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Dmitry Kiktev Hydrometcentre of Russia / Roshydromet

Dmitry Kiktev Hydrometcentre of Russia / Roshydromet. WWRP RDP/FDP FROST-2014 activities in 2011/2012 (FROST: Forecast and Reseach – Olympic Sochi Testbed). 16 April 2012, Moscow. Two clusters of «Sochi-2014» Olympic venues. Snow sports competitions. Ice sports competitions.

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Dmitry Kiktev Hydrometcentre of Russia / Roshydromet

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  1. Dmitry Kiktev Hydrometcentre of Russia / Roshydromet WWRP RDP/FDP FROST-2014 activities in 2011/2012(FROST: Forecast and Reseach – Olympic Sochi Testbed) 16 April 2012, Moscow

  2. Two clusters of «Sochi-2014» Olympic venues Snow sports competitions Ice sports competitions

  3. Goals of RDP/FDP FROST-2014: • To improve and exploit:– high-resolution deterministic mesoscale forecasts of meteorological conditions in winter complex terrain environment, including downscaled modeling; – regional meso-scale EPS (Ensemble Prediction System) forecast products in winter complex terrain environment; – nowcast systems of high impact weather phenomena (snow levels, wind, visibility, precipitation type and intensity) in complex terrain. • To improve the understanding of physics of high impact weather phenomena in the region; • To deliver deterministic and probabilistic forecasts in real time to Olympic weather forecasters and decision makers. • To assess benefits of forecast improvement (verification and societal impacts) As the project evolves these goals might be detailed.

  4. Project components: • Obsevations • Nowcasting • Deterministic NWP • Ensemble NWP • Data assimilation • Information Technologies • Training and understanding • Verification and Impact Assessments

  5. Observational network in the region of the Games None of practically realizable near-surface atmospheric monitoring networks can be representative enough given the complexity of the region and high Olympic demands. In situ observations are mostly concentrated along the coast. Vast sea area from one side and nearby mountains on another side of KrasnayaPolyana are data sparse areas. Nevertheless, today situation is substantially better than 1-2 years ago, and enhancement of the network will continue. + 48 near-surface automatic stations are installed to enhance the observational network in the region. + Data flow from new Doppler radar, wind and temperature/humidity profilers, and micro-rain radars will be available by the next winter; + More frequent sounding data at the nearest aerological stations will be available

  6. Current Instrumentul Setup: AMSs and Sensors Installed

  7. Current Instrumentul Setup: AMSs and Sensors Installed - II

  8. Current network of AMSs in the region of Sochi and its foreseen enhancement Designations: Red markers – Roshydromet’s AMSs; White – AMSs of sport venue owners; Yellow – AMSs already installed by Megafon company Green – AMSs to be installed by Megafon company

  9. Sensors installed for individual meteorological variables Snow Height Solid Precipitation Visibility Cloud Base

  10. Instrumentul Setup: Remote Sounding • Vaisala Doppler radar WRM200 was bought 1 year ago, but it is being installed on Akhun mountain in Sochi only now (considerable time has been spent to get endorsements). • Two profilers will be installed on mobile platform:- Temperature/Humidity – HATPRO (RPG GmBh, Germany)- Wind Profiler (Scintec Corporation, U.S.A.); • Scintec SFAS wind- and MTП-5 temperature profilers; • Micro Rain vertically pointing Radars (MRR-2, METEK Corp.) • Data flow – autumn 2012.

  11. Nowcasting Many issues should be tackled within this project component, e.g.: - Winter nowcasting of multi-weather elements (wind speed and wind gust, visibility, precipitation intensity and time); - Improvement of blending procedures for NWP and extrapolated observations for winter; - Radar retrieval of precipitation type and intensity; - Assessment and account for observational uncertainty. The project gives a chance to develop mesoscale NWP to fill the gap in 4-6 hour. Nowcasting potential of participating NWP models should be assessed for direct and post-processed (e.g. Kalman filter, 1-D model, MOS) model forecasts. Besides the meso-scale models, the specialized nowcasting systems are expected to be used in the project – ABOM, CARDS, INTW, STEPS, INCA, WSDDM, GRAPES.

  12. Numerical weather prediction • Complexity of Sochi region stimulates application of high-resolution modeling. • Key areas to be addressed: data assimilation; physics, validation and numerical challenges at high resolution; predictability and uncertainty. • High-resolution data assimilation is a necessary prerequisite for meso-scale forecasting. The remote sounding is the main source of meso-scale structures in the initial data for such a modeling. Potential input for assimilation: Doppler radars; Wind and temperature/humidity profilers; Satellite radiances (AMSU-A, AMSU-B, AVHRR, IASI, SSMIS); Satellite winds (AMV, ASCAT). • Convective-scale multi-model ensemble forecasting might be a new experience of Sochi-2014

  13. NWP component: progress and achivements in 2011/2012 FDP: in blue; RDP:in green

  14. NWP component: progress and achivements in 2011/2012 - II FDP: in blue; RDP:in green

  15. NWP component: Milestones for 2012/2013

  16. NWP component: Milestones for 2012/2013 - II FDP: in blue; RDP:in green

  17. NWP component: Milestones for 2012/2013 - III FDP: in blue; RDP:in green

  18. Project IT support • Project data storage with Internet-access is established; • Project web-site - http://frost2014.meteoinfo.ru (MAP D-Phase-like interface is being developed)

  19. Verification • Data storage with Internet-access is already in place; • More advanced data quality control is needed for observations; • Home-made tools, VERSUS, MET …; • As for SNOW-V10, it is of interest to quantify the added value of forecast refinement between: • Global model;- Regional model without and with its own data assimilation; - High-resolution model with and without data assimilation; - Post-processed model output (Kalman filter, MOS, 1D-model etc.);- Nowcasting (based on latest observations and blended with NWP). • Distributed verification activity ? • (Roshydromet–FMI (JWG on Verification Research))

  20. “- Forecasters do not always like probabilities (at any scale!) - End-users «hate» probabilities.” Andrea Montani, Michael Ttsyrulnikov (1st FROST-2014 meeting) • That’s funny, but the problem behind is very serious. It comes from misunderstanding and lack of training. • Training for Olympic forecasters is held on regular basis and participants are involved into provision of meteorological services for test sport events… • Despite this training is getting a crucial issue… • FROST-2014 is RDP/FDP… As the project has an FDP component, it must be an “end-to-end” project and include impact assessment component. First steps in this direction are tried...

  21. Thank you! http://frost2014.meteoinfo.ru

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