Precipitation Scaling with Temperature in the Northeast US: Variations by Weather Regime, Season, and Precipitation Intensity

We present a novel hierarchical Bayesian quantile regression model to estimate how precipitation scales with temperature depending on season, weather regime (WR; i.e., large-scale patterns of atmospheric circulation), and percentile. The approach develops regional scaling estimates by partially pooling data across sites, accounting for uncertainty stemming from variable record lengths. Results using long-term records daily hourly both dry-bulb dew point the Northeast US suggest that rates vary 0% 8% per °C. Scaling rate variability is driven most season percentile precipitation, only modest variations WRs. Daily are highest in winter summer, while at percentiles greatest summer. Lower more extreme quantiles handful storms occurring cooler temperatures but strong vertical uplift heavy precipitation.