1. Report on the WWRP, THORPEX, WCRP Workshop “Improvement of Weather and Environmental Prediction in Polar Regions” (6 to 8 October 2010, Oslo, Norway) Gilbert Brunet WWRP/JSC Chair WWRP/THORPEX, Kick off meeting of the Polar Prediction Research Project (Geneva, 30 November – 1 December 2011)

3. 1. Background At its 15th session (November 2009), the WMO Commission of Atmospheric Sciences (CAS) recommended, as a legacy of the International Polar Year (IPY) to: Establish a THORPEX Polar Research project to: – improve understanding of the impact of polar processes on polar weather; – the assimilation of data in Polar Regions; – and the prediction of high impact weather over Polar Regions.

4. The Executive Council Panel of Experts on Polar Observations, Research, and Services (EC- PORS) recommended that efforts be made to further polar prediction for weather and climate and to extend efforts to snow, ice, carbon, and ecosystem modelling and analysis. This requires involvement from: – World Weather Research Programme (WWRP), including THORPEX, – the Global Atmospheric Watch (GAW), – and the World Climate Research Programme (WCRP) and support from WMO Members.

5. Improving Polar Predictions – General Recommendations Verification – formal inter-comparison of polar predictions (pole-wards of 60 o N and 60 o S) using the existing WMO procedures and, if necessary, the adoption of new metrics for these comparisons need to be initiated; – strengthening of verification activity utilizing operational and research data bases such as the TIGGE data bases is needed. Data Assimilation and Observation – the establishment of the utility of existing surface based and satellite observations through data assimilation experiments (e.g. CONCORDIASI project); – “data mining” to catalogue existing databases and reports – this may require the establishment (or nomination) of a few archive centres to manage IPY data and data from past campaigns; – there is a requirement for new observations for the Polar Regions.

6. General Recommendations (ctd.) Predictability and Physical and Dynamical Processes – There is an urgent need for concerted physical process studies which will need new field campaigns; – We need to establish well thought out numerical experiments with coupled models in the Polar Regions in collaboration with WCRP (CMIP5, SPARC); – More efforts need to focus on research and development for coupled atmosphere–hydrological–cryosphere–surface modelling and observation.

7. The Gulf of St. Lawrence (GSL) Coupled Atmosphere-Ice-Ocean Forecasting System -5°C -15°C -25°C A dynamic representation of sea surface conditions improves the meteorological forecast locally; Time-evolving ice cover in coupled model allows vast stretches of ice-free water to open up, buffering atmospheric temperatures; Use of coupled model results in significantly improved forecasts all around the GSL; Demonstrates importance of air- sea-ice coupling even for short- range weather forecasts; Next step: implementation in the Canadian Arctic (METAREA).

8. Scientific Challenges Assimilation must rely more on the use of satellites. – most radiative channels used for satellite retrieval are for the free atmosphere, while near-surface and lower troposphere coverage is lacking; – the satellite data is more difficult to use over land and sea-ice than over the ocean due to snow covered (cold) surfaces; – when using data from microwave channels accurate values for sea-ice emissivity, penetration depth (into snow and ice) of microwave radiation, and a realistic first guess of surface temperature have all to be taken into account; – There is a close link between the microphysical properties of the NWP model and successful satellite data retrieval.

9. Scientific Challenges (ctd.) The underlying surface and the need for surface–sea-ice coupled models – Need for an accurate and detailed description of the underlying surface in terms of ice, snow, leads, polynyas and tides and sea-ice characteristics and sea surface temperature; – There is a lack of observations and an understanding of the physical processes in Polar regions; – Other issues that were recognized as important for NWP are how to initialize (snow analysis) and how to treat blowing snow; – There is a need for detailed process studies and careful parameterizations supported by observations.

10. Scientific Challenges (ctd.) Planetary Boundary Layer (PBL) parameterization including PBL clouds The Arctic offer significant challenges relative to the lower latitudes – semi-permanent Arctic inversion ( NB: Most models have problems predicting the lowest level temperatures over the continent; also winds at 300hPa and at the surface.); – very frequent occurrence of clouds peaking at more than 90% in summer ; – PBL schemes need to consider the presence of clouds, while in order to solve the polar cloud issue, one has to work on cross-cutting issues linked to the PBL, surface, microphysics, and radiation, as these processes are closely linked; – to much stress (turbulence) in stable boundary layers in existing schemes; – the lack of a spectral gap significantly complicates the parameterization problem as stability functions may have to depend on model resolution; – our fundamental knowledge of cloud processes is highly limited, and we lack key observations to constrain even highly simplified cloud parameterizations; – it is currently not known what determines the phase and mixture of clouds.

11. Low Visibility and Precipitation in the Arctic Goals: Using NWP models, surface observations, and satellites to better detect and predict low visibility conditions associated with ice fog, freezing fog, and precipitation Impacts: Aviation, weather, marine and land transport, and climate. Ice fog in Yellowknife, NWT, FRAM project Icing, turbulence, radiation sensors POSS prec. sensorFrost on particle sensor due to ice fog, Barrow AL Ice crystals during a light snow in Yellowknife (taken by Canon camera) Ice fog from PMWR at -35C in Yellowknife Ice fog from MODIS satellite in Yellowknife GCIP ice particle spectra GCIP ice sensor YK FRAM instrument set for fog, precip, radiation, turbulence, vis etc. MRR radar FD12P Vis

12. Establishment of an IPY Legacy Project This legacy project should be based on a few NWP internationally coordinated polar initiatives (new or existing); Additionally support for the observational component would be needed from: (GOS/WWW), (GAW), (GOOS), (WHYCOS), (GTOS – hydrological cycle parameters (GTN-H)), GCOS Terrestrial Network for Permafrost (GTN-P)), GCOS Terrestrial Network for Glaciers (GTN-G, – parameters of the cryosphere. A new IPY legacy project should tap into the scientific and human capacity of the National Meteorological and Hydrological Services (NMHSs) who have an interest in scientific, societal, and economic applications for Polar Regions and should include the participation of the WWRP (SERA, MFRWG, JVWG, NWG), THORPEX, and the WCRP (SPARC, CLIC, SOLAS) communities of scientists;

13. High Resolution Deterministic Prediction System at Environment Canada GEM (Global Environmental Multiscale) model, limited area model (LAM) configuration; 1 LAM grid,  x = 2.5 km; 24-36 hour predictions, 2-4 runs per day; Full data assimilation system of atmospheric measurements; Land data assimilation system (250 m) for detailed initial conditions of surface fields; Associated ensemble prediction system to provide forecast uncertainties.  By 2015, Environment Canada will have complete coverage over Canada by an unprecedented convection permitting and non- hydrostatic high-resolution numerical weather prediction system

14. Polar Prediction Project The Report from the Workshop on “Improvement of Weather and Environmental Prediction in Polar Regions” (Met No Oslo, 6 to 8 October 2010) has been published to the web http://www.wmo.int/pages/prog/arep/wwrp/new/documents/Polar_NWP_Meeting_ Outcomes_FINAL.pdfhttp://www.wmo.int/pages/prog/arep/wwrp/new/documents/Polar_NWP_Meeting_ Outcomes_FINAL.pdf; Three forecast prediction ranges are of interest: – short-term regional forecasts (one hour to 48 hours); – medium-range forecasts (one day to two weeks); – sub-seasonal to one season forecasts. It was clear from the workshop discussions on “gaps” that many of the problems are common to all prediction systems (including climate) whatever the range – notably, problems with the parameterization of atmospheric, oceanic, and land- surface physical processes. – Example: Climate models may under-predict the rate of Arctic warming because their boundary layers are too stable  12

15. World Meteorological Congress WWRP World Meteorological Organization 2011 Congress Polar Prediction project – “Congress acknowledged the success of the ten projects of the International Polar Year THORPEX cluster, and supported the CAS recommendation that, as a legacy of the IPY, a THORPEX Polar Research project be established to improve the understanding of the impact of high impact weather over Polar Regions. Congress also emphasized the need to have an adequate observational and telecommunication network for the Polar Regions in order to provide the relevant high impact weather services for the region. “ “Congress strongly urged all those concerned to ensure that such a Polar Prediction Research project is established in support of, inter alia, the Global Framework for Climate Services. Furthermore, the EC-PORS, at its Second Session in Hobart in October 2010, agreed to the concept of a major decadal initiative to develop a Polar Prediction System (Global Integrated Polar Prediction System - GIPPS). Congress recognized the importance of effective coordination between these various initiatives, and invited Members to contribute as appropriate. “ Sub-seasonal to Seasonal Prediction – “Congress noted that the JSCs of the WWRP and the JSC for WCRP and WWRP/THORPEX ICSC set up an appropriate collaborative structure to carry out and international research initiative on sub-seasonal to seasonal forecasting. This initiative should be closely coordinated with the CBS infrastructure for long-range forecasting and with the future developments of climate service delivery and the Global Framework for Climate Services. “ “Congress was pleased to note that the WWRP-THORPEX / WCRP workshop on “Sub-seasonal to seasonal prediction” (Exeter, December 2010) had recommended the establishment of a Panel/Project for Sub-seasonal Prediction Research and Applications - Panel members being drawn from WWRP- THORPEX, WCRP, CBS, CCl, JCOMM, CHy, CAS and CAgM and their relevant programme bodies. “

16. Polar Prediction Contd., This project will require a Steering Group (consisting of members with scientific and operational expertise and representatives of the user community). The first task for the Steering Group (supported by a WMO consultant) will be the preparation of an Implementation Plan, which includes estimates of resources and a strategy for the coordination of polar prediction research; If the plan is well received by the community, and if the YOTC model is followed, a Project Office should be established at an institution with a major interest in polar prediction;  14

17. Polar Prediction Initiative Steering Committee Membership 1.Thomas Jung (Chair, AWI, Germany) 2.Peter Bauer (ECMWF) 3.David Bromwich (Byrd Polar Research Centre, USA) 4.Trond Iversen (Norwegian Met Service, Norway) 5.Greg Smith (Environment Canada, Canada) 6.Pertti Nurmi (Finish Meteorological Institute, Finland) 7.Ian Renfew (University of East Anglia, UK) 8.Chris Fairall (NOAA/ESRL, USA) 9.SERA Expert (TBD) 10.Mikhail Tolstykh (HRC, Russia) 11. Data Assimilation Expert (TBD) Secretary Neil Gordon (Secretary, National Weather Service, New Zealand)

18. Improving Polar Predictions – Scientific Challenges Thank you Merci