Examining Severe Weather Events Using Reanalysis Datasets

The higher-resolution North American Regional Reanalysis (NARR) data are compared to the coarser National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP-NCAR) reanalysis data. It is found that the higher-resolution NARR data contain the most significant improvements in the lower levels, particularly within the boundary layer. The impact of these improved details is evident on low-level fields such temperatures, winds, moisture, and mean-sea level pressure.

In addition to the higher resolution of the data, the NARR contains many new fields not available in the original NCEP-NCAR dataset. Models derived fields, such as convectively available potential energy (CAPE) and convective inhibition (CIN), have been included and may help depict conditions associated with severe weather events. Several examples will be shown in the presentation.

Standardized anomalies are computed from each data set using the means and standard deviations derived from the coarser NCEP-NCAR reanalysis data. It is revealed that the NARR analyses show more detailed anomaly patterns, primarily at lower-levels in the atmosphere. Furthermore, the impacts on the locations of low-level moisture and precipitable water anomalies in case studies are significant.

Data from several winter storms and recent widespread severe weather events will be presented. The emphasis will be on the effects of the finer resolution data on the low-level fields with respect to the location of the standardized anomalies and the improved gradients of the individual fields. In addition, the case studies are supplemented with examples of new analysis fields, such as CAPE, which may provide more insight to the pattern configurations of significant weather events.