@ -17,10 +17,10 @@ The basic work-flow when using Grond is as follows:
1. Set up a project folder containing input data and Green's functions.
2. Set up a configuration file for Grond.
3. Check the set-up with :option:`grond check`.
3. Check the setup with :option:`grond check`.
4. Run the optimisation with :option:`grond go`.
5. Create result plots and report with :option:`grond report`.
6. Export results with :option:`grond check`.
6. Export results with :option:`grond export`.
Details on these steps are given in the following sections.
@ -30,7 +30,7 @@ Details on these steps are given in the following sections.
Project folder layout
---------------------
To use Grond with your data and earth model of your choice, we suggest the following folder structure.
To use Grond with your own dataset, we suggest the following folder structure.
Single files and data formats listed here are explained below. The folders ``runs`` and ``reports`` are generated during and after the optimisation, respectively.
@ -76,10 +76,10 @@ Single files and data formats listed here are explained below. The folders ``run
Input data (observables)
------------------------
Grond can combine different observational input data in an earthquake source optimisation:
Grond can combine different observational input data in an earthquake source optimisation.
1. Seismic waveform data
........................
Seismic waveform data
.....................
Required input files are:
@ -90,26 +90,26 @@ Various tools exists to download raw waveforms and instrument response informati
Grond can use continuous data (recommended) as well as event-based cut-outs. **If event-based data is used, make sure that the time windows are long enough.** Generously enlarge the window before and after the signal to be analysed. Add at least 5 times the longest period to be analysed to both sides. Add more if pre-event noise should be analysed for data-weighting.
2. InSAR data
.............
InSAR data
..........
Grond uses `Kite`_ containers for surface deformation maps.
`Kite`_ provides an interactive tool for inspection and transport of static displacement maps. It can be used for data noise estimations, easy quadtree data sub-sampling and calculation of data error variance-covariance matrices for proper data weighting.
Grond requires :file:`kite_scene.yml` and :file:`kite_scene.npz` which can be generated by `Kite`_.
Grond requires files like :file:`kite_scene.yml` and :file:`kite_scene.npz` which can be generated by `Kite`_.
3. GNSS data
............
GNSS data
.........
Required input file is a simple `YAML`_ file containing GNSS station positions, displacement values and measurement uncertainties. The `Pyrocko`_ manual provides more information on the `GNSS data handling`_.
Green's functions stores
------------------------
Green's function stores
-----------------------
A Pyrocko Green's function (GF) store is needed for forward modelling seismograms and surface displacements. Such a GF store holds transfer functions for many possible source-receiver configurations which can be looked up quickly.
You can either download from the online repository (`online GF databases`_) or compute them with the `fomosto`_ module of `Pyrocko`_. Depending on the application, different set-ups of GF stores or methods for calculation are suitable:
You can either download them from the online repository (`online GF databases`_) or compute them with the `fomosto`_ module of `Pyrocko`_. Depending on the application, different setups of GF stores or methods for calculation are suitable:
@ -121,17 +121,17 @@ For the point-source analysis of large global earthquakes, a global GF store wit
::
fomosto download kinherd global_2s store
fomosto download kinherd global_2s
GFs for regional and local seismic waveform data
................................................
Regional analyses may require region-specific GF stores. Given a suitable 1D-layered velocity model, GF stores can be built with the `Fomosto QSEIS backend`_.
Regional analyses may require region-specific Green's functions. Given a suitable 1D-layered velocity model, GF stores can be built with the `Fomosto QSEIS backend`_.
GFs for near-field static displacement data (InSAR, GNSS)
Near-field static displacements require high spatial sampling and mostly only little temporal sampling. With the `Fomosto PSGRN/PSCMP backend`_, you can build your on GF store for any given local 1D-layered velocity model.
Near-field static displacements require high spatial sampling and mostly only little temporal sampling. With the `Fomosto PSGRN/PSCMP backend`_, you can build your own GF store for any given local 1D-layered velocity model.
Terminology
-----------
@ -155,22 +155,22 @@ strategies.
The dataset is a section in the config file telling Grond where to look for input data (waveforms, InSAR scenes, GNSS data) and meta-data (station coordinates, instrument responses, blacklists, picks, event catalogues, etc.).
Misfit
The misfit is the value of the objective function obtained for a given source model proposal. The global misfit may by aggregated from weighted contributions of multiple Grond targets (see below).
The misfit is the value of the objective function obtained for proposed source model. The global misfit may by aggregated from weighted contributions of multiple Grond targets (see below).
Target
In a typical Grond set-up, many modelling targets may contribute to the global misfit. For example, An individual modelling target could be a single component seismogram at a given station, an InSAR scene, or an amplitude ratio at one station. The target knows how to filter, taper, and weight the data. It also contains configuration about how to compare synthetics with the observations to obtain a misfit contribution value (e.g. time-domain traces/amplitude spectra/cross correlations, L1-norm/L2-norm, etc.).
In a typical Grond setup, many modelling targets may contribute to the global misfit. For example, an individual modelling target could be a single component seismogram at a given station, an InSAR scene, or an amplitude ratio at one station. The target knows how to filter, taper, and weight the data. It also contains configuration about how to compare synthetics with the observations to obtain a misfit contribution value (e.g. time-domain traces/amplitude spectra/cross correlations, L1-norm/L2-norm, etc.).
Problem
In the context of a Grond set-up, the "problem" groups the choice of source model and parameter bounds to be used in the optimisation.
In the context of a Grond setup, the "problem" groups the choice of source model and parameter bounds to be used in the optimisation.
Analyser
Before running the optimisation, station weights and other internal parameters may need to be adapted to the observed data and configured set-up of Grond. Such pre-optimisation tasks are done by one or more of Grond's analysers.
Before running the optimisation, station weights and other internal parameters may need to be adapted to the observed data and configured setup of Grond. Such pre-optimisation tasks are done by one or more of Grond's analysers.
Optimiser
This refers to the optimisation strategy, how to sample model space to find solutions in a given Grond set-up.
This refers to the optimisation strategy, how to sample model space to find solutions in a given Grond setup.
Store
Refers to Green's functions databases to be used for the forward modelling. In Grond these stores are adressed with paths and an individual ``store_id``.
Refers to Green's functions databases to be used for the forward modelling. In Grond these stores are adressed with directory paths and an individual ``store_id``.
Engine
Forward modelling in Grond is done through the Pyrocko GF engine, which allows fast forward modelling for arbitrary source models based on pre-calculated Green's functions stores (databases). Its configuration may contain information about where to find the pre-calculated Pyrocko Green's function stores.
An empty project structure can be created with the subcommand :option:`grond init`. Different configurations can be added by flags, see ``grond init --help`` for more information.
An empty project structure can be created with the subcommand :option:`grond init`. Different configurations can be added by flags (see :option:`grond init```--help``).
.. code-block :: sh
@ -214,14 +214,14 @@ This is the default and corresponds to
Identically, for static near-field displacement (InSAR, GNSS data sets) and finite source optimisation set-ups, initial Grond configuration file can be created with
Identically, for static near-field displacement (InSAR, GNSS data sets) and finite source optimisation setups, initial Grond configuration file can be created with
The ``targets`` (data and misfit setups for seismic waveforms, InSAR and or GNSS data) can be combined and sources types can be exchanged. A Grond configuration file showing all possible options with their default values is given using:
The different ``targets`` (data and misfit setups for seismic waveforms, InSAR and or GNSS data) can be combined and source model types can be exchanged. A Grond configuration file showing all possible options with their default values is given using:
.. code-block :: sh
@ -354,7 +354,8 @@ The results can be exported in various ways by running the subcommand
