CUWALID

Contents:

  • Introduction
  • Installation
  • Models Information
  • Tutorials
  • Training Notebooks
    • DRYP Training Notebooks
    • stoPET Training Notebooks
    • STORM Training Notebooks
    • Forecast Training Notebooks
      • 01_Climate_Forecasting
        • Contents
        • 4.1. Create an ensamble of precipitation for the Tana basin
        • 4.2. Create ensamble of potential evapotranspiration for the Tana basin
      • 02_Hydrological_Forecasting
        • Contents
        • Please, download one simulation from the ICPAC server for the following examples
      • 03_Forecasting_Analysis
        • Contents
        • Working with historical grided datasets
        • Visualizing anomalies
  • Processing
  • cuwalid
  • Developer Maintenance
  • CUWALID: Workflow for contributions
  • Introduction
  • Acknowledgements
  • Licences
CUWALID
  • Training Notebooks
  • Forecast Training Notebooks
  • View page source

Forecast Training Notebooks

01_Climate_Forecasting

  • Contents
    • 4. Convert climate seasonal forecasting into model forcing datasets
  • 4.1. Create an ensamble of precipitation for the Tana basin
  • 4.2. Create ensamble of potential evapotranspiration for the Tana basin
    • Please restart the Kernel before running the code, as it saves all the variables from the previous run.

02_Hydrological_Forecasting

  • Contents
    • 4. Translate climate forecasting into hydrological forecasting
    • 4.1. Create an ensamble of model simulation files
    • 4.2. Prepare multiple simulation on HPC
    • 4.3. Understanding hydrological outputs
  • Please, download one simulation from the ICPAC server for the following examples

03_Forecasting_Analysis

  • Contents
    • 3. Translate climate forecasting into hydrological forecasting
    • 3.1 Forcast: Preparation
    • Prepare Historical simulation
    • Forecast analysis
    • 3.2 Understanding seasonal hydrological forecast
    • Working with historical total averages
  • Working with historical grided datasets
  • Visualizing anomalies
    • Visualizing deterministic and probabilistic forecast
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