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The following procedures describe how to compute the pressure and geopotential on model levels, geopotential height and geometric height.
Pressure on model levels
In ERA5, pressure is provided at the surface, but not on individual model levels. However, pressure on model levels (p_ml) is shown in Figure 1, and can be computed using the procedure described below.
You will need the following Inputs:
logarithm of surface pressure (lnsp)
Code Block language py title Example to download ERA5 lnsp data for a given area at a regular lat/lon grid in NetCDF format collapse true #!/usr/bin/env python import cdsapi c = cdsapi.Client() c.retrieve('reanalysis-era5-complete', { # Requests follow MARS syntax # Keywords 'expver' and 'class' can be dropped. They are obsolete # since their values are imposed by 'reanalysis-era5-complete' 'date' : '2013-01-01', # The hyphens can be omitted 'levelist': '1', # 1 is top level, 137 the lowest model level in ERA5. Use '/' to separate values. 'levtype' : 'ml', 'param' : '152', # Full information at https://apps.ecmwf.int/codes/grib/param-db/ # The native representation for temperature is spherical harmonics 'stream' : 'oper', # Denotes ERA5. Ensemble members are selected by 'enda' 'time' : '00/to/23/by/6', # You can drop :00:00 and use MARS short-hand notation, instead of '00/06/12/18' 'type' : 'an', 'area' : '80/-50/-25/0', # North, West, South, East. Default: global 'grid' : '1.0/1.0', # Latitude/longitude. Default: spherical harmonics or reduced Gaussian grid 'format' : 'netcdf', # Output needs to be regular lat-lon, so only works in combination with 'grid'! }, 'ERA5-ml-lnsp-subarea.nc') # Output file. Adapt as you wish.
a(n) and b(n) coefficients defining the model levels; these are included in the GRIB header of each model level GRIB message and are also tabulated here.
The model half-level pressure (p_half) as shown in Figure 2 is given by:
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where sp (
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\text{sp} = e^{lnsp} |
) is the surface pressure (and lnsp is it's natural logarithm).
The pressure on model levels (p_ml) is shown in Figure 1, and is given by the mean of the pressures on the model half levels immediately above and below:
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This means that the pressure on model levels is in the middle of the layers defined by the model half levels (Figure 2).
For more details about the vertical discretisation please see Part-iii Dynamics and numerical procedures, section 2.2 and the FULL-POS documentation at:
http://www.umr-cnrm.fr/gmapdoc/spip.php?article157
Illustrations of model levels, model half levels and model layers
Figure 1. An illustration of IFS model levels, showing | Figure 2. An illustration of model half-levels and model layers. The pressure |
Geopotential on model levels
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In ERA5, geopotential (z) is provided at the surface, but not on individual model levels
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. However, geopotential on model levels can be computed using the procedure described below.
Inputs:
- geopotential
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- at the surface
- logarithm of surface pressure (lnsp)
- temperature and specific humidity on all the model levels
Output: Geopotential for each level, in m2/s2
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.
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In the procedure below, the output data is written in GRIB format.
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Please note, this procedure is an approximation to the calculation performed in the IFS
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(which also takes account of the effects of cloud ice and water and rain and snow).
Prerequisites to calculating Geopotential on model levels
You will need:
- A computer running Linux
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- Python3
The CDS API installed; Your computer must be set up for downloading ERA5 model level data (from the 'reanalysis-era5-complete' dataset, stored in ECMWF's MARS catalogue) through the CDS API. For more details, please follow the instructions here (step
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B).
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- The ecCodes
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- library to read and write data.
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Step 1: Download input data
First
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we must retrieve the required ERA5 data. We need:
- Temperature (t) and specific humidity (q) on each model level.
- The logarithm of surface pressure (lnsp) and geopotential (z) on model level 1.
We use a Python script to download the ERA5 data from the MARS catalogue
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using the CDS API. The procedure is:
- Copy the script below to a text editor on your computer
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- Edit the date, type, step, time, grid and area in the script to meet your requirements
- Save the script (for example with the filename as 'get_data_geopotential_on_ml.py')
- Run the script
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#!/usr/bin/env python import cdsapi c = cdsapi.Client() # data download specifications: cls = "ea" # do not change expver = "1" # do not change levtype = "ml" # do not change stream = "oper" # do not change date = "2018-01-01" # date: Specify a single date as "2018-01-01" or a period as "2018-08-01/to/2018-01-31". For periods > 1 month see https://software.ecmwf.int/wiki/x/l7GqB tp = "an" # type: Use "an" (analysis) unless you have a particular reason to use "fc" (forecast). time = "00:00:00" # time: ERA5 data is hourly. Specify a single time as "00:00:00", or a range as "00:00:00/01:00:00/02:00:00" or "00:00:00/to/23:00:00/by/1". c.retrieve('reanalysis-era5-complete', { 'class' : cls, 'date' : date, 'expver' : expver, 'levelist': '1/2/3/4/5/6/7/8/9/10/11/12/13/14/15/16/17/18/19/20/21/22/23/24/25/26/27/28/29/30/31/32/33/34/35/36/37/38/39/40/41/42/43/44/45/46/47/48/49/50/51/52/53/54/55/56/57/58/59/60/61/62/63/64/65/66/67/68/69/70/71/72/73/74/75/76/77/78/79/80/81/82/83/84/85/86/87/88/89/90/91/92/93/94/95/96/97/98/99/100/101/102/103/104/105/106/107/108/109/110/111/112/113/114/115/116/117/118/119/120/121/122/123/124/125/126/127/128/129/130/131/132/133/134/135/136/137', # For each of the 137 model levels 'levtype' : 'ml', 'param' : '130/133', # Temperature (t) and specific humidity (q) 'stream' : stream, 'time' : time, 'type' : tp, 'grid' : [1.0, 1.0], # Latitude/longitude grid: east-west (longitude) and north-south resolution (latitude). Default: 0.25 x 0.25 'area' : area, #example: [60, -10, 50, 2], # North, West, South, East. Default: global }, 'tq_ml.grib') c.retrieve('reanalysis-era5-complete', { 'class' : cls, 'date' : date, 'expver' : expver, 'levelist': '1', # Geopotential (z) and Logarithm of surface pressure (lnsp) are 2D fields, archived as model level 1 'levtype' : levtype, 'param' : '129/152', # Geopotential (z) and Logarithm of surface pressure (lnsp) 'stream' : stream, 'time' : time, 'type' : tp, 'grid' : [1.0, 1.0], # Latitude/longitude grid: east-west (longitude) and north-south resolution (latitude). Default: 0.25 x 0.25 'area' : area, #example: [60, -10, 50, 2], # North, West, South, East. Default: global }, 'zlnsp_ml.grib') |
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Running the script produces two new files in the current working directory:
- 'tq_ml.grib' (a GRIB file containing temperature and specific humidity)
- 'zlnsp_ml.grib' (a GRIB file containing geopotential and log of surface pressure).
Step 2: Compute geopotential on model levels
We then use a Python script to compute geopotential (z) for all model levels:
- Copy the script below to a text editor
- Save the script as 'compute_geopotential_on_ml.py'
- Run the script 'compute_geopotential_on_ml.py' with the correct arguments, i.e. :
python compute_geopotential_on_ml.py tq_ml.grib zlnsp_ml.grib -o z_on_ml.grib
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This script is from ECMWF's generic article Compute geopotential on model levels .
Alternatively, there is a customer-supplied script (which runs on Microsoft Windows) that computes geopotential on model levels
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for a specific location. This script was written for the ERA-Interim dataset, but can be adapted to ERA5. Please see the article ERA-Interim: compute geopotential on model levels for details.
Geopotential height
In ERA5, and often in meteorology, altitudes (the altitude of the land and sea surface, or specific altitudes in the atmosphere) are not represented as geometric altitude (in metres above the spheroid), but as geopotential height (in metres above the geoid, which is represented by the mean sea level in ERA5). However, ECMWF archive the geopotential (in m2/s2), not the geopotential height.
To obtain the geopotential height (h) of the land and sea surface in metres, simply divide the geopotential (geopotential at the surface is called orography in the Climate Data Store (CDS)) by the Earth's gravitational acceleration, 9.80665 m/s2. This geopotential height is relative to mean sea level - for more information see ERA5: data documentation.
Geometric height
The geometric height or altitude (alt) is given by:
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where Re is the radius of the Earth. This geometric height is relative to mean sea level and it is assumed that the Earth is a perfect sphere - for more information see ERA5: data documentation - spatial reference systems.
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This document has been produced in the context of the Copernicus Climate Change Service (C3S).The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.The users thereof use the information at their sole risk and liability. For the avoidance of all doubt, the European Commission and the European Centre for Medium-Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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