Details of Award
NERC Reference : NE/Z504269/1
NERC-NSFGEO Quantifying error and uncertainty in the Antarctic passive microwave sea ice record
Grant Award
- Principal Investigator:
- Dr M M Rogers, NERC British Antarctic Survey, Science Programmes
- Co-Investigator:
- Mr A Cziferszky, NERC British Antarctic Survey, Environment and Information Division
- Co-Investigator:
- Mr N Hughes, Norwegian Metrological Institute, Norwegian Ice Service
- Co-Investigator:
- Mrs P Wagner, Norwegian Metrological Institute, Norwegian Ice Service
- Co-Investigator:
- Mr A Fleming, NERC British Antarctic Survey, Environment and Information Division
- Co-Investigator:
- Dr J Wilkinson, NERC British Antarctic Survey, Science Programmes
- Co-Investigator:
- Mr J Byrne, NERC British Antarctic Survey, Corporate Services
- Grant held at:
- NERC British Antarctic Survey, Science Programmes
- Science Area:
- None
- Overall Classification:
- Unknown
- ENRIs:
- None
- Science Topics:
- None
- Abstract:
- Passive microwave (PM) derived sea ice concentration (SIC) data are possibly the most utilised satellite product for the polar regions for monitoring trends in sea ice conditions. It is regularly used by scientists, local communities, policy makers, and media, as well as industries such as fishing, tourism, and shipping. Despite the fundamental importance of the PM-derived SIC products, it is widely acknowledged within the sea ice community that their present form is inadequate, due to a lack of rigour in their assessment of uncertainty on both temporal and spatial scales, and the diverse range of algorithms that can be used to derive SIC value from PM records. The fundamental difficulty derives from the coarse, 36 - 625km2, size of the PM pixels, which precludes the use of traditional ground-truthing methods as viable routes to assess the accuracy of PM measurements over a range of spatial and temporal scales. Two recent developments mean that we can now overcome these challenges. Firstly, there has been a step-change increase in the rate of satellite image acquisition with petabytes of high-resolution satellite imagery pertaining to sea ice conditions now being available to validate the accuracy of the PM SIC pixels. Secondly, advances in the capabilities of digital technologies, including machine learning (ML), means we can for the first time automate the storage, processing, and analysis of these big satellite data archives. By unifying these two developments we are able to quantify the error and uncertainty in Antarctic PM-derived SIC data at unprecedented temporal and spatial scales. The specific goal of the proposal is to use digital technologies and ML methods in satellite imagery to: SO1 Develop and enhance ML techniques to automatically generate high-resolution sea ice concentration (SIC-HR) charts from multispectral and radar satellite imagery. SO2 Develop a modular pipeline to automate the quantification of uncertainty in PM-derived SIC at unprecedented spatial and temporal scales. SO3 Quantify the spatial and temporal uncertainties associated with the calculation of Antarctic SIC derived from PM data at a decadal, pan-Antarctic scale. SO4 Refine decadal-scale time series of pan-Antarctic sea ice area via sensitivity of ice edge location. Our analyse and the generation of error and uncertainty values will be used to refine the half-centennial time-series of Antarctic sea ice extent, a crucial product recognised by the World Meteorological Organisation as a key Global Climate Indicators for describing the changing climate and an Essential Climate Variable, critical for characterising the Earth's evolving climate. When our objectives are fulfilled, our project will provide increased trust in this invaluable product and improve understanding of the sensitivity of Antarctic sea ice to a warming world.
- NERC Reference:
- NE/Z504269/1
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Research Grants
- Grant Status:
- Active
- Programme:
- Pushing the Frontiers
This grant award has a total value of £658,836
FDAB - Financial Details (Award breakdown by headings)
| Exception - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | Exception - Staff | Exception - T&S |
|---|---|---|---|---|---|
| £279,130 | £2,619 | £5,372 | £655 | £339,549 | £31,513 |
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