A. Advances in Drought Monitoring
a. Developing the North American Land Data Assimilation System for drought monitoring
SM percentiles are good indicators of agricultural drought. However, in contrast to the SPI used as an indicator of meteorological drought, there are few long-term, in-situ measurements useful to construct SM levels necessary to establish anomalous conditions. Earlier, the information on agricultural drought was provided by a simple "leaky bucket" model and the Palmer Drought Severity Index. Long-term multi-institution research investments (from the MAPP Program and its predecessors) have led to the development of the North American Land Data Assimilation System (NLDAS), an important step to provide Drought Monitor authors and Drought Outlook forecasters more accurate and objective information on SM levels and runoff. The NLDAS products are now used operationally in the CPC monthly Drought Briefing to assess the current development of drought. These products are also used by the Drought Monitor authors and Drought Outlook forecasters for their operations.
Currently, both NCEP's Environmental Modeling Center (EMC) and the University of Washington (UW) run parallel drought monitoring systems over the continental U.S. based on the NLDAS. Because these two systems use different forcing and models, the comparison between the NLDAS from the EMC/NCEP and the UW system show that there are significant differences for the period 1979-2008, which point to remaining uncertainties. As an example, Figure 1 displays the monthly mean standardized SM anomalies and runoff index SRI6 averaged over the area 38-42oN and 105-110oW for the UW (green line) and NCEP (red line) ensemble means. For SM levels and runoff indices, differences are relatively small among different land surface models in the same system. However, the ensemble mean differences between the two systems are large and consistent over the western United States. Currently, NCEP CPC uses both systems for operational drought monitoring. Research is continuing on how to reduce uncertainties and further improve NLDAS for operational drought monitoring.
Figure 1: (a) Monthly mean standardized SM anomalies averaged over the area of (38-42oN, 105-110oW) for the UW (green line) and NCEP (red line) ensemble means; (b) same as (a), but for each individual member from the UW system (green lines) and the NCEP system (red lines); and (c)-(d) same as (a)-(b), but for SRI6
b. Advancing drought monitoring using remote sensed data
There is an urgent need for independent indicators to verify soil moisture and evaporation from the NLDAS because of remaining uncertainties in the NLDAS systems. An independent drought indicator can give water resource managers additional information to assess drought conditions. Satellite-derived drought indices have great potential to fulfill this need. Hence, much research has gone into developing methodologies to exploit remote-sensed data for drought monitoring with good payoffs. For example, thermal infrared imagery from the GOES satellite and a fully-automated inverse model of Atmosphere-Land Exchange (ALEXI) have been used to model hourly evapotranspiration (ET) and surface moisture stress over a 10-km resolution grid covering the contiguous United States. Validation studies for 2002-2004 over a range of land cover and climatic conditions indicate 10-15% accuracy in hourly ET. In May 2012, the USDA implemented the use of Evaporative Stress Index (ESI) in operations, an important recognition of its utility. The NCEP CPC also uses ESI, for drought monitoring. Figure 2 shows an example of the ESI, which can be compared with the soil moisture percentiles from the University of Washington NLDAS system. Both indicate drought over the Colorado basin and over the Ohio Valley. Research is ongoing to evaluate and understand differences between ESI and NLDAS systems, as well as to develop new methodologies to exploit a variety of remotely-sensed drought-relevant data for direct assimilation in NLDAS.
Figure 2: Soil moisture percentiles from the VIC model (University of Washington, left) and ESI (right), for June 2012. Contours are indicated by the color bar.
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