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Data · dataset · 2025

SIMCAST Spatial: A Python Pipeline for Gridded Climate Processing, Point Masking, and Distributed Late Blight Modeling

Listed in International Potato Center

This dataset contains SIMCAST Spatial, a Python-only pipeline for spatial late blight modeling that processes gridded climate datasets and runs the SIMCAST model on a point grid at scale using Dask Distributed.

Description

The workflow supports: (1) resampling precipitation NetCDF rasters to a target grid, (2) masking/extracting monthly NetCDF values onto a point grid and writing monthly Parquet files, (3) running SIMCAST per point/season to produce per-region/year results and optional application (APP) rasters, (4) generating BU/FU raster summaries and an “all lands” animation, and (5) optional trend significance analysis (OLS over years) for APP/ABU/AFU.

The pipeline is configured and executed via main.py and config.py, and is currently tuned to a Peru potato-zoning workflow but intended to be reusable by passing paths and resource settings. This deposit includes only software; input data (NetCDFs, point grids) are provided by the user and are not included.

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
International Potato Centerdoi:10.21223/P3/J37CJB12 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:life-sciencesmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].local:field:medicine-healthmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].local:field:ocean-atmosphericmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
created_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
descriptionsource · data cipotato orgconnector:data_cipotato_org@1.0.0/description
publication_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
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