TroughIdentification

Trough Identification

Thomas Schartner

*

Institut für Meteorologie, Freie Universität Berlin

Version from June 9, 2016

*

thomas.schartner@met.fu-berlin.de

This is only a brief documentation about the Trough Identification Plugin and is currently still under construction. Comments or any kind of feedback is highly appreciated. Please send an e-mail to the authors.

1 Introduction

Precipitation in the the equatorward part of the midlatitudes and the subtropics are connected with minima of geopotential height in the mid- and upper troposphere [Knippertz, 2003]. The mechanism is caused by the advection of positive vorticity in front of a moving upper-level trough. The advection of positive vorticity leads to divergence and dynamical lifting while the equatorward transport of cold air back of the trough axis leads to a destabilsation of the atmosphere. Upper Level troughs may but need not be induce surface cyclogenesis. In section 2, the methods of the calculation procedure are described [Knippertz, 2004] Sections 3 and 4 explain the input respectively the output of the TroughIdentification. In the last section (4) an example is given.

2 Methods

2.1 Throug Identification

The trough identification scheme assumes a basically north-south-oriented axis of minimum geopotential height, which measures up the mostly wavy structures often found on the anticyclonic side of the polar jet, where troughs tend to stretch out meridionally and thin. The scheme should be applied on the 500-hPa geopotential height field. The following figures shows the most important steps for the identification:

Figure 1: (a) Definition of the TP (trough parameter)

First, 500-hPa geopotential height averages are calculated over a 3x4 gridpoint box $Z_{2}$ and the 3x5 gridpoint boxes $Z_{1}$ and $Z_{3}$ to the west and east of $Z_{2}$ . The so-called trough parameter (TP) at the center point P of $Z_{2}$ is then defined as the difference between the mean over $Z_{1}$ and $Z_{3}$ minus the mean over $Z_{2}$ . This reflecting the zonal geopotential height gradient assuming a longitudinal extension of the trough of about 2000 km (at 35 $\circ$ N).

Figure 2: (b) horizontal distribution of TP for the underlaid real example; light shadding: TP >25 gpm, dark shading: TP >100 gpm

If TP is greater than 25 gpm (lightly shaded area in figure 2), P is denoted as trough point. The point P with the maximum value TP along a longitudinal range of trough points is termed a trough axis point (TAP).

Figure 3: shematic of the trough axis definition. The trough axis is marked by a thick black line in figure 2

Several of those are aligned to a trough axis, provided that the TAPs on neighboring lines of latitude are not more than two grid point(5 $\circ$ ) apart in the longitudinal direction (black lines in the conceptional sketch of figure 3). Upper-Level cyclones are characterized by ther nort-south axis and not by the location of their center.

A detailed discussion about the scheme and an application can be found in [Knippertz, 2004].

3 Input

The calculation of the trough identification is based on 6 hourly geopotential height field in 500 hPa.

Outputdir	Output directory
mandatory	default: /scratch/user/evaluation_system/output/troughidentification
Cachedir	Cache directory
mandatory	default: /scratch/user/evaluation_system/cache/troughidentification
Cacheclear	Option switch to NOT clear the cache.
mandatory	default: True
Variabel	geopotential height (zg)
mandatory	default: zg
Project	Choose project, e.g. reanalysis, cmip5, baseline1, baseline0
mandatory
Product	Choose product, e.g. reanalysis, output
mandatory
Institute	Choose institute of experiment, e.g. MPI-M, ECMWF
mandatory
Model	Choose model of experiment, e.g. MPI-ESM-LR, IFS
mandatory
Experiment	Choose experiment name, e.g. decadal1971, ERAINT
mandatory
Ensemble	Choose ensemble, e.g. r1i1p1, r2i1p1 or ”*” for all members
mandatory	default: *
Firstyear	Choose first year to be processed.
Lastyear	Choose last year to be processed.
Level	Choose level [in Pa], e.g. 50000 only reasonable for zg
mandatory	default: 50000
Ntask	Number of tasks.
mandatory	default: 24
Makepic	Set ”True” for make picture with tool movieplotter
mandatory	default: False
Dryrun	Set ”True” for just showing the result of find_files and set ”False” to process data.
mandatory	default: True
Caption	An additional caption to be displayed with the results

Table 1: Input options for Trough Identification

At first, you have to specify your output (Outputdir) and cache (Cachedir) directories. The data paths of input files can be selected via the typical MiKlip data structure. Choose the Project, Product, Institute, Model and Experiment you want to process. Further, select ensemble member(s) in the Ensemble field and specify the variable (Variable) you want to analyze. In Firstyear and Lastyear you can choose the range of years which will be processed. The upper level (Level up) and bottom level (Level down) can be chosen. Finally, you have the option to visualize some results (Makepic), to remove the cache directories (Cacheclear) and to show the found input file(s) from your input parameters based on freva - -databrowser (Dryrun).

4 Output

The processed files can be found in the selected Outputdir. The ti file contain the trough parameter, the trough points, the trough axis points, the trough axis, the number of through points and the number of trough axis points. If selected, the trough axis is visualized in a time loop for the first ten time steps.

Figure 4: Example of Trough Axis for ERA-int (1990-01-01 00 UTC).

References

Peter Knippertz. Tropical-extratropical interactions causing precipitation in northwest africa: statistical analysis and seasonal variations. Monthly weather review, 131(12):3069–3076, 2003.

Peter Knippertz. A simple identification scheme for upper-level troughs and its application to winter precipitation variability in northwest africa. Journal of climate, 17(6):1411–1418, 2004.