1. The WWRP Polar Prediction Project (2013-2022)
Thomas Jung
Chair of the WWRP Polar Prediction Project
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
10 January 2014

2. Arctic Climate Change
Climate change has moved in the polar regions into the focus: Opportunities and risks (see next slide)
Northern Sea Route:
Used by 34 (50) vessels in 2011 (2012)
Estimates suggest that cargo carried through the NSR will increase by a factor of 80 by 2020
NSR: reduction of 22% from Rotterdam to Shanghai
NWP: reduction of 15% from Rotterdam to Shanghai

3. Opportunities and Risks
Some statements from the report:
The Arctic is likely to attract substantial investment over the coming decade ($100 bn)
The environmental consequences of disasters in the Arctic are likely to be worse than in other regions
Significant knowledge gaps across the Arctic need to be closed urgently

4. Increasing interest in polar regions
Akademik Shokalskiy, Dec 2013, Antarctica
Recent example of ships getting stuck in sea ice in the Antarctic. Not necessarily only climate change, Tourims and research activities are playing an increasingly important role.
Snowdragon, Dec 2013, Antarctica

5. PPP Mission Statement
„Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hourly to seasonal“
An important addition:
„This constitutes the hourly to seasonal research component of the WMO Global Integrated Polar Prediction System (GIPPS)“

6. The WWRP-PPP Steering Group
Thomas Jung (chair)
Peter Bauer
David Bromwich
Paco Doblas-Reyes
Chris Fairall
Marika Holland
Trond Iversen
Brian Mills
Pertti Nurmi
Don Perovich
Phil Reid
Ian Renfrew
Gregory Smith
Gunilla Svensson
Mikhail Tolstykh
SG4, Boulder, 1-3 October 2013
Jonny Day (APECS liasion)
Neil Gordon (WMO consultant)

7. International Coordination Office for Polar Prediction
Sponsored by AWI
Website is available
Support PPP activities and ensure coordination with other activities, especially PCPI

8. WWRP-PPP Plans Available from the ICO website
Implementation Plan is recommended

9. Research Areas Service-oriented Research Underpinning Research
Societal and Economic Research Applications (SERA)
Verification
Service-oriented Research
Predictability and Diagnostics
Teleconnections
Underpinning Research
Data Assimilation
Ensemble Forecasting
Modelling
Observations
Forecasting System Research

10. Tropical vs Arctic Atmosphere
Tropical Ocean
Arctic Ocean
Mean tendencies. In the long-term and without model drift the dynamical and physical tendencies balance each other. In the tropical free atmosphere there are a number of processes contributing significantly to the balance; In the polar region teh inflow of mild air from the mid-laitudes is balanced by radiative cooling. The Arctic PBL is more complicated.
Further reading: Rodwell and Jung, Q. J. R. Meteorol. Soc. 134: 1479–1497 (2008)
Mean Temperature Tendency (K/day)
Mean Temperature Tendency (K/day)
ECMWF model
6-hourly initial tendencies
120 forecasts (DJF )
Serrar and Jung (AWI)

11. Tropical vs Arctic Atmoshere
Tropical Ocean
Arctic Ocean
Large value imply that the respective scheme is very active. Dramatic differences between the Arctic and the tropics are apparent.
StDev Temperature Tendency (K/day)
StDev Temperature Tendency (K/day)
Serrar and Jung (AWI)

12. Observations: Data Coverage
All conventional data that entered the ECMWF analysis on 1 January 2012
Synop, AIREP, DRIBU, TEMP and PILOT
Polar data coverage of conventional observations in the ECMWF operational analysis on 1 January 2012
P. Bauer (ECMWF)

13. The Role of Sea Ice in Weather Prediction
T2m Difference: Observed Minus Persisted Sea Ice
Background: One set of 10-day weather forecasts has been run with observed sea ice (in hindcast mode) and the other with persistet sea ice. Shown is the mean difference for October 2011 in 2m temperature between the run with observed and persisted (that‘s what is done operationally at ECMWF) SST. The effect of growing sea ice has already a noticable effect on T2m after a few days. (We need coupled models for polar weather prediction)
P. Bauer (ECMWF)

14. Mean September sea ice concentrations (1979-2007)
Sea ice prediction
Mean September sea ice concentrations ( )
“Finally the wind has turned and a crack in the ice has developed which allows us to move slowly northward.“ (Captain of the Akademik Shokalskiy)
This is a snapshot of sea ice thickness from a high-resolution integration with a sea ice-ocean model. Once can clearly see cracks (leads) in the ice which have some resemblence with what is seen in satellite data. It will be important to validate these models and establish the predictability of leads and pressure ridges.
4km resolution, Simulation desribed in Nguyen et al (2012) and Rignot et al. (2012)

15. Role of the Arctic for weather prediction
MSLP DJF D+10-D+14
MSLP MAM D+10-D+14
MSLP JJA D+10-D+14
MSLP SON D+10-D+14
Change in MSLP forecast error for day 10 to day 14 forecasts when the Arctic atmosphere (north of 75N) is relaxed to observed data. Results are based on large large number of forecasts.
Take home messages:
Strongest mid-latitude influence over eastern Europe, Asia and North America. In summer the Arctic influence on the mid-latitudes appears to be weakest.
Further reading: Jung et al. (2010). Diagnosing the Origin of Extended-Range Forecast Errors. Mon Wea Rev
Jung, Kasper, Semmler and Serrar (AWI)

16. PPP Flagship Activities
Sea ice prediction
Explore predictability
Develop prediction systems
Linkages between polar regions and lower-latitudes
Determine mechanisms and strengths
Implications for predictions in the mid-latitudes
The Year of Polar Prediction (YOPP)

17. Year of Polar Prediction (YOPP)
Aims:
Intensive observational and modelling period to advance polar prediction capabilities
Research into forecast-stakeholder interaction
Enhanced verification
Education of students and early career scientists (APECS)

18. Year of Polar Prediction (YOPP)
YOPP Implementation plan:
Draft YOPP Implementation Plan available via
WGSIP is listed on page 12/13 as a key partner.
Comments on the Plan welcome, including:
What may be missing
How best we can ensure WGSIP involvement in achieving the objectives of the Plan
Send any comments to by the end of April 2014.

19. YOPP: Time line Community engagement
Align with other planned activities
Preparatory experimentation
Prepare observational and modelling strategy
Develop implementation plan
Summer school
Liaise with funders
...
Intensive observing periods
Dedicated model experiments
Research into the use and value of forecasts
Intensive verification effort
...
Data denial experiments
Model development
Dedicated reanalyses
Operational implementation
YOPP publications
...

20. Upcoming meetings
International workshop on polar-lower latitude linkages and their role in weather and climate prediction:
Barcelona December 2014.
Keynote talks and breakout groups, with the aim of drafting a roadmap of the research on polar/nonpolar linkages in a prediction context.
Sponsored by WCRP, WWRP, GFCS, European Commission, EGU.
By invitation only. Please, express your interest to
There will be a dedicated session on polar prediction.

21. Summary Polar prediction is a topic of increasing importance
Decision making in the high-latitudes
Implications for the lower-latitudes
PPP promotes research in polar prediction
PPP also promotes research into the use and value of polar predictions in decision making
PPP has a strong educational component
PPP flagship themes
Sea ice prediction
Linkages between polar and non-polar regions