.83 -2.34
102 0.06 0.02 0.04 -0.12 -0.03 0.01 0.02 -0.05 0.05 0.01 -0.14 -0.02
144 -0.12 0 -0.04 0.01 -0.19 0.02 0.15 0.29 0.17 -0.22 -0.19 -0.13
170 0.19 0.25 0.23 0.41 0.39 0.44 0.44 0.44 0.4 0.12 0.13 0.17
183 -0.06 -0.07 0.18 0.07 -0.12 0.22 0.4 0.29 0.2 -0.13 -0.27 -0.21
212 0.2 0.33 0.29 0.2 0.28 0.3 0.33 0.21 0.26 0.11 0.19 0.19
235 -0.68 -0.59 -0.49 -0.39 -0.31 -0.22 -0.34 -0.47 -0.45 -0.59 -0.39 -0.68
250 -0.19 -0.1 -0.19 -0.06 0.1 0.1 0.24 0.14 0.08 -0.09 -0.1 -0.18
264 0 0.14 0.12 -0.18 0.13 -0.11 -0.18 -0.13 -0.11 -0.13 0.04 -0.05
557 1.9 1.86 2.21 2.38 2.15 2.08 1.67 1.98 1.99 1.57 1.93 1.84
530 -0.19 -0.11 0.02 -0.1 -0.14 -0.05 -0.32 -0.05 -0.05 -0.29 -0.27 -0.11
535 0.28 0.4 0.51 0.67 0.64 0.74 0.71 0.65 0.67 0.44 0.33 0.24
541 -0.06 0.02 0.1 0.15 0.18 0.46 0.32 0.48 0.47 0.22 0.06 -0.07
543 0.07 0.27 0.49 0.59 0.71 0.73 0.64 0.7 0.69 0.4 0.13 0.07
548 0.27 0.31 0.35 0.41 0.45 0.69 0.82 0.85 0.69 0.41 0.34 0.21
551 -0.1 0.15 0.29 0.14 0.17 0.06 0.16 0.04 -0.18 -0.28
558 0.16 0.2 0.24 0.34 0.47 0.47 0.56 0.53 0.45 0.3 0.2 0.16
560 -0.35 -0.45 -0.28 -0.16 -0.11 -0.13 -0.03 -0.03 -0.23 -0.26 -0.3 -0.3
562 -0.08 -0.05 0.04 0.03 0.24 0.09 -0.04 -0.03 -0.04 0.03 -0.04 -0.04
567 -0.12 -0.09 -0.08 -0.05 -0.06 -0.03 -0.01 -0.1 -0.09 -0.11 -0.07 -0.11
568 -0.06 -0.13 -0.08 -0.04 -0.01 -0.05 0.01 -0.06 0.01 -0.04 -0.09 -0.09
570 -0.04 0.06 0.13 0.18 0.23 0.27 0.29 0.27 0.23 0.15 0.05 -0.02
571 -0.06 0 0.15 0.25 0.49 0.49 0.48 0.38 0.31 0.16 0.03 -0.07
575 -0.05 -0.08 0.07 0.15 0.36 0.37 0.33 0.26 0.15 0.17 -0.04 -0.06
579 -0.03 0.02 0.08 0.17 0.27 0.37 0.52 0.5 0.33 0.13 0.04 0.01
Tmin Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
5 -0.15 -0.08 -0.16 -0.14 -0.17 -0.19 -0.18 -0.2 -0.18 -0.19 -0.18 -0.15
11 -0.05 0.06 0.01 0.03 0.07 0.08 -0 -0.08 -0.06 -0.03 0.03 0.08
19 1.08 1.22 0.56 1.13 0.57 0.85 0.97 1.08 1.05 1.53 1.28 1.12
32 0.18 0.29 0.4 0.71 0.59 0.45 -0.21 0.54 0.35 0.73 1.33 0.5
35 -0.11 -0.08 0.03 -0.09 -0.11 -0.07 -0.31 -0.07 -0.14 0.12 -0.12 -0.06
85 1.64 1.58 1.91 1.23 0.27 1.08 1 0.27 2.18 2.74 1.18 1.52
102 0.07 0.05 0.05 0.16 0.03 -0.1 -0.05 0.04 -0.05 0.06 0.02 -0.04
144 -0.42 -0.6 -0.33 -0.26 -0.3 -0.43 -0.55 -0.65 -0.65 -0.57 -0.56 -0.53
170 -0.64 -0.58 -0.57 -0.49 -0.57 -0.68 -0.53 -0.61 -0.66 -0.56 -0.59 -0.66
183 -0.56 -0.43 -0.52 0.07 -0.28 0.38 0.05 1.17 0.6 0.83 -0.89 0.03
212 0.66 0.71 0.77 0.78 0.53 0.55 0.49 0.49 0.64 0.41 0.48 0.74
235 0.07 0.1 0.1 0.18 0.2 0.02 0.21 -0.08 0.26 0.24 -0.1 0.08
250 -0.13 -0.11 -0.12 -0.26 -0.37 -0.42 -0.44 -0.33 -0.24 -0.05 -0.01 -0.18
264 0.13 0.01 0.13 -0.13 -0.33 -0.09 -0.01 0.19 -0.03 0.13 0.31 -0.09
557 0.2 0.15 0.09 0.09 0.1 0.05 0.08 0.04 0.1 0.04 0.3 0.14
530 0.29 0.2 0.23 0.69 0.3 0.29 0.15 0.01 0.48 0.24 0.44 0.17
535 -0.03 -0.03 -0.09 -0.18 -0.1 -0.17 -0.19 -0.23 -0.18 -0.12 -0.04 -0.06
541 -0.21 -0.19 -0.26 -0.18 -0.21 -0.24 -0.23 -0.21 -0.3 -0.21 -0.17 -0.3
543 -0.04 -0.17 -0.22 -0.15 -0.22 -0.31 -0.35 -0.39 -0.39 -0.24 -0.15 -0.15
548 -0.22 -0.29 -0.32 -0.43 -0.51 -0.52 -0.53 -0.5 -0.51 -0.39 -0.2 -0.18
551 -0.05 -0.23 -0.27 -0.18 -0.29 -0.22 -0.03 -0.07 -0.14 -0.1
558 -0.4 -0.3 -0.2 -0.13 -0.12 -0.14 -0.12 -0.16 -0.1 -0.2 -0.25 -0.43
560 -0.17 -0.18 -0.15 -0.19 -0.22 -0.28 -0.27 -0.29 -0.24 -0.21 -0.19 -0.18
562 -0.2 -0.21 -0.26 -0.25 -0.41 -0.32 -0.27 -0.22 -0.26 -0.25 -0.18 -0.14
567 -0.27 -0.27 -0.32 -0.29 -0.38 -0.45 -0.44 -0.46 -0.42 -0.36 -0.3 -0.28
568 -0.14 -0.09 -0.11 -0.11 -0.07 -0.05 -0.15 -0.13 -0.04 -0.18 -0.18 -0.12
570 0.07 0.03 0.01 0 -0.06 -0.06 -0.05 -0.04 -0.03 -0.02 0.02 0.01
571 -0.07 -0.02 -0.04 -0.05 -0.07 -0.04 -0.05 -0.04 -0.02 -0.04 -0.06 -0.05
575 -0.07 0.02 -0.03 -0.02 -0.14 -0.06 -0.03 -0.06 -0.03 0.04 -0.07 -0.12
579 -0.1 -0.12 -0.14 -0.23 -0.22 -0.28 -0.28 -0.26 -0.18 -0.18 -0.17 -0.11
VI Seminar Homogeniza
tion, Budapest
2008
Example of statistic analysis for individual series (1/4)
Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tot
Ndays 232 186 179 162 161 149 147 132 158 199 190 189 2084
Mean CS 3.36 3.50 5.99 6.02 9.34 13.39 13.63 14.90 12.95 8.96 5.21 3.88 7.92
Mean AWS 4.44 4.72 6.55 7.16 9.91 14.23 14.60 15.98 13.99 10.48 6.50 5.01 8.97
Min CS 0.1 0.1 0.1 1.0 2.0 5.0 7.0 10.0 7.0 3.0 0.1 0.1 0.1
Min AWS -2.4 -1.9 -4.7 0.3 1.5 5.5 8.1 10.4 8.1 3.7 0.0 -0.3 -4.7
Max CS 10.0 9.0 13.0 15.0 18.5 23.0 21.0 23.0 20.0 19.0 12.0 11.0 23.0
Max AWS 11.4 10.2 15.0 15.7 20.6 24.6 23.5 25.7 21.6 18.7 14.2 11.9 25.7
StdDev CS 2.192 1.900 2.729 2.760 3.306 3.524 2.862 2.924 2.619 2.480 2.344 1.987 4.838
StdDev AWS 2.731 2.650 3.267 3.013 3.460 3.499 3.061 3.480 2.591 2.713 2.702 2.417 4.988
Assimetry CS 0.636 0.366 0.008 0.915 0.544 0.263 0.355 0.425 0.253 0.452 0.290 0.152 0.519
Assimetry AWS 0.245 -0.196 -0.417 0.324 0.630 0.286 0.517 0.929 0.372 0.014 0.346 0.034 0.401
Kurtosis CS -0.279 -0.206 -0.216 0.924 0.107 -0.053 -0.363 -0.230 -0.100 1.397 0.062 0.220 -0.515
Kurtosis AWS -0.155 -0.434 0.742 -0.052 0.878 0.175 0.081 0.177 0.286 0.101 0.158 -0.102 -0.268
Bias 1.075 1.223 0.562 1.131 0.571 0.846 0.969 1.08 1.048 1.527 1.282 1.122 1.05
Tmin.:Cabril
VI Seminar Homogeniza
tion, Budapest
2008
Example of statistic analysis for individual series (2/4)
Tmax.:Cabril
Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tot
Ndays 232 186 179 162 161 149 147 132 158 199 190 189 2084
Mean CS 12.48 14.71 16.30 17.86 21.14 26.38 27.78 29.64 26.32 19.48 14.94 13.19 19.26
Mean AWS 11.28 13.73 15.49 17.03 20.63 26.16 27.12 29.12 25.48 18.45 13.44 11.55 18.32
Min CS 5.0 7.0 8.0 8.0 11.0 15.0 17.0 18.0 16.5 12.0 6.0 7.0 5.0
Min AWS 3.5 5.1 7.0 8.0 9.2 13.0 15.9 17.3 15.1 8.9 6.4 5.8 3.5
Max CS 24.0 22.0 28.0 30.0 35.0 36.0 38.0 39.0 35.0 33.5 26.0 19.0 39.0
Max AWS 23.6 22.3 27.4 29.9 34.2 36.3 37.6 39.9 35.0 31.4 25.4 19.6 39.9
StdDev CS 2.723 3.329 4.464 4.857 5.053 5.254 4.725 4.571 4.363 3.750 3.332 2.577 7.010
StdDev AWS 3.059 3.837 4.619 5.243 5.497 5.669 5.038 5.124 4.391 4.323 3.153 2.736 7.439
Assimetry CS 0.336 -0.039 0.370 0.422 0.284 -0.352 -0.273 0.000 -0.077 0.566 0.209 0.155 0.554
Assimetry AWS 0.414 -0.030 0.431 0.452 0.339 -0.378 -0.094 0.003 -0.062 0.455 0.278 0.401 0.554
Kurtosis CS 1.329 -0.501 -0.352 -0.296 -0.400 -0.637 -0.361 -0.397 -0.763 0.185 0.731 -0.534 -0.585
Kurtosis AWS 1.354 -0.563 -0.385 -0.598 -0.440 -0.507 -0.632 -0.415 -0.647 -0.219 0.451 -0.082 -0.583
Bias -1.205 -0.983 -0.808 -0.834 -0.517 -0.216 -0.663 -0.518 -0.838 -1.030 -1.505 -1.639 -0.939
VI Seminar Homogeniza
tion, Budapest
2008
Example of statistic analysis for individual series (3/4)
Tmin:Lisboa
Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tot
Ndays 230 211 229 239 253 239 285 285 281 266 246 267 3031
Mean CS 7.35 8.41 10.56 11.54 14.09 16.94 18.10 18.88 17.64 15.06 11.00 8.35 13.42
Mean AWS 7.25 8.29 10.42 11.31 13.87 16.66 17.83 18.62 17.46 14.87 10.83 8.24 13.23
Min CS 0.5 2.1 -0.6 6.8 7.6 12.3 14.2 14.1 13.5 9.2 4.5 1.2 -0.6
Min AWS 0.5 1.9 -0.4 6.7 7.5 11.7 13.8 14.8 13.9 9.2 4.2 1.4 -0.4
Max CS 15.0 14.0 15.5 17.1 24.3 24.2 26.6 28.2 22.7 21.4 18.8 15.4 28.2
Max AWS 15.0 13.7 15.4 16.6 23.9 24.3 26.0 28.2 22.7 20.9 18.4 15.3 28.2
StdDev CS 2.936 2.343 2.628 1.926 2.343 2.087 2.148 2.062 1.670 2.065 2.817 2.974 4.635
StdDev AWS 2.864 2.270 2.593 1.929 2.328 2.126 2.123 2.023 1.636 2.035 2.770 2.946 4.575
Assimetry CS 0.218 -0.317 -0.874 0.081 0.897 0.549 1.348 1.185 0.353 -0.058 0.082 0.101 -0.203
Assimetry AWS 0.250 -0.313 -0.834 0.104 0.905 0.588 1.305 1.280 0.454 -0.066 0.079 0.141 -0.190
Kurtosis CS -0.083 -0.401 1.574 -0.111 2.275 0.495 2.310 2.347 0.373 -0.253 -0.262 -0.320 -0.560
Kurtosis AWS -0.022 -0.348 1.457 -0.119 2.192 0.590 2.227 2.554 0.299 -0.268 -0.244 -0.250 -0.578
Bias -0.099 -0.121 -0.138 -0.225 -0.224 -0.283 -0.277 -0.26 -0.184 -0.181 -0.171 -0.114 -0.192
VI Seminar Homogeniza
tion, Budapest
2008
Example of statistic analysis for individual series (4/4)
Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tot
Ndays 230 211 229 239 253 239 285 285 281 266 246 267 3031
Mean CS 14.20 15.73 18.14 18.99 22.23 26.35 27.64 28.71 26.53 22.01 17.37 14.44 21.34
Mean AWS 14.18 15.75 18.22 19.15 22.50 26.72 28.15 29.21 26.85 22.14 17.41 14.45 21.56
Min CS 7.0 10.0 10.1 11.4 13.4 17.2 20.6 21.4 19.5 16.1 11.7 8.5 7.0
Min AWS 6.9 10.0 10.2 11.5 13.2 17.2 20.8 21.5 19.4 15.9 11.7 8.8 6.9
Max CS 22.0 20.8 27.5 29.4 35.3 39.0 37.7 41.5 38.7 33.2 25.5 19.2 41.5
Max AWS 22.1 20.6 28.0 29.4 35.4 39.3 38.5 42.0 39.0 33.3 25.7 19.4 42.0
StdDev CS 2.326 2.226 3.429 3.431 4.135 4.195 3.911 3.905 3.678 3.000 2.313 2.115 6.106
StdDev AWS 2.347 2.218 3.432 3.494 4.185 4.257 3.976 3.960 3.806 3.037 2.346 2.113 6.284
Assimetry CS -0.199 -0.089 0.437 0.765 0.800 0.441 0.596 0.749 0.549 0.882 0.259 -0.246 0.398
Assimetry AWS -0.145 -0.113 0.425 0.731 0.747 0.429 0.602 0.677 0.499 0.848 0.272 -0.203 0.397
Kurtosis CS 0.676 -0.324 0.148 0.271 0.418 -0.266 -0.318 0.019 -0.240 0.884 0.231 -0.415 -0.529
Kurtosis AWS 0.732 -0.315 0.153 0.183 0.366 -0.300 -0.329 -0.039 -0.348 0.872 0.216 -0.461 -0.565
Bias -0.025 0.018 0.080 0.169 0.271 0.374 0.515 0.499 0.325 0.130 0.041 0.010 0.212
Tmax:Lisboa
VI Seminar Homogeniza
tion, Budapest
2008
Statistical Testing:Total data mean values (AWS-CS)
Tmax Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total
5 1.228 0.985 0.419 0.423 0.124 0.240 0.041 0.301 0.685 1.025 0.625 0.632 0.913
11 3.526 2.270 1.653 1.880 1.046 0.760 1.026 0.395 0.773 1.909 3.465 2.896 2.952
19 4.480 2.640 1.683 1.485 0.878 0.341 1.163 0.867 1.702 2.538 4.521 5.995 4.193
32 2.387 0.901 -0.014 0.792 0.079 1.041 1.042 0.953 0.513 1.424 0.505 2.395 1.459
35 0.483 0.584 0.387 0.204 0.030 0.021 -0.073 -0.077 0.084 0.017 0.135 0.121 0.222
85 4.344 3.428 2.846 2.240 0.962 2.139 0.888 1.723 1.966 1.335 4.272 7.495 4.402
102 -0.290 -0.058 -0.108 0.412 0.081 -0.027 -0.056 0.164 -0.210 -0.034 0.545 0.078 0.103
144 0.552 -0.012 0.117 -0.025 0.434 -0.044 -0.415 -0.826 -0.441 0.662 0.802 0.682 0.084
170 -0.744 -0.926 -0.709 -1.141 -0.921 -1.063 -1.194 -1.290 -1.236 -0.376 -0.502 -0.897 -1.719
183 0.228 0.220 -0.367 -0.122 0.188 -0.491 -0.987 -0.687 -0.517 0.327 0.733 0.723 -0.310
212 -0.501 -0.925 -0.679 -0.455 -0.536 -0.626 -0.772 -0.467 -0.525 -0.286 -0.513 -0.656 -0.992
235 2.776 2.002 1.243 1.052 0.675 0.539 0.997 1.364 1.211 1.769 1.375 3.536 2.032
250 0.624 0.232 0.418 0.116 -0.136 -0.201 -0.519 -0.321 -0.192 0.151 0.239 0.532 0.009
264 -0.002 -0.428 -0.324 0.374 -0.229 0.248 0.374 0.301 0.290 0.326 -0.149 0.213 0.182
557 -4.546 -4.575 -3.602 -3.131 -3.771 -3.518 -2.431 -3.120 -3.241 -3.293 -5.322 -5.938 -6.592
530 0.975 0.459 -0.084 0.539 0.681 0.165 1.835 0.252 0.263 1.342 1.123 0.544 1.370
535 -1.273 -1.719 -1.628 -2.074 -1.654 -2.059 -2.167 -2.098 -2.106 -1.695 -1.403 -1.184 -3.276
541 0.307 -0.066 -0.322 -0.545 -0.564 -1.368 -1.117 -1.738 -1.760 -0.905 -0.203 0.297 -1.323
543 -0.316 -1.034 -1.352 -1.566 -1.705 -1.607 -1.604 -1.859 -1.953 -1.369 -0.516 -0.402 -2.973
548 -1.223 -1.169 -1.012 -1.119 -1.089 -1.672 -2.267 -2.353 -1.887 -1.421 -1.404 -1.141 -2.990
551 0.277 -0.258 -0.235 -0.174 -0.146 -0.051 -0.146 -0.063 0.240 0.545 -0.126
558 -0.608 -0.744 -0.744 -0.891 -0.959 -1.098 -1.375 -1.418 -1.189 -0.898 -0.840 -0.792 -1.602
560 1.314 1.210 0.708 0.360 0.227 0.289 0.078 0.085 0.531 0.748 1.114 1.450 1.108
562 0.360 0.163 -0.120 -0.082 -0.484 -0.202 0.102 0.091 0.096 -0.080 0.126 0.169 -0.043
567 0.326 0.226 0.185 0.108 0.113 0.074 0.018 0.243 0.218 0.288 0.210 0.356 0.330
568 0.188 0.348 0.182 0.077 0.026 0.105 -0.026 0.159 -0.028 0.094 0.247 0.262 0.249
570 0.140 -0.184 -0.361 -0.453 -0.487 -0.684 -0.794 -0.752 -0.557 -0.441 -0.167 0.084 -0.704
571 0.224 0.000 -0.402 -0.621 -1.048 -1.171 -1.259 -1.006 -0.766 -0.459 -0.118 0.332 -1.064
575 0.159 0.211 -0.164 -0.354 -0.759 -0.888 -0.833 -0.643 -0.359 -0.485 0.118 0.250 -0.618
579 0.114 -0.083 -0.251 -0.535 -0.732 -0.967 -1.559 -1.514 -1.030 -0.498 -0.197 -0.057 -1.333
Tmin Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total
5 0.329 0.215 0.329 0.444 0.537 0.691 0.692 0.842 0.747 0.702 0.385 0.280 1.018
11 0.146 -0.146 -0.013 -0.094 -0.192 -0.247 0.005 0.266 0.227 0.110 -0.098 -0.197 -0.041
19 -4.678 -5.115 -1.767 -3.524 -1.515 -2.079 -2.805 -2.728 -3.576 -5.858 -4.941 -4.930 -6.901
32 -0.304 -0.637 -0.734 -1.800 -1.593 -1.359 0.544 -1.600 -1.108 -1.686 -2.045 -0.883 -1.879
35 0.165 0.172 -0.040 0.167 0.150 0.059 0.544 0.143 0.212 -0.154 0.121 0.091 0.251
85 -3.693 -4.880 -4.609 -3.153 -0.443 -2.821 -2.239 -0.537 -5.636 -7.900 -2.879 -3.903 -6.909
102 -0.203 -0.187 -0.163 -0.759 -0.119 0.501 0.275 -0.239 0.278 -0.266 -0.057 0.121 -0.146
144 1.025 1.502 0.856 0.817 1.035 2.035 2.683 3.218 2.278 1.631 1.256 1.242 3.239
170 1.491 1.638 1.725 1.577 1.961 2.800 2.150 2.963 2.811 2.005 1.425 1.758 4.050
183 1.223 0.817 1.230 -0.184 0.825 -1.478 -0.234 -3.971 -2.155 -1.867 1.356 -0.042 -0.675
212 -1.397 -1.636 -1.641 -1.974 -1.438 -1.730 -1.694 -1.516 -1.882 -1.015 -0.739 -1.216 -2.991
235 -0.207 -0.296 -0.294 -0.814 -0.711 -0.066 -0.841 0.322 -1.250 -0.943 0.301 -0.269 -0.734
250 0.295 0.253 0.357 0.664 0.915 1.176 1.363 1.017 0.982 0.135 0.014 0.337 1.082
264 -0.353 -0.035 -0.401 0.453 1.078 0.390 0.029 -0.733 0.139 -0.396 -0.720 0.218 -0.155
557 -0.525 -0.449 -0.235 -0.221 -0.294 -0.146 -0.168 -0.100 -0.314 -0.126 -0.936 -0.446 -0.614
530 -0.860 -0.712 -1.154 -2.921 -1.434 -1.899 -1.319 -0.089 -2.392 -0.707 -1.143 -0.419 -2.240
535 0.129 0.129 0.354 0.937 0.401 0.810 0.997 1.249 1.093 0.654 0.153 0.246 0.978
541 0.773 0.681 1.028 0.850 0.997 1.260 1.454 1.394 1.649 0.925 0.420 0.927 1.842
543 0.117 0.494 0.677 0.565 0.908 1.231 1.839 2.033 1.730 0.893 0.414 0.375 1.730
548 0.735 1.134 1.118 2.012 2.050 2.352 3.009 2.445 2.694 1.765 0.673 0.645 3.249
551 0.046 0.460 0.267 0.323 0.347 0.319 0.049 0.116 0.213 0.077 0.439
558 1.129 0.917 0.667 0.511 0.434 0.581 0.471 0.747 0.511 0.749 0.820 1.418 1.527
560 0.624 0.607 0.501 0.640 0.617 0.906 0.895 0.930 0.892 0.871 0.736 0.779 1.623
562 0.683 0.814 0.980 0.961 1.419 1.100 1.017 0.816 1.229 0.969 0.559 0.463 1.866
567 0.771 0.903 1.019 1.063 1.173 1.586 1.633 1.630 1.787 1.421 0.872 0.755 2.397
568 0.478 0.276 0.327 0.265 0.183 0.119 0.393 0.365 0.130 0.563 0.547 0.397 0.670
570 -0.261 -0.112 -0.038 -0.007 0.180 0.202 0.185 0.132 0.121 0.085 -0.090 -0.054 0.071
571 0.287 0.081 0.126 0.145 0.172 0.092 0.126 0.112 0.071 0.149 0.235 0.262 0.320
575 0.190 -0.049 0.083 0.079 0.412 0.233 0.118 0.225 0.132 -0.148 0.185 0.318 0.291
579 0.365 0.538 0.566 1.274 1.078 1.468 1.550 1.522 1.322 1.017 0.678 0.446 1.627
Z- values: two tailed test (significance levels: 10% , 5% and 1%)
For each month, results are significant (90%) for most of the stations;For each station results may change between Tmax and Tmin
VI Seminar Homogeniza
tion, Budapest
2008
Statistical testing ofmonthly data differences to normal values 1961-90
Z- values: two tailed test (significance levels: 10% , 5% and 1%)
Nr. Y M61-90 vs.
AWS61-90 vs.
CSAWS vs.
CS
19 2000 11 -4.771 -8.152 1.865
19 2001 1 0.874 -2.465 2.244
19 2001 10 1.726 -3.030 3.281
19 2003 6 1.701 -1.035 1.989
19 2003 8 3.650 -0.742 3.233
19 2003 9 0.433 -5.085 3.711
19 2003 10 -3.481 -8.314 2.543
19 2004 1 2.477 -0.199 1.928
19 2004 3 -2.677 -3.669 0.315
19 2004 4 -1.497 -4.297 1.354
19 2004 5 1.026 -0.158 0.860
19 2004 6 5.123 2.460 2.029
19 2004 7 -1.047 -2.747 1.224
19 2004 12 -4.088 -5.250 0.637
19 2005 1 -2.280 -3.707 0.691
19 2005 2 -8.983 -9.919 -0.852
19 2005 3 -0.235 0.294 -0.367
19 2005 5 1.000 1.501 -0.488
19 2005 6 4.204 5.902 -1.191
19 2005 7 -0.362 0.490 -0.582
19 2005 8 2.127 3.374 -0.388
19 2005 9 -5.529 -0.929 -2.457
19 2005 10 0.932 -5.694 4.655
Nr. Y M61-90 vs.
AWS61-90 vs.
CSAWS vs.
CS
579 1997 12 2.701 3.155 -0.319
579 1998 2 4.906 5.072 -0.243
579 1998 7 0.000 0.694 -0.494
579 1999 10 1.816 1.845 0.000
579 2000 4 -1.105 -0.553 -0.391
579 2001 8 1.608 3.259 -1.145
579 2001 9 -0.754 -0.247 -0.353
579 2001 10 3.700 3.988 -0.218
579 2004 4 1.132 1.705 -0.401
579 2004 9 0.375 1.519 -0.801
579 2004 10 0.000 0.902 -0.642
579 2005 3 0.145 0.281 -0.101
579 2005 5 6.666 7.558 -0.502
579 2005 7 2.510 3.687 -0.771
579 2006 2 -3.135 -2.896 -0.158
579 2006 3 3.321 3.493 -0.193
579 2006 4 7.367 8.060 -0.520
579 2006 5 4.286 4.895 -0.433
579 2006 6 9.471 11.049 -1.116
579 2006 7 4.290 4.944 -0.456
579 2006 9 1.519 2.774 -0.865
579 2006 10 9.768 11.235 -1.189
579 2006 12 -1.410 -1.339 0.000
Tmin
Nr. Y M61-90 vs.
AWS61-90 vs.
CSAWS vs.
CS
579 1997 12 2.427 2.826 -0.218
579 1998 2 5.576 5.967 -0.389
579 1998 7 0.728 -0.146 0.619
579 1999 10 -2.913 -2.940 0.000
579 2000 4 -6.228 -6.703 0.223
579 2001 8 0.000 -1.594 1.089
579 2001 9 -1.154 -1.751 0.410
579 2001 10 -2.834 -3.524 0.500
579 2004 4 2.432 2.176 0.204
579 2004 9 -0.190 -0.771 0.406
579 2004 10 -0.138 -0.278 0.098
579 2005 3 0.000 -0.319 0.227
579 2005 5 2.609 2.203 0.353
579 2005 7 1.115 0.378 0.530
579 2006 2 -1.653 -1.385 -0.165
579 2006 3 -2.025 -2.074 0.000
579 2006 4 4.008 3.932 0.125
579 2006 5 5.283 4.849 0.287
579 2006 6 1.530 1.047 0.365
579 2006 7 2.515 2.389 0.105
579 2006 9 0.592 0.362 0.169
579 2006 10 1.650 1.323 0.191
579 2006 12 -0.716 -0.720 0.000
Nr. Y M61-90 vs.
AWS61-90 vs.
CSAWS vs.
CS
19 2000 11 -6.320 -4.819 -1.175
19 2001 1 -2.674 0.283 -2.138
19 2001 10 0.159 2.347 -1.500
19 2003 6 3.124 3.101 0.293
19 2003 8 4.535 5.705 -0.292
19 2003 9 1.131 3.207 -1.392
19 2003 10 -2.350 -0.165 -1.781
19 2004 1 1.003 6.164 -3.970
19 2004 3 -0.658 1.900 -1.787
19 2004 4 2.460 3.344 -0.436
19 2004 5 2.148 3.040 -0.418
19 2004 6 7.230 7.269 0.000
19 2004 7 3.077 4.845 -0.920
19 2004 12 -1.145 1.616 -1.912
19 2005 1 1.017 3.299 -1.405
19 2005 2 -0.366 1.541 -1.327
19 2005 3 1.184 1.481 -0.157
19 2005 5 3.322 4.605 -1.055
19 2005 6 4.427 5.230 -0.358
19 2005 7 2.026 2.775 -0.484
19 2005 8 5.808 5.918 0.000
19 2005 9 1.169 3.096 -1.419
19 2005 10 1.683 2.336 -0.084
Tmax
VI Seminar Homogeniza
tion, Budapest
2008
Climatological analysis of extreme values
Tmin
Nr. M
Cold Days (AWS)
Tmin<-10ºCCold Days (CS)
Tmin<-10ºC
Tropical Night (AWS)
Tmin>20ºCTropical Night
(CS) Tmin>20ºC TN10 (ºC)T<TN10 (AWS)
T<TN10 (CS) TN90 (ºC)
T>TN90 (AWS)
T>TN90 (CS) Ndays
19 1 0 0 0 0 2 26 18 7.9 4 11 23219 2 0 0 0 0 1.5 17 13 8.6 1 7 18619 3 0 0 0 0 3 11 13 10 5 11 17919 4 0 0 0 0 3 4 6 12 2 6 16219 5 0 0 0 1 5.4 10 5 13.5 13 14 16119 6 0 0 4 8 9.5 10 8 18 8 16 14919 7 0 0 1 8 11.5 23 15 21 0 4 14719 8 0 0 5 23 12 14 6 19.5 9 17 13219 9 0 0 0 4 10.6 17 7 19.5 1 3 15819 10 0 0 0 0 7.5 29 12 14.9 2 4 19919 11 0 0 0 0 3.3 21 12 12.5 0 2 19019 12 0 0 0 0 2.2 22 13 9.9 0 2 189
579 1 0 0 0 0 3.4 8 9 11 11 10 230579 2 0 0 0 0 4.2 3 3 11.9 4 3 211579 3 0 0 0 0 6.5 7 7 12.3 23 23 229579 4 0 0 0 0 7.7 2 2 13.4 16 14 239579 5 0 0 7 5 10 2 2 15.4 23 19 253579 6 0 0 21 18 12.5 0 0 17.9 28 24 239579 7 0 0 45 39 14.7 0 2 21.2 8 7 285579 8 0 0 60 50 15.4 1 1 19.8 22 20 285579 9 0 0 22 16 14.8 3 2 20 7 5 281579 10 0 0 1 1 11.1 2 2 16.9 20 17 266579 11 0 0 0 0 7.2 9 10 14.6 8 7 246579 12 0 0 0 0 4.6 10 10 12.5 8 7 267
At Lisboa AWS detects more tropical nights than the CS, the opposite at Cabril
VI Seminar Homogeniza
tion, Budapest
2008
Climatological analysis of extreme values
At Lisboa AWS detects less warm, summer and tropical daysthan CS, at Cabril there is seasonal dependancy
Tmax
Nr. M
Warm Days (AWS)
Tmax>20ºC
Warm Days (AWS)
Tmax>20ºC
Summer Days (AWS) Tmax>25ºC
Summer Days (CS)
Tmax>25ºC
Tropical Day T1 (AWS)
Tmax>30ºC
Tropical Day T1 (CS) Tmax>30ºC
Tropical Day T1 (AWS)
Tmax>35ºC
Tropical Day T1
(CS) Tmax>35ºC TX10 (ºC)
T<TX10
(AWS)T<TX10 (CS)
TX90 (ºC)
T>TX90
(AWS)T>TX90 (CS) Ndays
19 1 1 2 0 0 0 0 0 0 7.5 2 9 15.2 9 7 23219 2 8 9 0 0 0 0 0 0 7.5 0 6 16.1 31 26 186
19 3 31 32 4 4 0 0 0 0 10.0 3 7 20.0 17 17 17919 4 46 50 12 13 0 0 0 0 9.5 1 3 22.5 17 16 162
19 5 83 77 27 35 4 10 0 0 11.3 1 1 25.0 16 21 161
19 6 124 125 87 89 39 43 2 4 16.0 2 6 30.0 26 28 14919 7 136 134 103 97 40 42 5 6 20.0 5 8 33.5 10 12 147
19 8 129 126 109 106 51 54 15 18 21.0 2 5 32.0 28 29 132
19 9 144 140 92 88 32 30 0 0 18.0 1 5 31.5 11 8 15819 10 78 69 14 16 1 1 0 0 13.2 2 9 25.2 7 7 19919 11 11 4 2 1 0 0 0 0 9.7 4 14 20.0 5 2 19019 12 0 0 0 0 0 0 0 0 8.0 1 7 16.0 10 6 189
579 1 2 2 0 0 0 0 0 0 11.3 11 10 16.3 15 14 230
579 2 4 5 0 0 0 0 0 0 11.6 3 2 17.8 17 16 211
579 3 52 57 10 9 0 0 0 0 14.6 10 11 22.0 15 17 229
579 4 67 73 18 21 0 0 0 0 14.7 6 7 22.9 15 16 239
579 5 169 178 55 59 16 18 1 1 16.6 3 3 26.6 14 15 253
579 6 230 231 129 138 52 55 7 8 20.5 4 3 31.6 12 15 239
579 7 285 285 198 215 70 75 15 24 23.3 11 7 33.9 9 12 285
579 8 285 285 238 253 86 98 23 28 24.4 9 7 33.0 16 18 285
579 9 279 279 168 177 57 69 5 5 23.0 16 14 33.2 4 6 281
579 10 195 197 42 42 3 4 0 0 18.8 10 9 27.5 6 6 266
579 11 34 34 1 1 0 0 0 0 13.9 4 5 20.7 8 9 246
579 12 0 0 0 0 0 0 0 0 11.6 8 8 17.3 7 8 267
VI Seminar Homogeniza
tion, Budapest
2008
Connection with the Project “SIGN”:Signatures of environmental change in the observations
of the Geophysical Institutes
Recovery of 19th and early 20th century Portuguese historical meteorological data M.Valente,M.Barros,L.Nunes,E.Alves,R.Trigo,E.Pinhal,F.Coelho,M.Mendes,J.Miranda•This work presents the joint efforts of the 3 Portuguese Geophysical Institutes (of Lisbon, Oporto and Coimbra) and the Portuguese Meteorology Institute to convert to a digital database the historical meteorology data, recorded since 1856 until 1940 in several publications by the institutes. The different sets of historical data contain monthly, daily and sometimes hourly records of pressure, temperature, precipitation, humidity, wind speed and direction, cloud cover, evaporation & ozone.•The published data cover several stations in mainland Portugal, the Azores and Madeira islands and in former Portuguese African and Asian colonies. One of the aims is to use the data to study the changes that have taken place in the historical records during the last 150 years, when the recovered data are joined with the post-1941 data stored in the Meteorology Institute digital database.•The other aim is to make the data available to the meteorology community at large. Direct observations of pressure data for Lisbon and for the 1856-1940 period were prioritized and have been manually digitized, being later subjected to quality control tests. Digital historical records of Lisbon temperature, relative humidity and precipitation data have been obtained through corrected OCR techniques applied to published hourly or bi-hourly tables.•Preliminary digital results are also available for several stations in mainland Portugal, Azores and Madeira. All datasets are subjected to an initial quality control test, to detect wrong values, with more comprehensive tests to be applied at later stages. At the same time, detailed metadata files are being compiled for each station. First analysis results for the digital historical database are available.
VI Seminar Homogeniza
tion, Budapest
2008
Final remarks/questions
• Availability of 10 years of daily data x 30 stations• Overlapping data series have been characterized and compared,• Some results regarding air temperature have been shown, but many other variables
(humidity, pressure, …) have also been analyzed,• For Tmax & Tmin 2/3 of stations have bias +/-0.25ºC, for T09 only 1/3 of stations• There is a problem with missing data from AWS, which lowers the confidence,• Climatological extremes are different if calculated with AWS or CS!• For air temperature (well behaved variable, 2 types of inhomogenities were
shown:• seasonal dependence and offset
• For most of the stations, conventional observations will stop in a couple of years (only few sites will remain for more years), so, we’ll have to rely on AWS data,
• Then, most recent “break-point” of the series will be known (CS=>AWS),• An homogenization plan is required! First for monthly data and then daily data...• Continuation of the SIGN project is desirable• IM-Portugal welcomes cooperation in this filed (in relation with COST HOME?)