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The fourth meeting of the International Ice Charting Working Group (IICWG ) St.Petersburg, Russian Federation, April 7-11, 2003. Experience of short-range (1-5 days) numerical ice forecasts for the freezing seas. Sergey Klyachkin, Zalman Gudkovich, Roman Guzenko - PowerPoint PPT Presentation
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Experience of short-range (1-5 days) numerical ice
forecasts for the freezing seas.
Sergey Klyachkin, Zalman Gudkovich, Roman Guzenko
Arctic and Antarctic Research Institute, St. Petersburg
Tel.: (812) 352 03 07;
E-mail:[email protected]
The fourth meeting of the International Ice Charting Working Group The fourth meeting of the International Ice Charting Working Group (IICWG(IICWG) )
St.Petersburg, Russian Federation, April 7-11, 2003St.Petersburg, Russian Federation, April 7-11, 2003
Regions General view of model regions
Barents and Kara Seas
Bathymetry
Grid mesh of the model
(cell dimension is
25×25 km)
Initial data
Principle of GRID data interpolation
(atmospheric pressure distribution)
Interpolated atmospheric pressure and
calculated surface wind (forecast)
Interpolated air temperature (forecast)
Satellite images often do not cover the entire model area.
In this case the initial data for new forecast are prepared
by composing the new image data and results of previous forecast.
Actual distribution on the new image…
Previous forecast…
Composite ice chart used as initial data for new forecast
Sea temperature is prepared by correcting the climatic distribution in accordance with actual location of ice edge
The model consists of four principal components:
1) thermal evolution of the sea water (based on the equations
of heat and salinity budget);
2) sea water dynamics (based on the equations of hydrodynamics);
3) thermal evolution of ice cover (based on the heat budget equation);
4) ice cover dynamics (based on the non-stationary equations of ice dynamics with viscous-plastic rheology).
MODEL
Results
Forecast of ice drift and weighted-mean thickness
Forecasted and actual distribution
Examples for other regions Pechora Sea
Laptev Sea
East-Siberian Sea
1) Skill score of the model forecast P;
Ncorrect – number of cells in which forecasted and actual values are close (difference is not more than permissible error);
Ntotal – total number of cells2) Skill score of the inertial forecast I;
Ninert – number of cells in which the initial and final actual values are close (difference is not more than permissible error);
Ntotal – total number of cells3) Efficiency E
E = P - I
Criteria of quality
total
inert
NN
I
The sense of these formulas is as follows:
The model forecast affirms: “Ice conditions will change in accordance with the model results”.
The inertial forecast affirms: “The changes of ice conditions will not be significant, and we may accept them constant.”
The forecast efficiency shows: “which of these two hypotheses is closer to reality”.
If:
1) efficiency is positive (the model forecast has higher skill score than the inertial forecast): the changes of ice conditions are significant, hence, we may not accept them constant and it is more reasonable to employ the model forecast;
2) efficiency is negative or zero (the model forecast has lower or equal skill score than the inertial forecast): it is more reasonable to assume the ice conditions constant than to employ the model forecast.
PE 68.0max
Typical formula for maximum permissible error:
where Emax – maximum permissible error, - standard error, P - natural variability of forecasted parameter for the temporal scale equal to prognostic period
As for ice concentration, maximum permissible errors coincide with standard concentration gradations defined in the “International Symbols for Sea Ice Charts and Sea Ice Nomenclature” as follows:open water – 0 tenths (0%); very open ice – 1-3 tenths (less than 35 %);open ice – 4-6 tenths (36-65 %);close ice – 7-8 tenths (66-85 %);very close ice – 9-10 tenths (more than 85%)
Algebraic error
Absolute error
Skill score, %
Efficiency, %
Ice concentration, tenths
0.03 1.75 85.6 5.0
Ice drift velocity, cm/s
2 5 79.9 26.0
Ice drift direction, degrees
-13 35 84.0 48.4
Ice thickness, cm 1 8 88.9
Equivalent thickness of ridges, cm
-3 3 85.9
Ice pressure, points (3 point scale)
0.08 0.19 7.8
Verification Generalized results of ice forecasts
Statistical distribution
of ice concentration
forecast errors
Algebraic errors
Absolute errors
Interface General view of interface panel
Entering the forecast parameters
Entering initial data
Running
Results demonstration
Conclusions
The main directions of development.•Improvement of methodology of initial ice chart composing;
•Improvement of methodology of initial water temperature correction;
•More detailed simulations of the sea currents (including tides);
•More accurate estimate of horizontal heat fluxes in the near-edge zones;
•Elaboration of fast ice boundary forecasting.