Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
NOAA’s new National Water Model (NWM) offers fine spatial and temporal analyses and predictions of hydrologic variables of relevance to drought monitoring and forecasts. In particular, the state-of-the-art NWM has a Richard’s equation representation of the vertical unsaturated flow, and thus we present preliminary results exploring the potential for NWM soil moisture nowcasts to inform drought monitoring. Because drought monitoring relies on an accurate representation of climatological soil moisture values to establish anomalies, we begin our analysis focused on comparisons of this climatology in the NWM with climatologies from in situ soil moisture observations and soil moisture climatologies from other gridded datasets currently used to inform the National Drought Monitor, specifically those from the NOAA Climate Prediction Center’s soil moisture model and from North American Land Data Assimilation System (NLDAS).
In this study, we utilize NOAA PSD’s instrumentation network in California’s Russian River watershed (a NIDIS Pilot basin) to establish a simple, information-rich method for displaying an anomaly given soil moisture’s highly non-Gaussian, strongly seasonally varying probability density function. This method is used to illustrate differences in the climatology and anomalies during California’s recent drought and the extremely wet water year 2017 across the various soil moisture datasets. Differences in the climatologies and anomalies will be discussed in the context of implications for drought monitoring.
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