Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.
Scroll pdf ignore
Panel
titleDownload
Expand
titleClick here for files to download...
Excerpt Include
A Quick Tour of Metview
A Quick Tour of Metview
nopaneltrue

Attachments
uploadfalse
oldfalse
patterns*.tar.gz,*.grib,*.grb
sortByname

Overview

...

One of Metview's most powerful features is its data processing ability. Data from various sources can be combined and manipulated using high- or low-level commands.

XXXX Download data

Fieldset Manipulation

A fieldset is a collection of fields stored physically in GRIB files. Metview has many built-in functions and operators to manipulate fieldsets, from simple arithmetic operators to vertical integrations through the atmosphere. Many of these operations are available from the icon-based user interface, all are available in the Macro language. The results can be stored on disk, or passed to other functions for further manipulation.

Most of these functions work on each gridpoint value of each field in the fieldset. For example, if we add 1 to a fieldset which contains 3 fields, this will return a new fieldset with 3 fields, the values of which whose gridpoints are 1 greater than those in their respective input fields, as shown below:

...

This example also illustrates what happens when missing values are in the data, represented here by an "x". In most cases it is not valid to use the missing value in the result, so that point in the result will itself be set to the missing value indicator.

The meta-data in a resulting field is taken from the first field in the computation.

Computing a Forecast - Analysis Difference

...

As a simple example, let's compute the difference between a set of forecast fields and the corresponding set of analysis fields for the same time step.

Have a look at Examine the supplied GRIB files (right-click, examine) to confirm that temperature_forecast.grib contains, at multiple vertical levels, 48-hour temperature forecasts for the same date and time as the analysis data in temperature_analysis.grib.

Create a new Simple Formula icon and rename it to fc_an_diff. Edit the icon, ensure that the first tab Formula type is selected (F+G) and that the operator is minus ( - ). Drop your temperature_forecast.grib icon into the Parameter 1 box, and drop temperature_analysis.grib into the Parameter 2 box. Save the icon and execute it. The icon should turn green, indicating the result has been computed and cached. Further operations on this icon will not re-compute the result unless either of its input icons are modified. If you simply wanted the result to be stored, you could right-click and choose save result to bring up a file save dialogue; but instead choose visualise to plot it. Note that all 6 fields in each data icon are used in the computation - the result is a set of 6 fields.

The solutions folder contains two Two Contouring icons are supplied, which can be used to show the differences. Drop pos_shade and then neg_shade into the Display Window. Notice that the second one replaces the first one - this is not what we want! Select both icons with the mouse and drop them both together into the Display Window to use them both in the plot. Edit the icons to see which parameters were used to create the positive and negative shading effects. There is also a Contouring icon called rainbow_diffs - this uses Metview's ability to draw isolines of different colours rather than using shading. This can be useful if it is important to see another layer underneath the temperature.

We could have done this a bit quicker - there was no need to execute the fc_an_diff icon. If you Clear the cache by right-click clicking the icon and choose choosing clear result, you can now directly choose visualise . Now directly visualise the icon - the execute action is performed in the background, as it is required before visualisation can occur.

...

Ensure that the difference fieldset is visualised with the a contouring applied. One way to generate a Metview Macro script from this plot is to click the Generate Macro button (also available from the File menu). A new Macro script will be generated - have a look at it to confirm that it contains code to read the data, compute the difference and plot the result. Run the macro to obtain the plot, either by using the Run button from the Macro Editor, or by selecting visualise from the icon's context menu). By default, the macro is written so that it will produce an interactive plot window; it will generate a PostScript file if it is run with the execute command, or if it is run from the command line.

...

Create a new Observation Filter icon and rename it to filter_obs_t2m., setting these parameters:

DataDrop the obs.bufr icon here
OutputGeographical Points
Parameter012004

Note that 012004 is the code for 'Dry bulb temperature at 2m'. Confirm that the result of this icon's filtering is a set of geopoints with temperature values.

...

Computing Wind Speed from U/V

The GRIB file uv850.grib contains forecast data for U and V wind components at 850hPa at various forecast steps (visualise it to confirm). The task is to compute the wind speed from this using a macro, so create a new Macro icon, rename it compute_wind_speed and edit it.

...

  1. filter the U wind component into a variable called u (you may find it useful to use the GRIB Filter icon to do this and then drop it into the Macro Editor)
  2. filter the U V wind component into a variable called v
  3. apply the formula speed = sqrt(u*u + v*v)

  4. plot the result

...

  1. apply some shading to the data with a Contouring icon, only contouring wind speeds above 20m/s
    1. note that we use Wind Plotting icons to modify the plotting of vector fields, but this is now a scalar field, so we use the Contouring icon
  2. overlay the original wind field and change the colour of the arrows to 'charcoal' with a Wind Plotting icon
  3. shade the land and the sea with a Coastlines icon

Returning the Result of a Computation for Further Interactive Use

The result of the above macro does not have to live entirely inside the macro - it can be passed back to the user interface or used as input to other icons. Do this:

  1. in the above macro, comment out the plot() command (using the hash, #, symbol)
  2. add a new line of code at the end:
    return speed

This passes the fieldset speed back to the user interface. Try it by right-clicking on the macro's icon and selecting examine, save or visualise. This icon can also be dropped into an existing Display Window to plot the data there. It could also be used as an input to another icon, for example a Simple Formula icon, for further processing.

Writing the result of a computation to disk

Again, modify the last line of the compute_wind_speed icon so that we now instead write the result to a file:

...

A full path could also have been supplied if you do not wish the file to be written to the current directory.

Field Interpolation and Sub-area Extraction

Metview's GRIB Filter icon has parameters which enable the interpolation of data onto a new grid, or the extraction of a sub-area of data. This can be useful if you wish to compare two fields which are currently at different resolutions (e.g. from different model runs) - both fields need to be on the same grid before Metview can perform computations between them.

Field Interpolation

Image Added

Visualise the U wind field (via the GRIB Filter icon you created earlier) and apply the supplied gridpoints icon The GRIB icon reduced_gg_320 contains one field which is stored as a reduced Gaussian grid. Visualise the field and apply the gridpoints icon (in the solutions folder) to display the locations of the grid points - they are on a regular 1.5 degree grid.

Now create a new GRIB Filter icon with these parameters:

DataDrop
the reduced_gg_320
the uv850.grib icon here
ParamU
Grid2.5/2.5

The result will be the same data interpolated onto a 2x2 2.5x2.5 degree grid. Visualise the result and apply the supplied gridpoints icon to confirm the new grid. Visualise the two fields side-by-side with coloured contour shading to also confirm that they look very similar in terms of their data values.

Sub-area Extraction from a Fieldset

Image Added

The GRIB Filter icon also allows the extraction of a sub-area from a fieldset. Create a new one and, using the Area parameter, extract just the data over a region for any of the supplied GRIB files. The area is defined as a list of 4 numbers, forward slash-delimited, representing its North/West/South/East bounds.

Conversion Between Fields and Points

...

Image Added

Metview provides two icons, Geopoints to GRIB and GRIB to  Geopoints To Grib and Grib To Geopoints for the purpose of converting between GRIB (gridded) and geopoints (scattered) formats.

Use a GRIB to Geopoints icon to convert the result of the last exercise GRIB file temperature_analysis.grib to geopoints format. Examine the result to confirm that it is now geopoints and that we have a list of all the individual points. You can also visualise it, applying the supplied symb_colours icon. Converting to geopoints format is an easy way to export the data in an ASCII format.

Use a Geopoints to GRIB icon to convert the geopoints result of the fc_obs_diff icon to GRIB. We now have gridded data derived from scattered points. This icon contains some parameters to help define the output grid and the interpolation process used in the conversion; it is also possible to supply a template GRIB file which will be used to define the output grid.

Extra Tasks

Computing

...

Adapt the macros from this tutorial so that they compute relative differences rather than absolute differences between the values. By this we mean compute the differences as percentages of the original analysis values. You will need to create new Contouring and Symbol Plotting icons to plot these nicely.

Overlaying wind speed with wind arrows

...

statistics fields

Your forecast-analysis difference macro works on fieldsets containing 6 fields (6 different vertical levels in the atmosphere), so the result also contains 6 fields. Instead of plotting all 6 fields, compute fields which represent the minimum, maximum and means of these fields. For example, if we have 6 fields in fieldset variable fs, then the following code computes a single field, the values of which are the minimums across all 6 input fields:

Code Block
languagepy
min_field = min(fs)

Plot the results and cross-reference with the original result of 6 fields to confirm that you understand what has been computed.

Extract field values at a set of locations

Extract the temperature values from the t2m_forecast.grib file at all the locations in the geopoints data returned by the filter_obs_t2m icon. Hint:

  • the Macro function interpolate(field, geopoints) returns a new geopoints variable whose locations are from its input geopoints and whose values are interpolated from the input field

Extracting point values

There are many ways to extract the value of a field at a given point or set of points. Try this one - call nearest_gridpoint_info ( fieldset,number,number ) with the latitude and longitude of a geographical location and print the result to see which data gridpoint is closest to it.

Automatic conversion between grids

Write some macro code which automatically converts t2m_forecast.grib to use the same grid as the first field in uv850.grib. Hints:

  • read both files
  • use the grib_get_double(fieldset, string) function twice to extract the grid resolution from the first field in uv850 (uv850[1])
    • use the Grib Examiner to find which GRIB_API keys define these parameters
  • use the read() command to set the grid on the temperature field