reanalysismeteoret

Jupyter notebooks with analyses for paper "Evaluation of reanalysis datasets as meteorological input for estimating reference evapotranspiration over Africa and the Near East"

https://github.com/trngbich/reanalysismeteoret

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 15 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (6.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Jupyter notebooks with analyses for paper "Evaluation of reanalysis datasets as meteorological input for estimating reference evapotranspiration over Africa and the Near East"

Basic Info
  • Host: GitHub
  • Owner: trngbich
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 137 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 3
Created over 1 year ago · Last pushed 10 months ago
Metadata Files
Readme License Citation

README.md

DOI

ReanalysisMeteoRET

This repository provides jupyter notebooks with analyses for paper "Evaluating reanalysis datasets as meteorological input for estimating reference evapotranspiration over Africa and Southwest Asia" (Submitted to Hydrological Sciences Journal)

Methods

In this study, we evaluated the meteorological input for RET from reanalysis data.

Our assessment entails three components: uncertainty between products, nominal accuracy, and quantitative impact of uncertainty in inputs on RET.

Repo structure

The uncertainty between products was assessed by spatial and temporal pair-wise comparison. The nominal accuracy was assessed by comparison with time-series data from in-situ measurements. Finally, the impact of uncertainty in inputs on RET was assessed by two error propagation methods (Monte Carlo simulations and Taylor expansion)

Study area

Study area

Data

Python environment

conda env create --file environment.yml

Citation

Tran, B. N., Dehati, S., Seyoum, S., van der Kwast, J., Jewitt, G., Uijlenhoet, R., and Mul, M. (2024). Evaluating reanalysis datasets as meteorological input for estimating reference evapotranspiration over Africa and Southwest Asia (Version 2.0) [Code]. https://doi.org/10.5281/zenodo.13970799

Owner

  • Name: Bich N Tran
  • Login: trngbich
  • Kind: user
  • Company: @wateraccounting

PhD candidate in Water Resources Management | 🌍 #EO 🛰#RS 🗺 #GIS 📊 #WaterAccounting 💧#IWRM ♻️ #SDGs 🐳🌱#ecohydrology 🌾🐄 #agrohydrology

GitHub Events

Total
  • Release event: 3
  • Public event: 1
  • Push event: 16
  • Create event: 2
Last Year
  • Release event: 3
  • Public event: 1
  • Push event: 16
  • Create event: 2