Fifty-Seven-Year California Reanalysis Downscaling at 10 km (CaRD10). Part II: Comparison with North American Regional Reanalysis

Abstract

The California Reanalysis Downscaling at 10 km (CaRD10) was compared with the North American Regional Reanalysis (NARR), which is a data assimilation regional analysis at 32-km resolution and 3-hourly output using the Eta Model for the period 1979 through the present using the NCEP/Department of Energy (DOE) reanalysis as lateral boundary conditions. The objectives of this comparison are twofold: 1) to understand the efficacy of regional downscaling and horizontal resolution and 2) to estimate the uncertainties in regional analyses due to system differences. The large-scale component of atmospheric analysis is similar in CaRD10 and NARR. The CaRD10 daily winds fit better to station observations than NARR over ocean where daily variability is large and over land. The daily near-surface temperature comparison shows a similar temporal correlation with observations in CaRD10 and NARR. Several synoptic examples such as the Catalina eddy, coastally trapped wind reversal, and Santa Ana winds are better produced in CaRD10 than NARR. These suggest that the horizontal resolution of the model has a large influence on the regional analysis, and the near-surface observation is not properly assimilated in the current state-of-the-art regional data assimilation system. The CaRD10 near-surface temperature and winds on monthly and hourly scales are similar to NARR with more regional details available in CaRD10. The Southwestern monsoon is poorly reproduced in CaRD10 because of the position of the lateral boundary. The spatial pattern of the two precipitation analyses is similar, but CaRD10 shows smaller-scale features despite a positive bias. The trends of 500-hPa height and precipitation are similar in the two analyses but the near-surface temperature trend spatial patterns do not agree, suggesting the importance of regional topography, model physics, and land surface schemes. A comparison of a major storm event shows that both analyses suffer from budget residual. CaRD10?s large precipitation is related to wind direction, spatial distribution of precipitable water, and a large moisture convergence. Dynamical downscaling forced by a global analysis is a computationally economical approach to regional-scale long-term climate analysis and can provide a high-quality climate analysis comparable to current state-of-the-art data-assimilated regional reanalysis. However, uncertainties in regional analyses can be large and caution should be exercised when using them for climate applications.