Quoting Kelly Brunt, an ice scientist with NASA and at the University of Maryland, from What the Heck Is the Deal with This Weird, Square Iceberg? at LiveScience.com:
What makes this one a bit unusual is that it looks almost like a square,
which does not rhyme with anything in your suggested 1:4:9 ratio.
The article mentions the obvious
As @gerrit pointed out, the Pytroll project has a couple of package which could be useful.
To answer your question and get the next overpasses for the next twelve hours above a given location, you can use Pyorbital (https://github.com/pytroll/pyorbital):
from pyorbital.orbital import Orbital
from datetime import datetime
orb = Orbital("SMAP")
There have been rectangular tabular icebergs in the past so this is not uncommon at all.
Kelly Brunt, an ice scientist with NASA and the University of Maryland said:
Tabular icebergs form, she said, through a process that's a bit like a fingernail growing too long and cracking off at the end. They're often rectangular and geometric as a result
This is not a satellite acquisition plan, but it may be something to get you started. I've used the Python package Skyfield to get the subsatellite point of SMAP based on the most recent two line element set from Celestrak.
Please feel feel free to leave comments with questions if a tweak is needed!
I'm not an expert on dates and times in Python, the times ...
Google Earth Engine's NASA NEX dataset (or this) might be of interest to you. It is an online repository, where you can do your analysis using the GEE platform without having the need to download to local machine.
To download the data from earth data, the following needs to be done
Go to https://urs.earthdata.nasa.gov/ and create an account. Note the username and password which will be used to download the data.
In your linux root create a file .netrc and enter the following
machine urs.earthdata.nasa.gov login your_login password your_password
Go to https://disc....
I did download and process some of the NEX files a year or so ago. Maybe there is a more efficient way to do that now, but what I used is this R script to download the files:
opts = curlOptions(proxy='http://10.xxx.xxx.xx:xxxx', userpwd = "you needed NEXGDDPusr:pswd at that time", netrc = TRUE)
var = c("pr","tasmax","tasmin") ##here the ...