55 An Evaluation of Quantitative Precipitation Estimators over the Western United States

Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Matthew E. Jeglum, NOAA/NWS, Salt Lake City, UT; and C. Kahler, P. Veals, and A. Edman

Handout (2.1 MB)

Accurate gridded Quantitative Precipitation Estimation (QPE) is critical as input to hydrologic models, to calibrating post-processed numerical weather model output, and situational awareness of operational weather forecasters. Due to the complexity of terrain in the Western US and the very tight gradients of precipitation that can occur there, creating high-quality QPE has historically been challenging in this region. Large areas of the Western US have minimal or no radar coverage from the WSR-88D network, and surface observations tend to be concentrated in valleys and populated areas, leaving much of the relatively wet high elevations unsampled. While the expanding Snowpack Telemetry (SNOTEL) network has helped to alleviate the latter problem, many areas are still unsampled. Integration of observations into the analysis, as well as extrapolation and interpolation of observations to unobserved areas, are critically-important part of any QPE product. We will assess how those methods perform at gauge locations in this paper.

There are currently a number of methods utilized in the United States to produce QPE, which vary from simple radar derived products to multi-sensor automated algorithms to heavily human-edited products. In this paper we will compare 7 different products computed at 6-h accumulation intervals over the Western US for a 12-month period from July 2016- July 2017. Analyzed QPE products include the radar-derived, gauge-corrected radar- derived and Mountain Mapper products from the Multi-radar/Multi-sensor System (MRMS), the QPE from the Unrestricted Mesoscale Analysis (URMA), QPE produced by the Parameter-elevation Regression on Independent Slopes Model (PRISM), the Climatology-Calibrated Precipitation Analysis, and QPE from the National Water Model. Each product will be compared to quality-controlled gauge data across the Western US to establish its quality using standard skill metrics, such as the Brier Skill Score. Results will be stratified by season, elevation, and geographic region.

The relative quality of each QPE product was found to vary by season and location within the Western US. The MRMS radar-only and gauge-corrected radar perform better in summer relative to other methods than in winter, where the lack of radar coverage is detrimental. Despite that fact that many of the products utilize gauge data in creating the analysis, their performance at the gauge locations varied considerably. Post hoc combinations of QPE products performed better than individual products in some cases.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner