Weather Generator and Climate Change Scenario Generator for Climate Risk Assessment (WECCS-Gen) Tool
Introduction
Weather Generator and Climate Change Scenario Generator for Climate Risk Assessment (WECCS-Gen) Tool has been designed to facilitate Climate Risk Assessment (CRA) process. This tool allows for
- Generation of multiple climate realizations using k-nearest neighbor (k-NN) based multisite multivariate weather generator.
- Bias correction and Spatial Disaggregation (BCSD) for statistical downscaling of future climate projections. It is based research by Wood et al (2002) and Thrasher et al (2022).
Why we need this tool?
At present and in future, climate resiliency in water resources infrastructures is largely needed for sustainable development by addressing uncertainties and future climate risks. This requires a thorough climate risk assessment of water resources projects. And there are two basic frameworks for conducting climate risk assessment.
The first one, a bottom-up, context-based CRA can serve as a decision support tool for WR development under uncertainty (Ray and Brown, 2015). Uncertainties of GCM projections and thus conclusions derived from them lack systematic risk analysis (Ray et al., 2018). Therefore, bottom-up or system-driven approaches like Decision Tree Framework (Ray and Brown, 2015), CRIDA (Mendoza et al, 2018) and Hydropower Sector Climate Resilience Guide (IHA, 2019) are adopted. These frameworks identify performance indicators of the hydro-system through stakeholders’ consultation and run climate stress test to expose vulnerability and risk (Ray et al., 2018). This allows the decision-makers to adopt adaptive and resilience design of water resources infrastructures (Ray and Brown, 2015). Key step in the bottom-up climate risk assessment is to generate multiple realisations of the key climate variables (precipitation, temperature) and then generate the climate vulnerability domain of the selected performance indicator under scrutiny or test, for instance, streamflow, dry energy under various climatic realisations (Ray et al., 2018). This requires generation of multiple climate realizations. It allows for altering the parameters like mean, coefficient of variation and transition probabilities of current climate and generate wide possible range of future scenarios (Steinschneider, and Brown 2013). In this aspect, the first part of the tool - ‘k-nearest neighbor (k-NN) based multisite multivariate weather generator’ becomes a handy tool to aid in climate stress test and CRA. This aspect in WECCS-Gen tool is based on paper by Apipattanavis et al (2007) and Steinschneider and Brown (2013).
The second framework for climate risk assessment is top-down approach which is traditional approach. This is also climate model (like General Circulation Model) driven approach. It is common practice to use the climate models using ensemble (e.g. Whetton et al. (2012)) or envelope approach (e.g Lutz et al. (2016)) to address uncertainties. Climate model projections are then treated using climate downscaling (like Wood et al., 2004) and bias correction (like quantile mapping in Gudmundsson et al., 2012) procedures to reduce biases and contextualise it to local conditions. These are widely used in national and international context, like in the National Adaptation Plan of Nepal (MoFE, 2019), The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) and many others. In order to facilitate top-down approach, Bias correction and Spatial Disaggregation (BCSD) has been integrated into the WECCS-tool. This aspect is based on papers by Wood et al. (2002) and Thrasher et al. (2022).
Given the technical complexities involved in either simulating climate realizations or downscaling, this WECCS-Gen tool provides a and accessible platform to WR practitioners to facilitate CRA using either of the approaches.
Usages of this tool:
- Generation of synthetic dataset in case of limited observed data
- Generation of climatic data enforced with future climate change conditions
- Climate stress test and climate risk assessment of water resources system
- Statistical downscaling of the future climate projections
Basic steps used in generating climate data using weather generator with this tool:
a) Generation of annual series using ARMA process
b) Conditioned in annual series, generation of daily weather series using k-NN based multisite multivariate weather generator
c) Enforcement of long term shifts in climate means and distributions using quantile mapping techniques
Supported by:
Weather Generator and Climate Change Scenario Generator for Climate Risk Assessment (WECCS-Gen) Tool was initially developed in 2019 by Water and Climate Program, Nepal Development Research Institute (NDRI). Upgrade of this WECCS-Gen tool by integration of the Bias Correction and Spatial Disaggregation (BCSD) component is currently ongoing with the financial support from Asia Pacific Network (APN) in 2022-2023.
Basic steps used in statistical downscaling with this tool:
- Bias correction of climate variables using quantile mapping techniques
- Spatial disaggregation that merges the observed spatial climatology with the relative changes simulated by climate models
Please download the Weather Generator and associated documents using following links:
A. Older version (0.1.0 Beta version)
1. Technical_Documentation_WG_CRA
2. Users_Manual_WG_CRA
3. WG_CRA
B. Updated version (0.2.0) – Draft version
1. CODES
2. Technical Documentation on BCSD
