gridwxcomp
A package for comparing weather station data to gridded weather data that are hosted on Google Earth Engine. Major functionality includes:
parsing of multiple weather stations and weather variables and metadata
downloading point data from gridded datasets on Google Earth Engine at weather station locations
temporal pairing of station and gridded data
unit handling and automated conversions
calculation of mean bias ratios between station and gridded data and related statistics
performing spatial mapping and interpolation of bias ratios with multiple options
calculation of residuals between spatially interpolated bias ratios and those computed at station locations
building geo-referenced vector and raster data of spatially interpolated and point data
zonal averaging of spatially interpolated bias results using a fishnet grid
interactive graphics (time series, scatter, and bar charts) comparing station and gridded data
Bias ratios calculated by gridwxcomp can be used to correct bias of grid to station data based on the properties of the stations. For example, monthly humidity ratios between station and grid for stations within agricultural settings can be used to estimate grid bias relative to agricultural locations.
gridwxcomp has been used to create monthly bias ratios of gridMET reference evapotranspiration (ETo) data relative to ETo calculated at irrigated weather stations. The bias ratios were subsequently interpolated and used to correct gridMET ETo which is a key scaling flux for most of the remote sensing models that are part of the OpenET platform.
Documentation
Installation
Currently we recommend using the provided conda environment file to install gridwxcomp and its dependencies in a virtual environment. Download the environment.yml file and then install and activate it. If you don’t have conda get it here. To install dependencies in a virtual environment run
$ conda env create -f environment.ymlTo activate the environment before using gridwxcomp run
$ conda activate gridwxcompOptionally, install using pip,
$ pip install gridwxcompDue to dependency conflicts you may have issues directly installing with pip before activating the conda environment.
Alternatively, or if there are installation issues, you can manually install. First activate the gridwxcomp conda environment (above). Next, clone or download the package from GitHub or PyPI and then install locally with pip in “editable” mode. For example with cloning,
$ git clone https://github.com/WSWUP/gridwxcomp.git
$ cd gridwxcompIf you are experiencing errors on installing the gridwxcomp conda environment above with dependencies. For example, if the Shapely package is not installing from the enironment.yml file, remove it or modify it from the “setup.py” file in the install requirements section before you install gridwxcomp from source with:
$ pip install -e .More help with installation issues related to dependency conflicts can be found in the gridwxcomp issues on GitHub, be sure to check the closed issues as well.
1 maintainer
Metadata
1 maintainer
Release files for gridwxcomp 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gridwxcomp-0.2.0.tar.gz | 1.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gridwxcomp-0.2.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 3.8 MB
Release files / gridwxcomp-0.2.0.tar.gz
| Download URL | gridwxcomp-0.2.0.tar.gz |
|---|---|
| Size | 1.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.5
|
Release files / gridwxcomp-0.2.0-py2.py3-none-any.whl
| Download URL | gridwxcomp-0.2.0-py2.py3-none-any.whl |
|---|---|
| Size | 1.9 MB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.5
|
