World Meteorological Organization CCl-XV/INF. 15

COMMISSION FOR CLIMATOLOGY Submitted by UK Met Office

Date: 10.II.2010

FIFTEENTH SESSION Original Language: English

Antalya, Turkey, 

19-24 February 2010 

PROPOSAL FOR A NEW INTERNATIONAL ANALYSIS OF 

LAND SURFACE AIR TEMPERATURE DATA 

CONTENT OF DOCUMENT: 

UK Met Office submits this document for consideration by the CCl session 

Appendix: 

• Proposal for a new international analysis of land surface air temperature data 
CCl-XV/INF. 15, APPENDIX 

PROPOSAL FOR A NEW INTERNATIONAL ANALYSIS OF LAND SURFACE AIR 

TEMPERATURE DATA 

Submitted by UK Met Office 

Executive summary 

Surface temperature datasets are of critical importance for detecting, monitoring and 

communicating climate change. They are also essential for testing the validity of the climate 

models that are used to produce predictions of future climate change. The current datasets, 

constructed in the UK and US using different methodologies, agree in showing that the world is 

warming. Taken together these records provide a robust indicator of global change and form part 

of the evidence base that led the IPCC Fourth Assessment Report to conclude that “warming of the 

climate system is unequivocal”. 

To meet future needs to better understand the risks of dangerous climate change and to adapt to 

the effects of global warming, further development of these datasets is required, in particular to 

better assess the risks posed by changes in extremes of climate. This will require robust and 

transparent surface temperature datasets at finer temporal fidelity than current products. 

The current surface temperature datasets were first put together in the 1980s to the best standards 

of dataset development at that time; they are independent analyses and give the same results, 

thereby corroborating each other. 

In the case of the CRU land surface temperature dataset (CRUTEM3, which forms the land 

component of the HadCRUT dataset) there are substantial IPR issues around the raw station data 

that underpin the dataset; we are actively pursuing resolution of these issues so that the base data 

can be made openly available. We know that several stations have already been explicitly 

forbidden from release by the rights’ holders so we will not be able to release all the under-pinning 

station data. 

Consequently we have been considering how the datasets can be brought up to modern standards 

and made fit for the purpose of addressing 21st Century needs. We feel that it is timely to propose 

an international effort to reanalyze surface temperature data in collaboration with the World 

Meteorological Organization (WMO), which has the responsibility for global observing and 

monitoring systems for weather and climate. 

The proposed activity would provide: 

1. Verifiable datasets starting from a common databank of unrestricted data at both monthly 

and finer temporal resolutions (daily and perhaps even sub-daily); 

2. Methods that are fully documented in the peer reviewed literature and open to scrutiny; 

3. A set of independent assessments of surface temperature produced by independent 

groups using independent methods; 

4. Robust benchmarking of performance and comprehensive audit trails to deliver 

confidence in the results; 

5. Robust assessment of uncertainties associated with observational error, temporal and 

geographical in homogeneities. 

It is important to emphasize that we do not anticipate any substantial changes in the resulting 

global and continental-scale multi-decadal trends. This effort will ensure that the datasets are 

completely robust and that all methods are transparent. 
CCl-XV/INF. 15, APPENDIX, p. 2 

Background 

In many respects HadCRUT has been the default choice of surface dataset in all 4 IPCC 

Assessment Reports. However we must stress that other independent datasets are used which 

support the HadCRUT data. There are three centres which currently calculate global average 

temperature each month: 

• Met Office, in collaboration with the Climatic Research Unit (CRU) at the University of 

East Anglia (UK); 

• Goddard Institute for Space Studies (GISS), which is part of NASA (USA); 

• National Climatic Data Center (NCDC), which is part of the National Oceanic and 

Atmospheric Administration (NOAA) (USA). 

These groups work independently and use different methods in the way they process data to 

calculate the global average temperature. Despite this, the results of each are similar from month 

to month and year to year, and there is robust agreement on temperature trends from decade to 

decade. 

All existing surface temperature datasets are homogenized at the monthly resolution, and are 

therefore suitable for characterizing multi-decadal trends. These are adequate for answering the 

pressing 20th Century questions of whether climate is changing and if so how. But they are 

fundamentally ill-conditioned to answer 21st Century questions such as how extremes are changing 

and therefore what adaptation and mitigation decisions should be taken. Monthly resolution data 

cannot verify model projections of extremes in temperature which by definition are (sub-) daily 

resolution events. 

Through collaboration with NCDC we have two quality controlled, but not homogenized products at 

the daily and sub-daily resolution (HadGHCND and HadISD – the latter about to be submitted to 

peer review), spanning 1950 onwards and 1973 onwards respectively. However, because these 

are not homogenized, they may retain time-varying biases. It is an open scientific question as to 

whether homogenization is feasible at these timescales whilst retaining the true temporal 

characteristics of the record. In particular, seasonally invariant adjustments which are adequate for 

monthly timescale data will be grossly inadequate at the daily or sub-daily resolution. Clearly 

homogenization of these data is highly desirable but some detailed research is needed to define 

the best approach. 

The way forward 

Recognizing that no single institution can undertake such a fundamental data collection, 

re-analysis and verification process single-handedly, we would envisage this as a broad 

community effort – a ‘grand challenge’ so to speak - involving UK and international partners. 

The UK would convene a workshop to be hosted by the Met Office Hadley Centre and invite key 

players who could plausibly create such datasets with the aim of initiating an agreed community 

challenge to create an ensemble of open source land temperature datasets for the 21st Century 

both at monthly temporal resolution and also at the daily and sub-daily timescales needed to 

monitor extremes. Such an approach would help distribute many of the basic tasks, ensuring that 

the most appropriate parties were responsible for each part as well as providing a focused 

framework and timeline. This effort would ideally have involvement from, and be coordinated 

under, the umbrella of one or more of the Commission for Climatology, the Global Climate 

Observing System, or the World Climate Research Programme, with assistance from other WMO 

constituent bodies as appropriate. 
CCl-XV/INF. 15, APPENDIX, p. 3 

Activities that would be required within any overall programme are: 

1. Creation of an agreed international databank of surface observations to be made available 

without restriction, akin to the I-COADS databank in the ocean domain. Note that NCDC 

already have substantial efforts in this regard and would be a key participant and likely 

host as the designated world data bank. Data to be available at monthly, daily and subdaily resolutions; 

2. Multiple independent groups undertake efforts to create datasets at various temporal 

resolutions based upon this data-bank. Participants will be required to create a full audit 

trail and publish their methodology in the peer-reviewed literature. Strong preference will 

be given to automated systems and creations of ensembles that reflect the uncertainties 

in the observations and methods; 

3. One or more groups to create realistic test-cases of the spatio-temporal observational 

availability by sampling output from a range of climate simulations from a number of 

models, adding realistic error structures; 

4. Groups to run their algorithms against the test-cases and one or more groups, preferably 

completely independent, to undertake a holistic assessment based upon the results of this 

verification exercise from all groups. 

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