recent development of visualisation at finnish ... · kilpinen & sarkanen 313.11.2003...
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13.11.2003KIlpinen & Sarkanen 1
Recent development of visualisation at Finnish Meteorological Institute (FMI)
Juha Kilpinen and Annakaisa SarkanenFinnish Meteorological Institute (FMI)
http://www.fmi.fi/
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13.11.2003KIlpinen & Sarkanen 2
Recent development of visualisation at Finnish Meteorological Institute (FMI)
Juha Kilpinen and Annakaisa SarkanenFinnish Meteorological Institute (FMI)
http://www.fmi.fi/
• Developments in present production system
– new features of the grid editor software: SmartTools– aviation applications and products– some verification results – oil spill movement model (customer application)– atmospheric dispersion model (customer application)
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13.11.2003KIlpinen & Sarkanen 3
Background of recent developments at FMI
• To apply latest technology the forecasting and production process has to be changed (re-engineering, typically the most difficult part)
• The migration to new automated production process began at mid 1990’s, the work is still continuing;
• The core of the new system is the real time database (grid data, observations etc)
• The forecasters duty is to keep the quality of data in database in best possible level: the grid editor is used to interact withthe data
• Most commercial products for customers are made automatically from this data (the number of products is thousands); still the old manual process also in use
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13.11.2003KIlpinen & Sarkanen 4
and editing of
Real timedatabase:• observations• numericalforecasts• final forecasts• interpretations
Climatologicaldatabase
Post processing: createscustomer products fromthe data edited byforecasters; texts,graphics, etc.
Customers:
Observations:• satellites• weather radars• surfaceobservations• soundings
Numerical weatherforecast models (bysupercomputers)
Forecasting process at FMI (technical aspect)
Visualisation andEditing byforecaster
Old Vax WorkstationOld manual process
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Forecasting process at FMIOld manual forecast process and production still exits:Hand drawing of maps, human Made text bulletins etc.....
The new forecast process expanding:integration of TAF-production to editedgrid data; integration of road condition model and forest fire risk model
TAF editor systemwith partly manualprocess
New Grid editor system with automated production process
Old VAX workstation
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13.11.2003KIlpinen & Sarkanen 6
The Grid Editor
• Time series editing using masks
• Paint brush
• Time-shifting and Smoothing
• Control point editing
• Combination of data from different sources
• Integrated visualisation and product generation
• SmartTools
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13.11.2003KIlpinen & Sarkanen 7
The Grid Editor
Chooce of the initial data/model
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13.11.2003KIlpinen & Sarkanen 8
The Grid Editor
Time series editing tool
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13.11.2003KIlpinen & Sarkanen 9
The Grid EditorGrid editing windows
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The Grid Editor
Mask editing windows
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The Grid Editor
Paint brush tool
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Control point editing
Every time series can be edited separately using “delta functions” and finally the changes are interpolated (using “delta functions”) to all grid points
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The Grid Editor
Text generation tool:
generates automated textforecasts for 1 and 3 daysfor the location indicated bycursor and time window
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The Grid EditorSmart Tools: ability to makescripts to perform more complicated and oftenrepeated editing actions ina more easy manner
IF (N>5) T=T+3
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Grid Editor - SmartTools
• Own scripting language:
• Editing window
• An error log window
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13.11.2003KIlpinen & Sarkanen 16
Grid Editor - SmartTools
• Operators;T = T + P * 0.123 – RH/100 * WS + (T - DP) ^ 2
• Blocks:{T = T + 1P = P + 1RH = RH + 1}
• Conditionals:IF(T – DP > 2) T = T + 1P = P + 1 // both are executed if condition fulfills.
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13.11.2003KIlpinen & Sarkanen 17
Grid Editor - SmartTools
• More complicated conditionals:
IF(T – DP > 4) T = T + 1P = P + 1ELSEIF(T – DP > 2) // means actually that (T-DP) is
betweenn 2 and 4.T = T + 2P = P + 2ELSE // in all other cases, if T – DP <= 2, then ELSE is
executedT = T + 3P = P + 3
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13.11.2003KIlpinen & Sarkanen 18
Grid Editor - SmartTools• T TEMPERATURE• P SURFACE PRESSURE• RH RELATIVE HUMIDITY• KIND K-INDEX• DP DEW POINT • LRAD LONG WAVE RADIATION• SRAD SHORT WAVE RADIATION• WD WIND DIRECTION• WS WIND SPEED• N TOTAL CLOUD COVER• CL AMOUNT OF LOW CLOUDS• CM AMOUNT OF MEDIUM CLOUDS • CH AMOUNT OF HIGH CLOUDS• RR INTENSITY OF PRECIPITATION• PREF PRECIPITATION TYPE (RAIN, SLEET, SNOW)• PRET PRECIPITATION TYPE (CONTINOUS, SHOWER,..)• THUND PROPABILITY OF THUNDER• FOG INTENSITY OF FOG• HSADE PRECIPITATION SYMBOL (NOT EDITABLE; SYNOP)• HESSAA WEATHER SYMBOL (NOT EDITABLE)
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Grid Editor - SmartTools• FL1BASE Flight Level 1 cloud Base• FL1TOP Flight Level 1 cloud Top• FL1COVER Flight Level 1 cloud COVER• FL1CLOUDTYPE Flight Level 1 cloud TYPE• FL2BASE Flight Level 2 cloud Base• FL2TOP Flight Level 2 cloud Top• FL2COVER Flight Level 2 cloud COVER• FL2CLOUDTYPE Flight Level 2 cloud TYPE• FL3BASE Flight Level 3 cloud Base• FL3TOP Flight Level 3 cloud Top• FL3COVER Flight Level 3 cloud COVER• FL3CLOUDTYPE Flight Level 3 cloud TYPE• ……• FL8BASE Flight Level 8 cloud Base• FL8TOP Flight Level 8 cloud Top• FL8COVER Flight Level 8 cloud COVER• FL8CLOUDTYPE Flight Level 8 cloud TYPE• FLCBBASE Flight Level CB BASE• FLCBCOVER Flight Level CB COVER• FLMINBASE Flight Level cloud minimum BASE• FLMAXBASE Flight Level cloud maximum BASE• AVIVIS Aviation Visibility• VERVIS Vertical Visibility
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13.11.2003KIlpinen & Sarkanen 20
Grid Editor - SmartTools
STATIC AND NON STATIC FUNCTIONS
• TOPO TOPOGRAPHY (static)• SLOPE SLOPE OF SURFACE • SLOPEDIR DIRECTION OF DEEPIST SLOPE• DISTSEA SHORTEST DISTANCE TO SEA• DIRSEA DIRECTION TO SEA• DISTLAND SHORTES DISTANCE TO LAND• DIRLAND DIRECTION TO LAND• LANDSEAMASK LAND SEA MASK• RELTOPO RELATIVE TOPOGRAPHY• LAT LATITUDE (non static)• LON LONGITUDE (non static)• EANGLE ELEVATION ANGLE (non static)
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13.11.2003KIlpinen & Sarkanen 21
Grid Editor - SmartToolsIntegrating functions• AVG calculates the arithmetic average• MIN seeks the minimum value• MAX seeks the maximim value• SUM calculates the sum• WAVG calculates the weighted average (?)
Mathematical functions• SIN, COS, LN, SQRT, LOG, ATAN, EXP, ….
Ramp functions• RU (ramp up)• RD (ramp down) • DD (douple ramp)
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Grid Editor - SmartTools// Säteilykorjaus (Radiation correction)// SN 2002.09.30// pilvisyys korjataan => säteilyt korjataan// ECMWF-lyhytaaltosäteily liian pieni selkeissä tilanteissa => 20% lisäys,// Viitteet: Lauros Johanna, 2001, Tienpinnan talviset liukkausolosuhteet ja niiden mallintaminen,// pro gradu, Helsingin yliopiston meteorologian laitos// Katso myös gradun kirjallisuusviitteet: Niemelä Sami, Räisänen Petri, Savijärvi Hannu// SRAD = (1 - 0.67 * (N/100) ^ 3.32) / (1 - 0.67 * (N_ORIG/100) ^ 3.32) * SRAD_ORIG// LRAD = (1 + 0.22 * (N/100) ^ 2.75) / (1 + 0.22 * (N_ORIG/100) ^ 2.75) * LRAD_ORIG// SRAD_SELKEA = 1000 * (1 - EXP(-0.06 * EANGLE)) * SIN(EANGLE) + 5 + 96 * (1 - EXP(-0.05 * EANGLE))// missä EANGLE >= 0IF (SRAD == SRAD_EC AND (N_ORIG <= 30 OR N <= 30)){
SRAD = 1.2 * (1 - 0.67 * (N/100) ^ 3.32) / (1 - 0.67 * (N_ORIG/100) ^ 3.32) * SRAD_ORIGLRAD = (1 + 0.22 * (N/100) ^ 2.75) / (1 + 0.22 * (N_ORIG/100) ^ 2.75) * LRAD_ORIG
}ELSE{
SRAD = (1 - 0.67 * (N/100) ^ 3.32) / (1 - 0.67 * (N_ORIG/100) ^ 3.32) * SRAD_ORIGLRAD = (1 + 0.22 * (N/100) ^ 2.75) / (1 + 0.22 * (N_ORIG/100) ^ 2.75) * LRAD_ORIG
}// IF ( SRAD > SRAD_SELKEA)// SRAD = SRAD_SELKEA// missä EANGLE >= 0IF ( ( SRAD ) - ( 1000 * (1 - EXP(-0.06 * EANGLE)) * SIN(EANGLE) + 5 + 96 * (1 - EXP(-0.05 * EANGLE)) ) > 0 AND EANGLE >= 0 )
SRAD = 1000 * (1 - EXP(-0.06 * EANGLE)) * SIN(EANGLE) + 5 + 96 * (1 - EXP(-0.05 * EANGLE))ELSEIF ( ( SRAD ) - ( 1000 * (1 - EXP(-0.06 * EANGLE)) * SIN(EANGLE) + 5 + 96 * (1 - EXP(-0.05 * EANGLE)) ) > 0 AND EANGLE < 0 )
SRAD = 1000 * (1 - EXP(-0.06 * 0)) * SIN(0) + 5 + 96 * (1 - EXP(-0.05 * 0))IF ( SRAD < 0 )SRAD = 0
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13.11.2003KIlpinen & Sarkanen 23
Grid Editor – SmartToolsApplication: Small scale editing
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13.11.2003KIlpinen & Sarkanen 24
Grid Editor - SmartTools
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13.11.2003KIlpinen & Sarkanen 25
Grid Editor – SmartToolsApplication: Icing predictor for Oceans
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Editing of aviation parameters (near future)
Edited parameters:
cloud amount in ICAO layersintensity of fog (0,1,2)intensity of precipitation (mm/h)(edited already elsewhere)
SmartTools scripts are mainly used
Visibility and ceiling height arederived from edited and interpretedparameters
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Editing of aviation parameters (cloud base)
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13.11.2003KIlpinen & Sarkanen 28
Editing of aviation parameters (visibility/rr)
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Editing of standart parameters (ps/T2m)
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MAE of pooled temperature forecasts (3 stations, 11 seasons, 0.5-5 d)
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
Dec 2000-Feb 2001
Mar 2001-May 2001
Jun 2001-Aug 2001
Sep 2001-Nov 2001
Dec 2001-Feb 2002
Mar 2002-May 2002
Jun 2002-Aug 2002
Sep 2002-Nov 2002
Dec 2002-Feb 2003
Mar 2003-May 2003
Jun 2003-Aug 2003
Mean
MA
E(C
)
Forecaster_PointsForecaster_EditorModelsBest_model
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MAE of temperature forecasts (3 stations, 2 years)
1
1,5
2
2,5
3
3,5
4
1 2 3 4 5
MA
E of
T
Forecaster_Gridbest model
Forecast length (days)
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HIT RATE of Ceiling height forecast based on ECMWF data (raw data)
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HIT RATE of Ceiling height forecast based on ECMWF data (smart fit with METARs)
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The model for oil spill movement in the Gulf of Finland
• 3D hydrodynamic model• Wind and current forecasts
(ECMWF/HIRLAM data)• Spill information, start/end time,
location etc.• Duty forecasters and oil
combating authorities on duty are main users (also Coast Guard, fire pricades etc. use system)
• User interface with Java• Co-operation between FMI,
Finnish Environment Institute and Finnish Institute of Marine Research
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13.11.2003KIlpinen & Sarkanen 40
The model for oil spill movement in the Gulf of Finland
• Wind field (vectors) • Surface current field (vectors)
• Drift trajectories (output)• time series of wind and current
forecasts (output)• Additional information: SST and
ice cover
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13.11.2003KIlpinen & Sarkanen 41
SILAM atmospheric dispersion and dose assessment model
• Trajectory model (based on ECMWF/HIRLAM data)
• Partical distributions and risk area calculations
• Duty forecasters and Radiation safety authorities on duty are main users
• User interface on web (PHP)• Co-operation between FMI,
Radiation and Nuclear Safety Authority of Finland and Technical Research Centre of Finland
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SILAM atmospheric dispersion and dose assessment model
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13.11.2003KIlpinen & Sarkanen 43
SILAM atmospheric dispersion and dose assessment model
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SILAM atmospheric dispersion and dose assessment model
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Conclusions
• Changing the old forecasting process has been more complicated than expected
• The problems have been less scientific or technical than psychological
• Due to the highly automated forecasting process FMI still has commercial services
• There is still much to do on the non-commercial side of weather service
• In the next generation production system (on planning) the present and past experiences are to be taking into account
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Thank you