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

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Presentation on theme: "Rozinkina Inna, Kukanova Evgenia, Revokatova Anastasia, & Muravev Anatoly, Glebova Ekaterina."— Presentation transcript:

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

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

3 Regions of meteo-support 26.05.2016 3 Coastal cluster (Olympic Park) Mountain Cluster (Krasnaya Polyana ) Sochi Krasnaya polyana 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 Choice of classification (period 1/12/2012 – 20/03/2013) Project COST-733 - “Harmonisation and Applications of Weather Type Classifications for European regions“ Weusthoff T: 2011,Weather Type Classification at MeteoSwiss – Introduction of new automatic classifications schemes, Arbeitsberichte der MeteoSchweiz, vol. 235, 46 p Amount of days which couldn’t be ranged to a certain class Weusthoff,T:2011,WeatherTypeClassificationatMeteoSwiss–Introductionofnewautomaticclassifications schemes,ArbeitsberichtederMeteoSchweiz,vol.235,46p http://geo23.geo.uni-augsburg.de/cost733wiki

6 GWT27: 27 circulation types

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

8 Weather types in different months

9 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 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

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 without Weather types without heavy precipitation (<10mm): 2,6,8,10,11,12,13,18,22,27

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

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

15 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:http://cost733.met.no/ - 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 Typification of 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

21 460 - ski-jump, 628 м; 59 – bobsleigh, 701 м; 58 – bobsleigh, 835 м; 53 – snowboard, 1027 м; 62 – biathlon stadium, 1471 м Г. Аибга Mt. Aibga Krasnaya Polyana Black sea Mt. Aibga Krasnaya Polyana 7 АМS (at Olympic objects): 20 Feb. – 20 March 2 network meteo station (Mt. Aibga, Krasnaya Polyana): 1 Dec.-20 March South-East

22 1 – ski centre «Rosa Hutor»; 2 – Extreme-park – «Rosa Hutor»; 3 – bobsleigh centre; 4 – ski-jump; 5 – Complex for biathlon and cross-country skiing 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

23 , 1471 m 1027 m 835 m 701 m 628 m H 2 mm -Heights of stations

24 Ski-jump, 628 м Bobsleigh, 701 м Bobsleigh, 835 м Snowboard, 1027 biathlon stadium, 1471 м Ski-jump, 628 m-0,860,850,800,75 Bobsleigh, 701 m0,86-0,950.910,82 Bobsleigh, 835 m0,850,95-0,910,82 Snowboard 1027 m 0,800.910,91-0,81 biathlon stadium, 1471 m 0,750,82 0,81-

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

26 Features of precipitation regimes at different points Station H, m Geographic features Amounts feb – march 2013 Features Krasnaya Polyana 538 valley 217 Low correlation of amounts ski-jump, 628S - exp213 bobsleigh 701S - exp219 bobsleigh 835S - exp248 snowboard 1027S - exp241 biathlon stadium 1471N - exp207 Slightly less Mt. Aibga 2225S – exp, top79 Significantly less Krasnaya Polyana Mt. Aibga Krasnaya Polyana

27 ASSESSMENT OF COSMO-RU2 PRECIPITATION FORECAST  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

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

29 Ski-jump, 628 м Bobsle igh, 701 м Ski- jump, 800 м Bobsle igh, 835 м Snowboard, 1027 м Freestyle, 1077м Biathlon stadium, 1471 м Ski-jump, 628 м -0.760.920.790.420.330.31 Bobsleigh, 701 м 0.76-0.820.990.380.320.18 Ski-jump, 800 м 0.920.82-0.860.380.310.2 Bobsleigh, 835 м 0.790.990.86-0.40.340.2 Snowboard, 1027 м 0.420.38 0.4-0.20.45 Freestyle, 1077м 0.330.320.310.340.2-0.44 Biathlon stadium, 1471 м 0.310.180.2 0.450.44- 20 Feb. – 20 March

30 < 100 m< 200 m< 500 m< 1000 m >10 000 Ski-jump, 628 m 041112 0 Bobsleigh, 701 m 7121415 4 Ski-jump, 800 m 7111516 5 Bobsleigh, 835 m 7121415 4 Snowboard, 1027 m 8111214 4 Freestyle, 1077 m 7121516 4 Biathlon stadium, 1471 m 91216185

31 VERSUS

32 Temperature under north wind

33 Temperature assessment under different wind directions East South South-westWest

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

35 Temperature forecast is more exact under solid cloud cover; diurnal variation is underestimated by 2 о с Temperature forecast with cloudy weather

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

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

38 Wind NESE nightdaynightdaynightday Т2м +0.5 о С+2 о С+0.5..1 о С+2.5 о С0оС0оС Тd2м -0.5… -1 о С0…-1 о С-1..-1.5 о С  V  -1.5 m/s-0.5 … -1.5 m/s-2…-2.5 m/s VV - 57..67 о 0о0о +60 о - 50 …60 о Wind SSWW nightdaynightdaynightday Т2м +0.5 о С+2.5 о С0оС0оС +0.5 о С- 1 о С Тd2м -1.5…-2.5 о С-1… -2 о С-0.5… -1 о С  V  -2 … 2.5 m/s-1.5 … 2 m/s VV -70 о 0о0о - 90 о … 110 о - 60 о … 70 о - 80 о …130 о 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

40

41 1471 m 1027 m 835 m 701 m 628 mH 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 1-2 о С  Model wind is rotated clockwise relatively real wind by 30 - 120 о  Successful forecast of pressure with precision up to 1hPа Other results

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