On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States

Abstract

Flooding over the central United States is responsible for large socioeconomic losses. Atmospheric rivers (ARs), narrow regions of intense moisture transport within the warm conveyor belt of extratropical cyclones, can give rise to high rainfall amounts leading to flooding. Short-term forecasting of AR activity can provide basic information toward improving preparedness for these events. This study focuses on the verification of the skill of five numerical weather prediction models in forecasting AR activity over the central United States. We find that these models generally forecast AR occurrences well at short lead times, with location errors increasing from one to three decimal degrees as the lead time increases to about 1 week. The skill (both in terms of occurrence and location errors) decreases with increasing lead time. Overall, these models are not skillful in forecasting AR activity over the central United States beyond a lead time of about 7 days.

Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States

“…Because most of the water vapor content in the atmosphere is within the first 5 km altitude from the surface, we used data from the surface to 300hPa (28 vertical levels in MERRA) to calculate IVT. This is consistent with other studies over the central United States (Lavers and Villarini, 2013;Nayak et al, 2014).…”

“…Improved understanding of the distribution of rainfall during ARs and how it relates to water vapor transport can help to better model or constrain the precipitation process in regional and numerical weather prediction models. Over the central United States, numerical weather prediction models forecast ARs with good skill up to a lead-time of 7 days (Nayak et al, 2014). The results from the present study, therefore, can have a direct impact on developing flood protection strategies during ARs as once we know the AR location and duration, it is possible to anticipate the location and intensity of maximum rainfall.…”

“…For an identified AR, the set of maximum IVT grid points is referred to as the AR major axis. The length criterion for ARs is the distance between 40ºN to 30.5ºN which is more than 1050km, similar toNayak et al (2014). If three consecutive time steps (18 hours) are identified as AR steps, we consider the collection of the AR steps as a persistent AR (or simply an AR).…”

Evaluation of the moisture sources in two extreme landfalling atmospheric river events using an Eulerian WRF tracers tool

“…There are several proposed methods of AR detection, most of which are based on thresholds of integrated water vapor (IWV) and/or IVT, shape criteria, and from satellite or reanalysis data (e.g., Ralph et al, 2004;Bao et al, 2006;Lavers et al, 2011Lavers et al, , 2012Dettinger, 2011;Nayak et al, 2014;Ramos et al, 2015;Eiras-Barca et al, 2016;Brands et al, 2016). Guan and Waliser (2015) developed a global detection method using filters of intensity, direction, geometry and coherence of the structures.…”

Climate and rivers

“…There is a burgeoning number of studies that demonstrate direct AR–flood associations. For the central United States, more than 70% of the annual instantaneous peak discharges and peaks‐over threshold floods have been found to be associated with AR, particularly during the winter and spring (Nayak, Villarini, & Lavers, ). Similarly, ARs play a significant role in generating floods across the western United States where the probability that an AR will generate a given runoff threshold increases significantly when daily mean water vapour transport increases from 300 kg·m −1 ·s −1 to greater than 600 kg·m −1 ·s −1 (Konrad & Dettinger, ).…”