Standardized anomaly methods have successfully been used to analyze meteorological data such as height fields, moisture fields, wind fields, and mean sea level pressure (MSLP) fields, however, little attention, if any, has been given to the creation of standardized anomalies for horizontal gradient fields. Forecasters and researchers often use gradient fields to diagnose, forecast, and perform post-analysis on different weather events. If a gradient field can be standardized, standardized anomaly methods can be applied to create standardized anomalies of gradient fields.

In this study mean monthly pressure gradients over a specified distance (in this case, between two observing sites) were calculated, followed by the calculation of standard deviation values for each month. Based on these standard deviations, standardized anomalies were created. Taking this method one step further, since forecasters frequently use “pressure gradient trends” (the 24 hour change in the pressure gradient), a set of standardized anomalies for the pressure gradient trend was also developed. Although not done here, a graphic can be made using this method. For example, it would require the values of the mean pressure gradients over 100 km segments in the u direction to be assigned to their respective midpoints, after which standard deviations can be determined, and finally standardized anomalies can be used for all of the points to form a graphic. The same can be done in the v direction resulting in a similar graphic. This u and v format currently enjoys widespread use as a standardized anomaly field for wind speed graphics.

Gradients in the height field have proven to be successful tools for applications such as forecasting high winds or heavy rainfall that can lead to flash flooding. With this in mind, standardized anomalies at the 850 mb level were developed using the gradient between a sounding in southern California and a sounding in southern Arizona. Both the height gradient field and the height gradient trend along with their standardized anomalies were calculated.

This study includes the application of standardized anomalies generated from gradient fields to various meteorological forecast problems. Also included is an application of the standardized anomaly method to national indices as well as locally created indices to look at weather problems such as convection.

As an example, a good correlation was noted between the results of the standard anomaly computation and the occurrence of heavy rain. For events with strong positive anomalies (3.7 or larger) in the 850 mb height gradient field at 1200 UTC, 3 of the 4 events resulted in over 1.25 inches of rainfall at San Diego Lindbergh Field (KSAN) during the period 1998-2002. Twice as much rain can easily be expected in the mountains with at least some flooding, and possibly up to 7 times that amount and more significant flooding under warm rain scenarios. A relationship between El Nino, La Nina, and the size of the standardized height gradient anomalies was noted in the data.