reinhard böhm central institute for meteorology and geodynamics vienna, austria

13.7.2010, Edinburgh 10th IMSC

Bridging the gap from indirect to direct climate data

experience with homogenizing long climate time series in the early instrumental period

and some general remarks on the problem original vs. processed (faked?) data

Reinhard Böhm

Central Institute for Meteorology and GeodynamicsVienna, Austria

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EIP-CORRECTED HOM-VERSION - 2008

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Sligachan Hotel Isle of Skye


1550 1600 1650 1700 1750 1800 1850 1900 1950 2000

DAWN OF THE INSTRUMENTAL PERIOD

EARLY INSTRUMENTAL

PERIOD

FULLY DEVELOPED INSTRUMENTAL

PERIOD

Proxies necessary to understand climate

variability and trends

Proxies and instrumental „at eye level“

Systematic networks of meteorological

services

Invention of principal meteorological instruments

1597: T

hermom

eter (G

alileo)

1643: Barom

eter (T

orricelli)

1732: Anem

ometer

(Pitot)

1769: Hygrom

eter (Lam

bert)

1792: Psychrom

eter (H

uton)

1838: Pyrheliom

eter (P

ouillet)

1853: Sunshine

recorder (Cam

pbell)

Some basic facts on indirect and direct climate information


CLIMATEGATE, 2009:

One of the “arguments”:

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My clear answer:

(based on some 20 years of experience in the field of homogenizing)

Let me argue this briefly in the next minutes

the original data were intentionally not posed to everybody’s free access to conceal the “tricks” applied to the original data (to increase the amplitude of anthropogenic warming)

WE NEED SUCH TRICKS TO TRANSFER „MEASURED NUMBERS“ TO „CLIMATE DATA“


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My arguments in a nutshell:

This is much work which should preferably be done by specialised regional groups close to the metadata – this produces the best results, is more effective and saves the time of research groups wanting to analyse the data

No single longterm climate time series is a priori homogeneous (free from non climatic noise)

At average each 20 to 30 years a break is produced which significantly modifies the series

Many but not all of these single breaks are random if a regional (global) sample is averaged

The biases are of the order of the real climate signal

There are a number of mathematical-statistical procedures which - preferably if combined with metadata information from station history files – are able to detect and remove (or at least reduce) the non climatic information


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My Examples will be from Central Europe (HISTALP):





The biases of the order of the real climate signal

There are a number of mathematical-.statistical procedures which - preferably if combined with metadata information from station history files – are able to detect and remove (or at least reduce) the non climatic information

region: GAR (4 to 19°E, 43 to 49 deg N)

more than 500 series on 200 sites

7 climate elements

monthly series:

quality improved (homogenised, outlier corrected, gaps filled)

maximum achievable length (100 to 250 years)

element specific network density (190 precip – 60 pressure series)

different modes:

station mode and 3 different grid-modesAvailable in the Web: http://www.zamg.ac.at/histalp


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Examples for:







KLAGENFURT, 1813-2009: 7 relocations – different urban bias


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Examples for:







KLAGENFURT, 1813-2009: 7 relocations – different urban bias

5

6

7

8

9

10

1810 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010

°C TEMPERATURREIHE KLAGENFURT 1813-2007einzelne Jahresmittel und 20-jährig geglättet

grün: homogenisiert (angepasst an aktuellen Zustand)rot: Originaldaten

Quelle: ZAMG-HISTALP Datenbank, Auer et al., 2007

Achatzel1 2 Prettner Sl1 Landesmuseum ZAMG-Annabichl

Klagenfurt composite series: red original green homogenized

red: original data green: homogenized

City center Aiport sites


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Examples for:







400

600

800

1000

1200

1400

1600

1800

1810

1820

1830

1840

1850

1860

1870

1880

1890

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

mm

KAR ORI 1 to 12

KAR HOM 1 to 12

PRECIPITATION (MM)

Precipitation in Karlsruhe with a bias of nearly 100% in the 1870s and 1880s


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Examples for:







HISTALP - PRECIPITATION DATASET: BREAK ANALYSISseries 192available data (incl. closed gaps) 26063 yearsavailable data (incl. closed gaps) 312756 monthsmean length of series 135.7 yearsdetected breaks (total) 966mean homogeneous subperiod 22.7 yearsmean breaks per station per year 0.037square mean break 17.9 %maximum break 238 %mean break amplitude 23.4 %corrected overshooting adjustments 1861detected real outliers 529closed gaps 14927mean gap rate (%) 4.8 %


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Examples for:








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An example for systematic biases: EARLY PRECIP- SERIES







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1800 1825 1850 1875 1900 1925 1950 1975 2000

m a

bove

gro

und

(lo

g)

The development from high to low elevated raingages in the climate network of 154 central European sites with sufficient

station history documentation

source: ZAMG-HISTALP metadata thin: single sites, bold, red:

average 1820: 17m

average 2000: 1.4m

average 1870: 3.5m

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JU

L

AU

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SE

P

OC

T

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V

DE

C

14

.5m

/1.3

m

(%)

Comparison of mean monthly precipitationPula (HR) 1873-1897:

rooftop (14.5m) versus 1.3m near to ground

parallel measurements 1873-1897tower (14.5m above ground)

near to ground (1.3m above ground)

kk. Hydrographisches Amt in Pula: 2 sites (25 years of parallel measurements)

Early rain-gauges systematically higher above ground early precip-series systematically too dry


Another problem a bit more in detail here:

the EARLY INSTRUMENTAL TEMPERATURE BIAS described in:

Frank D, Büntgen U, Böhm R, Maugeri M, Esper J, 2008.

Warmer early instrumental measurements versus colder reconstructed temperatures: shooting at a moving target.

Quaternary Science Reviews, (2008), doi:10.1016/j.quascirev.2007.08.002

Hiebl J, 2006.

The early instrumental climate period (1760-1860) in Europe. Evidence from the Alpine region and Southern Scandinavia

Diploma Thesis, Inst. f. Geography, Uni-Wien, 103 pages

Böhm R, Jones PD, Hiebl J, Brunetti M, Frank D, Maugeri M, 2010

THE EARLY INSTRUMENTAL WARM-BIAS: A SOLUTION FOR LONG CENTRAL EUROPEAN TEMPERATURE SERIES 1760-2007

Climatic Change 101: 41-67

Büntgen U, Frank DC, Nievergelt D, Esper J 2006.

Summer temperature variations in the European Alps: AD 755-2004.

Journal of Climate 19: 5606-5623

13.7.2010, Edinburgh 10th IMSC NW NE S alle HISTALP sites

S

NENW

The HISTALP-early instrumental potential


248 years of GAR-temperature: the result so far (version 2006)

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HOMOGENISED (NO EIP-CORRECTION)-3

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HOMOGENISED (NO EIP-CORRECTION)

??

original series (smoothed)

homogenized


the nucleus of the EI-problem:Diverging instrumental and proxy warm season temperatures before 1860

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°C CRSM-LOW vs TR-Büntgen JJAS

rela

tive

to 1

901

-200

0Described in:

Frank et al, 2007 Hiebl , 2007 Büntgen et al., 2005

pre-1860-proxy temperatures (here: high elevation TRX-series)

pre-1860 HISTALP temperatures


Our solution: strictly staying within the instrumental domain:

•Intensive re-analysis of station history of the more than 30 EI-series•Combined with the evidence from Kremsmünster:•(multianual parallel measurements of a preserved original EI-site with a nearby typical modern installation (AustrianTAWES network)


The Kremsmünster evidenceOrientation NNE

6m above ground

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JAN FEB MARAPR MAY JUN

Temperature Kremsmünster 1995-2002 historic minus modern site (means)

time (MLT)

°C

NE-facing wall(measured)

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JUL AUG SEPOCT NOV DEC


time (MLT)

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Mean differences historic minus modern installation


Three correction models derived from Kremsmünster

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time (MLT)

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N-facing wall(modelled)


4 examples from the intensive new metadata studies :

yellow: still missing information (status: 2007-06-05)

ID name acr. nat alt CRS from - to name od subseriesheight above

ground orientation observing times or

means calc in EI

m N - deg - E

METADATA SAMPLER FOR THE EARLY INSTRUMENTAL PERIOD OF THE HISTALP T01 LONG SERIES SUBSET

TOR IT *) 4 1760-1786Ignazio Somis, *)mostly Università, via Po, but also other locations 10 to 25 28° variable (a)

TOR IT 250 4 1787-1802/05 Accademia delle Scienze, biblioteca 12,5 28° variable (a)TOR IT 4 1802/06-1802/12/21 sunrise, 14, sunsetTOR IT 4 1802/12/22-1851/01/05 sunrise, 12, sunsetTOR IT 4 1851/01/06-1857/07 09, 12, 15TOR IT 4 1857/08-1865/06 (max+min)/2TOR IT 232 4 1865/07-1865/11 Castello del Valentino 2,0 28° 08, 16

TOR IT 276 4 1865/12-1919/02 Palazzo Madama 37,7 20° Tmin, Tmax

44,2Accademia delle Scienze, specola282 0°?

di Napoli G, Mercalli L, 2007. Il clima di Torino. Ca.900 pages, in press

139 TORINO

INN AT 576 2 1777-1784 Jesuiten Colleg Sillgasse (Franz v. Zallinger) second floor -9° 4, 13.30

INN AT 576 2 1784-1828Kapuziner Kloster, Universitätsstrasse (Franz v. Zallinger)

8 15° near min, near max

INN AT 590 2 1828/09-1855/12 6, 13.30INN AT 590 2 1856/01-1859/12 (7+14+2*21)/4INN AT 590 2 1860/01-1870/12 6, 14INN AT 576 2 1865/01-1870/12 (7+14+2*21)/4INN AT 576 2 1871/01-1875/07 6, 14, 22

8 15°

8 -19°INNSBRUCK

Prämostratenser Kloster Wilten (Prantner)59

Old University-Botanical Institute

Auer et al., 2001: ALOCLIM - Austrian long-term climate 1767-2000. Österreichische Beiträge zu Meteorologie und Geophysik 25 147pages plus data and metadata CDZallinger F, 1833. Innsbrucker meteorologische Beobachtungen von 50 Jahren. Ferdinandeum, Wagnersche Schriften 107 pages

STR SA 2 1801-1843 (?) Astronomical observatory, Place de St. Thomas (J.L.A. Herrenschneider) 3,9 0° 6-7 / noon / 21-22

STR SO 2 several years Vorstadt Neudorf (Besson) 1,5STR MO 2 1891/04-before 1915 Institut de Physique du Globe 6 0° (7+13+2*21)/4STR DI 2 before 1915- Institut de Physique du Globe 6 0° (7+14+2*21)/4

STRASBOURG135

1890-1950: Annales de l'Institut de Physique du Globe (before 1918: Elässische Jahrbücher)Herrenschneider, J.L.A., 1825. Résumé des observations météorologiques faites a Strasbourg depuis le commencement de l'an 1811 jusqu'à la fin de 1820. Mémoires de la Société des Sciences de Strasbourg 2 46 pages plus 10 tablesHerrenschneider, J.L.A., 1815. Résumé des observations météorologiques faites a Strasbourg depuis le commencement de l'an 1801 jusqu'à la fin de 1810. Mémoires de la Société des Sciences de Strasbourg 1

AUG DE 1 1812-1822 station Stark 1 (western part of historic centre) 12 WSW and ENE

AUG DE 1 1822-1829 station Stark 3 (near cathedral) 5,5AUG DE 1 1829-1836 station Stark 2 (astronomical observatory) 12AUG DE 1 1838-1872 8,3 W and E true meanAUG DE 1 1872- 8,3 3°

159

Benedictine Monastery St. Stephan

AUGSBURG

2nd yearbook of Bavaria, 24-28

(7+14+2*21)/4

Not important in this context, but very impotant for tx, tn DTR-studies:

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40

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me

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The development from high to low elevated thermometers in the climate network of 97 central European sites with sufficient station history

documentation

average 1760-1860: 13.7m

average 2000: 2.5m

thin: single sites, bold, red: mean source: ZAMG-HISTALP metadata


4 examples from the intensive new metadata studies :

yellow: still missing information (status: 2007-06-05)

ID name acr. nat alt CRS from - to name od subseriesheight above

ground orientation observing times or

means calc in EI

m N - deg - E

METADATA SAMPLER FOR THE EARLY INSTRUMENTAL PERIOD OF THE HISTALP T01 LONG SERIES SUBSET

TOR IT *) 4 1760-1786Ignazio Somis, *)mostly Università, via Po, but also other locations 10 to 25 28° variable (a)

TOR IT 250 4 1787-1802/05 Accademia delle Scienze, biblioteca 12,5 28° variable (a)TOR IT 4 1802/06-1802/12/21 sunrise, 14, sunsetTOR IT 4 1802/12/22-1851/01/05 sunrise, 12, sunsetTOR IT 4 1851/01/06-1857/07 09, 12, 15TOR IT 4 1857/08-1865/06 (max+min)/2TOR IT 232 4 1865/07-1865/11 Castello del Valentino 2,0 28° 08, 16

TOR IT 276 4 1865/12-1919/02 Palazzo Madama 37,7 20° Tmin, Tmax

44,2Accademia delle Scienze, specola282 0°?

di Napoli G, Mercalli L, 2007. Il clima di Torino. Ca.900 pages, in press

139 TORINO

INN AT 576 2 1777-1784 Jesuiten Colleg Sillgasse (Franz v. Zallinger) second floor -9° 4, 13.30

INN AT 576 2 1784-1828Kapuziner Kloster, Universitätsstrasse (Franz v. Zallinger)

8 15° near min, near max

INN AT 590 2 1828/09-1855/12 6, 13.30INN AT 590 2 1856/01-1859/12 (7+14+2*21)/4INN AT 590 2 1860/01-1870/12 6, 14INN AT 576 2 1865/01-1870/12 (7+14+2*21)/4INN AT 576 2 1871/01-1875/07 6, 14, 22

8 15°

8 -19°INNSBRUCK

Prämostratenser Kloster Wilten (Prantner)59

Old University-Botanical Institute

Auer et al., 2001: ALOCLIM - Austrian long-term climate 1767-2000. Österreichische Beiträge zu Meteorologie und Geophysik 25 147pages plus data and metadata CDZallinger F, 1833. Innsbrucker meteorologische Beobachtungen von 50 Jahren. Ferdinandeum, Wagnersche Schriften 107 pages

STR SA 2 1801-1843 (?) Astronomical observatory, Place de St. Thomas (J.L.A. Herrenschneider) 3,9 0° 6-7 / noon / 21-22

STR SO 2 several years Vorstadt Neudorf (Besson) 1,5STR MO 2 1891/04-before 1915 Institut de Physique du Globe 6 0° (7+13+2*21)/4STR DI 2 before 1915- Institut de Physique du Globe 6 0° (7+14+2*21)/4

STRASBOURG135

1890-1950: Annales de l'Institut de Physique du Globe (before 1918: Elässische Jahrbücher)Herrenschneider, J.L.A., 1825. Résumé des observations météorologiques faites a Strasbourg depuis le commencement de l'an 1811 jusqu'à la fin de 1820. Mémoires de la Société des Sciences de Strasbourg 2 46 pages plus 10 tablesHerrenschneider, J.L.A., 1815. Résumé des observations météorologiques faites a Strasbourg depuis le commencement de l'an 1801 jusqu'à la fin de 1810. Mémoires de la Société des Sciences de Strasbourg 1

AUG DE 1 1812-1822 station Stark 1 (western part of historic centre) 12 WSW and ENE

AUG DE 1 1822-1829 station Stark 3 (near cathedral) 5,5AUG DE 1 1829-1836 station Stark 2 (astronomical observatory) 12AUG DE 1 1838-1872 8,3 W and E true meanAUG DE 1 1872- 8,3 3°

159

Benedictine Monastery St. Stephan

AUGSBURG

2nd yearbook of Bavaria, 24-28

(7+14+2*21)/4

important for EIP-tm-bias-correction (for chosing the convenient corr-model)


„from – to“: the individual lengths of the EIP:

EIP length

1750 1775 1800 1825 1850 1875

BaselGeneve

TorinoMilano

KremsmünsterRegensburg

PadovaWienBern

InnsbruckKarlsruheBudapest

Hohenpeißenbg.München

VeronaStuttgart

StrasbourgUdine

NiceAugsburg

KlagenfurtBologna

LinzTrento

Gr. St. BernardMantova

ZürichGraz

TriesteSalzburg

detection rates

0 25 50 75 100[%]

80% of the introduction of regular screens happened within 15 years


the individual EIP-bias corrections

-1.0

-0.5

0.0

0.5

JAN

FE

B

MA

R

AP

R

MA

Y

JUN

JUL

AU

G

SE

P

OC

T

NO

V

DE

C

EIP minus non EIP (K)

-1.0

-0.5

0.0

0.5

1.0

JAN

FE

B

MA

R

AP

R

MA

Y

JUN

JUL

AU

G

SE

P

OC

T

NO

V

DE

C

EIP minus non EIP (K)

series with sufficient metadata detection

series with insufficient metadata detection

detection rates

0 25 50 75 100[%]


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR








-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-20

07

(K)

SUMMER HALF YEAR

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-2

007

(K

)


originalhomogenized-2006

EIP-corrected-2008

1971: evening observations from 9pm tp 7pm in AT and CH

Since 1980s: automation of networks ??? – effects not clear yet

WW-2: systematic relocations from historic centers to airports

THE NETWORK BECOMES MORE RURAL!

1830s to 1870s: systematic EI-bias due to insufficient shading of thermometers

THE RESULT: mean over all 32 single EI-series (20-yrs- smoothed, anomalies from 1978-2007 average)


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR


Total of systematic temperature-biases:







-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-20

07

(K)

SUMMER HALF YEAR

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-2

007

(K

)


originalhomogenized-2006

EIP-corrected-2008

SYSTEMATIC BIAS = +0.55°C

SYSTEMATIC BIAS = +0.45°C

13.7.2010, Edinburgh 10th IMSC-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-2

007

(K

)

SUMMER- minus WINTER-HALfYEARS

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

1750 1800 1850 1900 1950 2000

anom

alie

s to

197

8-2

007

(K

)

YEAR (Jan-Dec)

Smoothed annual means

THE RESULT: mean over all 32 single EI-series (20-yrs- smoothed, anomalies from 1978-2007 average)

Smoothed seasonal asymmetry:

19th century more continental than 20th

This

has severe implications due to the given seasonal asymmetry of many natural proxies


-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

1750 1800 1850 1900 1950 2000

°C

summer half year (APR–SEP)

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

1750 1800 1850 1900 1950 2000

°C

winter half year (OCT–MAR)

bold black: HISTALP-LSS-Tm-2008, EI-corrected (Böhm et al., 2008), bold grey: HISTALP-LSS-Tm-2007, not EI-corrected (Auer et al, 2007),thin red: ISAC-homogenised, mean of 7 N-Italian series (Brunetti et al., 2006b), thin pink: Central European mean of CRUtem2v gridboxes 40-50N, 10-20E (Trenberth and Jones, 2007), thin light blue: Uppsala-Stockholm mean, not EI-corrected (Moberg et al., 2002, Bergström and Moberg, 2002),thin dark blue: Uppsala-Stockholm mean, EI-corrected (Moberg et al., 2003, Moberg et al., 2005), thin green: central England series (Manley, 1974, Parker et al., 1992), thin violet: de Bilt series (van Engelen et al., 1995), thin brown: St. Petersburg series (Jones and Lister, 2002)

OUR RESULT: compared to other EIP-series (20-years smoothed, anomalies from1851-2000 average)

St.PetersburgISAC Northern Italy

Moberg ori corr

CRU-CEU

De-Bilt

CRU-CEN

My conclusion:

we are nearer to the truth now

but to be realistic, we still have an unpleasant

„spaghetti-type“ situation in the early instrumental period


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR








THE REMAINING THREE POINTS:


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR








the size of the problem: breaks – outliers - gaps

histalp T01-gap rate (%)

0

5

10

15

20

25

30

17

60

17

70

17

80

17

90

18

00

18

10

18

20

18

30

18

40

18

50

18

60

18

70

18

80

18

90

19

00

19

10

19

20

19

30

19

40

19

50

19

60

19

70

19

80

19

90

20

00

1 532 3 4 3 6

1: early period2: first networks with continuity problems3: well organised period of meteorological services (IMO - since 1873)4: world war 15: world war 26: recent problems in the Italian network and due to the political situation in Bosnia and Herzegovina

HISTALP-T01: Frequency distribution of detected and removed breaks

0

50

100

150

200

250

300

350

-6.0

-5.5

-5.0

-4.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

deg C (class width 0.5 deg)

pe

rmill

e

minimum: -5.1 deg

maximum: +4.6 deg

HISTALP-T01-2004: frequency distribution of detected and removed real outliers

1

10

100

1000

-28

-25

-22

-19

-16

-13

-10 -7 -4 -1 2 5 8 11 14 17 20

min = -27.5°C max = 16.0 °C

deg C (class width = 1 deg)

rela

tive

freq

uenc

y (p

erm

ille)

Sample: all HISTALP temperature series (135)

breaksgaps

outliers


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR







There are a number of mathematical-statistical procedures which - preferably if combined with metadata information from station history files – are able to detect and remove (or at least reduce) the non climatic information

TAKE-HOME MESSAGE 1:

Alexandersson

Vincent

Caussinus-Mestre Peterson-Easterling

Rhodes-Salinger Craddock

INTERNATIONAL JOURNAL OF CLIMATOLOGY 18: 1493–1517 (1998)HOMOGENEITY ADJUSTMENTS OF IN SITU ATMOSPHERIC CLIMATE DATA: A REVIEWTHOMAS C. PETERSON, DAVID R. EASTERLING, THOMAS R. KARL, PAVEL GROISMAN, NEVILLE NICHOLLS, NEIL PLUMMER, SIMON TOROK, INGEBORG AUER, REINHARD BOEHM, DONALD GULLETT, LUCIE VINCENT, RAINO HEINO, HEIKKI TUOMENVIRTA, OLIVIER MESTRE, TAMAS SZENTIMREY, JAMES SALINGER, EIRIK J. FØRLAND, INGER HANSSEN-BAUER, HANS ALEXANDERSSON, PHILIP JONES and DAVID PARKER

Szentimrey

Bradley-JonesPRODIGE

MASH

SNHT

HOCLIS

LIKE A 15 YEARS OLD SINGLE MALT:

Della Marta

Currently some of them are critically analysed and compared within cost action HOME


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR


TAKE-HOME MESSAGE 2:







BUT:


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR


A challenge not adequatly solved yet :

The ongoing automation of networkse.g.: the change from CAPBELL-STOKES to photoelectric sunshine recorders

-15

-10

-5

0

5

10

15

20

25

JAN

FE

B

MA

R

AP

R

MA

I

JUN

JUL

AU

G

SE

P

OC

T

NO

V

DE

C

%

<600m asl

>2000m asl

NEW minus OLD SYSTEM

An example from 10 Austrian sites with parallel measurements – 4 at high and 6 at low elevation

Overburning at H-elev.-sites due to intermittant cumulus clouds there in summer

Wetting losses at Low elev. sites in winter


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR


Another one:

DOING THE STEP FROM MONTHLY RESOLVED TO DAILY SERIES

SPATIAL DECORRELATION TO 50% COMMON VARANCE

(EUROPE, SYNOP NETWORK)

Source:

Scheifinger and Böhm, 2005)42

993

765

722

533

149

120

105

0 200 400 600 800 1000

YEARLY

SEASONAL

MONTHLY

DAILY

YEARLY

SEASONAL

MONTHLY

DAILY

TE

MP

ER

AT

UR

EP

RE

CIP

ITA

TIO

N

mean Dekorrelation-distance (km)

THE MAIN PROBLEM: HIGHER NETWORK DENSITY NECESSARY – IN PARTICULAR FOR PRECIPITATION


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR


More about the homogenizing business:

this afternoon (14.30-17.45) in session 8 (St. Trinneann)

Starting with Olivier Mestre‘s and Victor Venema‘s homogenization procedures intercomparison (cost action HOME)

and at the poster session 8 (Pentland) starting here right now


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies to 1

85

1-2

000

in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

ano

ma

lies t

o 1

85

1-2

000

in K

SUMMER HALF YEAR


-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

851

-20

00 in K


ORIGINAL

-3

-2

-1

0

1

2

3

4

1750 1800 1850 1900 1950 2000

anom

alie

s t

o 1

85

1-2

000 in K

WINTER HALF YEAR

EIP-CORRECTED HOM-VERSION - 2008THANK‘S FOR LISTENING ANYWAY

MUCH OF WHAT I HAVE SAID TO AN AUDITORIUM LIKE THIS WAS OF COURSE

CARRYING

EDINBURGH

TO

OWLS

reinhard böhm central institute for meteorology and geodynamics vienna, austria

Documents

climate variability

direct climate data

real climate signalthere

time of research groups

early instrumental periodand

minutesthe original

specialised regional

metadata information