Historical Ocean Surface Temperatures: Adjustment, Characterisation and Evaluation (HOSTACE)
Lead Research Organisation:
NATIONAL OCEANOGRAPHY CENTRE
Department Name: Science and Technology
Abstract
The surface temperature of the land and sea is the main measure of "global warming". Measurements of sea surface temperature (SST) have been made for more than 200 years, first on sailing ships, now on a mixture of ships and buoys (drifting and moored). Technology has changed dramatically over this period, raising serious questions about whether technology changes over time give a misleading impression of how the temperature has changed - and therefore how climate has changed.
People first measured the temperature of a seawater sample hauled up in a wooden bucket. Buckets are now made of insulating rubber. Most direct SST measurements are now sent via satellites from drifting buoys. Many other measurement methods have also been used. Different methods don't yield precisely the same SST values, and because global warming is a gradual change, these subtle discrepancies (or "biases") could distort our picture about the timing and magnitude of global warming. So, we must be sure that we understand how the different methods used to measure SST have affected the observations.
These biases in SST have been a known problem for years, so why do we believe we can solve it? One reason is that recently many more observations have been retrieved from historical sources. Many ships' logbooks containing weather observations have been digitised. This has nearly doubled the number of observations before World War 2. Another reason is new, stable observations of SST from sensors on satellites orbiting Earth. Most satellite sensors give a detailed picture of patterns in SST and are tuned to drifting buoy SSTs to give reasonable accuracy. But compared to the subtle trends of global warming, they are not stable enough from year to year and across large distances. New high-quality SST measurements from a reworking of the SST measurements of a particular series of sensors are accurate and stable enough. Even better, they do not rely on ship or buoy SST observations, so we can use them as an independent point of reference.
A major challenge is that the biases in SST made on ships are different for different measurement methods and we don't always know what methods were used. But we do know how we expect the biases for each method to vary with factors like the amount of heating by the Sun and wind speed. We will use these variations of the biases for each ship or buoy to assign measurement methods to observations (or, where it is not clear cut, the likelihood that the method is one or another type). E.g., we might be 80% confident that a particular ship used a canvas bucket to sample the water, but allow a 20% chance that a wooden bucket was used. We can then adjust for the expected biases according to method, and indicate how uncertain our adjustment may be.
The next step will be to combine the scattered observations into maps of monthly average SST over the whole ocean. We must also calculate our degree of uncertainty in these monthly maps. There are few observations in the 19thC, so a global SST map requires sophisticated gap-filling methods. The final step is to compare our maps of SST with those produced by other scientists. Normally when such comparisons are made it is hard to understand the source of differences between the datasets. Was it due to different input data? Or different bias adjustments? Or the way the gaps were filled? Collaborating with other dataset producers, we will separate these different effects. For example, we will all use identical inputs, and isolate the effects of different gap-filling methods. This will also test our the uncertainty estimates - if important factors affecting the SST biases have been missed, then estimates of uncertainty may be too small to explain the differences between the SST maps produced by different groups.
Such problems can mislead us in interpreting climate changes. We will use the new SST history to reassess explanations of phases of climate warming during in the 20th C.
People first measured the temperature of a seawater sample hauled up in a wooden bucket. Buckets are now made of insulating rubber. Most direct SST measurements are now sent via satellites from drifting buoys. Many other measurement methods have also been used. Different methods don't yield precisely the same SST values, and because global warming is a gradual change, these subtle discrepancies (or "biases") could distort our picture about the timing and magnitude of global warming. So, we must be sure that we understand how the different methods used to measure SST have affected the observations.
These biases in SST have been a known problem for years, so why do we believe we can solve it? One reason is that recently many more observations have been retrieved from historical sources. Many ships' logbooks containing weather observations have been digitised. This has nearly doubled the number of observations before World War 2. Another reason is new, stable observations of SST from sensors on satellites orbiting Earth. Most satellite sensors give a detailed picture of patterns in SST and are tuned to drifting buoy SSTs to give reasonable accuracy. But compared to the subtle trends of global warming, they are not stable enough from year to year and across large distances. New high-quality SST measurements from a reworking of the SST measurements of a particular series of sensors are accurate and stable enough. Even better, they do not rely on ship or buoy SST observations, so we can use them as an independent point of reference.
A major challenge is that the biases in SST made on ships are different for different measurement methods and we don't always know what methods were used. But we do know how we expect the biases for each method to vary with factors like the amount of heating by the Sun and wind speed. We will use these variations of the biases for each ship or buoy to assign measurement methods to observations (or, where it is not clear cut, the likelihood that the method is one or another type). E.g., we might be 80% confident that a particular ship used a canvas bucket to sample the water, but allow a 20% chance that a wooden bucket was used. We can then adjust for the expected biases according to method, and indicate how uncertain our adjustment may be.
The next step will be to combine the scattered observations into maps of monthly average SST over the whole ocean. We must also calculate our degree of uncertainty in these monthly maps. There are few observations in the 19thC, so a global SST map requires sophisticated gap-filling methods. The final step is to compare our maps of SST with those produced by other scientists. Normally when such comparisons are made it is hard to understand the source of differences between the datasets. Was it due to different input data? Or different bias adjustments? Or the way the gaps were filled? Collaborating with other dataset producers, we will separate these different effects. For example, we will all use identical inputs, and isolate the effects of different gap-filling methods. This will also test our the uncertainty estimates - if important factors affecting the SST biases have been missed, then estimates of uncertainty may be too small to explain the differences between the SST maps produced by different groups.
Such problems can mislead us in interpreting climate changes. We will use the new SST history to reassess explanations of phases of climate warming during in the 20th C.
Planned Impact
There is intense public interest in climate change and the level of certainty we have in those changes. Our research will provide new clarity in the understanding of biases and uncertainty that exist in historical observations of sea surface temperature (SST). All the results of our research will be made available to the public, including estimates of bias and uncertainty for every observation in the archive. We will make our results available through partnership with the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Value-Added Database project (IVAD). This will ensure that our results are integrated with the original data archives. Such transparency will help to build confidence in the bias adjustments we apply and hence in the climate change signals seen in the adjusted SST observations. Anyone will be able to download the adjustments and explore their characteristics of our bias adjustments themselves. Further public engagement is through our partnership with the oldWeather citizen science digitisation activity and through material specifically developed for use in secondary schools.
One important outcome from the proposed work will be a comparison of SST datasets from different providers, including ourselves, the National Climate Data Center and Lamont Doherty Earth Observatory in the US and the Met Office in the UK. The comparison will be designed to tease out the causes of the differences seen between the datasets and also to provide some verification of the uncertainty estimates. Such comparisons have been shown to be important in reconciling and understanding climate datasets, for example different datasets of upper-air temperatures are now much better understood following such comparisons. To make the information derived from the dataset comparison more relevant to users of SST datasets we will, with our project partners, produce advice on the strengths and weaknesses of the datasets for different applications. Direct users of our research outside the academic community will include fisheries research, and planning for commercial and military marine operations.
Better estimates of SST and its uncertainty will feed through to better climate predictions. One of our aims is to improve the regional accuracy of historical SST. Improved regional prediction of climate change will have wide societal and economic impact. Benefits will be felt by policy makers who will have improved information for decision making, by everyone affected by climate change and mitigation policies, by engineers designing structures resilient to a changing environment and many others. Our main point of engagement with policy makers themselves is through the UK Department of Energy and Climate Change (DECC) and we will also continue to contribute directly to the Marine Climate Change Impacts Partnership (MCCIP) Annual Reports which transfer high quality evidence on marine climate change impacts to the UK and devolved governments, their agencies and industry.
The early-career researchers and PhD studentships engaged by this project will gain skills in analysis techniques that will be widely applicable beyond the immediate area of their research. Such skills will include statistical and physical analysis, the quantification of uncertainty in observations and analyses, the management of large datasets and the dissemination of complex information.
One important outcome from the proposed work will be a comparison of SST datasets from different providers, including ourselves, the National Climate Data Center and Lamont Doherty Earth Observatory in the US and the Met Office in the UK. The comparison will be designed to tease out the causes of the differences seen between the datasets and also to provide some verification of the uncertainty estimates. Such comparisons have been shown to be important in reconciling and understanding climate datasets, for example different datasets of upper-air temperatures are now much better understood following such comparisons. To make the information derived from the dataset comparison more relevant to users of SST datasets we will, with our project partners, produce advice on the strengths and weaknesses of the datasets for different applications. Direct users of our research outside the academic community will include fisheries research, and planning for commercial and military marine operations.
Better estimates of SST and its uncertainty will feed through to better climate predictions. One of our aims is to improve the regional accuracy of historical SST. Improved regional prediction of climate change will have wide societal and economic impact. Benefits will be felt by policy makers who will have improved information for decision making, by everyone affected by climate change and mitigation policies, by engineers designing structures resilient to a changing environment and many others. Our main point of engagement with policy makers themselves is through the UK Department of Energy and Climate Change (DECC) and we will also continue to contribute directly to the Marine Climate Change Impacts Partnership (MCCIP) Annual Reports which transfer high quality evidence on marine climate change impacts to the UK and devolved governments, their agencies and industry.
The early-career researchers and PhD studentships engaged by this project will gain skills in analysis techniques that will be widely applicable beyond the immediate area of their research. Such skills will include statistical and physical analysis, the quantification of uncertainty in observations and analyses, the management of large datasets and the dissemination of complex information.
Organisations
- NATIONAL OCEANOGRAPHY CENTRE (Lead Research Organisation)
- UNIVERSITY OF EDINBURGH (Collaboration)
- Meteorological Office UK (Collaboration)
- HARVARD UNIVERSITY (Collaboration)
- National Oceanic and Atmospheric Administration (Collaboration)
- Japan Meteorological Agency (Collaboration)
- Colorado State University (Collaboration)
- Columbia University (Collaboration)
- University of Bonn (Collaboration)
- University of East Anglia (Collaboration)
Publications
Berry D
(2016)
Assessing the health of the in situ global surface marine climate observing system
in International Journal of Climatology
Carella G
(2015)
A probabilistic approach to ship voyage reconstruction in ICOADS
in International Journal of Climatology
Carella G
(2017)
Measurements and models of the temperature change of water samples in sea-surface temperature buckets
in Quarterly Journal of the Royal Meteorological Society
Carella G
(2018)
Estimating Sea Surface Temperature Measurement Methods Using Characteristic Differences in the Diurnal Cycle
in Geophysical Research Letters
Chan D
(2019)
Correcting datasets leads to more homogeneous early-twentieth-century sea surface warming.
in Nature
Cornes R
(2020)
CLASSnmat: A global night marine air temperature data set, 1880-2019
in Geoscience Data Journal
Cropper T
(2023)
Quantifying Daytime Heating Biases in Marine Air Temperature Observations from Ships
in Journal of Atmospheric and Oceanic Technology
Duchez A
(2016)
Drivers of exceptionally cold North Atlantic Ocean temperatures and their link to the 2015 European heat wave
in Environmental Research Letters
Freeman E
(2016)
ICOADS Release 3.0: a major update to the historical marine climate record
in International Journal of Climatology
Hyder P
(2018)
Critical Southern Ocean climate model biases traced to atmospheric model cloud errors.
in Nature communications
Description | The HOSTACE project established that the use of physically-based statistical models would enable the construction of improved estimates of biases in historical measurements of sea surface temperature. Key to this approach was the need to associate these measurements with an individual observing platform (usually a ship) to enable the characteristics of the measurements to be established. Many observations from the historical record do not have information that allows them to be unambiguously associated with a particular platform, and clustering these observations together proved unexpectedly challenging. Nevertheless a "ship tracking" methodology was developed and implemented and the results showed that the temperature observations from reports clustered by the algorithm were more similar to each other than to nearby reports from other clusters. It was thereby demonstrated that accounting for differences in measurements between different ships would lead to a more homogeneous temperature record. Laboratory-based measurements were used to identify the main environmental drivers of biases in historical sea surface temperature measurements made from bucket samples and to establish the physical basis for the statistical adjustment model. Exploratory data analysis revealed a new physical dependence of the biases in some observations made by the most common modern method of measurement: recording the temperature of the engine cooling intake water. A method was developed to classify observation methods (bucket or engine intake) from the characteristics of the measurements, and successfully applied to the observational record to enable observations from different measurement methods to be identified. In past analyses, uncertainty in observational methods was a major contributor to uncertainty in bias adjustments and hence global surface temperature. Once classified by measurement method adjustments were applied to the appropriate observations and shown to reduce differences between the observations from different methods thus producing a more consistent temperature record. Integral to the analysis was the use of information from modern data sources, moored buoys and satellites, to enable the scatter in historical measurements of SST due to real environmental variability to be accounted for in the analysis. The project also developed new dataset construction methods that allow the spatio-temporal distribution of the observations within the fairly coarse resolution of the grid cells used in the construction of historical gridded analyses to be accounted for in the calculation of the gridcell mean and uncertainty. |
Exploitation Route | Because the quality of the historical databases proved to be a barrier to the analysis methods developed a case was built for the need to reprocess the historical surface marine observational record. This has been funded in part by Copernicus. This fundamental work is ongoing and will, when complete, enable more sophisticated analysis of the observations and lead to improved estimates of global surface marine temperature change and its uncertainty. The improvements to the historical databases, and the gridding procedures developed under HOSTACE, have been used in the construction of a new gridded analysis of night marine air temperature. Collaborations established under this project have led to community statement papers outlining recommended approaches to the construction of long term climate records and bias adjustment models. |
Sectors | Environment |
Description | Publications from HOSTACE have been cited as supporting evidence in the Intergovernmental Panel on Climate Change 6th Assessment Report (2021). |
First Year Of Impact | 2021 |
Sector | Environment |
Impact Types | Policy & public services |
Description | Global Surface Air Temperature (GloSAT) |
Amount | £1,329,833 (GBP) |
Funding ID | NE/S015647/2 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 11/2019 |
End | 09/2024 |
Description | Global Surface Air Temperature (GloSAT), NERC Large Grant |
Amount | £3,314,772 (GBP) |
Funding ID | NE/S015647/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 09/2019 |
End | 09/2023 |
Title | International Comprehensive Ocean-Atmosphere Data Set, Release 3.0 |
Description | The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a global ocean marine meteorological and surface ocean dataset. It is formed by merging many national and international data sources that contain measurements and visual observations from ships (merchant, navy, research), moored and drifting buoys, coastal stations, and other marine and near-surface ocean platforms. Each marine report contains individual observations of meteorological and oceanographic variables, such as sea surface and air temperatures, wind, pressure, humidity, and cloudiness. The coverage is global and sampling density varies depending on date and geographic position relative to shipping routes and ocean observing systems. The latest Release 3.0 (R3.0) of ICOADS covers 1662-2014, and is coupled with improved "preliminary" monthly data and product extensions past 2014. R3.0 includes changes designed to enable more effective exchange of information describing data quality between ICOADS, reanalysis centers, data set developers, scientists and the public. These user-driven innovations include the assignment of a unique identifier (UID) to each marine report, to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the International Maritime Meteorological Archive (IMMA) common data format incorporate new near-surface oceanographic data elements and cloud parameters. Many new input data and metadata sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. |
Type Of Material | Database/Collection of data |
Year Produced | 2016 |
Provided To Others? | Yes |
Impact | Development of new gridded sea surface temperature long-term datasets: Boyin Huang, Peter W. Thorne, Viva F. Banzon, Tim Boyer, Gennady Chepurin, Jay H. Lawrimore, Matthew J. Menne, Thomas M. Smith, Russell S. Vose, Huai-Min Zhang, Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons, Journal of Climate, 2017, 30, 20, 8179 |
URL | http://onlinelibrary.wiley.com/doi/10.1002/joc.4775/abstract |
Description | Collaboration with researchers at Colorado State University, leading to publication in Bulletin of the American Meteorological Society |
Organisation | Colorado State University |
Department | Department of Atmospheric Science |
Country | United States |
Sector | Academic/University |
PI Contribution | Collaborative research leading to publication in Bulletin of the American Meteorological Society |
Collaborator Contribution | Collaborative research leading to publication in Bulletin of the American Meteorological Society |
Impact | Davis, L. B. B., D. W. J. Thompson, J. J. Kennedy and E. C. Kent, 2019: The importance of unresolved biases in 20th century sea-surface temperature observations, Bull. Amer. Meteor. Soc, 100, 621-629, doi: 10.1175/BAMS-D-18-0104.1. |
Start Year | 2017 |
Description | Collaboration with researchers at Harvard University, leading to publication in Nature |
Organisation | Harvard University |
Department | Department of Earth and Planetary Sciences |
Country | United States |
Sector | Academic/University |
PI Contribution | Collaborative research into biases in sea surface temperature measurements. |
Collaborator Contribution | Collaborative research into biases in sea surface temperature measurements. |
Impact | Chan D., E. C. Kent, D. I. Berry and P. Huybers, 2019: Correcting datasets leads to more homogeneous early 20th century sea surface warming, Nature, 571, 393-397, doi: 10.1038/s41586-019-1349-2. |
Start Year | 2018 |
Description | SST bias collaboration |
Organisation | Columbia University |
Department | Lamont Doherty Earth Observatory |
Country | United States |
Sector | Academic/University |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | Japan Meteorological Agency |
Department | Global Environment and Marine Department |
Country | Japan |
Sector | Public |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | Japan Meteorological Agency |
Country | Japan |
Sector | Public |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | Japan Meteorological Agency |
Country | Japan |
Sector | Public |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | Meteorological Office UK |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | National Oceanic And Atmospheric Administration |
Country | United States |
Sector | Public |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | University of Bonn |
Country | Germany |
Sector | Academic/University |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | University of East Anglia |
Department | Climate Research Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | SST bias collaboration |
Organisation | University of Edinburgh |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, led high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Collaborator Contribution | Co-convened workshop of SST bias experts at the Met Office in 2015, contributed to high-profile publication in Bulletin of the American Meteorological Society "A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature". |
Impact | Kent, E.C., J.J. Kennedy, T.M. Smith, S. Hirahara, B. Huang, A. Kaplan, D.E. Parker, C.P. Atkinson, D.I. Berry, G. Carella, Y. Fukuda, M. Ishii, P.D. Jones, F. Lindgren, C.J. Merchant, S. Morak-Bozzo, N.A. Rayner, V. Venema, S. Yasui, and H. Zhang, 2017: A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature. Bull. Amer. Meteor. Soc., 98, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00251.1 |
Start Year | 2015 |
Description | Contribution to BBC documentary "Climate Change by Numbers" |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Discussions with BBC researcher regarding the use of buckets to sample water for sea surface temperature measurements. Loan of replica historical buckets for use in program and digital thermometer. Resulting program broadcast as 75 minute documentary on BBC4. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.bbc.co.uk/programmes/p02jsdrk |
Description | Contribution to piece on US National Public Radio |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Research published with colleagues at Harvard University was featured in a piece including interviews with US colleagues on National Public Radio. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.wbur.org/npr/750778010/how-much-hotter-are-the-oceans-the-answer-begins-with-a-bucket |
Description | Filmed piece for BBC on historical SST measurements |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Filmed piece on boat RV Callista, formed part of an item on historical climate observations broadcast on BBC breakfast (7 March 2019) and BBC News Channel, estimated reach 99 million people. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.youtube.com/watch?v=x_iWTFv-qeM |
Description | London Ocean Forum |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | Presentation and panel discussion at London Ocean Group "London Ocean Forum" meeting 17th June 2019. Presentation entitled "Understanding the global marine surface temperature record". Outcome was raised awareness of attending undergraduate and postgraduate students and researchers into recent progress in research into the production of surface temperature marine climate data records. |
Year(s) Of Engagement Activity | 2019 |
URL | https://mecheng.ucl.ac.uk/londonoceangroup/ |
Description | University of East Anglia Atmosphere Ocean and Climate Seminars |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation in regular seminar series "New estimates of sea surface temperature biases from 1850". Outreach to researchers normally working with land climate record, discussion followed. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.uea.ac.uk/environmental-sciences/news-and-events/atmosphere-ocean-and-climate-seminars/a... |