VI Seminar Homogenization, Budapest 2008

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

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CS

AWS

BRAGANÇA MONTHLY MEAN MAXIMUM TEMPERATURE

0

5

10

15

20

25

30

35

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41

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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

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42

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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

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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



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


tion, Budapest

2008

Spatial distribution ofBias results for air temperature (AWS-CS)


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


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


tion, Budapest

2008


Tmax.:Cabril


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


tion, Budapest

2008


Tmin:Lisboa


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


tion, Budapest

2008



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


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


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


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


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


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.


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?)

VI Seminar Homogenization, Budapest 2008

Documents