atmospherically – induced hazards in the coastal zone and the possibility of their decadal and...

Atmospherically – induced hazards in the Atmospherically – induced hazards in the coastal zone and the possibility of their coastal zone and the possibility of their

decadal and centennial prediction decadal and centennial prediction

A.Kislov, G.Surkova, D.Gushina, P.Toropov, A.Kislov, G.Surkova, D.Gushina, P.Toropov, D.Blinov. D.Blinov.

Dpt. Of Meteorology and ClimatologyDpt. Of Meteorology and Climatology

NRAL, 14.12.2012

ContentsContents

1.1. Preparation of thePreparation of the meteorological meteorological observations for all working groupsobservations for all working groups

2.2. Preparation of initial conditions for the start Preparation of initial conditions for the start of the "sea models” of the "sea models”

3.3. Hazardous weather explicit modeling (bora, Hazardous weather explicit modeling (bora, cyclones) in the COSMO and WRF cyclones) in the COSMO and WRF

4.4. Identification of synoptic conditions, Identification of synoptic conditions, corresponding to different hazards corresponding to different hazards

5.5. Projection of extreme atmospheric processes Projection of extreme atmospheric processes under the climate changeunder the climate change

ContentsContents

1.1. Preparation of thePreparation of the meteorological meteorological observations for all working groupsobservations for all working groups

2.2. Preparation of initial conditions for the start of the "sea models” Preparation of initial conditions for the start of the "sea models”

3.3. Hazardous weather explicit modeling (bora, cyclones) in the COSMO and WRF Hazardous weather explicit modeling (bora, cyclones) in the COSMO and WRF

4.4. Identification of synoptic conditions, corresponding to different hazards Identification of synoptic conditions, corresponding to different hazards

5.5. Projection of extreme atmospheric processes under the climate changeProjection of extreme atmospheric processes under the climate change

Archive of station dataArchive of station dataVariables:Pressure, surface air temperature, water vapor pressure, wind speed and direction, characteristics of cloudiness, current weather

OBSERVATION PERIOD: maximum period of the data span is 01.01.1871 to 01.01.2001 most stations (more 60%) operated during the period 1936-1990 The measurements were made: 3times a day before 1936 4 times a day at mean astronomic times during the 1936-1965 period. 8 times a day at United Time Coordinate (UTC) since 01.01. 1966

structure of the data archive:Archive contains three types of data files (ID – index of station):STN_ID.dat (2095 files, 1 per station), data in ASCIISTN_ID.flg (2095 files, 1 per station), quality marks of dataussr_hly_stn.list.txt (1 file with essential station metadata such as station identifier, coordinates, elevation, date of the first and the last records, and station name) Density measuring network

Calendars of hazardous weather Calendars of hazardous weather

Hazardous weather (HW) cases selection – three calendars

1) Calendar for extreme observed wave storms and surges (1948-2012)

2) Calendar for wave storms with significant wave height 4 m modelled by wave model SWAN (1948-2012)

3) Calendar of hazardous weather (HW) in the future (2046-2065) – detected by the statistical methods, data of numerical climate simulations (CMIP3)

ContentsContents

1.1. Preparation of thePreparation of the meteorological observations for all working groups meteorological observations for all working groups

2.2. Preparation of initial conditions for the Preparation of initial conditions for the start of the "sea models” start of the "sea models”

3.3. Hazards explicit modeling (bora, cyclones) in the COSMO and WRF Hazards explicit modeling (bora, cyclones) in the COSMO and WRF



Initial and boundary conditions for wave modelling

Reanalysis

NCEP/NCAR (1948-2012)1,9x1,9 degree

Mesoscale non-hydrostatic atmospheric model COSMO-RU

ERA-40 (1958-2002)2,5x2,5 degree

Surface WIND DATA

ERA-Interim (1979-2012) , 1x1 degree

Every 6 hours

Downloading data => decoding => preparing for selected area

ContentsContents



3.3. Hazardous weather explicit modeling Hazardous weather explicit modeling (bora, cyclones) in the COSMO and WRF (bora, cyclones) in the COSMO and WRF



Some results of the statistical Some results of the statistical evaluation of forecast accuracyevaluation of forecast accuracy

a) the average forecast (blue line) and observed (red line) wind speed; b) the empirical pdf of forecast (red bars) and actual (blue bars) wind speeds over the “test area” (along the horizontal axis – the intervals in m/s), c) modal values of wind speed: forecast (red line) and the actual value (blue line) (along the horizontal axis – hours forecast).

Wind speed (a,c) and wave heights (b,d) at the time of Novorosiysk bora averaged over 26. 01.2012

analysis of NCEP/NCAR 1 × 1

WRF-ARW

wave heights calculated by the model SWAN

On the way to the forecast of water flood in Sochi-Tuapse in October 2010 by COSMO-RU

Precipitation during last 12 hours. Forecast for 10:00 MSK 16.10.2010

66 hours ahead48 hours ahead24 hours ahead

Model is capable to simulate the extreme runoff during the

flood.

Forecast of water surface runoff by COSMO-RU.

Runoff during previous 24 hours

ContentsContents




4.4. Identification of synoptic conditions, Identification of synoptic conditions, corresponding to different hazards corresponding to different hazards


Predictors: large zonal frontal zone expanding in north-south direction, temperature jumps precipitations fall conditions, wind direction in the mouth of river etc

Predictors: the main factor is abundant precipitation. No unified scheme of synoptic situation, but the intensive frontal zone is always presented

Synoptic situations associated to the various types of flood Storm surges

Water-flow

Predictors: trajectories of depressions, wind speed and wind direction, duration of wind forcing

Ice-jam

Neva River 28.10.2006 12 UTC Don River 28.02.2005 12 UTC

Mzymta 26.10.1997 00 UTC

Pechora 2.06.2008 12 UTC

ContentsContents





5.5. Projection of extreme atmospheric Projection of extreme atmospheric processes under the climate changeprocesses under the climate change

Interannual, decadal and centennial Interannual, decadal and centennial hazardous weather projections. How projections. How

they can be predicted?they can be predicted?

NAO

ЕNSO

SahelSahel

PDOPDO

CMIP5 (Coupled Model Intercomparison Project)

G.Meehl

Method of hazardous weather Method of hazardous weather projection for a long time:projection for a long time:

step by step step by step

Wind speed more than 15 m/s: Wind speed more than 15 m/s: observation, hindcasting, projectingobservation, hindcasting, projecting

The Black Sea costal wind observations (1948-2011)

Climate change and storm events Climate change and storm events frequencyfrequency

-time series of V 15 m/s don’t show obvious trends;

-synoptic features for storm events: it is reveled that prevailing of 1st type of SLP fields for storms took place for the last 60 years and it is expected to continue in the 21 century;

-climate projection based on ECHAM5 simulation shows slight redistribution of monthly frequency of strong winds and conservation of the ration of storms SLP fields types

The same projecting extreme wind The same projecting extreme wind speed for the Caspian Seaspeed for the Caspian Sea

MPI-ECHAM5

I type65 %

II type35 %

Caspian Sea – 137 cases of HW (wave height >4 m)

Number of

cases1961-1980 1981-2000 2046-2065

Winter

303 381 217 grad T> 18oC/1000 km

13 17 13grad T>18oC/1000 km

precipitation>20 mm/day

Summer

20 38 75 grad T> 12oC/1000 km

1 1 2grad T>12oC/1000 km

precipitation>20 mm/day

• The probability of occurrence of predictors for water flows in the Black sea region was estimated for modern climate and global warming conditions using the outputs of ECHAM5/MPI-OM model.

• It is shown that the occurrence of intensive frontal zone in the South of Russia will increase (decrease) in summer (winter) under warmer climate conditions which may contribute to the increase of water flow risks in summer.

Change of occurrence of water flows predictorunder warmer climate in the Black sea area

Number of cases with intensive frontal zoneWinter

Nu

mb

er

of

cases

Years

Number of cases with intensive frontal zoneSummer

Nu

mb

er

of

cases

Years

Change of intensive frontal zone occurrence in the Black sea area

Conclusions and future planConclusions and future plan

-efficiency of prognostic methodology for changes of hazardous weather have been demonstrated

-model MPI-ECHAM5 shows good agreement with assessment of frequency of storms SLP fields and used for projection of storms frequency in 21 century; it allows to hope that this technique can give relevant practice information

-All CMIP5 models will be used for realization of this task, based both on different RCPs and different decadal forecasting

Thank you!Thank you!

1948-2010reanalysis MPI-ECHAM5

Frequency of each of 19 HW and climate projection

Black Sea

EOFHW type

I II

1 0,44 0,45

2 0,20 0,21

3 0,10 0,10

4 0,07 0,07

5 0,04 0,04

6 0,03 0,03

7 0,03 0,02

8 0,02 0,02

HW types for data series 2 and 3 (SWAN calendar, 1948-2010)

Black Sea – 137 cases of HW (wave height >4 m)

Weather types are revealed by EOF and cluster analysis – two main statistically significant types

I type43 %

II type57 %

Surface pressure - centroids

How we can predict unmodelable processes based on climate How we can predict unmodelable processes based on climate simulation:simulation: application to the problem of predictingapplication to the problem of predicting of hazardous of hazardous

storm wind speeds on the shores of the Black Seastorm wind speeds on the shores of the Black Sea

•First, we have to establish a relationship in quantitative terms (based on observations) between storm wind speed and sea-level pressure (SLP) field•Second, we will test how well climate model reproduce the desired features of SLP. •Third, to determine what changes occur in the SLP climate forecast. •Fourth, we have to make the transition to the prediction of the studied hazard storm. /First & Second/ Storms over the Black Sea area have been studied for the last 60 years based on reanalysis data and coastal observations. A wind speed of 15 m/s is chosen as a threshold to detect the storm situation. EOF analyses of SLP are applied to identify the main types of atmospheric circulations causing severe winds and storm waves. The first three EOFs cover more than 70% of the total dispersion in all cases. This fact allows to create a ‘data bank’ of filtered SLP pattern for previous storms and to compare any single case with the data base.

wind

Important changes of the storm activity on Important changes of the storm activity on the shores of the Black Sea will not be the shores of the Black Sea will not be

expected under the future global warming expected under the future global warming scenarioscenario/Third &Fourth /

Data source: CMIP3Data type: daily sea level pressure (SLP)Climate model:MPI-ECHAM5 (Max Planck Institute for Meteorology,Hamburg, Germany)Numerical experiments ID:- 20C3M (1961-2000); -A2(SRES scenario) – 2046-2065Purpose:-to verify model ability to simulate relative frequency and number of storm- events (similarity of SLP fields with corr>=0.85); - to check possible changes of storm events frequency in 21 century;

MPI-ECHAM5: Relative frequency of storm events (left) and number of days (right)

Wind direction frequency for events when daily V>=15 m/s

Monthly frequency for events when daily V>=15 m/s

Wind speed over the sea for events when daily V>=15 m/s at least in one grid point

Спасибо за внимание!

А.В.КисловМГУ, географический факультет, кафедра метеорологии и климатологии

[email protected]

atmospherically – induced hazards in the coastal zone and the possibility of their decadal and...

Documents

data span

climate change slide

station identifier

network slide

boundary conditions

quality marks of data

meteorological observations

working groups