> For the complete documentation index, see [llms.txt](https://jonas.gitbook.io/seismo_rain/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jonas.gitbook.io/seismo_rain/seismic-data/extracting-seismic-data.md). # Extracting seismic data To match the specific characteristics of the chosen rainfall event, we selected four seismic stations (2A.1517, 2A.199, 2A.465, 2A.763) positioned along the same latitude, spanning west to east and approximately 7 km apart from each other. The decision to limit the number of seismic stations for analysis to four was based on time constraints related to loading seismic waveform data.

Four selected seismic station (2A.1517, 2A.199, 2A.465, 2A.763) for this study (edited from Hua et al., 2023)

## ObsPy library to import seismic data from a data centre using the FDSN client interface Obspy is a Python framework for processing seismological data (Beyreuther et al., 2010), you can access its detailed documentation via this [link](https://docs.obspy.org/index.html#). ```python import obspy from obspy.clients.fdsn import Client # The 2A network seismic data is saved at the IRIS PH5 repository IRISPH5 = Client('IRISPH5',timeout=3600) ``` ## Extract the waveforms from all four seismic stations ```python # Print the wall time of this cell (It might take up to 20 mins to run) %%time # FDSN seismic network code net = "2A" # Select the seismic station of interest station = "1517,199,465,763" # Select the location code within the seismic station (use "*" to select all) location = "*" # Select the channel ("*Z": only select the vertical channel) channel = "*Z" # Select the time range of the seismic waveform # obspy.UTCDateTime is in the order: year, month, day, hour, minute, second, microsecond starttime = obspy.UTCDateTime(2016,4,19,22) endtime = obspy.UTCDateTime(2016,4,20,2) # Saving the waveforms as a stream (st) st = IRISPH5.get_waveforms(net,station,location,channel,starttime,endtime) # Backing up "st" st.bak = st.copy() # Print the stream print(st) ``` The output from `print(st)` reveals that within the stream, each waveform is designated as an individual trace. ``` 4 Trace(s) in Stream: 2A.1517..DPZ | 2016-04-19T22:00:00.000000Z - 2016-04-20T01:59:59.998000Z | 500.0 Hz, 7200000 samples 2A.199..DPZ | 2016-04-19T22:00:00.000000Z - 2016-04-20T01:59:59.998000Z | 500.0 Hz, 7200000 samples 2A.465..DPZ | 2016-04-19T22:00:00.000000Z - 2016-04-20T01:59:59.998000Z | 500.0 Hz, 7200000 samples 2A.763..DPZ | 2016-04-19T22:00:00.000000Z - 2016-04-20T01:59:59.998000Z | 500.0 Hz, 7200000 samples CPU times: user 2.52 s, sys: 1.57 s, total: 4.08 s Wall time: 17min 36s ``` If you're interested in understanding how the channel codes are composed, you can explore the documentation via this [link](https://docs.fdsn.org/projects/source-identifiers/en/latest/channel-codes.html) (FDSN, 2020). ## Plotting the waveform ```python import matplotlib.pyplot as plt # Plotting waveforms st.plot() # Close a figure window plt.close() ```

The unprocessed waveform of the four selected seismic stations

## Applying a bandpass filter to all the waveforms As mentioned in [Frequency of interest](/seismo_rain/seismic-data/frequency-of-interest.md), we will be applying a bandpass filter of 80 Hz to 150 Hz to all the waveforms. ```python st.filter('bandpass',freqmin=80,freqmax=150) st.plot() plt.close() ```

Bandpass filter of 80-150 Hz is applied to all waveforms

## Converting the waveforms to the magnitude of displacement of the seismic sensor We now need to convert the "count value" displayed on the y-axis of the waveforms to a meaningful metric representing displacement in meters. Before proceeding, it is important to remove all instrumental responses from the seismic sensor data. These responses are known to be frequency-dependent ([Wilson et al., 2013](https://ui.adsabs.harvard.edu/abs/2013AGUFM.S42A..04W/abstract#:~:text=Neglecting%20to%20remove%20the%20frequency,typically%20presumed%20to%20be%20flat.)) and neglecting this step may result in significant errors in both amplitude and phase. The instrument response of each station can be accessed by the `IRISPH5.get_stations` where `level="response"` returns the full response information for the requested channels. ```python # Extracting instrument response from each channel inv = IRISPH5.get_stations(network="2A",station="1517,199,465,763",level='response',channel='DPZ') # Plotting the displacement (m) amplitude of the seismic sensor st.remove_response(inv,output='DISP') st.plot() plt.close() ```

The displacement amplitude (in meters) of all four seismic stations

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