How to use harmony-py to spatially subset ICESat-2 data

Problem

How do I use a bounding box to spatially subset ICESat-2 data using NASA Harmony services via the harmony-py Python library?

Solution

from harmony import BBox, Client, Collection, Request
import datetime as dt

Initialize your Harmony client

harmony_client = Client()

Define which data set you’d like to access using the collection concept-id (see how-to for retrieving collection concept-ids). For this example, we’ll use ATL06 version 007, C3564876127-NSIDC_CPRD.

collection = Collection(id='C3564876127-NSIDC_CPRD') 

Define your spatial bounds (min_lon, min_lat, max_lon, max_lat). The example below is over the Juneau Ice Field in Alaska.

bbox = BBox(-134.7,58.9,-133.9,59.2)

Define your temporal range (passed as a dictionary with “start” and “stop” keys, and dates supplied as datetime objects).

temporal = {'start': dt.datetime(2020, 4, 27),'stop': dt.datetime(2020, 5, 28)}

Build the request

request = Request(
    collection=collection,
    spatial=bbox,
    temporal=temporal
)

Submit the request. This returns a Harmony job ID that can be used to check on progress.

job_id = harmony_client.submit(request)
job_id

‘6a512b21-1b22-4cff-acec-bfb28fdb9985’

Check on Harmony job progress

harmony_client.wait_for_processing(job_id, show_progress=True)

[ Processing: 100% ] |###################################################| [|]

Download the results to your local directory

futures = harmony_client.download_all(job_id, directory=".", overwrite=False)
filelist = [f.result() for f in futures]  # get filepaths
len(filelist)

./152623268_ATL06_20200509204541_06770702_007_01_subsetted.h5 ./152623269_ATL06_20200511091850_07000706_007_01_subsetted.h5

2

Discussion

NASA Harmony is comprised of cloud-based services that allow you to customize many NASA data sets, providing the ability to subset, reproject and reformat files. Not all transformation services are available for all datasets. Table of Harmony services available for select ICESat-2 data sets.

A longer form tutorial demonstrating NASA Harmony and the harmony-py Python library can be found here.