Monday, 23 January 2017: 1:30 PM
602 (Washington State Convention Center )
Youlong Xia, EMC/NCEP/IMSG, College Park, MD; and M. Ek, K. Mitchell, D. M. Mocko, B. Narapusetty,
S. Kumar, and C. D. Peters-Lidard
NCEP EMC has developed and implemented the North American Land Data Assimilation System (NLDAS) for monitoring droughts and floods over the Continental United States (CONUS) in support of NIDIS activities such as the US Drought Monitor (USDM). The phase 2 NLDAS (NLDAS-2) drought monitor is executed daily by NCEP and produces daily, weekly and monthly CONUS fields of the anomaly and percentile values of soil moisture, snow water equivalent (SWE), total runoff, stream-flow, evaporation and precipitation, all in ensemble mode via execution of four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid (~ 14 km) using common hourly surface forcing. The foundation of the anomaly and percentile fields is the NLDAS-2 climatology, which is currently a 28-year climatology (1980-2007). As several recent severe drought episodes occurred in Texas (2011), CONUS (2012), and California (2013-2014), the extension of the climatology length becomes a critical task.
In this presentation, we show that replacement of the 28-year with a newer 36-year climatology (1980-2015) has surprisingly strong impacts on the derived anomaly and (especially) percentile fields of key drought events, in particular for extremely severe drought events (D3 and D4 in USDM). In contrast, there is small impact on extremely wet events (W3 and W4 categories), possibly because there were relatively fewer extremely wet events during 2008-2015. Also, we analyze two mutually exclusive 18-year climatologies to further confirm our conclusions and investigate uncertainties from models and climatology lengths. At present, we are working with NASA scientists to investigate methods for deriving an “optimal climatology” (such as the method of Narapusetty et al., 2009, J. Climate), by means of which a new NLDAS climatology (e.g., up-dated routinely about every 5 years) would exhibit suitably less impact on the percentile fields in “before and after” comparisons for well-known historical drought episodes.
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