Summary
The study evaluates three bias‑correction and downscaling methods (QDM, BCCAQ, ISI‑MIP) for improving MIROC‑ESM climate projections for Indonesia under SRM (G4) and RCP4.5 scenarios. ISI‑MIP performs best, showing strongest correlation with observations across regions and seasons. Using this method, extreme‑climate indices reveal that SRM consistently lowers maximum temperatures (TXx) compared with RCP4.5, while effects on extreme rainfall (Rx1Day) are inconsistent. Overall, SRM is effective at reducing future temperature extremes but less reliable for precipitation.
Abstract
Solar Radiation Management (SRM) is a controversial idea for minimizing global warming. Simulations have been carried out to generate the future projection of the climate condition from the Earth System Models (ESM). However, the outputs are available on low-resolution data with some degree of bias. Downscaling is a solution to obtain ESM data that resembles the local climate. This study also applied several popular bias correction methods to correct the bias of Marine-Earth Science and Technology (MIROC)-ESM historical data and further assessed the significance test for each grid through correlation map and Taylor diagram. Extreme index (e.g. the max 1-day precipitation amount (RX1Day) and the hottest day (TXx)) projected with SRM and without SRM is derived, based on the downscaled output and the best correction bias. We found an inconsistent pattern of difference Rx1Day index between with and without SRM scenarios, while the TXx index of the with SRM scenario is consistently below the without SRM scenario. It indicated that SRM will effectively reduce the level of future maximum temperature.
