Abstract
Both spatial and temporal information sources contribute to the predictability of precipitation occurrence at a given location. These sources, and the level of predictability they provide, are relevant to forecasting and understanding precipitation processes at different time scales. We use information theory-based measures to construct connected “chains of influence” of spatial extents and timescales of precipitation occurrence predictability across the continental U.S, based on gridded daily precipitation data. These regions can also be thought of as “footprints” or regions where precipitation states tend to be most synchronized. We compute these chains of precipitation influence for grid cells in the continental US, and study metrics regarding their lengths, extents, and curvature for different seasons. We find distinct geographic and seasonal patterns, particularly longer chain lengths during the summer that are indicative of larger spatial extents for storms. While synchronous, or instantaneous, relationships are strongest for grid cells in the same region, lagged relationships arise as chains reach areas farther from the original cell. While this study focuses on precipitation occurrence predictability given only information about precipitation, it could be extended to study spatial and temporal properties of other driving factors.
Highlights
The generation and movement of precipitation across the continental U.S varies seasonally and between individual events
If there is no path crossing and a statistically significant relationship between precipitation occurrences at the last link added and the central cell, we check whether the chain has attained some maximum length. We choose this length as 200 grid cells, which is nearly the gridded length of the continental U.S we find few cases were a precipitation chain moves in a single direction, as instead paths tend to curve around and fill the grid cells in a region closer to the original central cell
We find that on average, chains are longer in terms of both D and N in the summer (JJA) relative to other months. This behavior of longer precipitation chains in the summer indicates that in this season, precipitation occurrence at a location is more predictable at a larger distance
Summary
The generation and movement of precipitation across the continental U.S varies seasonally and between individual events. There is persistence, or patterns, in terms of typical timescales of storm events and directions of movement. This leads to an average predictability of precipitation at any location, based on some defined subset of driving factors. These driving factors range widely in timescales from long, such as decadal or longer climatic indices (Ting and Wang, 1997; Barlow et al, 2001; Carvalho, 2020), to short, such as moisture advection and precipitation recycling (Dominguez et al, 2006, 2008), or storm movement on subdaily timescales (Hurrell and Deser, 2010; Seo et al, 2012; Gao and Fang, 2018). We focus on the predictability of daily precipitation occurrence at a certain location, given information about precipitation occurrence at increasingly distant locations
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