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irrigation_param_analysis

This repository contains the code for the analysis of the irrigation parameterization implemented into REMO2020-iMOVE.

https://github.com/christina-pop/irrigation_param_analysis

Science Score: 49.0%

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    CITATION.cff file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 10 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    Scientific vocabulary similarity
    Low similarity (7.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

This repository contains the code for the analysis of the irrigation parameterization implemented into REMO2020-iMOVE.

Basic Info
  • Host: GitHub
  • Owner: Christina-Pop
  • License: mit
  • Language: Python
  • Default Branch: master
  • Size: 135 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 2
Created almost 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Zenodo

README.md

irrigationparamanalysis

DOI test

This repository contains the code for the analysis of the irrigation parameterization implemented into REMO2020-iMOVE[^1].

Figure overview

Figure | directory | plotting routine --- | --- | --- | Fig003 | experimentsetup | Fig03Modeldomainirrigatedfractionspatial.py Fig004 | testingschemes | Fig04Testschemesirrigationwaterhourlydevelopment.py Fig005 | testingschemes | Fig05Testschemesirrigationwaterspatial.py Fig006 | meteocondition | Fig06Meteoconditionspatial.py Fig007 | meteocondition | Fig07MeteoconditionAMJJAseries.py Fig008 | processanalysis | Fig08Processanalysissoilsurfacevars.py Fig009 | processanalysis | Fig09Processanalysissoilsurfacefluxesspatial.py Fig010 | processanalysis | Fig10Processanalysissurfaceenergybudgetdiurnalseries.py Fig011 | processanalysis | Fig11Processanalysist2mrh.py Fig012 | processanalysis | Fig12Processanalysisprecip.py Fig013 | processanalysis | Fig13ProcessanalysisLAINPPAMJspatial.py Fig014 | processanalysis | Fig14ProcessanalysisLAINPPseries.py Fig015 | delayedeffects | Fig15Delayedeffectst2mspatial.py Fig016 | delayedeffects | Fig16Delayedeffectsheatwavecombinedseries.py FigA2 | appendix | A2schemessoilmoisturerunoffdrainageseries.py FigA3 | appendix | A3A4schemeseffectssoilmoisturesurfacetemp.py FigA4 | appendix | A3A4schemeseffectssoilmoisturesurfacetemp.py FigB1 | appendix | B1irrigationAug.py FigC1 | appendix | C1stationlocationsspatialscatter.py

Installation

Create a new conda environment using, e.g.

bash conda env create -f environment.yaml

Afterwards, you can install the required plotting and analysis_functions using pip install -e .

Data access

To reproduce the analysis, please download the model output data from

DOI

using, e.g.,

bash python download_zenodo.py.

The observational data for the analysis in

  • /compare_obs/Tab3_Eval_Scia_t2m.py
  • /appendix/C1_station_locations_spatial_scatter.py

was originally downloaded from serverstazioni. It is included in V2 from https://doi.org/10.5281/zenodo.10014915

[^1]: Asmus, C., Hoffmann, P., Pietikäinen, J.-P., Böhner, J., and Rechid, D.: Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization, Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, 2023.

Owner

  • Name: Christina Pop
  • Login: Christina-Pop
  • Kind: user

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