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 Global Integrated Polar Prediction System (GIPPS)  The WWRP Polar Prediction Project (PPP)  The WCRP Polar Climate Predictability Initiative (PCPI)

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Presentation on theme: " Global Integrated Polar Prediction System (GIPPS)  The WWRP Polar Prediction Project (PPP)  The WCRP Polar Climate Predictability Initiative (PCPI)"— Presentation transcript:

1  Global Integrated Polar Prediction System (GIPPS)  The WWRP Polar Prediction Project (PPP)  The WCRP Polar Climate Predictability Initiative (PCPI)  Year of Polar Prediction (YOPP)  MOSAiC Thanks to Thomas Jung, Chair of the WWRP Polar Prediction Project

2 WMO GIPPS  Global Integrated Polar Prediction System Global: International effort and poles have global influences Integrated: Interconnection between systems and system will be integrated (research, observations and services) Polar prediction will be central  Three time scales Short-term prediction (hours to seasonal, PPP) Medium-term predictability (seasonal to decadal, PCPI) Long-term projection of ice mass balance and sea level (centuries, SLR, cryo…)

3 The WWRP Polar Prediction Project (2013-2022) 3 Mission: „Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hourly to seasonal.“

4 Research areas Source: PPP Implementation Plan

5 Science Goals: 1) Improve the understanding of the requirements for, and evaluate the benefits of, enhanced prediction information and services in polar regions 2) Establish and apply verification methods appropriate for polar regions 3) Provide guidance on optimizing polar observing systems, and coordinate additional observations to support modelling and verification 4) Improve representation of key processes in models of the polar atmosphere, land, ocean and cryosphere 5) Develop data assimilation systems that account for the unique characteristics of polar regions 6) Develop and exploit ensemble prediction systems with appropriate representation of initial condition and model uncertainty for polar regions 7) Determine predictability and identify key sources of forecast errors in polar regions 8) Improve knowledge of two-way linkages between polar and lower latitudes, and their implications for global prediction

6 Flagship PPP themes  Sea ice prediction Explore predictability Develop coupled prediction systems  Linkages between polar regions and lower-latitudes Determine mechanisms and strengths Implications for predictions in middle latitudes International workshop on polar-lower latitude linkages and their role in weather and climate prediction (Barcelona, 10-12 December 2014, PPP is one of sponsors)  Improved availability of observations from polar regions  The Year of Polar Prediction (YOPP)

7 WCRP Polar Climate Predictability Initiative (PCPI, 2010 - …) WMO GIPPS (G lobal I ntegrated P olar P rediction S ystem ) research on ice sheets and sea level WWRP Polar Prediction Project (PPP) Regional Grand Challenge PCPI Initiatives Cryosphere Grand Challenge Leads: Cecilia Bitz & Ted Shepherd Understand past polar climate variations, (palaeo, up to 100 years) Assess reanalyses in polar regions Understand polar climate predictability on seasonal to decadal timescales Assess perfor- mance of CMIP5 models in polar regions Model error Understand how jets and non- zonal circulation couple to the rest of the climate system in the Southern Hemisphere Days -> Months -> Years -> Decades -> Centuries

8 The Year of Polar Prediction  Comprehensive observational snapshot In situ and satellite data Observing system design (data denial experiments) Supersites (model grid boxes  MOSAiC)  Model development (e.g. Transpose-CMIP)  Community data sets (reforecasts, special archiving etc.)  Frontier experiments (e.g. high-resolution modelling)  Draft YOPP Implementation Plan

9 The Year of Polar Prediction Preparation Phase 2013 to mid-2017 Consolidation Phase mid-2019 to 2022 Community engagement Liaising with funders Alignment with other pl anned activities Preparatory research Summer school Workshops Development of implementation plan Intensive observing periods Dedicated model experiments Research into use & value of forecasts Intensive verification effort Model developments Dedicated reanalyses Operational implementation YOPP publications Data denial experiments Preparation Phase 2013 to mid-2017 YOPP mid- 2017 to mid- 2019 Consolidation Phase mid- 2019 to 2022 YOPP conference Summer school

10 MOSAiC Multidisciplinary drifting Observatory for the Study of Arctic Climate Multi-year, coordinated, and comprehensive measurements, extending from the atmosphere through the sea-ice and into the ocean, in the central Arctic Basin to provide a process- level understanding of the changing central Arctic climate system that will contribute towards improved modeling of Arctic climate and weather, and prediction of Arctic sea-ice concentrations.

11 Previous experiences within the Arctic ice pack: Russian drifting stations SHEBA Shorter-term campaigns Many disciplinary obs. Some inter-disciplinary obs. Each of these has key limitations: Length of time Comprehensiveness Spatial context Not in the “new” Arctic Russian drifting station SHEBA Building off the past

12 What: 1)Heavily instrumented, manned, ship-based, Arctic Ocean observatory for comprehensive, coordinated observations of the Arctic atmosphere, cryosphere, and ocean. 2)Network of spatial measurements to provide context and variability (buoys, gliders, UAVs, aircraft, ships, satellites, ice stations). 3)Coordinated modeling activities at many scales from process-study to regional climate models. MOSAiC Who: Coordinated through IASC International participation (e.g. US, Germany, Sweden, France, Russia, Finland, Norway, Canada, Korea, Japan, China,….) International infrastructure Synchronized international funding Transpolar Drift track Objectives: Observe full sea-ice “life cycle,” starting in new ice Trajectory that will last for at least 1 year Observe an understudied region

13 Measurements Micro- meteorology gases, aerosols, clouds & precip. atmospheric profiling, BL, & dynamics leads & ocean surface ocean state, profiling, & dynamics aircraft + UASs ocean and ice bio/chem buoys, AUVs, gliders ice profiling, thermodynamics, mass budgets surface energy budget

14 Conclusions: 2017-2019: unique opportunity to study climate predictability and improve polar predictions through a combination of PPP, PCPI, YOPP, and MOSAiC. Situation similar to pre-TOGA for research on ENSO. Need engagement of all potential contributors. Need for a satellite snapshot for all key polar variables Need oceanographic data exchange to enable coupled Arctic data assimilation.


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