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Prototype application for GCM bias-correction and downscaling

License: Apache License 2.0

Python 99.51% Dockerfile 0.40% Makefile 0.09%

dodola's Introduction

DOI Test Build

dodola

Containerized application for running the steps in a larger, orchestrated CMIP6 bias-correction and downscaling workflow.

This is under heavy development.

Features

Commands can be run through the command line with dodola <command>.

Commands:
    adjust-maximum-precipitation  Adjust maximum precipitation in a dataset
    apply-dtr-floor               Apply a floor to diurnal temperature...
    apply-non-polar-dtr-ceiling   Apply a ceiling to diurnal temperature...
    apply-qdm                     Adjust simulation year with quantile...
    apply-qplad                   Adjust (downscale) simulation year with...
    cleancmip6                    Clean up and standardize GCM
    correct-wetday-frequency      Correct wet day frequency in a dataset
    get-attrs                     Get attrs from data
    prime-qdm-output-zarrstore    Prime a Zarr Store for regionally-written...
    prime-qplad-output-zarrstore  Prime a Zarr Store for regionally-written...
    rechunk                       Rechunk Zarr store in memory.
    regrid                        Spatially regrid a Zarr Store in memory
    removeleapdays                Remove leap days and update calendar
    train-qdm                     Train quantile delta mapping (QDM)
    train-qplad                   Train Quantile-Preserving, Localized...
    validate-dataset              Validate a CMIP6, bias corrected or...

See dodola --help or dodola <command> --help for more information.

Example

From the command line, you replicate one of the downscaling workflow's validation steps with:

dodola validate-dataset <InsertZarrStoreURLhere> \
  --variable "tasmax" \
  --data-type "downscaled" \
  -t historical

Alternatively, the service used by this command can be called directly from Python in dodola.services.

Installation

dodola is generally run from within a container. But, you can install the application and access the command-line interface or Python API with pip:

pip install git+https://github.com/ClimateImpactLab/dodola

the dependencies used in the container are in ./environment.yaml.

Support

Source code is available online at https://github.com/ClimateImpactLab/dodola. This software is Open Source and available under the Apache License, Version 2.0.

dodola's People

Contributors

brews avatar dgergel avatar emileten avatar delgadom avatar

Watchers

James Cloos avatar

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