Workflows for Galaxy Climate
A space managed by WorkflowHub administrators for teams that don't want/need to manage their own space.
Teams: IBISBA Workflows, NMR Workflow, UNLOCK, NanoGalaxy, Galaxy Climate, PNDB, IMBforge, COVID-19 PubSeq: Public SARS-CoV-2 Sequence Resource, LBI-RUD, Nick-test-team, usegalaxy-eu, Italy-Covid-data-Portal, UX trial team, Integrated and Urban Plant Pathology Laboratory, SARS-CoV-2 Data Hubs, lmjxteam2, virAnnot pipeline, Ay Lab, iPC: individualizedPaediatricCure, Harkany Lab, Genomics Coordination Center, EJPRD WP13 case-studies workflows, Common Workflow Language (CWL) community, Testing, SeBiMER, IAA-CSIC, MAB - ATGC, Probabilistic graphical models, GenX, Snakemake-Workflows, ODA, IPK BIT, CO2MICS Lab, FAME, CHU Limoges - UF9481 Bioinformatique / CNR Herpesvirus, Quadram Institute Bioscience - Bioinformatics, HecatombDevelopment, Institute of Human Genetics, Testing RO Crates, Test Team, Applied Computational Biology at IEG/HMGU, INFRAFRONTIER workflows, OME, TransBioNet, OpenEBench, Galaxycompchem, Bioinformatics and Biostatistics (BIO2 ) Core
Web page: Not specified
Abstract CWL Automatically generated from the Galaxy workflow file: GTN 'Pangeo 101 for everyone - Introduction to Xarray'.
In this tutorial, we analyze particle matter < 2.5 μm/m3 data from Copernicus Atmosphere Monitoring Service to understand Xarray Galaxy Tools:
- Understand how an Xarray dataset is organized;
- Get metadata from Xarray dataset such as variable names, units, coordinates (latitude, longitude, level), etc;
- Plot an Xarray dataset on a geographical map and learn to customize ...
This workflow extracts 5 different time periods e.g. January- June 2019, 2020 and 2021, July-December 2019 and 2020 over a single selected location. Then statistics (mean, minimum, maximum) are computed. The final products are maximum, minimum and mean.
This workflow is used to process timeseries from meteorological stations in Finland but can be applied to any timeseries according it follows the same format.
Take a temperature timeseries from any meteorological station. Input format is csv and it must be standardized with 6 columns:
- Year (ex: 2021)
- month (ex: 1)
- day (ex: 15)
- Time (ex: 16:56)
- Time zone (such as UTC)
- Air temperature (degC)
Description: SSP-based RCP scenario with high radiative forcing by the end of century. Following approximately RCP8.5 global forcing pathway with SSP5 socioeconomic conditions. Concentration-driven. Rationale: the scenario represents the high end of plausible future pathways. SSP5 is the only SSP with emissions high enough to produce the 8.5 W/m2 level of forcing in 2100.
This workflow is answering to the following scientific question:
- Is it worth investing in artificial snowmaking equipment ...
Type: Unrecognized workflow type
Submitter: Anne Fouilloux