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  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    1

    ItriCorp-NRLMRY STTR N06-T037

    Ensemble Forecast Application System [EFAS] for

    Conveying METOC Forecast Certainty in Decision Making

    Summary

    Jim Etro Itri Corporation, CEO

    831-324 -0499 (office)

    703-489-8507 (mobile)

    [email protected]

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    2

    ItriCorp - NRL Monterey Collaboration

    Itri Corporation Jim Etro, PI

    NRL Monterey John Cook

    Science Team Lead Scott Sandgathe

    Sponsor/TPOC ONR/Ron Ferek

    Contract # NOOOI4-08-C-OI73

    Lead Engineer Arthur Etro

    Science Team NRL - J Hansen

    NRL- C Bishop

    NPS - T Eckel

    FNMOC - M Sestak

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Significant Findings

     Ensembles help quantify forecast uncertainty, and

    NOGAPS & WW3 & COAMPS Ensembles can be represented in a deterministic

    forecast to convey:

    A value, a range of the value, and a measure of confidence in the value

    At All FCST TAUs Ensembles offer the most skillful deterministic forecast

     WRT Post Processing

     On global scale and in data sparse areas such as oceans and upper atmosphere the model

    analysis can be used for ensemble bias corrections and calibrations

     In most cases Bias Corrections gives best results. Spread Adjustments (by least squares)

    have not shown improved skill

     An object oriented architecture can be implemented to

    • Accommodate any ensemble or sets of ensembles

    • be upgraded and improved as science and operational experiences grow

    • Provide new products and valuable comparison and validations

    3

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    4

    Ensemble Handling Process

    From Operational NOGAPS & WW3 and COAMPS Ensembles from FNMOC

    Determine METOC parameters to be input into Products

    Post Process at every Grid Point in the domain of interest (maybe global or can be 1 grid point)

    Extract Results and Apply into Application/TDA

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Ensemble Post Processing 1. Bias Correction to Parameters by capture of average TAU error across all

    members to their verifying analysis then averaging of all the errors for 30

    previous days applied to current TAU.

    - Use Kalman Filter (Jim Hanson) in Next Stage

    2. Spread Adjustment to Parameters by Linear Regression using Method of

    Ordinary Least Squares over 60 previous days to establish coefficients.

    - No Value

    3. Simple Density (Kernel) Smoothing of Histogram of Parameters from

    Members at each point to Form PDF

    4. Determine

    1. Ensemble Averages from Raw and Bias Corrected Averages

    2. Most Likely Value From PDF

    3. Range from PDF

    4. Confidence from PDF or Parameter Value Counting of each Member

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Comparisons & Validations - NOGAPS

    6

    Forecasted Parameter

    Tau Best Ensemble Average Conditioning Method

    Ensemble Improvement Over Single Model FCST

    Ave Error Ensemble's Ave

    Global Improvement

    Ensemble’s Improvement in a Mid-Lat

    Location

    Analysis – Single Model

    Analysis – Best Ensemble

    06 Bias Correction 132.5 40.0 .9 mb 1 – 3 mb

    SFC Pressure 24 Bias Correction 182.5 98.75. .8 mb

    48 Bias Correction 275.0 178.75 .9 mb 2 – 6 mb

    06 Bias Correction .67 .48 .20: K

    SFC Temperature 24 Bias Correction .98 .74 .24: K

    48 Bias Correction 1.23 .94 .29: K

    06 Bias Correction .222 .164 .057 M .1 - .26 M

    Sig Wave Hgt 24 Bias Correction .243 .174 .069 M

    48 Bias Correction .313 .230 .082 M .1 – 1.5 M

    06 Bias Correction 1.04 .64 .4 m/s 1 – 3 m/s

    SFC Wind Speed 24 Bias Correction 1.38 1.0 .38 m/s

    48 Bias Correction 1.68 1.25 .43 m/s 2 – 3.5 m/s

    06 Raw Ensemble 30 23 7:

    SFC Wind Direction 24 Raw Ensemble 38 30 8:

    48 Raw Ensemble 47 38 9:

    06 Raw Ensemble 24 19 5 %

    Total Clouds 24 Raw Ensemble 29 23 6 %

    48 Raw Ensemble 22 17 5 %

    http://services.itriware.com/Workflow/lab/ensemble/index.html

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    0

    5000

    10000

    15000

    20000

    winddir 48hr 30s-

    30n

    winddir 48hr north

    30-90

    winddir 48hr

    global

    Raw Ensemble Average

    Bias Corrected Average

    0

    5000

    10000

    15000

    20000

    windspd 48hr 30s-

    30n

    windspd 48hr north

    30-90

    windspd 48hr global

    Raw Ensemble Average

    Bias Corrected Average

    0

    0.5

    1

    1.5

    2

    windspd 48hr 30s-30n

    windspd 48hr north 30-90

    windspd 48hr global

    Raw Ensemble Average

    Bias Corrected Average

    0 10 20 30 40 50 60 70

    winddir 48hr 30s-30n

    winddir 48hr north 30-90

    winddir 48hr global

    Raw Ensemble Average

    Bias Corrected Average

    C o u

    n ts

    C o

    u n

    ts

    48hr Wind Direction

    48hr Wind Speed

    D eg

    re es

    M et

    er s/

    S ec

    error

    error

    Error

    Analysis - Fcst

    NOGAPS

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    0

    50

    100

    150

    200

    250

    300

    350

    400

    SFC Pressure 30s-30n

    SFC Pressure 30n-90n

    SFC Pressure global

    Raw Ensemble Average

    Bias Corrected Ensemble Average

    Analysis - One Member

    0

    5000

    10000

    15000

    20000

    25000

    SFC Pressure 30s-30n

    SFC Pressure 30n-90n

    SFC Pressure

    global

    Raw Ensemble Average

    Bias Corrected Ensemble Average

    NOGAPS 48hr SFC Pressure

    C o u

    n ts

    M et

    er s

    error

    0

    0.5

    1

    1.5

    2

    2.5

    3

    sig wave 48hr 30s-

    30n

    sig wave 48hr north 30-90 lat

    sig wave 48hr south

    30-90lat

    sig wave 48hr global

    Raw Ensemble Average - Analysis

    Bias Corrected Average - Analysis

    Analysis - One Member

    0 2000 4000 6000 8000

    10000 12000 14000 16000

    sig wave 48hr 30s-

    30n

    sig wave 48hr

    north 30- 90 lat

    sig wave 48hr

    south 30- 90lat

    sig wave 48hr

    global

    Raw Ensemble Average

    Bias Corrected Average

    WW3 48hr Sig_Wave_Height

    C o

    u n

    ts

    M et

    er s error

    Error

    Analysis - Fcst

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Comparisons & Validations - COAMPS

    9

    Forecasted Parameter

    Tau LvL Best Ensemble

    Average Conditioning Method

    Ensemble Improvement Over Single Model FCST

    Ave Error Ensemble's Ave Global

    Improvement Analysis –

    Single Model Analysis – Ensemble

    Virtual Temperature (derived)

    12 All

    Bias Correction ≈.7:K ≈.5:K .2:K

    24 Bias Correction ≈1.4:K ≈1:K .3:-.4:K

    Sea Lvl Pressure 12

    MSL Bias Correction ≈1.2mb ≈.6mb ≈.6mb

    24 Bias Correction ≈1.6mb ≈1mb ≈.6mb

    http://services.itriware.com/Workflow/lab/ensemble/index.html

    Impact on vertical stability???

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    1.4

    1

    Raw Ensemble Average

    Bias Corrected Average

    Analysis - One Member

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    1.4

    1

    Raw Ensemble Average

    Bias Corrected Average

    Analysis - One Member

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    1.4

    1

    Raw Ensemble Average

    Bias Corrected Average

    Analysis - One Member

    24hr COAMPS Virtual Temp

    all Lvls

    8450 meters

    10 meters

    Error

    Analysis - Fcst

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Run Times (on NRL Work Station)

    NOGAPS and WW-3 Ensembles Operate on 16 Members, One Level, 6 parameters, 00Z Tau 0-54 every 6hrs

    – 3.3 hrs/day (1.8 hrs/day for spread adjustment)

    COAMPS Ensemble Operate on 32 Members, 40 Levels, SLP and full parameter (TV), 00Z &12Z Tau 12,24

    – 8.5 hrs/day (6.2 hrs/day for spread adjustment)

  • There are no boundaries when enthusiasm and excitement are applied to the task at hand.

    Forecast Confidence User Focused

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