4. Environmental discriminators for Surface-based and Elevated Thunderstorms

Objective

  1. Compare Bureau of Meteorology Temperature soundings to ECMWF Era Interim Temperatures, by calculating the MEAN T differences (Tdiff = Tbom - Tera), at all Era Int pressure levels

  2. Compare Bureau of Meteorology Temperature soundings to ECMWF Era Interim Temperatures, by calculating the MEAN TD differences (TDdiff = TDbom - TDera), at all Era Int pressure levels

  3. Calculate standard deviation of all T differences at all Era Int pressure levels

  4. Calculate standard deviation of all TD differences at all Era Int pressure levels

  5. identify stable layers in BoM sounding data

  6. identify stable layers in Era Int data

  7. Calculate percentage of BoM stable layers NOT captured by Era Int

An Atypical Approach to Discriminating ES from SS

3. Era Int

  • - what it is

  • - how it reanalyses the data (interpolate from model levels to pressure levels therefore smoothing of fields?)

  • - surface and upper air observations – what is ingested and when for Australia

4. BoM Soundings

  • - what it is and the network

  • - how is it is detected

  • - strengths and limitations

2. Era Int Verification with BoM Soundings

  • - proximity GPATS to BoM soundings space and time – why +-1 hour and +-0.25deg

  • - BoM soundings capital cities 2008-2014 with GPATS in proximity – BoM TS soundings

  • - BoM TS soundings mapped to EraInt times (00,06,12,18) if sounding time is within 23-00, 05-06, 11-12, 17-18

  • - BoM TS soundings reduced to Era Int vertical resolution

  • - EraInt soundings at same locations and times

  • - EraInt soundings reduced to BoM TS sounding max elevation

  • - Thermodynamic indices calculated using SHARPpy – Tv corrections in CAPE/CIN calculations

Many thunderstorm climatologies use surface and upper air observations to discriminate ES from SS. Again there is concern too few identified Australian ES events would result from observations-based discriminators. As an alternative to sparse surface and upper air observations, the ECMWF Era Interim Reanalysis (hereafter referred to as EraInt) does have finer spatial resolution (spatial information on a 0.75 degrees x 0.75 degrees grid), however the vertical and temporal resolution is courser ( 37 vertical levels, 6 hour temporal resolution). Like other model-based reanalyses, EraInt contains biases. Bao and Zhang (2013) compared 3000 observed soundings from the Tibetan Plateau, a region where observed soundings are excluded from EraInt reanalysis, thus EraInt are independent of observed soundings. Large moist mean biases through lowest 300hPa depth were found (relative humidity +10 to +25% above observed), along with small low level low level cool mean biases (-0.25 to -1.5 degrees Celsius). To investigate if these same mean biases occur in Australia, observed and EraInt soundings at 2 sites (one coastal and one inland) for one year will be compared.

Despite EraInt reanalysis low level moist and cool biases shown by Bao and Zhang (2013), Allen and Karoly (2013) found EraInt surface mixed-layer (50mb depth) CAPE