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Rozinkina Inna, Kukanova Evgenia, Revokatova Anastasia , & Muravev Anatoly, Glebova Ekaterina

Classification of large-scale processes and local forecasting for objects of mountain cluster in Sochi Olympic region. Rozinkina Inna, Kukanova Evgenia, Revokatova Anastasia , & Muravev Anatoly, Glebova Ekaterina. Large-scale approach (COST-733) Microclimatic analysis Verification

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Rozinkina Inna, Kukanova Evgenia, Revokatova Anastasia , & Muravev Anatoly, Glebova Ekaterina

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  1. Classification of large-scale processes and local forecasting for objects of mountain clusterin Sochi Olympic region Rozinkina Inna,Kukanova Evgenia, Revokatova Anastasia, & Muravev Anatoly, Glebova Ekaterina

  2. Large-scale approach (COST-733) Microclimatic analysis Verification Conclusions Subject

  3. Regions of meteo-support Mountain Cluster (Krasnaya Polyana) Krasnaya polyana Sochi Coastal cluster (Olympic Park) In mountain Cluster all venues are on the slopes

  4. Motivation: Forecasting for Mountain cluster based on microclimatic analysis methods and classification of large-scale processes Recommendations for forecasters

  5. • Weusthoff , T : 2011 , Weather Type Classification at MeteoSwiss – Introduction of new classifications automatic Choice of classification (period 1/12/2012 – 20/03/2013) Project COST-733 - “Harmonisation and Applications of Weather Type Classifications for European regions“ WeusthoffT:2011,WeatherTypeClassificationatMeteoSwiss–Introductionofnew automaticclassificationsschemes,ArbeitsberichtederMeteoSchweiz,vol.235,46p Amount of days which couldn’t be rangedto a certain class http://geo23.geo.uni-augsburg.de/cost733wiki schemes, Arbeitsberichte der MeteoSchweiz , vol . 235 , 46 p

  6. GWT27: 27 circulation types

  7. Period: 1.12.2012-20.03.2013 The most often types: 1, 4, 14, 16, 17, 23, 24, 26 № 4

  8. Weather types in different months

  9. Type №4 • Periphery of cyclone. • Atmospheric front alter direction because of the mountains. • Front can stop between mountains and does not change location during several days • When it is type 4, it is 50% that heavy precipitation • Precipitation under type 4 were 14 times (from 21) • The heaviest precipitation during this winter were observed under 4 type • Weather type 4 was observed often then others

  10. Real example of type №4 March, 13 Precipitation - 40 mm/day COSMO-Ru2 forecast Cold flux from the north -> intensification of atmospheric fronts -> interaction with mountains -> low speed -> fronts stop in the valley -> heavy precipitation

  11. Precipitation and weather types GWT_27

  12. Weather types withoutheavy precipitation (<10mm): 2,6,8,10,11,12,13,18,22,27

  13. Weather types withheavy precipitation (>10mm): 1,4,7,9,14,16,17,19,25

  14. Deference (gradient) between continental and coastal temperature Coastal (sea) air temperature Continental air temperature

  15. Dependence of precipitation on sea and continental temperature difference Dependence of precipitation on sea and continental temperature difference

  16. Additional investigations of COST-733 • Program software from http://cost733.met.no/ was used for Europe and Western Siberia in order to: • - obtain new types of circulation • - find out how discrimination to different types (for temperature and precipitation) statistically significant. How temperature and precipitation distribution under weather type differ from mean values for whole period (1957-2013).

  17. Typificationof large-scale processes by k-mean distance method Period: December – March, resolution 1.5x1.5 degrees 01.09.1957 – 31.08.2002 ERA-40 01.09.2002 – 31.03.2013 ERA Interim Amount of weather type – 20 Domain of typification takes into account main synoptic processes

  18. Calculation results • Set of circulation types (map of ground pressure) • List of dates for whole period (1957-2013) with weather types (from 1 to 20) Inter annual frequency of different types doesn’t show significant trends for this period

  19. Discrimination of different weather types How distribution of temperature and precipitation under different weather types (20) differ from mean values during period (1957-2013)? Statistical criterion of Kolmogorov-Smirnov shows how different two data distributions from each other We found out that for Sochi region only 4 types differ from “climate” in terms of precipitation (there is a tendency to dry or wet weather). Under others 16 types precipitations with big variety of intensity can be observed 11 types differ from “climate” in terms of temperature

  20. Microclimatic characteristics identified by observations of SOCHI 2014 network

  21. 7 АМS (at Olympic objects): 20 Feb. – 20 March2 network meteo station (Mt. Aibga, Krasnaya Polyana): 1 Dec.-20 March Black sea Г. Аибга Mt. Aibga Mt. Aibga South-East Krasnaya Polyana Krasnaya Polyana Krasnaya Polyana 460 - ski-jump, 628 м; 59 – bobsleigh, 701 м; 58 – bobsleigh, 835 м; 53 – snowboard, 1027 м; 62 – biathlon stadium, 1471 м

  22. Location of Olympic objects Valley is protected from the large-scale wind streams, the height of venues (800 – 1500 m) are close to the top of cloudiness The resolution of COSMO-2 is not sufficient for reproducing the local values of critical parameters - the additional techniques are necessary 1 – ski centre«Rosa Hutor»; 2 – Extreme-park – «Rosa Hutor»; 3 – bobsleigh centre; 4 – ski-jump; 5 – Complex for biathlon and cross-country skiing

  23. H 1471 m 1027 m 835 m 701 m 628 m Precipitation at different Olympic objects20 Feb. – 20 March , • Heights • of stations 2 mm

  24. Correlationcoefficients for precipitation series at different heights

  25. Precipitation intensity 20 Feb. – 20 March Stations codes: 460 - ski-jump, 628 m; 59– bobsleigh, 701 m; 58– bobsleigh, 835 m; 53 – snowboard, 1027 m; 62 – biathlon stadium, 1471 m 31107 – KrasnayaPolyana 37109 – Mt. Aibga mm

  26. Features of precipitation regimes at different points Mt. Aibga Krasnaya Polyana Krasnaya Polyana Krasnaya Polyana

  27. From 20 Feb to 20 March 2013 • 00 and 06 model runs (will be used by synoptic in Sochi) • 5 АМS и 2 network stations • Only 3 cases when forecast was not successful. (2 times model predicted precipitation, but it was not, 1 time precipitation was not predicted but was observed). • Intensity of precipitation is overestimated by 1,5 – 2 times at 5 days of this period • High quality of COSMO-Ru2 precipitation forecast • Tendency to the overestimation ASSESSMENT OF COSMO-RU2 PRECIPITATION FORECAST

  28. Wind direction at Olympic objects bobsleigh, 701 м bobsleigh, 835 м snowboard, 1027 м ski-jump, 628 м ski-jump, 628 м ski-jump, 800 м

  29. Correlationcoefficients for minimum visibility at different heights 20 Feb. – 20 March

  30. Amount of days with different visibility

  31. Verification ofCOSMO-Ru2 VERSUS

  32. Temperature under north wind

  33. Temperature assessment under different wind directions South East South-west West

  34. Temperature Calculated in Met 2011-2012 Dec - March 2013, January - March

  35. Temperature forecast with cloudy weather Temperature forecast is more exact under solidcloudcover;diurnalvariation is underestimated by 2ос

  36. WIND assessment High speed (>7 m/s) Low speed (<5 m/s) Middle speed (5-7 m/s) Low speed Wind turned clockwise relatively to the real wind by 70 - 90о Wind speed overestimated by 1-2 m/s

  37. WIND, middle speed WIND, high speed Overestimation of wind speed by 4-5 m/s Overestimation of wind speed by 2-3 m/s Very stable assessment! Turned clockwise relatively to the real wind by 30 - 50о Turned diversely to the real wind by 30 - 40о

  38. Practical Proposals of values for Correction of COSMO-Ru2 Forecasts under different wind directions

  39. Some practical recommendations for forecasters in mountain cluster are obtained: - Microclimatic properties of wind, visibility and precipitation - Large- scale Synoptic situations which lead to heavy precipitation - Estimates of model forecast of temperature, dewpoint temperature, precipitation, wind speed and wind direction - Corrections coefficients to model forecast with dependence of weather conditions were defined Main Results:

  40. Thank you for your attention!

  41. H 1471 m 1027 m 835 m 701 m 628 m Time series of visibility Stations codes: 460 - ski-jump, 628 m; 59 – bobsleigh, 701 m; 58 – bobsleigh, 835 m; 53 – snowboard, 1027 m; 62 – biathlon stadium, 1471 m; 31107 – Krasnaya Polyana; 37109 – Mt. Aibga

  42. Tendency to the overestimation of dewpoint temperature by 1-2оС • Model wind is rotated clockwise relatively real wind by 30 - 120о • Successful forecast of pressure with precision up to 1hPа Other results

  43. - Attempt to Implementation of weather Types of COST 733: 2 approaches - Some microclimatic characteristics identified by observations of SOCHI 2014 network - Some practical results of conditional verification Outlook

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