The National Weather Service (NWS) is investigating approaches to provide local climate products to partners and customers. One approach, which has been developed in a partnership between NWS' CSD, CPC, and Western Region, is to apply CPC methods on locally-derived composites based on a climate variability mode. This study uses ENSO-based composites to identify potential predictability in climate forecasts.

The composite study was conducted at ten stations in Arizona and eight stations in Montana to assess the viability of this method. Composites were based on CPC ENSO classification combined into three categories: cold, neutral and warm events. Cold and warm events included moderate to strong ENSO anomalies as defined by CPC. The neutral category included all weak warm and cold anomalies as well as neutral events. The composites were computed for monthly and seasonal mean temperature and precipitation.

Seasonal composites for these 18 stations were used together with CPC consolidated probabilistic historical forecasts for Nino 3.4 to assess stations forecasts for 1982 to 2002. These assessments were tested with observations from the same time period. The verification tests included rank probability skill scores and bias analysis. Preliminary results indicate significant local variations in the large-scale ENSO teleconnection pattern. This is especially important in areas with complex terrain such as Western United States.