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High-resolution climate projection dataset based on CMIP6 for Peru and Ecuador: BASD-CMIP6-PE.

Carlos Antonio Fernandez-Palomino1,2, Fred F Hattermann3, Valentina Krysanova3

  • 1Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, PO Box 60 12 03, D-14412, Potsdam, Germany. palomino@pik-potsdam.de.

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A new high-resolution climate dataset for Peru and Ecuador, BASD-CMIP6-PE, was created using bias-adjusted and statistically downscaled climate projections. This reliable dataset aids in assessing climate change impacts on water resources and agriculture.

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Area of Science:

  • Climate Science
  • Hydrology
  • Environmental Science

Background:

  • Global Climate Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) often exhibit biases when simulating regional climate patterns.
  • High-resolution climate data are crucial for accurate impact assessments in vulnerable regions like Peru and Ecuador.
  • Existing climate datasets may not adequately capture the nuances of regional precipitation and temperature variability.

Purpose of the Study:

  • To develop a high-resolution (10 km) climate dataset for Peru and Ecuador, named BASD-CMIP6-PE.
  • To provide bias-adjusted and statistically downscaled CMIP6 GCM projections for historical and future climate scenarios.
  • To evaluate the performance of the Bias Adjustment and Statistical Downscaling (BASD) method for regional climate modeling.

Main Methods:

  • Employed the trend-preserving Bias Adjustment and Statistical Downscaling (BASD) method to process CMIP6 GCM outputs.
  • Generated a dataset encompassing historical simulations (1850-2014) and future projections (2015-2100) for temperature and precipitation.
  • Utilized observational data and hydrological modeling for performance evaluation across Peruvian and Ecuadorian river basins.

Main Results:

  • The BASD method significantly reduced biases between CMIP6 GCM simulations and observational data.
  • The adjusted data accurately represent long-term statistical properties, including mean and extreme values, and seasonal climate patterns.
  • Hydrological model evaluations confirmed the suitability of the adjusted GCM simulations for streamflow prediction (mean, low, and high flows).

Conclusions:

  • The BASD-CMIP6-PE dataset offers a reliable and high-resolution resource for climate change impact studies in Peru and Ecuador.
  • The validated BASD method enhances the utility of GCM outputs for regional climate research and adaptation planning.
  • This dataset is essential for informed decision-making in sectors such as agriculture, water resource management, and disaster risk reduction.