Characteristics of National Water Model and North American Land Data Assimilation System Soil Moisture Climatological Distributions in the Mediterranean Climate of the California Russian River Basin

NOAA’s new National Water Model (NWM) offers a 1 km spatial and 1 hour temporal analyses and provides predictions of hydrologic variables of relevance to drought monitoring and forecasts. Because agricultural drought monitoring relies on an accurate representation of climatological soil moisture values to establish anomalies, our analysis focused on comparisons of this climatology from the NWM with climatologies from in situ soil moisture observations and climatologies from other gridded datasets currently used to inform the U.S. Drought Monitor, specifically those from the NOAA Climate Prediction Center’s (CPC) leaky bucket soil moisture model and from the North American Land Data Assimilation System (NLDAS). The NWM provides an opportunity to better describe physical processes and drought conditions at finer spatial and temporal scales than has been accomplished with previous land surface models.

This study investigates the skewed and narrow soil moisture climatological distributions during the dry season in the California Russian River basin region for the NWM, NLDAS, and CPC model data and NOAA Physical Science Division’s soil moisture network observations. Identification of drought conditions using soil moisture data provides unique challenges in Mediterranean climates, where the winter season provides most of the annual rainfall and the summer season is typically dry. Skewed climatological distributions during the dry season are found to have significant uncertainty for identifying low soil moisture percentiles needed to identify drought conditions at some locations in the Russian River basin and are notably different among the various models. Implications for deriving percentiles of soil moisture for these skewed distributions will be discussed.