Purposes:•Classify synoptic situations associated to various types of floods
•Assess the changes of synoptical conditions favorable for inundations in a changing climate.
Types of floods:Storm surgesWater-flowIce-jam
Areas:•Baltic sea•Black sea•Azov sea•Caspian sea•Barents sea
Method:Synoptic frontal analysis is applied
DATAData from GIS-Meteo system is used (since 1997). Time resolution – 3 hoursincludes:•SLP, •geopotential at all pressure levels (1000-10 hPa)•Precipitation•Cloudiness•temperature at 2m and pressure levels•Data of radiolocation•Wind speed and direction
Neva. February 2005 7.01.2005 12 GMT
H500 Surface map
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Large depression located to the north-west of St-Petersburg
Novorossiysk 7-9 December 2002Surface map
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Black sea area
Common predictor – intensive frontal zone
Pechora June 2008Surface map
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Frontal zone expanded in north-south direction, positive temperature in river source and negative temperature – in the river mouth
Initial idea – classify the synoptical situations associated with floods, Assess the changes of probability of these situations in a changing climate. Not possible as the large variability of situations resulting in the same type of flood exists.
Classification of synoptical situations for all floods
Identification of potential predictors – meteorological factors characteristics of all cases of specific flood type
Ice-jam –large zonal frontal zone expanding in north-south direction, temperature jumps, precipitations fall conditions, wind direction in the mouth of river etc Storm surges trajectories of depressions, wind speed and wind direction, duration of forcing Water flow – the main factor abundant precipitation No unified scheme of synoptic situation, but the intensive frontal zone is always presented
Temperature gradient – approximation of frontal
zone probability of gradient exceeding some
threshold for modern and future climate
Difificult to estimate the influence of climate changes, too many influencing factors which are not adequately represented in climate models
Possible to estimate the influence of climate changes, several factors should be included – current work
Estimated in climate model
Model - MPI-ECHAM5 (Max Planck Institute for Meteorology, Hamburg, Germany)
Predictor - Probability of intensive frontal zone
Number of cases
1961-1980 1981-2000 2046-2065
Year549 (7,5%) 638 (8,7%) 461 (6,3%)
grad T> 16oC/1000 km
862 (11,8%) 945 (12,9%) 754 (10,3%)grad T> 14oC/1000 km
Winter340 (18,9%) 424 (23,6%) 261 (14,5%)
grad T> 18oC/1000 km
490 (27,2%) 571 (31,7%) 423 (23,3%)grad T>16oC/1000 km
Summer29 (1,6%) 51 (2,8%) 96 (5,3%)
grad T> 12oC/1000 km
136 (7,4%) 158 (8,6%) 252 (13,7%)grad T>10oC/1000 km
1961-1980 1980-2000 2046-2065
Mean 22 26 19
Rms 8.996 10.658 9.760
Dispersion 80.937 113.589 95.263
Minimum
11 10 4
Maximum 48 44 42
Number of cases with intensive frontal zoneWinter
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years
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