AGU Fire Poster

1
How well can we determine the tropopause from
coarsely resolved model data? Thomas Reichler1,
Martin Dameris2, Robert Sausen2 (1) Meteorology
Department, University of Utah, Salt Lake City,
UT, USA (2) Institut fuer Physik der Atmosphaere,
Deutsches Zentrum fuer Luft- und Raumfahrt (DLR),
Germany
1. Objectives The vertical resolution of gridded
data in the vicinity of the tropopause is usually
on the order of 50 hPa. This raises the question
of how accurately the tropopause can be
determined from such coarse resolution data. We
present an accurate and robust method to
determine the tropopause height from gridded data
with low vertical resolution. The method is
verified by comparing the heights calculated from
analysis (ECMWF) with the observed heights at
individual radiosonde stations.
6. Overall verification
3. Observed tropopause We use operationally
reported tropopause heights from radiosonde
stations to verify our results. Daily heights for
January and July of 1992, 1993 and 1994 were used.
2. Method The algorithm uses a thermal definition
of the tropopause, which is based on the concept
of a threshold lapse-rate. We apply the same
criteria that are in use for the tropopause
determination from radiosonde soundings.
According to the WMO (1986), the tropopause is
defined as the lowest level at which the
lapse-rate decreases to 2C/km or less, provided
that the average lapse-rate between this level
and all higher levels within 2 km does not exceed
2C/km. Interpolation is performed to identify
the pressure at which this threshold is reached
and maintained for a prescribed vertical
distance.
Fig. 2 Distribution of the 340 regularly
reporting (Ndays ? 15) radiosonde stations that
were used for the evaluation.
4. Calculated tropopause Tropopause heights are
calculated using our algorithm from daily ECMWF
analyses in T42 resolution. Occasionally, no
tropopause could be determined, either because
the WMO criteria were not met, or because the
calculated height exceeded the lower or upper
limit. The failure rate was 0.1.
 
 
Fig. 4 Monthly mean differences between
calculated and measured tropopause pressures as a
function of latitude. Thin vertical lines denote
the temporal standard deviation of daily
differences (?), derived from all available time
series of a specific station.
5. European case study
7. Summary The mean rms-error of daily heights is
on the order of 30-40 hPa in the extratropics and
15 hPa in the tropics. The accuracy of the method
is limited by the resolution of the input data,
which is usually too coarse to resolve regional
structures and the steep tropopause gradients in
the tropical-extratropical transition zone.
Fig. 3 Time series of tropopause pressure over
Central Europe as calculated from analyses (top)
and as measured from radiosondes (middle). The
bottom panels show the differences (full line,
calculated minus measured), and the spatial
standard deviation (dotted line). The monthly
spatial standard deviation (?) and the monthly
mean (?) are specified in hPa. n denotes the
number of reports.
Fig. 1 Hypothetical temperature profile as a
function of pressure.
Table 1 Mean and rms-error (hPa) of model
derived tropopause pressure.