APPOSITE: Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales
Lead Research Organisation:
University of Reading
Department Name: Meteorology
Abstract
The Arctic is a region experiencing rapid climate changes. APPOSITE is a proposed three year research programme focusing on improving our ability to forecast the climate of the Arctic on seasonal to inter-annual timescales. Arctic predictions would be of great value to both the people that live and work in the Arctic regions and also for informing important policy decisions about the region. Additionally, the Arctic region exerts an influence on the climate outside the Arctic. Hence improved forecasts of Arctic climate may increase our ability to forecast climate in mid-latitude regions, such as Europe, on similar seasonal to inter-annual timescales.
Building such Arctic forecast systems will be a complex task, involving the construction of a detailed observation system to monitor Arctic climate, and sophisticated forecast models that can use these observations to enhance predictive capabilities. An important first step before committing to such a programme, is to assess the likely benefits that such a system may bring.
APPOSITE is specifically designed to provide this assessment by answering four key questions:
1) What aspects of Arctic climate can we predict?
2) How far in advance can we predict these aspects? Does this depend on the season?
3) What physical processes and mechanisms are responsible for this predictability?
4) What aspects of forecast models should be prioritised for development?
APPOSITE will use state-of-the art climate models to answer these questions. The answers to these questions will form a key part of the future development of seasonal to inter-annual Arctic forecasting systems nationally and internationally.
Building such Arctic forecast systems will be a complex task, involving the construction of a detailed observation system to monitor Arctic climate, and sophisticated forecast models that can use these observations to enhance predictive capabilities. An important first step before committing to such a programme, is to assess the likely benefits that such a system may bring.
APPOSITE is specifically designed to provide this assessment by answering four key questions:
1) What aspects of Arctic climate can we predict?
2) How far in advance can we predict these aspects? Does this depend on the season?
3) What physical processes and mechanisms are responsible for this predictability?
4) What aspects of forecast models should be prioritised for development?
APPOSITE will use state-of-the art climate models to answer these questions. The answers to these questions will form a key part of the future development of seasonal to inter-annual Arctic forecasting systems nationally and internationally.
Planned Impact
APPOSITE aims to assess the extent to which the climate and state of the Arctic system is predictable on seasonal to inter-annual timescales, and understand the physical processes that govern this predictability. The direct output from the project will provide information about the inherent predictability of the area and how the Arctic effects the mid-latitudes; this knowledge is essential for improving and understanding the limits of operational forecast systems.
The main direct beneficiaries of the knowledge generated by APPOSITE will be:
1. The international research community
2. The UK Met Office and other international forecast providers (e.g. ECMWF).
3. Policy makers: for the UK (Defra), and for the Arctic (DECC and FCO).This work also has the potential to be used by policy makers (DECC) in UNFCCC climate negotiations and could contribute to the fifth IPCC assessment report Chapter 11: Near-term Climate Change: Projections and Predictability.
By the use of the knowledge gained in this project the potential to improve forecast systems will also impact:
4. Business Community: indirectly the results also have the potential to impact industrial sectors such as shipping, oil and gas and tourism through better informed business decisions and assessments of opportunity
5. The general public through improved forecast systems for their locality.
The results of APPOSITE should benefit people, planning to or currently, living and working within the Arctic region such as local Arctic communities and industry operating in the region (shipping, tourism, fishing and future oil and gas exploration). Improved forecasts of weather and the state of the climate system (atmosphere, ocean and sea ice) inform better decision making that can improve lives or have economic reward. The results will also have an indirect impact on UK society and business through potentially improved seasonal forecasts for the European region.
The main direct beneficiaries of the knowledge generated by APPOSITE will be:
1. The international research community
2. The UK Met Office and other international forecast providers (e.g. ECMWF).
3. Policy makers: for the UK (Defra), and for the Arctic (DECC and FCO).This work also has the potential to be used by policy makers (DECC) in UNFCCC climate negotiations and could contribute to the fifth IPCC assessment report Chapter 11: Near-term Climate Change: Projections and Predictability.
By the use of the knowledge gained in this project the potential to improve forecast systems will also impact:
4. Business Community: indirectly the results also have the potential to impact industrial sectors such as shipping, oil and gas and tourism through better informed business decisions and assessments of opportunity
5. The general public through improved forecast systems for their locality.
The results of APPOSITE should benefit people, planning to or currently, living and working within the Arctic region such as local Arctic communities and industry operating in the region (shipping, tourism, fishing and future oil and gas exploration). Improved forecasts of weather and the state of the climate system (atmosphere, ocean and sea ice) inform better decision making that can improve lives or have economic reward. The results will also have an indirect impact on UK society and business through potentially improved seasonal forecasts for the European region.
Organisations
- University of Reading (Lead Research Organisation)
- National Oceanic and Atmospheric Administration (Collaboration)
- Catalan Institute of Climate Sciences (IC3) (Collaboration)
- European Centre for Medium Range Weather Forecasting ECMWF (Collaboration)
- Institut Pierre-Simon Laplace (Project Partner)
- National Center for Atmospheric Research (Project Partner)
- University of Washington (Project Partner)
Publications
Hodson D
(2012)
Identifying uncertainties in Arctic climate change projections
in Climate Dynamics
Day J
(2012)
Sources of multi-decadal variability in Arctic sea ice extent
in Environmental Research Letters
Day J
(2013)
The Greenland Ice Sheet's surface mass balance in a seasonally sea ice-free Arctic
in Journal of Geophysical Research: Earth Surface
Tietsche S
(2013)
Assimilation of sea-ice concentration in a global climate model - physical and statistical aspects
in Ocean Science
Day J
(2013)
The Greenland Ice Sheet's surface mass balance in a seasonally sea ice-free Arctic
in Journal of Geophysical Research: Earth Surface
Tietsche S
(2014)
Seasonal to interannual Arctic sea ice predictability in current global climate models
in Geophysical Research Letters
Guemas V
(2014)
A review on Arctic sea-ice predictability and prediction on seasonal to decadal time-scales
in Quarterly Journal of the Royal Meteorological Society
Hawkins E
(2014)
Pan-Arctic and Regional Sea Ice Predictability: Initialization Month Dependence
in Journal of Climate
Day J
(2014)
Will Arctic sea ice thickness initialization improve seasonal forecast skill?
in Geophysical Research Letters
Hawkins E
(2015)
Bouncing towards an ice-free summer
in Planet Earth
Melia N
(2015)
Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations
in The Cryosphere
Hawkins E
(2015)
Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems
in Quarterly Journal of the Royal Meteorological Society
Swart N
(2015)
Influence of internal variability on Arctic sea-ice trends
in Nature Climate Change
Goessling H
(2016)
Predictability of the Arctic sea ice edge
in Geophysical Research Letters
Day J
(2016)
Atmospheric and Oceanic Contributions to Irreducible Forecast Uncertainty of Arctic Surface Climate
in Journal of Climate
Holmes C
(2016)
Robust Future Changes in Temperature Variability under Greenhouse Gas Forcing and the Relationship with Thermal Advection
in Journal of Climate
Melia N
(2016)
Sea ice decline and 21st century trans-Arctic shipping routes
in Geophysical Research Letters
Day J
(2016)
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1
in Geoscientific Model Development
Melia N
(2017)
Towards seasonal Arctic shipping route predictions
in Environmental Research Letters
Marchi S
(2018)
Reemergence of Antarctic sea ice predictability and its link to deep ocean mixing in global climate models
in Climate Dynamics
Sandu I
(2021)
The potential of numerical prediction systems to support the design of Arctic observing systems: Insights from the APPLICATE and YOPP projects
in Quarterly Journal of the Royal Meteorological Society
Flocco D
(2021)
Sea ice and atmospheric potential predictability in coupled GCMs
Description | Different climate models produce different estimates of Arctic seasonal to interannual predictability. There is also a seasonal barrier to forecast skill with forecasts started after Spring being more skillful for predicting the summer sea ice conditions. Sea ice thickness observations are crucial to provide skillful forecasts. |
Exploitation Route | Met Office are considering using sea ice thickness information in operational sea ice forecasts. |
Sectors | Environment,Transport |
Description | Asked to write a review about Arctic shipping risks and opportunities for the Government Office for Science (GO-Science) |
First Year Of Impact | 2016 |
Sector | Government, Democracy and Justice |
Impact Types | Policy & public services |
Description | APPOSITE simulations |
Organisation | Catalan Institute of Climate Sciences (IC3) |
Country | Spain |
Sector | Charity/Non Profit |
PI Contribution | Collaboration with partners at multiple institutes to perform parallel simulations: ECMWF, Reading GFDL, Princeton MPI, Hamburg IC3, Barcelona |
Start Year | 2012 |
Description | APPOSITE simulations |
Organisation | European Centre for Medium Range Weather Forecasting ECMWF |
Country | United Kingdom |
Sector | Public |
PI Contribution | Collaboration with partners at multiple institutes to perform parallel simulations: ECMWF, Reading GFDL, Princeton MPI, Hamburg IC3, Barcelona |
Start Year | 2012 |
Description | APPOSITE simulations |
Organisation | National Oceanic And Atmospheric Administration |
Department | Geophysical Fluid Dynamics Laboratory (GFDL) |
Country | United States |
Sector | Public |
PI Contribution | Collaboration with partners at multiple institutes to perform parallel simulations: ECMWF, Reading GFDL, Princeton MPI, Hamburg IC3, Barcelona |
Start Year | 2012 |
Description | Attendance at Arctic Circle Conference |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | Yes |
Type Of Presentation | keynote/invited speaker |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Awareness of our Arctic research within UK and international policy arena |
Year(s) Of Engagement Activity | 2014 |
Description | Climate Lab Book blog |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Editor of Climate Lab Book blog which receives around 4000 visits per month Figures from blog posts have appeared in Mail on Sunday, Economist magazine, US Senate hearing, BBC News at 6, BBC News at 10 & Newsnight, Guardian & numerous online publications |
Year(s) Of Engagement Activity | 2012,2013,2014,2015,2016,2017 |
URL | http://www.climate-lab-book.ac.uk |
Description | Gave oral evidence to House of Lords inquiry into the Arctic |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Oral and written evidence submitted to the inquiry Invited to attend Arctic Circle conference |
Year(s) Of Engagement Activity | 2014 |
Description | General media activities |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Media activity. Full list at URL below. |
Year(s) Of Engagement Activity | 2009,2010,2011,2012,2013,2014,2015,2016,2017 |
URL | http://www.met.reading.ac.uk/~ed/home/outreach.html |
Description | Sources of multi-decadal variability in Arctic sea ice extent. |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Media coverage |
Year(s) Of Engagement Activity | 2012 |
Description | Twitter feed |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | The APPOSITE project has an active twitter feed (@arcticpredict) with 729 followers (as of 06/02/2017) Ongoing engagement via the medium of twitter |
Year(s) Of Engagement Activity | 2012,2013,2014,2015,2016 |