A hierarchicalBayesian regional model for nonstationary precipitation extremes inNorthernCalifornia conditioned on tropical moisture exports

Abstract

Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most extreme precipitation and flooding events in the midlatitudes. The interannual frequency and intensity of such atmospheric rivers (ARs), or tropical moisture exports (TMEs), are connected to the risk of extreme precipitation events in areas where moisture convergence occurs. This study presents a nonstationary, regional frequency analysis of precipitation extremes in Northern California that is conditioned on the interannual variability of TMEs entering the region. Parameters of a multisite peaks-over-threshold model are allowed to vary conditional on the integrated moisture delivery from TMEs over the area. Parameters are also related to time-invariant, local characteristics to facilitate regionalization to ungaged sites. The model is developed and calibrated in a hierarchical Bayesian framework to support partial pooling and enhance regionalization skill. The model is cross validated along with two alternative, increasingly parsimonious formulations to assess the additional skill provided by the covariates. Climate diagnostics are also used to better understand the instances where TMEs fail to explain variations in rainfall extremes to provide a path forward for further model improvement. The modeling structure is designed to link seasonal forecasting and long-term projections of TMEs directly to regional models of extremes used for risk estimation. Results suggest that the inclusion of TME-based information greatly improves the characterization of extremes, particularly for their frequency of occurrence. Diagnostics indicate that the model could be further improved by considering an index for frontal systems as an additional covariate.

An event synchronization method to link heavy rainfall events and large‐scale atmospheric circulation features

“…ARs are relatively narrow regions in the atmosphere that are responsible for most of the lateral transport of water vapour from the tropics to higher latitudes (Dacre et al, ). They appear to explain many of the heavy precipitation events (HPEs) in different areas of the world (Zhu and Newell, ; Lavers et al, ; Nakamura et al, ; Rutz and Steenburgh, ; Lu et al, ; Gimeno et al, ; Steinschneider and Lall, , ; Najibi et al, ). Recently Krichak et al .…”

A General Methodology for Climate‐Informed Approaches to Long‐Term Flood Projection—Illustrated With the Ohio River Basin

“…In some cases, extreme events are restricted to a particular season to enable identification of a clear link to large‐scale ocean‐atmospheric patterns (e.g., the summer season in Sun et al, ). Alternatively, peaks‐over‐threshold (POT) methods have been used to capture both number of occurrences and magnitude (e.g., Renard & Lall, ; Steinschneider & Lall, ). The choice of AMS or POT will be influenced by what information is useful for decision‐making (e.g., POT allows frequency to be modeled separately from magnitude) and whether predictors can be identified (e.g., Mallakpour et al, ; Renard and Lall, ; and Villarini et al, , apply a climate‐informed approach to the frequency of flood events from POT, but do not model magnitude).…”

If Precipitation Extremes Are Increasing, Why Aren't Floods?

“…This mechanism is represented in weather and climate models (Bao et al, ; Collins et al, ; Kharin et al, ; Prein, Rasmussen, et al, ) and is supported by observational evidence that shows average increases in observed precipitation extremes consistent with the Clausius‐Clayepron relationship (Asadieh & Krakauer, ; Barbero et al, ; Seth Westra et al, ). Notwithstanding, qualifiers exist, such as possible greater precipitation increases due to storm invigoration (Lenderink & van Meijgaard, ; Trenberth, ; Wasko et al, ); longer storm durations among other factors (Prein, Liu, et al, ), where moisture may be external to the atmospheric column (Trenberth, ); and changes in extremes due to changed atmospheric circulations at both regional (Steinschneider & Lall, ) and global scales (Mitas & Clement, ; Seidel et al, ).…”