TropopauseEstimate

This obsfunction creates a first-guess estimate of the tropopause pressure that is based on latitude with some adjustment for day-of-year. An optional parameter can convert the final answer from pressure to height using convert_p2z: true. The code in this method is crude and purely designed for estimating the tropopause when lacking a model-derived estimate that may otherwise arrive via GeoVaLs.

To begin, the code assumes an equatorial belt of 15 degrees north and south of the equator then applyies a linear transition toward the poles starting from 130 hPa and lowering to 370 hPa. To account for the seasons, the so-called equator is shifted to be about one month delayed from actual solar solstice to mimic that July (January) is typically hotter and has a corresponding higher tropopause than June (December) in the northern (southern) hemisphere.

Options

convert_p2z: true will use an ultra simple approximation of ICAO standard atmosphere from pressure to height because the code is making a tropopause estimate only.

tropo_equator is used to specify the pressure of the tropopause in the equatorial belt.

tropo_pole is used to specify the pressure of the tropopause at the poles.

Example 1

The most useful example of this obsfunction is to reject satellite-derived atmospheric motion vectors (satwinds) data when their vertical level information implies they exist well above the tropopause since clouds (which are tracked to provide a motion vector) are not likely to occur in the clear air of the stratosphere. This is handled by a Difference Check filter in which the air_pressure@MetaData is more than some threshold lower (higher altitude) than the supposed tropopause.

- filter: Difference Check
  filter variables:
  - name: eastward_wind
  - name: northward_wind
  reference: TropopauseEstimate@ObsFunction
  options:
    - tropo_equator: 13000         # 130 hPa
    - tropo_pole: 37000            # 370 hPa
  value: air_pressure@MetaData
  minvalue: -5000                  # 50 hPa above tropopause level, negative p-diff

Example 2

Another possible usage for this obsfunction is to inflate the observational error of water vapor (specific_humidity) or satellite radiance data when above the tropopause where clouds are nearly impossible to form.