Document Details

Evaluation of Non-hydrostatic Simulations of Northeast Pacific Atmospheric Rivers and Comparison to In-situ Observations

Daniel L. Swain, Bereket Lebassi-Habtezion, Noah S. Diffenbaugh | August 31st, 2015


Atmospheric rivers are long, narrow bands of concentrated atmospheric water vapor transport that provide an important atmospheric linkage between the subtropics and the midlatitudes, facilitating over 90% of meridional water vapor flux and often resulting in extreme precipitation events in regions of enhanced coastal orography. In this investigation, the authors conduct continuous (3 month), large-domain (3600 km × 3200 km), high-resolution (4 km), nonhydrostatic simulations using the Weather Research and Forecasting (WRF) Model and compare the observations to previously reported dropsonde observations from the California Land-Falling Jets Experiment (CALJET) and the Pacific Land-Falling Jets Experiment (PACJET) in order to address an existing gap in knowledge regarding the ability of atmospheric models to simulate the finescale vertical and horizontal structure of atmospheric rivers. The WRF simulations reproduce key structural and thermodynamic characteristics of atmospheric rivers—including well-defined corridors of strong water vapor transport, moist-neutral stability in the lower troposphere, and strong low-level jet/water vapor transport maxima near ~1 km MSL. While WRF does generally capture the extreme values of instantaneous vertically integrated water transport—a defining feature of real-world atmospheric rivers—constituent variables exhibit biases relative to observations, including −11.2% for integrated vapor transport, +5.9% for integrated water vapor, and −17.7% for 1 km MSL wind speed. Findings suggest that high-resolution nonhydrostatic atmospheric simulations are an appropriate tool for investigating atmospheric rivers in contexts where finescale spatial structure and realistic water vapor transport maxima are important.

Keywords

atmospheric rivers, flood management, modeling, water supply forecasting