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Sei-Young Park

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L. Quality Control and the application of Cross Validation in the Real-Time Mesoscale Analysis(RTMA) system. Sei-Young Park. Sei-Young Park. KMA/NWPD, NCEP/EMC. Manuel Pondeca, Jim Purser, David Parrish, Geoff Dimego John Derber, Xiujuan Su, Wan-Shu Wu, Geoff Manikin. NCEP/EMC. - PowerPoint PPT Presentation
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  • Sei-Young ParkQuality Control and the application of Cross Validation in the Real-Time Mesoscale Analysis(RTMA) systemKMA/NWPD, NCEP/EMCManuel Pondeca, Jim Purser, David Parrish, Geoff DimegoJohn Derber, Xiujuan Su, Wan-Shu Wu, Geoff ManikinNCEP/EMCSei-Young [email protected]

  • ContentsIntroduction of RTMAQuality control in RTMAGross error check Variational QCUse list vs. Reject listCross ValidationHilbert curvesSummary and conclusion

  • Real-Time Mesoscale Analysis (RTMA)The RTMA is a fast-track, proof-of-concept effort intended to:

    leverage and enhance existing analysis capabilities in order to generate experimental CONUS-scale hourly NDFD-matching analyses

    establish a real-time process that delivers a sub-set of fields to allow preliminary comparisons to NDFD forecast grids

    also provide estimates of analysis uncertainty

    establish benchmark for future AOR (Analysis Of Record) efforts

    build constituency for subsequent AOR development activities

  • Real-Time Mesoscale Analysis (RTMA)Procedure

    Temperature & dew point at 2 m & wind at 10 mRUC forecast/analysis (13 km) is downscaled by GSD to 5 km NDFD gridDownscaled RUC used as first-guess in NCEPs 2DVar analysis of ALL surface observationsEstimate of analysis error/uncertaintyPrecipitation NCEP Stage II analysisSky cover NESDIS GOES sounder effective cloud amount

    Logistics

    Hourly within ~30 minutes 5 km NDFD grid in GRIB2Operational at NCEP Q3 FY2006Distribution of analyses and estimate of analysis error/uncertainty via AWIPS SBN as part of OB7.2 upgrade end of CY2006Archived at NCDC

  • Quality control in RTMA1. Gross error check : decided by the observation increment (residual)

    2. Variational QC3. Use list vs. Reject list of Mesonet Wind

    Analysis will be concentrated on the Mesonet wind.temperature:wind:QC is very important when using the high density and unverified new data. This is one of the reasons why the Mesonets have not been used, despite their high data density. Therefore, applying QC with reasonable methods is the first step to using these data in the analysis system.

  • 1. Gross Error CheckLimit : (o-a)/R = 10Obs vs. AnalObs vs. GuessLimit : (o-a)/R = 5

  • 2. Variational QCBy Erik Andersson, 1999,2006The distributions of departure often reveal a more frequent occurrence of large departures than expected from the corresponding Gaussian (normal) distribution with the same mean and standard deviation-showing as wide Tails.(Y-Hxb )

  • Variational QCBy Erik Andersson, 1999,2006

  • Variational QCBy Erik Andersson, 1999,2006

  • A : 0.08(288)A : 0.1(288)Var QC weight function vs. IV( A :0.08 for Metar, Synoptic sea and land )A: 0.06(288)

  • Distribution of the innovation (VarQC)Obs vs. GuessLimit : (o-a)/R = 10Obs vs. AanlLimit : (o-a)/R = 5

  • 3. Uselist of Mesonet windMesonets comprise majority of obs but they are not as good as other conventional sfc obs sources

    5/6 of all Mesonet data are from AWS which includes most school sites and APRSWXNE(citizens network)No mesonet winds used in current RUC (or NAM) due to slow wind bias. GSD has constructed a Uselist of acceptable networks based on overall siting strategies etc. : It depends on the Mesonet provider name.GSD Uselist was applied in the RTMA and has been running on the parallel system.Continuing need for scrutiny of mesonet quality

    Provider name

    OK-Meso : Oklahoma MesonetWT-Meso : West Texas MesonetAPG : U.S. Army Aberdeen Proving GroundsCODOT : Colorado Department of TransportationFLDOT : Florida Dep of TransportationINDOT : Indiana Dep of TransportationMNDOT : Minnesota Dep of TransportationDCNet : DCNetGoMOOS : Gulf of Maine Ocean Observing SystemGPSMET : ESRL/GSD Ground-Based GPSNOS-PORT : National Ocean Service Physical Oceanographic Real-Time SystemRAWS : Remote Automated Weather Stations MesoWestAGRIMET : U.S. Bureau of ReclamationMesoWestAQ : NOAA Air Resources Laboratory Special Operations and Resource DivisionMesoWestARL FRD : NOAA Air Resources Laboratory Field Research DivisionMesoWestARL SORD : NOAA Air Resources Laboratory Special Operations and Resource DivisionMesoWestDOERD : Department of Energy Office of Repository DevelopmentMesoWestDUGWAY : U.S. Army Dugway Proving GroundsMesoWestITD : Idaho Transportation DepartmentMesoWestMT DOT : Montana Dep. of TransportationMesoWestTOOELE : U.S. Army Desert Chemical Depot, Tooele County

  • Number distribution of wind data (U)For Var QC Var_pg=0.05, wgtlim=0.25,Gross=10 m/sWithout uselistWith uselist400025045001000

  • Number distribution of wind data (V)For Var QC Var_pg=0.05, wgtlim=0.25,Gross=10 m/sWithout uselistWith uselist400025045001000

  • Verification of the Uselist2006.5.23.00.~2006.6.14.23. (23days, hourly)

  • Uselist of Mesonet windVarQCCASE 1 : 2006.3.14.15 UTCWith uselistWithout uselist All obs data All obs data

  • Uselist of Mesonet windVarQCCASE 1 : 2006.3.14.15 UTCWith uselistWithout uselist

  • Uselist of Mesonet windVarQCCASE 2 : 2006.11.25.12 UTCWith uselistWithout uselist All obs data All obs data

  • Uselist of Mesonet windVarQCCASE 2 : 2006.11.25.12 UTCWith uselistWithout uselist

  • 4. Reject list of Mesonet windRejest list : constructed by the rejected data in gross error check and VarQC - hourly made and updated - It depends on the station name.

    station name lat lon 1 MLGC1 x 32.880 243.570 2 FHCC1 x 32.990 243.930 3 LTHC1 34.020 243.810 4 BPNC1 x 34.380 242.310 5 PIVC1 x 35.450 241.720 6 INTC1 x 36.120 242.910 7 QTWA3 x 36.580 246.270 8 TS037 x 36.620 241.790 9 QBRA3 x 36.790 246.240 10 BADU1 x 37.150 246.050 11 HP001 32.890 243.580 12 GDSN2 x 35.810 244.530 13 A36 x 36.540 244.460 14 AR221 x 34.190 243.290 15 AR745 34.500 242.680 16 C6728 34.840 240.920 17 H0099 x 34.380 242.400 18 PHELN 34.450 242.370 19 HSPRA 34.450 242.680 20 APPLE 34.510 242.820

  • Distribution of rejected data25 ~ 50%(16.4%)50 ~ 75%(1.8%)75 ~ 100%(0.6%)0 ~ 25%(81.4%)2006.6.8.~2006.6.20. (13 days)

  • Distribution of rejected data2006.11.21.19.2006.11.21.12.

  • Verification of the reject list

    Chart1

    -0.05-0.07

    -0.09-0.09

    -0.08-0.09

    -0.11-0.11

    -0.11-0.13

    -0.14-0.15

    -0.13-0.15

    -0.17-0.18

    -0.16-0.19

    -0.17-0.19

    -0.18-0.2

    -0.15-0.19

    -0.15-0.17

    -0.11-0.14

    -0.03-0.05

    0.040.02

    0.130.11

    0.180.16

    0.140.14

    0.150.12

    0.090.08

    0.040.04

    0-0.01

    with reject list

    no reject list

    UTC

    BIAS

    Bias by reject list

    bias_rmse_uv_all_rjlist_nocv

    rjlist_nocvnocv

    stdout_uv.20061114013all13718-0.051.760.530.43stdout_uv.20061114013all14043-0.071.920.610.47

    stdout_uv.20061114023all13641-0.091.820.560.45stdout_uv.20061114023all13917-0.091.970.630.48

    stdout_uv.20061114033all13832-0.081.810.550.44stdout_uv.20061114033all14164-0.091.960.630.48

    stdout_uv.20061114043all14005-0.111.980.640.49stdout_uv.20061114043all14005-0.111.980.640.49

    stdout_uv.20061114053all13508-0.111.740.520.43stdout_uv.20061114053all13957-0.131.990.650.49

    stdout_uv.20061114063all14004-0.141.870.590.46stdout_uv.20061114063all14302-0.152.020.670.49

    stdout_uv.20061114073all12693-0.131.720.50.41stdout_uv.20061114073all12994-0.151.920.60.45

    stdout_uv.20061114083all13678-0.171.860.590.46stdout_uv.20061114083all13918-0.181.990.650.49

    stdout_uv.20061114093all13433-0.161.790.550.44stdout_uv.20061114093all13808-0.191.990.670.49

    stdout_uv.20061114103all13314-0.171.780.550.44stdout_uv.20061114103all13634-0.191.910.630.48

    stdout_uv.20061114113all13492-0.181.760.530.42stdout_uv.20061114113all13813-0.21.930.620.46

    stdout_uv.20061114123all14015-0.151.710.50.41stdout_uv.20061114123all14362-0.191.880.590.45

    stdout_uv.20061114133all13666-0.151.720.50.41stdout_uv.20061114133all13956-0.171.890.580.44

    stdout_uv.20061114143all13705-0.111.730.510.41stdout_uv.20061114143all13983-0.141.870.590.45

    stdout_uv.20061114153all13779-0.031.790.540.43stdout_uv.20061114153all14075-0.051.920.610.47

    stdout_uv.20061114163all136060.041.820.570.46stdout_uv.20061114163all139480.021.990.660.5

    stdout_uv.20061114173all135530.131.880.610.49stdout_uv.20061114173all138930.112.040.690.53

    stdout_uv.20061114183all141540.181.950.650.51stdout_uv.20061114183all145610.162.150.750.56

    stdout_uv.20061114193all134880.141.90.620.5stdout_uv.20061114193all139010.142.080.720.54

    stdout_uv.20061114203all135670.151.970.660.52stdout_uv.20061114203all139180.122.120.740.56

    stdout_uv.20061114213all136810.091.920.610.49stdout_uv.20061114213all141220.082.110.720.54

    stdout_uv.20061114223all123000.041.810.540.44stdout_uv.20061114223all126420.041.950.630.48

    stdout_uv.20061114233all1309601.820.570.46stdout_uv.20061114233all13386-0.011.940.640.49

    bias_rmse_uv_all_rjlist_nocv

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    rjlist_nocv

    nocv

    UTC

    Bias

    Bias by reject list

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