Matchups with point data

A common challenge when working with netCDF data is matching up with point data. This is often difficult because point data is sparse both spatially and temporally, and when working in the ocean this data can be at varying depths. From version 0.4.7 on, nctoolkit includes the ability to match datasets to spatiotemporal dataframes. Here we will provide an overview of how to do this.

Matching data at specific locations

First, we will illustrate how matchpoint works for data at specific spatial locations and depths. After this we will deal with different times. The data will be ocean nitrate from NOAA’s World Ocean Atlas.

We can download part of it as follows:

import nctoolkit as nc
ds = nc.open_thredds('https://data.nodc.noaa.gov/thredds/dodsC/ncei/woa/nitrate/all/1.00/woa18_all_n01_01.nc', checks = False)
ds.crop(lon =  [-40, 20], lat = [40, 70], nco = True)
ds.subset(variables = "n_an")
ds.run()

nctoolkit is using Climate Data Operators version 1.9.10

This is a subset of the data covering a large part of the North Atlantic, and it has nitrate values from the sea surface to the sea floor.

ds.plot()