Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: Ami T. Arthur x
  • Refine by Access: All Content x
Clear All Modify Search
Ami T. Arthur, Gina M. Cox, Nathan R. Kuhnert, David L. Slayter, and Kenneth W. Howard

The National Basin Delineation Project (NBDP) was undertaken by the National Severe Storms Laboratory to define flash-flood-scale basin boundaries for the country in support of the National Weather Service (NWS) Flash Flood Monitoring and Prediction (FFMP) system. FFMP-averaged basin rainfall calculations allow NWS forecasters to monitor precipitation in flash-flood-scale basins, improving their ability to make accurate and timely flash-flood-warning decisions. The NBDP was accomplished through a partnership with the U.S. Geological Survey Earth Resources Observation Systems (EROS) Data Center (EDC). The one-arc-second (approximately 30 m)-resolution digital terrain data in the EDC's National Elevation Dataset provided the basis for derivation of the following digital maps using a geographic information system: 1) a grid of hydrologically conditioned elevation values (all grid cells have a defined flow direction), 2) a grid of flow direction indicating which of eight directions water will travel based on slope, 3) a grid of flow accumulation containing a count of the number of upstream grid cells contributing flow to each grid cell, 4) synthetic streamlines derived from the flow accumulation grid, and 5) flash-flood-scale basin boundaries. Special techniques were applied in coastal areas and closed basins (basins with no outflow) to ensure the accuracy of derived basins and streams. Codifying each basin with a unique identifier and including hydrologic connectivity information produced a versatile, seamless dataset for use in FFMP and other national applications.

Full access
Steven M. Martinaitis, Andrew P. Osborne, Micheal J. Simpson, Jian Zhang, Kenneth W. Howard, Stephen B. Cocks, Ami Arthur, Carrie Langston, and Brian T. Kaney

Abstract

Weather radars and gauge observations are the primary observations to determine the coverage and magnitude of precipitation; however, radar and gauge networks have significant coverage gaps, which can underrepresent or even miss the occurrence of precipitation. This is especially noticeable in mountainous regions and in shallow precipitation regimes. The following study presents a methodology to improve spatial representations of precipitation by seamlessly blending multiple precipitation sources within the Multi-Radar Multi-Sensor (MRMS) system. A high spatiotemporal resolution multisensor merged quantitative precipitation estimation (QPE) product (MSQPE) is generated by using gauge-corrected radar QPE as a primary precipitation source with a combination of hourly gauge observations, monthly precipitation climatologies, numerical weather prediction short-term precipitation forecasts, and satellite observations to use in areas of insufficient radar coverage. The merging of the precipitation sources is dependent upon radar coverage based on an updated MRMS radar quality index, surface and atmospheric conditions, topography, gauge locations, and precipitation values. Evaluations of the MSQPE product over the western United States resulted in improved statistical measures over its individual input precipitation sources, particularly the locally gauge-corrected radar QPE. The MSQPE scheme demonstrated its ability to sufficiently fill in areas where radar alone failed to detect precipitation due to significant beam blockage or poor coverage while minimizing the generation of false precipitation and underestimation biases that resulted from radar overshooting precipitation.

Free access