Temperature

BCRMSE

     • BCRMSE displays a diurnal signal and a general increase with lead time for both the 00 and 12 UTC initializations and for all temporal aggregations.

Bias

     • A cold bias is observed at all forecast lead times for both 00 and 12 UTC initializations. The bias displays a strong diurnal modulation on top of a gentler trend of increasing bias (more negative) with lead time. The cold bias magnitude is the largest around 00 UTC, and smallest at 12 UTC for both 00 and 12 UTC initializations.

Dew Point Temperature

BCRMSE

     • BCRMSE displays a diurnal signal and a general increase with lead time for both the 00 and 12 UTC initializations and for all temporal aggregations.

Bias

     • Similar to the surface temperature, the surface dew point temperature displays a diurnal signal and general increasing trend with forecast lead time. When the cold bias in surface temperature is strongest, the dew point temperature exhibits a large wet bias.

Wind

BCRMSE

     • BCRMSE displays a diurnal signal and a general increase with lead time for both the 00 and 12 UTC initializations and for all temporal aggregations.

Bias

     • Similarly, wind speed bias shows strong diurnal variations for both initialization times and all temporal aggregations. A higher wind bias is typically seen in the forecasts for the overnight hours, and lower wind bias is seen during the daytime hours for the CONUS verification domain.
     • Apart from the diurnal trend, there is a shift of the bias toward negative values (low wind bias) for the West verification domain, and higher wind bias values for the East verification domain.
     • TWIND1 provides forecast improvement in during the overnight hours.

3-hourly and Daily Precipitation Accumulation

     • Regardless of initialization or forecast lead time, the 3 - hourly and daily QPF GSS steadily decreases as the threshold increases, while the 3-hourly and daily QPF frequency bias steadily increases as the threshold increases.

Temperature

BCRMSE

     • Regardless of forecast lead time or temporal aggregation, a minimum in the BCRMSE values occurs between 500 and 300 hPa and increases to a maximum at both the near-surface and upper levels.

Bias

     • For all temporal aggregations, a SS cold bias is seen for all lead times at the 850 hPa level transitioning to a SS warm bias with height. The level of transition occurs near 700 to 500 hPa, but is dependent on temporal aggreagtion and lead time. One exception is often noted at 150 hPa where there is large variability in the bias. A vertical local minimum is noted which translates into a larger cold bias or a smaller warm bias at that level.

Dew Point Temperature

BCRMSE

     • As the pressure level decreases from 850 to 50 0 hPa and the forecast lead time increases from 12 hours to 48 hours, the BCRMSE values general ly increase for all temporal aggregations.

Bias

     • A SS high bias is noted for most forecast leve ls and lead times for each temporal aggregations except summer, which has a SS low bias at 700 hPa for the 36-hour lead times.
     • Similar to the results for BCRMSE with pressur e level, the highest bias is seen at the 500 hPa level.

Wind

BCRMSE

     • A general increase from the minimum BCRMSE val ues at the lowest levels (typically at the 850 or 700 hPa level) to a maximum at the generally found at 300 hPa to 200 hPa level for all forecast lead times and temporal aggregations, is noted.
     • Overall, the errors generally range from 2.4 - 6.3 m s^-1 depending on lead time and temporal aggregation, with a SS increase in BCRMSE values between the 12- and 48-hour lead times seen for several levels.

Bias

     • In general, there is a SS low wind speed bias starting from the 12-hour lead time at all levels below 150 hPa, regardless of the temporal aggregation.
     • The forecast bias values are the smallest at the upper-most levels. The wind speed is unbiased most frequently at 850 hPa for all season aggregations.
     • The largest (low wind speed) bias is observed at 200 hPa for all temporal aggregations.