UCVM muscal
This page describes the Multi-Scale CALifornia (MUSCAL) velocity model and its integration into UCVM.
Contents
Model overview
The MUSCAL Vp and Vs model was created by Te-Yang Yeh and Yehuda Ben-Zion in 2025-6 by starting with the CANVAS tomography model as a base and then integrating multiple regional and local high-resolution models. Each submodel is evaluated to determine where it improves the fit through simulations of M4 historical events to 1 Hz, and then the overall model is updated where the submodel improves the fit.
Model Components
The model was built by starting with a base model (the CANVAS (Doody et al., 2023) tomography model). Next, regional and local models are added where they improve the fit, based on M4 simulations. These simulations were run to 1 Hz with topography using a minimum Vs of 450 m/s. Finally, a spatially varying taper following the Ely approach is added.
Regional Models
Regional models evaluated for inclusion are:
- Northern California
- Lin et al. (2010)
- Furlong et al. (2024)
- Guo et al. (2024)
- Central California
- CCA-06
- CVM-H v15.1.1
- CVM-S4.26
- Guo et al. (2024)
- Berg et al. (2021)
- Southern California
- Fang et al. (2022)
- CVM-S4.26
- CVM-H v15.1.1
- Berg et al. (2021)
Local Models
Below is a list of local high-resolution models that were evaluated for inclusion.
Northern and Central California:
- Ridgecrest regional (Li and Ben-Zion (2024))
- Ridgecrest fault zone (Zhou et al. (2022))
- San Joaquin basin (Shaw & Plesch (2016))
- SFCVM v21.1 (Hirakawa & Aagaard (2022))
Southern California:
- San Jacinto fault zone (Fang et al. (2019))
- San Gabriel-San Bernardino Basin (Li et al. (2023))
- Imperial Valley (Persaud et al. (2016))
- Coachella Valley (Ajala et al. (2019))
- Santa Maria Basin (Plesch et al. (2020))
Taper
MUSCAL includes a low-velocity taper using the Ely-Jordan approach. Vs30 for this method is produced by merging the Thompson (2018) Vs30 map with the USGS global Vs30 dataset.
The depth of the taper varies depending on the site and ranges from 300m to 1500m.
Delivered Model
The final version of MUSCAL is delivered in netCDF format. The dimensions of the model are <X x Y x Z>. Grid points have a spacing of <m>. The model is interpolated using trilinear interpolation.
Details about the model creation are provided in the paper and the Zenodo page.
Below is a plot of the 3D model extent.
Datasets
zone: 11
command use:
plot_depth_profile.py -n $UCVM_INSTALL_PATH/conf/ucvm.conf -i $UCVM_INSTALL_PATH -d vs -c muscal
-o muscal_small_depth_1000.png -C 'Multi-Scale Statewide California Velocity Model'
-v 1000 -b 0 -s 36.5054,-119.0587 -e 30000
big data in netcdf
model_MSCAL_CANVAS_dll0.01_dz50_cmpd.nc 4.5G
longitude:1301 from -126 to -113
latitude:1251 from 31 to 43.5
depth:671 from 0 to 100,000
50 increments until 30,000
1000 increments til 100000
Plot Depth profile at 36.5054,-119.0587 in different step increments. No interpretation and access data using nc api
File:Muscal big depth-50 matprops.json.txt File:Muscal big depth-100 matprops.json.txt File:Muscal big depth-500 matprops.json.txt File:Muscal big depth-1000 matprops.json.txt
small data in netcdf
model_MUSCAL_CANVAS_dll0.01_vardz_cmpd.nc 2.1G
longitdue:1301 from -126 to -113
latitude:1251 from 31 to 43.5
depth:210 from 0 to 99,000
50 increments upto 3000
100 increments upto 5000
250 increments upto 10000
500 increments upto 30000
1000 increments upto 99000
Depth profiles in different steps : 50m,100m,500m,1000m
Direct from netcdf as external file
File:Muscal small depth-50 matprops.json.txt File:Muscal small depth-100 matprops.json.txt File:Muscal small depth-500 matprops.json.txt File:Muscal small depth-1000 matprops.json.txt
Loaded in-memory as binary data no interpolation
File:Muscal small no interp-50 matprops.json.txt File:Muscal small no interp-100 matprops.json.txt File:Muscal small no interp-500 matprops.json.txt File:Muscal small no interp-1000 matprops.json.txt
Another small dataset in netcdf
model_MUSCAL_CANVAS_dll0.01_vardz_float32_cmpd.nc 1.4G
All longitude, latitude, and depth points are now saved as float32, as well as the vp, vs, and rho.
Loaded in-memory as binary data with interpolation
File:Muscal small interp-50 matprops.json.txt File:Muscal small interp-100 matprops.json.txt File:Muscal small interp-500 matprops.json.txt File:Muscal small interp-1000 matprops.json.txt
Validation
Several steps of pre/post processing are done to original MUSCAL model(netcdf format) in order to incorporate it into UCVM and CVM explorer.
Because of the speed of netcdf-C code is too slow to support in-time nature of the explorer and would like to have interpolation on query,
* Number of depth layer is reduced with deeper layers merged into fewer layers
* preprocessing the netcdf data into binary data files
* data are all in float32
File:MUSCAL test points deep.txt File:MUSCAL test points shallow.txt
Final result from ucvm_query, (with interpolation)
File:MUSCAL test points deep.final.txt File:MUSCAL test points shallow.final.txt
Extended Model
The 3D MUSCAL model is defined over the same volume as the CANVAS base model. However, some simulation regions may extend beyond the boundaries, like the blue corners in the example CyberShake volume for USC below:
To solve this in a consistent and reproducible way, we will extend the MUSCAL model through UCVM. The initial plan is to use the following algorithm:
- Query 3D MUSCAL model at a given point.
- If the model returns NaNs (indicating the point is beyond the bounds of the 3D model):
- Query the 1D MUSCAL model (Te-Yang to provide this).
- Determine Vs30 from the USGS Global Vs30 model.
- Apply the Ely taper (LVT) to the top 300m.
