We bias-corrected the daily mean and maximum temperature output of the HAPPI experiments against observations using the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) bias correction approach (63). We linearly interpolated the temperature output from the HadAM3P 1987–2016 simulations (in a 360-day calendar) to the standard Gregorian calendar for comparison with observations. For Fig. 1 (B to D), we followed the newest ISI-MIP protocol (27) and used the EWEMBI dataset (1979–2013 daily data at 0.5 × 0.5° horizontal resolution) (27, 28) as reference for bias correction. Specifically, we interpolated the EWEMBI data onto the N96 grid and used the common period between the HadAM3P 1987–2016 simulations and EWEMBI, i.e., 1987–2013, as the reference period for computing the bias correction factors (see below). For the rest of this study, we used the 1987–2000 NMMAPS daily mean temperature observations as reference for bias-correcting the HAPPI daily mean temperature simulations in the 15 U.S. cities in this study.

For each calendar month and over each grid cell, we added a constant offset that equaled the average difference between the observed and simulated monthly mean data over the reference period to the time series of simulated temperatures in the HAPPI experiments. To correct the daily variability in the HAPPI simulations, we adjusted the distribution of the daily temperature residuals (around the corresponding monthly means) in the HAPPI simulations to that of the observations through a transfer function. This transfer function was derived from linear regression between the ranked observed residuals and simulated residuals over the reference period. Please refer to Hempel et al. (63) for specific details. All in all, by doing so, we preserved the long-term absolute trend in the simulations while correcting the daily variability to that of the observations.

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