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.

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.

Publications

10 25 50
 
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