SWEpy: A Python Library for Analyzing SWE via Passive Microwave Imagery¶
SWEpy is a Python library designed to simplify access to a passive microwave brightness temperature dataset available at the National Snow and Ice Data Center (NSIDC). This dataset contains Northern/Southern hemisphere imagery and Equatorial imagery, and can be quite useful in analyzing snow water equivalent (SWE) over large spatial extents. SWEpy contains tools to web scrape, geographically subset, and concatenate files into time cubes. SWEpy also contains tools to aid in the initial processing of passive microwave data into proxy SWE information.
SWEpy can be used as a full data pipeline for downloading, subsetting, and concatenating imagery. However, SWEpy can also be used to accomplish any of these steps individually. See below for example usage of SWEpy on several different scenarios.
SWEpy is comprised of 4 modules:
swepy.pipelineThe primary data pipeline for swepy. It manages the downloading, subsetting, and concatenation of passive microwave data.
swepy.processThe processing module for SWEpy. It allows users to smooth spikes generated from the resampling process in the dataset.
swepy.analysisThe analysis module for SWEpy. It allows users to find quick information about their study area, like understanding how the intial date of total melt changes through the time series
swepy.nsidcDownloaderThe web scraping module that powers the
pipelinemodule. It can be used independently, but is completley interfaced inswepy.pipelineso there is little need to use it directly.
There are more in depth explanations of each module under their respective documentation page.