Assessment of Extreme Quantitative Precipitation Forecasts and Development of Regional Extreme Event Thresholds Using Data from HMT-2006 and COOP Observers

Abstract

Extreme precipitation events, and the quantitative precipitation forecasts (QPFs) associated with them, are examined. The study uses data from the Hydrometeorology Testbed (HMT), which conducted its first field study in California during the 2005/06 cool season. National Weather Service River Forecast Center (NWS RFC) gridded QPFs for 24-h periods at 24-h (day 1), 48-h (day 2), and 72-h (day 3) forecast lead times plus 24-h quantitative precipitation estimates (QPEs) from sites in California (CA) and Oregon-Washington (OR-WA) are used. During the 172-day period studied, some sites received more than 254 cm (100 in.) of precipitation. The winter season produced many extreme precipitation events, including 90 instances when a site received more than 7.6 cm (3.0 in.) of precipitation in 24 h (i.e., an ''event'') and 17 events that exceeded 12.7 cm (24 h) 21 [5.0 in. (24 h) 21 ]. For the 90 extreme events f.7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ]g, almost 90% of all the 270 QPFs (days 1-3) were biased low, increasingly so with greater lead time. Of the 17 observed events exceeding 12.7 cm (24 h) 21 [5.0 in. (24 h) 21 ], only 1 of those events was predicted to be that extreme. Almost all of the extreme events correlated with the presence of atmospheric river conditions. Total seasonal QPF biases for all events fi.e., $0.025 cm (24 h) 21 [0.01 in. (24 h) 21 ]g were sensitive to local geography and were generally biased low in the California-Nevada River Forecast Center (CNRFC) region and high in the Northwest River Forecast Center (NWRFC) domain. The low bias in CA QPFs improved with shorter forecast lead time and worsened for extreme events. Differences were also noted between the CNRFC and NWRFC in terms of QPF and the frequency of extreme events. A key finding from this study is that there were more precipitation events .7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] in CA than in OR-WA. Examination of 422 Cooperative Observer Program (COOP) sites in the NWRFC domain and 400 in the CNRFC domain found that the thresholds for the top 1% and top 0.1% of precipitation events were 7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] and 14.2 cm (24 h) 21 [5.6 in. (24 h) 21 ] or greater for the CNRFC and only 5.1 cm (24 h) 21 [2.0 in. (24 h) 21 ] and 9.4 cm (24 h) 21 [3.7 in. (24 h) 21 ] for the NWRFC, respectively. Similar analyses for all NWS RFCs showed that the threshold for the top 1% of events varies from ;3.8 cm (24 h) 21 [1.5 in. (24 h) 21 ] in the Colorado Basin River Forecast Center (CBRFC) to ;5.1 cm (24 h) 21 [3.0 in. (24 h) 21 ] in the northern tier of RFCs and ;7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] in both the southern tier and the CNRFC.It is recommended that NWS QPF performance in the future be assessed for extreme events using these thresholds.

Atmospheric rivers: a mini-review

“…Ralph et al (2010) showed that NWP models can have large forecasting errors in the landfalling of ARs. An analysis of the ability of a model to identify and predict an AR is possible via its ability to identify and predict the key characteristics of ARs, such as position, water vapor transport, extent, or frequency of occurrence.…”

Climatology and Environmental Characteristics of Extreme Precipitation Events in the Southeastern United States

“…In this type of pattern, heavy precipitation is supported by the poleward transport of warm, moist air along a LLJ positioned ahead of a slowmoving cold front (e.g., Lackmann 2002;Mahoney and Lackmann 2007) into a strongly ascending polewardmoving airstream associated with a warm conveyor belt (e.g., Browning 1990;Wernli and Davies 1997;Pfahl et al 2014). Additionally, water vapor fluxes into the region of heavy precipitation are sometimes concentrated within narrow, elongated corridors called ''atmospheric rivers'' (e.g., Newell et al 1992;Zhu and Newell 1998;Ralph et al 2004), which have been shown to support extreme flood-producing precipitation in the central and eastern United States (Moore et al 2012;Lavers and Villarini 2013).…”

“…Several prior studies (e.g., Johnson 2005, 2006;Kunkel et al 2012) have identified EPEs in the United States using the historical gauge-based recurrence interval precipitation thresholds calculated by Hershfield (1961), while others (e.g., Brooks and Stensrud 2000;Ralph and Dettinger 2012;Hitchens et al 2012Hitchens et al , 2013 have used fixed precipitation thresholds. We opted to use geographically varying upper quantiles of daily (24-h period ending 1200 UTC) precipitation amount, similar to Ralph et al (2010) and Sukovich et al (2014). Specifically, the 99th and 99.9th percentile values computed at each grid point for all days in all seasons during 2002-11 with .0 mm of precipitation ( Fig.…”

The More Rain, the Better the Model Performs—The Dependency of Quantitative Precipitation Forecast Skill on Rainfall Amount for Typhoons in Taiwan

“…Besides generally easy calculation and interpretation (section 2c), these measures are chosen also for physical and practical reasons. From timeaveraged scores that value successful forecast of events (i.e., hits) such as the TS, it is long recognized that model QPFs depend on forecast range (the longer the poorer), as forecast errors typically grow with time (e.g., Olson et al 1995;Ralph et al 2010). 1), the rainfall from forced uplift is phase locked to the windward slopes (i.e., nonmoving) and is often a significant component of total rainfall (e.g., Chang et al 1993;Cheung et al 2008;Chang et al 2013).…”