The International Surface Temperature Initiative (ISTI) Parallel Observations Science Team (POST)

Transcription

1 The International Surface Temperature Initiative (ISTI) Parallel Observations Science Team (POST) Members: Victor Venema, Renate Auchmann, Enric Aguilar, Ingeborg Auer, Cesar Azorin-Molina, Theo Brandsma, Michele Brunetti, Alessandro Delitala, Manuel Dienst, Peter Domonkos, Evyatar Erell, Bruce Forgan, Alba Gilabert, Jay Lawrimore, Xiaomao Lin, Jenny Lindén, Elin Lundstad, Ewa Milewska, Øyvind Nordli, Marc Prohom, Jared Rennie, Petr Stepanek, Peter Thorne, Blair Trewin, Lucie Vincent, Kate Willett, Mareile Wolff Associate members:, Andreas Becker, Stefan Brönnimann, Manola Brunet, Sorin Cheval, Mary Curley, Aryan van Engelen, Frank Kaspar, Rachel Killick, Albert Klein Tank, Constantinos Kolokythas, Franz Gunther Kuglitsch, Monika Lakatos, Anna Mamara, Hermann Mächel, Colin Morice, José Guijarro, Clara Oria, David Parker, Mário Gonzalez Pereira, Sarah Perkins, Michael de Podesta, Elke Rustemeier, Javier Sigro, Tamas Szentimrey, Gregor Vertacnik, Xiaolan L. Wang, Steven Worley, Markus Ziese

2 Multiple lines of evidence We need multiple lines of evidence on biases in the climate record Statistical homogenisation Comparison station with its neighbours Removes large-scale biases only partially Corrects for unknown problems Parallel measurements, comparisons methods Comparison methods at same location Noisy, but unbiased Corrects for known problems

3 Content Limits of statistical homogenization Large-scale change annual mean Distribution of daily data First results of POST Research with parallel data Requests to AOPC

4 Difference BEST, GISS, CRUCY ( ) BEST CRUCY GISTEM

5 Difference GHCN ( ) GHCNv3 GHCNv4

6 Inhomogeneities in GHCNv3 Global Land Surface Temperature Adjustments AWS Averaging: Zeke Hausfather Data: GHCNv3

7 Parallel measurements Transition to Stevenson screens North-West Europe: < 0.2 C (Various, Parker) Basel, Switzerland: ~0 (0.25) C (Wild screen) Kremsmünster, Austria: 0.2 C (North-wall) Adelaide, South Australia: 0.2 C (Glaisher stand) Spain: 0.35 (0.5) C (French screen) Sri Lanka: 0.37 C (Tropical screen) India: 0.42 (Tropical screen)

8 Transition to AWS

9 Parallel measurements Kremsmünster Böhm et al. (2010)

10 Kremsmünster percentiles difference Böhm et al. (2010)

11 Numerical validation: Daily Homogenisation Rachel Killick et al. in preparation Long term trend Standard deviation Purple: unchanged Blue: Improved PDF Mean Red: worse

12 Research on parallel data Large database with parallel measurements needed to study (daily) inhomogeneities o Study statistical & physical properties o Dependence on local weather and regional climate o Global biases due to common transitions o Most studies are currently about mid-latitudes o Develop daily correction methods o Weather dependent o Stochastic

13 Research on parallel data Large database with parallel measurements needed to study daily inhomogeneities o Generate benchmark data with realistic inhomogeneities o For example, second cycle of ISTI o Validate detected inhomogeneities

14 Parallel Data Initiative Produce an open database Initially data is restricted to contributors Tasks Incentive to contribute Until first joint paper(s) by contributors are written Inventory & accessing parallel datasets Data processing in R Conversion, QC, indices, various averages Analysis & publication

15 AOPC requests Recognition/endorsement Help in the sourcing of historical parallel observations GCOS focal points? Especially non-weird countries Formalise a process of permanent archiving and sharing of parallel measurement activities Network change management Formalise the archiving and sharing of metadata on known inhomogeneities

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17 Motivation: daily data [Inhomogeneous data] affects, in particular, the understanding of extremes, because changes in extremes are often more sensitive to inhomogeneous climate monitoring practices than changes in the mean. Trenberth, K.E., et al., 2007: Observations: Surface and Atmospheric Climate Change. In: Climate Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

18 Insolation Exposure Sun, hot ground, scattered radiation Humidity and clouds Infrared radiative cooling Wind Heat exchange Design Size sensor Shielding Mechanical ventilation

19 Physical causes of inhomogeneities Shelter type, exposure Radiation & wetting protection Natural or forced ventilation Snow cover Plastic screen: insolation on hot days Relocation of station City-> airport, suburbs, lower heights Deurbanisation of network Instrument Response, integration time Zero drift, shrinking glass initial years Calibration errors Temperature out of range Quicksilver thermometers: T < -39 C Change surrounding Urbanization, growing vegetation, irrigation Definitions Computation daily means Measurement procedures Reading times Maintenance procedures AWS: Icing, damage detection Painting & cleaning schedule Digitisation & database Minus sign forgotten Station names mixed up Pre-homogenised data

20 Physical causes of inhomogeneities Shelter type, exposure Radiation & wetting protection Natural or forced ventilation Snow cover Plastic screen: insolation on hot days Relocation of station City-> airport, suburbs, lower heights Deurbanisation of network Instrument Response, integration time Zero drift, shrinking glass initial years Calibration errors Temperature out of range Quicksilver thermometers: T < -39 C Change surrounding Urbanization, growing vegetation, irrigation Definitions Computation daily means Measurement procedures Reading times Maintenance procedures AWS: Icing, damage detection Painting & cleaning schedule Digitisation & database Minus sign forgotten Station names mixed up Pre-homogenised data Mean shift Tail shift (indirectly also mean) Mean and tail shift

21 Global temperature changes Figure: IPCC (2013)

22 Berkeley Earth global land temperature

23 Sea Surface Temperature (AR5)

24 Indications of more early warming Inhomogeneities in temperature observations Well-homogenized national dataset see more warming up to 1920 than global datasets Transition to Stevenson screen old data too warm Small adjustments for this transition in GHCNv3

25 Temperature difference series 3 countries

26 Temperature difference series 4 countries

27 Physical reasons: Radiation errors

28 Montsouris/French screen (in Spain) Photo: URV, Tarragona, SCREEN experiment

29 Radiation error Climates prone to radiation errors: * Strong insolation * Low wind * Dry ground * High specific humidity Tropical and continental climates

30 Parallel measurements Transition to Stevenson screens North-West Europe: < 0.2 C (Various, Parker) Basel, Switzerland: ~0 (0.25) C (Wild screen) Kremsmünster, Austria: 0.2 C (North-wall) Adelaide, South Australia: 0.2 C (Glaisher stand) Spain: 0.35 (0.5) C (French screen) Sri Lanka: 0.37 C (Tropical screen) India: 0.42 (Tropical screen)

31 Winter and summer trend

32 Inhomogeneities in GHCNv3 Global Land Surface Temperature Adjustments Averaging: Zeke Hausfather Data: GHCNv3

33 Climatic changes in 19 th century Trend in lake temperatures, ice season shorter Glacier retreat Sea level rise

34 Lake and river freezing

35 Temperature reconstruction from glaciers Oerlemans, J., 2005: Extracting a Climate Signal from 169 Glacier Records. Science, 308, no. 5722, pp

36 Sea level rise Church & White, 2011