A Snowpack Forecasting Model for the Eastern Sierra Nevada Based on Cointegration With the North Pacific High Sea-Level Pressure Anomaly

• Main Authors: John S. Rath, Mariza Costa-Cabral
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-05-01
• Series: Frontiers in Earth Science
• Subjects: cointegration; forecasting; North Pacific High; Owens valley; VECM models; categorical models
• Online Access: http://journal.frontiersin.org/article/10.3389/feart.2018.00054/full

A cointegrated relationship has been identified between the January sea level pressure anomaly at the climatological location of the North Pacific High (NPH) and seasonal precipitation throughout California (Costa-Cabral et al., 2016). This cointegration can be used for forecasting precipitation or snowpack indices at California locations. Here we develop a cointegration model, termed Vector Error Correcting Model (VECM), for issuing a forecast, in early February, for April 1 snow water content (SWC) at snow stations in the Eastern Sierra Nevada mountain range of California. We additionally develop a categorical model for forecasting the April 1 SWC category (dry, normal, or wet) based on the VECM forecast. Snowmelt from this region flows into the Owens River and serves as a major source of freshwater for the Los Angeles metropolitan area. The VECM relies on the cointegration between three variables: the January NPH sea level pressure, the February 1 SWC, and the April 1 SWC. Forecasts based on this VECM model have higher measures of skill compared to linear correlation methods. The statistical tool presented can be applied to other California watersheds and may provide reservoir operators the needed insight for making storage decisions in early February.