ISTI generic lo res

Initiative overview

08/19/11

Talk Outline

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Background

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Data rescue and databank

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Multiplicity of data products

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Common assessment through consistent

performance benchmarking

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Data and product portal development

Background

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Several independent global estimates of Land

Surface Air Temperatures

– _{Independently produced}

– _{Gross agreement on all timescales}

– _{Process metadata in some cases missing}

– _{Much of the work was undertaken in late 1980’s/ early}

1990’s - technology and expectations have changed since then

Examples of temperature reconstructions

IPCC Fourth Assessment Report (2007), Figure 3.1

Annual anomalies of global land-surface air temperature (°C), 1850 to 2005, relative to the 1961 to 1990 mean for CRUTEM3 updated from Brohan et al. (2006). The smooth curves show decadal variations … The black curve from CRUTEM3 is compared with those from NCDC (Smith and

Reynolds, 2005; blue), GISS (Hansen et al., 2001; red) and Lugina et al. (2005; green). See

ISI Congress, Dublin, August 26th 2011 5

Why the need to revisit?

• _{Global surface temperature records are key line of evidence} • _{Backed by many other indicators (ice loss, humidity increases,}

sea level increases etc.)

BUT:

• _{Link from station data to global averages is indirect (statistical}

problem – reconstruction depends on methodology used)

• _{Data holdings are dispersed with poor provenance} • _{Few user tools: access difficult for non-specialists}

• _{Concerns over: evolving station networks; changes in}

measurement technique / station location / recording practice (often undocumented); urban “heat island” effects; etc. etc.

• _{Increasing role of “blogosphere” & critiques outside}

Inhomogeneities: annual mean min temp at

Reno, Nevada, USA

Issues not well understood …

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Not all commentators / policymakers understand the

issues:

The big question

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Can we create a process that leads to a suite of well

characterized estimates of land surface temperatures

that can be used to answer scientific and societal

demands of the 21

Century?

– _{Open and transparent}

– _{Better understanding of fundamental instrument performance}

and measurement properties

– _{Consistent performance evaluation} – _{User tools}

– _{Not just monthly at the largest scales. Daily, sub-daily, regional}

How the initiative was started

• _{2010 UK Met Office Submission to World Meteorological}

Organization Commission for Climatology

– Call for creating new suite of products to meet 21st _Century

demands / expectations

• September 2010 instigation workshop, UK Met Office, Exeter UK

– _{80 international experts including climate scientists, metrologists,} statisticians, software engineers

– White papers posted online and public comments solicited – _{Agreed project outline and governance structure}

Databank Progress

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Working Group instigated

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Data rescue task team

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Provenance and version control task team

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Development version posted

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http://www.gosic.org/

GLOBAL_SURFACE_DATABANK/GBD.html

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First version release and accompanying

Stage 0 data in hardcopy / image format

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Millions of rescued images in the NOAA Foreign

Data Library

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2000+ boxes of data in the NCDC library

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Holdings in other libraries and repositories,

particularly former colonial powers

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Holdings literally rotting away or seen as a

nuisance in many countries

Data currently digitized

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Numerous public holdings

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NCDC

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UCAR

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RIHMI

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Regional and national holdings

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Some restricted for commercial or geopolitical

Stage 2 – common format

Stage 3

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Same format as stage 2

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One unique version for each station – recommended

version for most users

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Forms basis for creation of analogs (see later)

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Protocols used in merging sources are as yet to be

finalized

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Provenance tracking will ensure an unbroken chain to

earlier stages

Partnerships essential

• _{Bring together existing efforts, augment and ensure pull through. e.g. ACRE}

(“Atmospheric Circulation Reconstructions over the Earth”) project ( http://www.met-acre.org/), International Environmental Data Rescue Organisation (www.iedro.org) and other national / international programs.

• Pursue innovative approaches (crowdsourcing building upon success of oldweather.org etc.)

• _{Build on ICOADS model for sea surface temperatures (http://icoads.noaa.gov/) – easy}

submission and access to data to recognized global repository

• _{Recognize key partners and contributions} • _{And you can also help …}

– www.surfacetemperatures.org/databank

– [email protected]

– http://www.surfacetemperatures.org/databank/DataSubmission-Stage1-Guidance.pdf?attredirects=0

Multiplicity of data products

• _{Structural uncertainty is the key}

– _{Raw data is far from traceable to international measurement} standards

– _{Data artefacts are numerous and have myriad causes} – _{Metadata is patchy at best}

– _{Data is discrete in both space and time}

– _{No “how to” … rather very many cases of “it may work …”}

– _{Multiple subjective decisions required even in automated procedures} (thresholds, periods, test type etc.)

• _{Need multiple independent efforts with different choices}

– _{Station selection}

– _{Time and space resolution} – Quality control choices – _{Homogenization decisions} – _{Averaging procedures}

• _{Should not just be climate scientists as need broad range of}

approaches

– _{Statisticians, metrologists, software engineers, citizen scientists etc.}

• _{Distinct approaches pinpoint key uncertainties so redundancy is}

of fundamental scientific value …

• _{… at least providing the underlying algorithm is understood}

Benchmarking and assessment

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With real world data we do not have the luxury of

knowing the truth – we cannot measure

performance of a specific method or closeness to

real world truth of any one data-product.

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Instead focus on performance of underlying

algorithms

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Consistent synthetic test cases, simulating real world

Benchmarking progress

• _{Working group and task teams instigated} • _{Create c.10 analog-error-worlds}

– _{Climate model basis (maintains plausible far field correlation}

structure) tweaked with real station climate characteristics

– _{Add in random and systematic errors to approximate the real}

world error structures which may exist

– _{Algorithm assessment based upon ability to recover original}

data

– _{Error structures should enable answering a range of questions /}

assumptions regarding the true error to avoid over-tuning

• _{Analogs to be made available Nov. 2012 based upon version 1}

Benchmarking example

• _{For USHCN (lower 48 states)} • _{Step changes and white noise}

– _{4 identical error structure on 2 20}th _{Century runs, control and emission}

halt runs from different models

– _{No errors (do no harm)}

– _{Predominantly frequent small breaks (hard)}

– _{Perfect metadata, large breaks (easy)}

• _{100 member perturbed ensemble of the NCDC pairwise algorithm} • _{Consideration solely of timeseries and trends}

• _{Analyses that follow are for predominantly frequent small breaks}

Open issues on data product provision

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Data formats

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Degree of user interaction

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Ability to create graphical and tabular output

on the fly

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Limited progress to date

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Largely a reflection that this data provision is some

way down the road?

Progress to date summary

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Steering committee set up

– _{Terms of reference}

– _{World Meteorological Office and The International}

Environmetrics Society sponsored (seeking International Bureau of weights and measures)

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Working groups on databank and benchmarking active

– _{Databank prototype made public and data sources coming in.}

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Implementation Plan published

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Progress documented on initiative website at

You can help make this a success

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Help to find raw data sources

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Come up with novel ways of analyzing the

data

Questions and Answers

www.surfacetemperatures.org

[email protected]

Background materials

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Links to other relevant organizations (finite)

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http://www.met-acre.org

/ - ACRE – data rescue,

reanalyses, end-user engagement

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http://iedro.org

/ - IEDRO – data rescue

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http://icoads.noaa.gov

/ - ICOADS – marine

databank

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http://www.data-rescue-at-home.org

/ - data

Ecological Phenological Health & Disease Reinsurance Climate Monitoring Model Validation Environmental Assessments Extremes, Impacts & Risks Water resources Agricultural Forestry Energy Marine operations Fisheries Cultural landscapes and built heritage Education

Global historical reanalysis

56 realisations every 6 hours, 2⁰ x 2 ⁰ spatial resolution

O p e n P la tf o rm M e t O ffi c e -T S B -I B M P R E C IS D o w n sc a lin g H ig h e r R e so lu ti o n Citizen Science Crowd Sourcing (eg. Oldweather.org Data rescue@home) Global surface weather