Synoptic situations associated to floods in the river mouths

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

Нагонные наводненияStorm surges

Caused by

Wind foricing

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

Wind at 10 m07.01.2005 12 GMT

Strong continuous wind forcing, wind oriented along the river channel

Pregolya03-07.12.1999

Surface mapH500

Additional factor -precipitation

Norvegian cyclone 29.11.2011

Norvegian cyclone 29.11.2011

Mouth of Don river. April 1997 12.04.1997 00 GMT

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Surface map

Black sea area

12.04.1997 00 GMTWind at 10 m

Mouth of Kuban’ 28.10.1969 12GMT

Surface mapH500

Kalmykiya 12.11.1952 12GMT

H500 Surface map

Caspian sea area

North Dvina22.10.1965 12GMT

H500 Surface map

White sea area

Water flow

Caused by

Abundant precipitation

Snow and glacier’s melting

Novorossiysk 7-9 December 2002Surface map

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Black sea area

Common predictor – intensive frontal zone

Mzymta 25-27 October 1997Surface map

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Tuapse 31.07.1991

Dgubga16.12.1996

Pregolya 7-10 August 2005 Surface map

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Baltic sea area

Terek 15-24 June 2002 Surface map

H

Ice-jam

Pechora June 2008Surface map

LН

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Frontal zone expanded in north-south direction, positive temperature in river source and negative temperature – in the river mouth

Pechora June 1998Surface map

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Mouth of Kuban’7.01.2002 12ч

Black sea area

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

Nu

mb

er o

f ca

ses

years

  1961-1980 1980-2000 2046-2065

Mean 5.5 6 12

Rms 6.116 6.504 7.177

Dispersion 37.411 42.305 51.503

Minimum 0 0 1

Maximum 18 27 26

Number of cases with intensive frontal zoneSummer

Nu

mb

er o

f ca

ses

years