Colocalize Cruise¶
Example 1: Field Expedition¶
Colocalize Darwin model and satellite data with cruise. Compare the underway (in-situ) picoeukaryote abundance measurements performed during the “Gradient1.0” (aka SCOPE_16) with satellite chlorophyll data and picoeukaryote climatological estimates provided by Darwin model.
Notes:
- In-Situ picoeukaryote abundance measurements are results of the SeaFlow data set with 3-minute temporal resolution and irregular spatial resolution
- Satellite Chlorophyll data used in this example is a daily-global reprocessed and optimally interpolated data set with 4 km×4 km spatial resolution.
- Darwin_Climatology is a monthly climatology version of the Darwin model with spatial resolution 12∘×12∘ .
Code Tutorial¶
from opedia import plotCruise as CRS
DB_Cruise = True # < True > if cruise trajectory already exists in DB. < False > if arbiturary cruise file (e.g. virtual)
source = 'tblSeaFlow' # cruise table name or path to csv trajectory file
cruise = 'TN292' # cruise name, or file name of the csv trajectory file
resampTau = '6H' # resample the cruise trajectory making trajectory time-space resolution coarser: e.g. '6H' (6 hourly), '3T' (3 minutes), ... '0' (ignore)
fname = 'alongTrack' # figure filename
tables = ['tblSeaFlow', 'tblDarwin_Plankton_Climatology', 'tblCHL_OI_REP'] # list of varaible table names
variables = ['picoeuk_abundance', 'picoeukaryote_c03_darwin_clim', 'chl'] # list of variable names
spatialTolerance = 0.3 # colocalizer spatial tolerance (+/- degrees)
exportDataFlag = False # export the cruise trajectory and colocalized data on disk
depth1 = 0 # depth range start (m)
depth2 = 5 # depth range end (m)
df = CRS.getCruiseTrack(DB_Cruise, source, cruise)
df = CRS.resample(df, resampTau)
loadedTrack = CRS.plotAlongTrack(tables, variables, cruise, resampTau, df, spatialTolerance, depth1, depth2, fname, exportDataFlag, marker='-', msize=30, clr='darkturquoise')
Example 2: Virtual Cruise¶
Colocalize Darwin model, satellite data with a virtual cruise. Colocalize a virtual cruise with satellite chlorophyll data and picoeukaryote climatological estimates provided by Darwin model. The trajectory of the virtual cruise is stored in a .csv file.
Notes:
- Satellite sea surface temperatue data used in this example is a daily-global near-real-time and optimally interpolated data set with 4km × 4km spatial resolution 14∘×14∘ .
- Satellite Chlorophyll data used in this example is a daily-global reprocessed and optimally interpolated data set with 4 km×4 km spatial resolution.
- Darwin_Climatology is a monthly climatology version of the Darwin model with spatial resolution 1/2° X 1/2° .
Code Tutorial¶
from opedia import plotCruise as CRS
import os
DB_Cruise = False # < True > if cruise trajectory already exists in DB. < False > if arbiturary cruise file (e.g. virtual)
source = './virtual_parity_scope_2.csv' # cruise table name or path to csv trajectory file
cruise = os.path.splitext(source)[0] # cruise name, or file name of the csv trajectory file
resampTau = '6H' # resample the cruise trajectory making trajectory time-space resolution coarser: e.g. '6H' (6 hourly), '3T' (3 minutes), ... '0' (ignore)
fname = 'alongTrack' # figure filename
tables = ['tblSST_AVHRR_OI_NRT', 'tblCHL_OI_REP', 'tblDarwin_Plankton_Climatology'] # list of varaible table names
variables = ['sst', 'chl', 'picoeukaryote_c03_darwin_clim'] # list of variable names
spatialTolerance = 0.3 # colocalizer spatial tolerance (+/- degrees)
depth1 = 0.3 # depth range start (m)
depth2 = 5 # depth range end (m)
exportDataFlag = False # export the cruise trajectory and colocalized data on disk
df = CRS.getCruiseTrack(DB_Cruise, source, cruise)
df = CRS.resample(df, resampTau)
loadedTrack = CRS.plotAlongTrack(tables, variables, cruise, resampTau, df, spatialTolerance, depth1, depth2, fname, exportDataFlag, marker='-', msize=30, clr='darkturquoise')