We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.
Work in this area is concerned with improving our understanding of the processes that govern the climate system—including the interactions between the atmosphere, oceans, land surfaces, cryosphere, and biosphere—and how they contribute to climate change.
Using a 6-km-resolution regional climate simulation of Southern California, the effect of orographic blocking on the precipitation climatology is examined. To diagnose whether blocking occurs, precipitating hours are categorized by a bulk Froude number. The precipitation distribution becomes much more spatially homogeneous as the Froude number decreases, and an inspection of winds confirms that this results from the increasing prevalence of orographic blocking. Low Froude (Froude approximately less than 1), blocked cases account for a large fraction of climatological precipitation, particularly at the coastline where more than half is attributable to blocked cases. Thus, the climatological precipitation–slope relationship seen in observations and in the simulation is a hybrid of blocked and unblocked cases.
Simulated precipitation distributions are compared to those predicted by a simple linear model that includes only rainfall arising from direct forced topographic ascent. The agreement is nearly perfect for high Froude (Froude substantially larger than 1) cases but degrades dramatically as the index decreases; as blocking becomes more prevalent, the precipitation–slope relationship becomes continuously weaker than that predicted by the linear model. Because of its high fidelity during unblocked cases, it is surmised that blocking effects are the primary limitation preventing the linear model from accurately representing precipitation climatology and that the representation would be significantly improved during low Froude hours by the addition of a term to reduce the effective slope of the topography. These results suggest orographic blocking may substantially affect climatological precipitation distributions in similarly configured coastal areas.