premise-hydroclim 2.1.0

PREMISE-hydroclim v2.0: an open-source Python framework for multi-source precipitation harmonization, indices, and evaluation

PREMISE v1.0

PREMISE (PREcipitation Multi-source Indices and Software Evaluation) is an open-source Python framework for basin-oriented hydroclimatic data preparation, comparative product evaluation, and climate-diagnostic workflows in environmental modelling applications.

The redesigned v1.0 architecture is organized around six application-oriented modules:

1. Data acquisition for multi-source hydroclimatic products.
2. Data conversion and harmonization for heterogeneous raw formats and metadata.
3. Basin-oriented preprocessing for clipping, masking, aggregation, and forcing preparation.
4. Product evaluation for benchmarking multi-source products against a reference dataset.
5. Extreme climate and drought indices for precipitation and hydroclimatic diagnostics.
6. Visualization and reporting for publication-ready figures and structured summaries.

Optional correction and fusion utilities are retained as legacy or experimental extensions. They are not part of the six-module core architecture described in the current manuscript revision.

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Software availability

• Name of software: PREMISE v1.0
• Description: An open-source Python framework for basin-oriented preprocessing, harmonization, index generation, and comparative evaluation of multi-source gridded hydroclimatic datasets in environmental modelling workflows.
• Developer: Xinlong Le
• Programming language: Python
• System requirements: Linux, Windows, or macOS
• Repository: https://github.com/theshyyi/PREMISE-v1.0
• Version: 1.0.0
• DOI: 10.5281/zenodo.18093220

A manuscript-ready note is provided in docs/software_availability.md.

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Installation

Core installation

pip install -e .

Optional extras

pip install -e .[geo]
pip install -e .[tiff]
pip install -e .[grib]
pip install -e .[hdf]
pip install -e .[fusion]
pip install -e .[full]

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Six-module architecture

Module	Package path	Primary role
Data acquisition	premise.acquisition	Register and query hydroclimatic data sources, build download plans
Data conversion and harmonization	premise.conversion	Convert heterogeneous raw files to standardized NetCDF-ready datasets
Basin-oriented preprocessing	premise.basin	Clip, mask, aggregate, and prepare basin-facing forcing products
Product evaluation	premise.product_evaluation	Evaluate candidate products against a reference and summarize ranking workflows
Extreme climate and drought indices	premise.climate_indices	Compute drought indices and precipitation-extreme indicators
Visualization and reporting	premise.visualization	Generate maps, performance diagrams, Taylor diagrams, and grouped summaries

Legacy modules such as premise.preprocess, premise.indices, premise.evaluation, and premise.plotting are still available for backward compatibility.

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Quick start with the new module layout

1. Explore hydroclimatic source templates

from premise.acquisition import list_sources

for source in list_sources(variable="precipitation"):
    print(source.key, source.title, source.temporal_resolution)

2. Convert heterogeneous data to standardized NetCDF

from premise.conversion import convert_binary_to_nc

convert_binary_to_nc(
    meta_path="cpc_global_daily.meta",
    data_path="precip_20000101.bin",
    out_nc="precip_20000101.nc",
)

3. Prepare basin-oriented forcing summaries

from premise.basin import area_mean_by_region
from premise.climate_indices import calc_spi
import xarray as xr

pr = xr.open_dataset("precip_20000101.nc")["pr"]
spi3 = calc_spi(pr, scale=3)
regional = area_mean_by_region(spi3, "regions.shp")
print(regional)

4. Summarize evaluation or ranking workflow stages

from premise.product_evaluation import describe_ranking_workflow

print(describe_ranking_workflow())

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Examples

• examples/quickstart/basic_usage.py keeps the original minimal workflow.
• examples/quickstart/module_overview.py demonstrates the redesigned module structure.
• examples/basin_forcing_preparation/ is reserved for a basin-facing preprocessing case.
• examples/product_comparison/ is reserved for a comparative benchmarking case.
• examples/extreme_and_drought_indices/ is reserved for an index-generation case.

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Documentation

• docs/software_availability.md
• docs/benchmark_template.md
• docs/module_architecture.md
• docs/github_homepage_branding.md

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Testing

Minimal regression-oriented tests are provided under tests/:

pytest -q

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Citation and license

Please cite the associated Zenodo archive when using PREMISE in research outputs. A machine-readable citation file is included as CITATION.cff.

This project is released under the MIT License. See LICENSE.