Tracking Atmospheric Rivers Globally: Spatial Distributions and Temporal Evolution of Life Cycle Characteristics

January 22, 2020

CW3E collaborators Bin Guan (UCLA Project Scientist) and Duane Waliser (Chief Scientist of NASA/JPL Earth Science and Technology Directorate) recently published an article in the Journal of Geophysical Research: Atmospheres, titled “Tracking Atmospheric Rivers Globally: Spatial Distributions and Temporal Evolution of Life Cycle Characteristics”. The paper is included in the journal’s special issue on “Atmospheric Rivers: Intersection of Weather and Climate”. The research was supported by the California Department of Water Resources (DWR), the NASA Energy and Water cycle Study (NEWS) program, and the NASA GOES-16/17 special task.

The study documents Version 3, the latest iteration of the continual improvements in the Tracking Atmospheric Rivers Globally as Elongated Targets (tARget) algorithm, adding the capability to track AR life cycles globally along with other refinements. The algorithm was initially published in Guan and Waliser (2015) and later updated in Guan, Waliser, and Ralph (2018). As one of a few peer-reviewed and validated global AR detection algorithm currently available, the algorithm has been a vital tool used by scientists within the AR research and operations community, including many scientists at CW3E.

Using output from tARget Version 3, the study quantitatively characterized AR life cycles around the globe, including their spatial distributions, temporal evolution, and seasonal dependence, and examined the sensitivity of selected AR life cycle characteristics to various tracking considerations. It is expected that the consideration of AR life cycles will provide new insights into better understanding the fundamental processes of ARs – such as their moisture sources and pathways – and the representation of such processes in weather and climate models, and help improve our ability in predicting AR activity and impacts on subseasonal-to-seasonal (S2S) and longer time scales. S2S and seasonal prediction of ARs (and lack thereof, i.e., drought) is currently a key science and applications area of interest to DWR and with DWR-supported research and experimental forecast activities ongoing at CW3E, JPL, and UCLA.

Figure 1: Example output from the tARget algorithm, showing the track of one longer-lived AR (red) alongside other shorter-lived ARs. Only the 0600 time step every two days is shown for conciseness. The contour labels indicate the unique ID assigned to each track by the algorithm. For a given track, the ID number is populated to all grid cells within the boundary of all the AR shapes that belong to the given track. Key statistics for each track (lifetime, travel distance, mean travel speed, etc.; not shown) are also included in the output database. From Guan and Waliser 2019 (Figure 4).

Figure 2: Life cycle characteristics of ARs tracked by the tARget algorithm summarized from the results presented earlier. (upper) Spatial distributions of the long-term climatology. Smoothing was applied to highlight the most pronounced features. (lower) Temporal evolution of a typical/composite AR life cycle. Locations of the AR centroids (white dots) and track (light blue curve) are determined by propagating an AR centroid from an arbitrary starting point (here, 170°W, 36°N) forward in time based on the composite travel speed/direction at each stage of its life cycle as shown in Figure 15. Results are based on ~126,000 AR tracks in the NASA MERRA-2 reanalysis during 1980–2017. From Guan and Waliser 2019 (Figure 17).

Guan, B., & Waliser, D. E. (2019): Tracking Atmospheric Rivers Globally: Spatial Distributions and Temporal Evolution of Life Cycle Characteristics. Journal of Geophysical Research: Atmospheres, 124, 12523-12552 https://doi.org/10.1029/2019JD031205