Attributes {
    Y {
        String long_name "Latitude";
        String standard_name "latitude";
        Float32 pointwidth 0.05;
        Int32 gridtype 0;
        String units "degree_north";
    }
    L {
        String long_name "Forecast Lead Time in Months";
        Int32 pointwidth 0;
        Int32 gridtype 0;
        String units "months";
    }
    S {
        String standard_name "forecast_reference_time";
        Int32 pointwidth 0;
        String long_name "Forecast Issue Date";
        String calendar "360";
        Int32 expires 1707436800;
        Int32 gridtype 0;
        String units "months since 1960-01-01";
    }
    X {
        String standard_name "longitude";
        String long_name "Longitude";
        Float32 pointwidth 0.05000003;
        Int32 gridtype 0;
        String units "degree_east";
    }
    C {
        String long_name "Tercile Categories";
        Int32 gridtype 2;
        String units "ids";
    }
    Sh {
        String standard_name "forecast_reference_time";
        String long_name "Hindcast Issue Date";
        Int32 pointwidth 0;
        String calendar "360";
        Int32 gridtype 0;
        String units "months since 1960-01-01";
    }
    Forecast{
        DomTerProb {
            Int32 pointwidth 0;
            String colorscalename "tercileclassesscale";
            Int32 file_missing_value 0;
            Int32 expires 1707436800;
            String units "ids";
            String history "[   masklt ( { [   dominant_class ( Hydromet Seasonal_Forecast Precipitation Forecast TercProb )   - 1. ] * 11. } , 22 )   +   dominant_class ( Hydromet Seasonal_Forecast Precipitation Forecast TercProb Above_Normal )   ] + [   masknotrange ( { [   dominant_class ( Hydromet Seasonal_Forecast Precipitation Forecast TercProb )   - 1. ] * 11. } , 10 , 12 )   +   dominant_class ( Hydromet Seasonal_Forecast Precipitation Forecast TercProb Near_Normal )   ]", "  masklt [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 22 ]   +   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb Above_Normal ]  ", "masklt [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 22 ]", "dominant_class over C[Below_Normal, Above_Normal]", "dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb Above_Normal ]", "dominant_class over TercProb[<35, >80]", "  masknotrange [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 10 , 12 ]   +   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb Near_Normal ]  ", "masknotrange [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 10 , 12 ]", "dominant_class over C[Below_Normal, Above_Normal]", "dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb Near_Normal ]", "dominant_class over TercProb[<35, >80]", "  maskgt [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 0 ]   + [ (   dominant_class { Hydromet Seasonal_Forecast Precipitation Forecast TercProb Below_Normal }   * -1. ) + 12. ]", "maskgt [ ( {   dominant_class [ Hydromet Seasonal_Forecast Precipitation Forecast TercProb ]   - 1. } * 11. ) , 0 ]", "dominant_class over C[Below_Normal, Above_Normal]", "[   dominant_class ( Hydromet Seasonal_Forecast Precipitation Forecast TercProb Below_Normal )   * -1. ] + 12.", "dominant_class over TercProb[<35, >80]";
            Float32 missing_value NaN;
            String fnname "maskle";
            String CLIST ">80 Below", "75-80 Below", "70-75 Below", "65-70 Below", "60-65 Below", "55-60 Below", "50-55 Below", "45-50 Below", "40-45 Below", "35-40 Below", "<35 Below", "<35 Normal", "35-40 Normal", "40-45 Normal", "45-50 Normal", "50-55 Normal", "55-60 Normal", "60-65 Normal", "65-70 Normal", "70-75 Normal", "75-80 Normal", ">80 Normal", "<35 Above", "35-40 Above", "40-45 Above", "45-50 Above", "50-55 Above", "55-60 Above", "60-65 Above", "65-70 Above", "70-75 Above", "75-80 Above", ">80 Above";
            Int32 maxncolor 254;
            String colormap "null", "255", "255", "65535", "71", "16777215", "9", "16777215", "9", "10025880", "9", "25600", "71", "16777215", "16777215", "7", "16776960", "10", "13434880", "71", "13434880";
            String long_name "Dominant Tercile Probabilities";
            Int32 CE 33;
            Int32 CS 1;
            Int32 ncolor 254;
            Float32 scale_max 33.0;
            Float32 scale_min 1.0;
        }
        Forecast {
            Int32 pointwidth 0;
            Int32 expires 1707436800;
            Float32 missing_value -9999.0;
            String long_name "Forecast Mean";
            String units "mm";
            Int32 maxncolor 254;
            String colormap "null", "8036607", "8036607", "8036607", "8036607", "22", "42495", "42495", "14", "16776960", "13434880", "214", "13434880";
            Int32 CE 1700;
            Int32 CS 0;
            Int32 ncolor 254;
            Float32 scale_max 1700.0;
            Float32 scale_min 0.0;
        }
        PearsonR {
            Int32 pointwidth 0;
            Int32 expires 1707436800;
            String long_name "Pearson correlation skill values";
            Float32 missing_value -999.0;
            String units "unitless";
            Int32 ncolor 254;
            String colormap "null", "0", "8388608", "16711680", "25", "16760576", "26", "13959039", "39", "10025880", "26", "11920639", "11920639", "26", "65535", "36095", "38", "255", "38", "128", "39", "2763429";
            Int32 maxncolor 254;
            String colorscalename "correlationcolorscale";
            Int32 CE 1;
            Int32 CS -1;
            Float32 scale_max 1.0;
            Float32 scale_min -1.0;
        }
        PredErrorVars {
            Int32 pointwidth 0;
            Int32 expires 1707436800;
            Float32 missing_value -9999.0;
            String long_name "prediction error variance";
            String units "mm2";
            Int32 ncolor 254;
            String colorscalename "rainbowcolorscale";
            String colormap "null", "1973790", "16711680", "16776960", "51", "65280", "51", "65535", "51", "255", "51", "16711935", "51", "12632256";
            Int32 maxncolor 256;
            Int32 CS 0;
            Float32 scale_min 0.0;
        }
        TercProb {
            Int32 pointwidth 0;
            Int32 expires 1707436800;
            Float32 missing_value -1.0;
            String long_name "Tercile Probabilities";
            String units "percent";
            Int32 maxncolor 254;
            String colormap "null", "16777215", "16777184", "16777184", "44", "15658671", "15658671", "13", "13153410", "13153410", "12", "11834980", "11834980", "13", "12632256", "12632256", "2019940", "2019940", "10", "59045", "59045", "13", "65480", "65480", "12", "65535", "65535", "13", "54015", "54015", "12", "2139647", "2139647", "13", "2115034", "2115034", "12", "6303920", "83", "6303920";
            Int32 ncolor 254;
            String colorscalename "tercileclassesscale";
            Int32 CE 100;
            Int32 CS 0;
            Float32 scale_max 100.0;
            Float32 scale_min 0.0;
        }
    }
    hindcast_date {
        String standard_name "forecast_reference_time";
        String units "months since 1960-01-01";
        String calendar "360";
        String long_name "hindcast time";
        Int32 pointwidth 3;
    }
    hindcast_length {
        Float32 pointwidth 1.0;
        String calendar "360";
        Float32 missing_value NaN;
        String history "Averaged in T with overlapping interval 3";
        String units "days";
        String long_name "Length of hindcast time";
    }
    History{
        CrossValHind {
            Int32 pointwidth 0;
            String long_name "cross-validated hindcasts";
            Float32 missing_value -9999.0;
            String units "mm";
            Int32 maxncolor 254;
            String colormap "null", "8036607", "8036607", "8036607", "8036607", "22", "42495", "42495", "14", "16776960", "13434880", "214", "13434880";
            Int32 CE 1700;
            Int32 CS 0;
            Int32 ncolor 254;
            Float32 scale_max 1700.0;
            Float32 scale_min 0.0;
        }
        InputObs {
            Int32 pointwidth 0;
            String long_name "input observations";
            Float32 missing_value -9999.0;
            String units "mm";
            Int32 maxncolor 254;
            String colormap "null", "8036607", "8036607", "8036607", "8036607", "22", "42495", "42495", "14", "16776960", "13434880", "214", "13434880";
            Int32 CE 1700;
            Int32 CS 0;
            Int32 ncolor 254;
            Float32 scale_max 1700.0;
            Float32 scale_min 0.0;
        }
    }
    target_date {
        String standard_name "forecast_reference_time";
        String bounds "S";
        Int32 expires 1707436800;
        String units "months since 1960-01-01";
        String calendar "360";
        String long_name "forecast time";
        Int32 pointwidth 3;
    }
    target_length {
        Float32 pointwidth 1.0;
        String calendar "360";
        Float32 missing_value NaN;
        String history "Averaged in T with overlapping interval 3";
        String units "days";
        String long_name "Length of forecast time";
    }
NC_GLOBAL {
    Int32 expires 1707436800;
    String Conventions "IRIDL";
    Int32 Forecast.expires 1707436800;
    String Forecast.description "Forecast, Error and Skill";
    Int32 History.expires 1707436800;
    String History.description "Predictand and Hindcast";
}
}