Ensemble-Based Risk Assessment Model of Projected Precipitation Changes in Mexico
Sahar Mohsenzadeh-Karimi1, Eylon Shamir2, Hsin-I Chang1, Christopher L. Castro3,
Exequiel Rolon4, Lourdes Mendoza Fierro1, Norman Pelak2, Claire Acke1
1 Department of Hydrology & Atmospheric Sciences, Tucson, AZ
2 Hydrologic Research Center, San Diego, CA
3 National Center for Atmospheric Research, Research Applications Laboratory, Boulder, CO
4 Fresnillo PLC, Mexico City, Mexico
Climate risk management is essential for building resilience against extreme weather events, particularly in highly vulnerable regions like Mexico, where projections indicate an increase in both droughts and floods. The primary objective of this study is to support climate risk management and decision-making by assessing ensemble-based changes in precipitation. A novel methodology has been developed that integrates a Regional Climate Model (RCM) with a Stochastic Weather Generator (SWG) to produce an ensemble of likely-to-occur daily precipitation time series. The ensemble captures the natural variability of historical precipitation records and their associated uncertainties, providing a robust basis for probabilistic analysis. The future projected change in daily precipitation is based on an analysis of dynamically downscaled projections available from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX). The projections are derived from the RCP8.5 scenario of the MPI-ESM-LR CMIP5 Global Climate Model (GCM), dynamically downscaled to approximately 25 km² using the Weather Research and Forecasting (WRF) RCM. By identifying changes in the RCM projections and comparing the historic simulations (1986-2005) to simulate two future periods (2020-2039 and 2040-2059), the initially developed weather generator has been modified. These modifications, which incorporate the RCMs' historic-future differences, produced ensembles of projected likely-to-occur precipitation time series. Findings show summer precipitation changes drive annual variabilities, while winter exhibits the highest magnitude of change, particularly in northern regions. Central Mexico also experiences greater precipitation increases than other regions. The spatial-temporal variability highlights the need for location-specific climate evaluations to support effective adaptation planning.