Central California Research Articles

Using the Pumped Area Method for the Assessment of Recreational Razor Clam, Siliqua patula Populations in Washington State

Since 1898, the Pacific razor clam, Siliqua patula has represented an important resource for commercial and recreational diggers and has been an important source of economic revenue to coastal communities in the Pacific Northwest from central California to southern Alaska. In 1996, Washington State adopted the Pumped Area Method as the preferred method to accurately assess populations of razor clams on coastal beaches. The Pumped Area Method utilizes a water pump and a series of hoses to draw water out of the surf to liquefy the clam bed exposing clams so they can be measured and recorded. This method relies on a fixed stratified random sampling of transects across all managed beaches to produce a robust estimate of the total population of clams. The Pumped Area Method has been adopted by state and tribal management agencies along the west coast to determine the total allowable catch in each management area but never been formally described. This method in conjunction with a biweekly sampling of toxic algae abundance supports the sustainable harvest of razor clams, providing up to 40 million dollars annually in economic income to the state of Washington for the last 25 y.

Multi‐Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated With Atmospheric Rivers Over the Western U.S.

AbstractSubseasonal‐to‐seasonal (S2S) forecasts of atmospheric rivers (ARs) are in high demand in the water supply management and flood control communities. This study focuses on a new metric, the accumulated water vapor transport associated with ARs, which is closely related to the winter precipitation over the western U.S., and provides a multi‐model S2S prediction skill assessment. The prediction skill is evaluated at lead time 1–4 weeks in four dynamical model hindcast data sets from National Centers for Environmental Prediction (NCEP), European Center for Medium‐Range Weather Forecasts (ECMWF), Environment and Climate Change Canada (ECCC), and Global Modeling and Assimilation Office (GMAO) at National Aeronautics and Space Administration. Three reanalysis data sets are used to evaluate the uncertainty of prediction skills related to the choice of references. The AR‐related water vapor transport is underestimated in ECMWF and ECCC over most of the investigated region, while its maximum has a southeastward shift in NCEP and GMAO at lead time 3–4 weeks. The root mean square error, anomaly correlation coefficient, and Brier skill score are calculated to quantify the prediction skill in both deterministic and probabilistic sense. At week‐3 lead time, the models have significant skill near the lower latitudes (<40°N) of the eastern North Pacific, extending northeastward to the California coastal area. Models have higher skills in forecasting no and strong AR cases than weak cases. The Madden–Julian Oscillation can modulate the prediction skill at week‐3 lead over central and Southern California, but with large uncertainties across models.

The importance of open data describing prey item species lists for endangered species

Abstract Open data and code can be transformative tools in supporting evidence‐informed solutions for stakeholders. Data can take many forms of evidence in the discipline of applied ecology including tables, lists, maps and visualizations to name a few. Endangered and listed species are often a catalyst for research, conservation and planning. Here, a novel, open data set summarizing all the reported diet and prey items for all endangered, terrestrial dryland species listed in central California is provided as a case study. These data highlight the critical need for sharing data rapidly and transparently to support ecological solution science. Systematic review practices were used, data were compiled and the resulting data set was published in an open access, federated data repository using ecological metadata language and FAIR principles. The goal is to show that these data can now be used and analysed by applied ecologists and stakeholders to identify not only the habitat and spatial needs for the endangered species but to widen the conservation protection net to include prey species. Conserving viable habitat with higher likelihoods of prey presence will better support conservation of endangered species, and data describing reported species are a crucial first step. Interactive tables, local species lists and maps are simple tools that can now be developed regionally with open data such as these.

Phylogeography and cohesion species delimitation of California endemic trapdoor spiders within the Aptostichus icenoglei sibling species complex (Araneae: Mygalomorphae: Euctenizidae).

Species delimitation is an imperative first step toward understanding Earth's biodiversity, yet what constitutes a species and the relative importance of the various processes by which new species arise continue to be debatable. Species delimitation in spiders has traditionally used morphological characters; however, certain mygalomorph spiders exhibit morphological homogeneity despite long periods of population-level isolation, absence of gene flow, and consequent high degrees of molecular divergence. Studies have shown strong geographic structuring and significant genetic divergence among several species complexes within the trapdoor spider genus Aptostichus, most of which are restricted to the California Floristic Province (CAFP) biodiversity hotspot. Specifically, the Aptostichus icenoglei complex, which comprises the three sibling species, A. barackobamai, A. isabella, and A. icenoglei, exhibits evidence of cryptic mitochondrial DNA diversity throughout their ranges in Northern, Central, and Southern California. Our study aimed to explicitly test species hypotheses within this assemblage by implementing a cohesion species-based approach. We used genomic-scale data (ultraconserved elements, UCEs) to first evaluate genetic exchangeability and then assessed ecological interchangeability of genetic lineages. Biogeographical analysis was used to assess the likelihood of dispersal versus vicariance events that may have influenced speciation pattern and process across the CAFP's complex geologic and topographic landscape. Considering the lack of congruence across data types and analyses, we take a more conservative approach by retaining species boundaries within A. icenoglei.

Kelpwatch: A new visualization and analysis tool to explore kelp canopy dynamics reveals variable response to and recovery from marine heatwaves.

Giant kelp and bull kelp forests are increasingly at risk from marine heatwave events, herbivore outbreaks, and the loss or alterations in the behavior of key herbivore predators. The dynamic floating canopy of these kelps is well-suited to study via satellite imagery, which provides high temporal and spatial resolution data of floating kelp canopy across the western United States and Mexico. However, the size and complexity of the satellite image dataset has made ecological analysis difficult for scientists and managers. To increase accessibility of this rich dataset, we created Kelpwatch, a web-based visualization and analysis tool. This tool allows researchers and managers to quantify kelp forest change in response to disturbances, assess historical trends, and allow for effective and actionable kelp forest management. Here, we demonstrate how Kelpwatch can be used to analyze long-term trends in kelp canopy across regions, quantify spatial variability in the response to and recovery from the 2014 to 2016 marine heatwave events, and provide a local analysis of kelp canopy status around the Monterey Peninsula, California. We found that 18.6% of regional sites displayed a significant trend in kelp canopy area over the past 38 years and that there was a latitudinal response to heatwave events for each kelp species. The recovery from heatwave events was more variable across space, with some local areas like Bahía Tortugas in Baja California Sur showing high recovery while kelp canopies around the Monterey Peninsula continued a slow decline and patchy recovery compared to the rest of the Central California region. Kelpwatch provides near real time spatial data and analysis support and makes complex earth observation data actionable for scientists and managers, which can help identify areas for research, monitoring, and management efforts.

Environmental variability and krill abundance in the central California current: Implications for ecosystem monitoring

Krill are a direct conduit between primary productivity and recreationally and commercially important higher trophic level species globally. Determining how krill abundance varies with temporal environmental variation is key to understanding their function in coastal-pelagic food webs, as well as applications in fisheries management. We used nine years (2012–19 and 2021) of late spring/early summer hydroacoustic-trawl survey data in the California Current Ecosystem (CCE), coupled with new target strength models of two krill species (Euphausia pacifica and Thysanoessa spinifera), to investigate how adult krill biomass varied during a decade of unusual ocean climate variability. We estimate a mean biomass of 1.75–2.0 million metric tons on the central and northern California continental shelf. Overall, relative krill biomass was ~30% lower during 2015 and 2016, corresponding to a major warming event, and ~30% higher in 2013 and 2018, years of exceptionally strong upwelling. Variation in biomass was related to the prior year’s environmental conditions derived from our seasonal Multivariate Ocean Climate Index (MOCI), and E. pacifica and T. spinifera showed similar covariation during the study period. Biomass co-varied at different spatial scales and across sampling devices, suggesting that multiple indicators of abundance (and dispersion) are available and should be applied in ecosystem monitoring and modeling of krill and krill-dependent predators in the California Current ecosystem.

Coastal upwelling drives ecosystem temporal variability from the surface to the abyssal seafloor

Long-term biological time series that monitor ecosystems across the ocean's full water column are extremely rare. As a result, classic paradigms are yet to be tested. One such paradigm is that variations in coastal upwelling drive changes in marine ecosystems throughout the water column. We examine this hypothesis by using data from three multidecadal time series spanning surface (0 m), midwater (200 to 1,000 m), and benthic (~4,000 m) habitats in the central California Current Upwelling System. Data include microscopic counts of surface plankton, video quantification of midwater animals, and imaging of benthic seafloor invertebrates. Taxon-specific plankton biomass and midwater and benthic animal densities were separately analyzed with principal component analysis. Within each community, the first mode of variability corresponds to most taxa increasing and decreasing over time, capturing seasonal surface blooms and lower-frequency midwater and benthic variability. When compared to local wind-driven upwelling variability, each community correlates to changes in upwelling damped over distinct timescales. This suggests that periods of high upwelling favor increase in organism biomass or density from the surface ocean through the midwater down to the abyssal seafloor. These connections most likely occur directly via changes in primary production and vertical carbon flux, and to a lesser extent indirectly via other oceanic changes. The timescales over which species respond to upwelling are taxon-specific and are likely linked to the longevity of phytoplankton blooms (surface) and of animal life (midwater and benthos), which dictate how long upwelling-driven changes persist within each community.

California coastal access damage from early winter 2022-2023 storms: A photo essay

Atmospheric rivers, “bomb cyclones,” storm waves and high tides wreaked havoc along the central California coast from San Francisco to Monterey. From 26 December 2022 to 11 January 2023, more than 10 inches of rain fell in central California (Landers 2023). During this same time period, higher high tides were 6-ft or greater for 10 of these days and 35-ft high waves were noted. Beaches, beach accesses, and coastal trails were on the front lines for storm defenses and damage. In addition to the extensive new coverage, the National Oceanic and Atmospheric Administration’s National Geodetic Survey (NOAA/NGS) collected continuous post-storm(s) airborne photography along the west coast that will be invaluable in analyzing future long-term shoreline changes (NOAA/NGS 2023). The following photos, taken soon after the storms, show some of the coastal damage near and in Monterey Bay.

Development of a Statistical Subseasonal Forecast Tool to Predict California Atmospheric Rivers and Precipitation Based on MJO and QBO Activity

AbstractThis paper examines the empirical relationship between the Madden–Julian oscillation (MJO), the quasi‐biennial oscillation (QBO), and atmospheric river (AR) activity and precipitation in California on subseasonal time scales. We introduce an experimental forecast tool that uses observed anomaly patterns during a 38 yr period to predict the probability of above‐ and below‐normal AR activity and precipitation at lead times of 1–6 weeks based on the phase and amplitude of the MJO and QBO. The hindcast prediction skill of probabilistic AR activity and precipitation forecasts is evaluated for Northern, Central, and Southern California, as well as two sets of smaller geographical domains. These smaller domains are more relevant for water resource management and allow us to investigate the sensitivity of prediction skill to domain size. Consistent with previous studies, our results demonstrate that subseasonal AR activity and precipitation in California are strongly modulated by the MJO and QBO. The anomaly patterns of AR activity and precipitation vary considerably throughout the cool season, with a tendency toward below‐normal AR activity and precipitation during easterly QBO and above‐normal AR activity and precipitation during westerly QBO in JFM. The opposite patterns are generally observed in OND, but the anomaly signals are weaker and less coherent for AR activity. Certain combinations of MJO phase, QBO phase, lag time, and season yield notably higher skill scores, reinforcing the notion of “windows of opportunity” for skillful subseasonal‐to‐seasonal predictions. In California, these forecasts of opportunity are predominantly associated with easterly QBO in JFM and FMA.

Minimizing Data Waste: Conservation in the Big Data Era

Minimizing Data Waste: Conservation in the Big Data Era

Indigenous stewardship of coastal resources in native California

Indigenous people have profoundly influenced terrestrial and marine ecosystems by modifying coastal habitats to increase the productivity of target species and altering local biotas through their harvesting practices. In some cases, these actions led to local resource depression, while in other instances, Indigenous people engaged with terrestrial and marine resources in sustainable ways, increasing the resilience of ecosystems. In this paper, we interrogate human-environmental relationships that span the last ∼7,000 years of Indigenous engagement with coastal resources on the central California coast. Through a historical ecological framework, we assess how Indigenous peoples interacted with terrestrial and marine ecosystems differently across space and through time. In the Middle Holocene, the region’s archaeology is typified by mobile populations using diverse terrestrial and marine resources. By the Late Holocene, Indigenous peoples intensified their economies towards a limited number of marine and terrestrial species. During this time, Indigenous people initiated sustained fire management practices that created habitat mosaics still reflected in the contemporary landscape. In the Late Holocene, people also developed resource harvesting strategies for California mussels and forage fishes geared towards long-term productivity.

Comparison of Nonergodic Ground-Motion Components from CyberShake and NGA-West2 Datasets in California

ABSTRACTIn this study, we compare the Southern California Earthquake Center CyberShake platform against the Next Generation Attenuation-West2 empirical datasets. Because the CyberShake and empirical datasets cover very different magnitude ranges and site conditions, we develop ground-motion models (GMMs) for CyberShake datasets to compare trends with empirical GMMs and decompose the residuals for further analysis. We apply mixed effects regression to four CyberShake datasets in southern, central, and northern California at 2, 3, 5, and 10 s periods, and compare the results with the empirical datasets using the same approach. CyberShake captures the total variability of ground motions in the empirical datasets but tends to predict larger median ground motions relative to the empirical GMMs. We then calculate and compare the repeatable source-specific location, site, and path effects between CyberShake and empirical datasets. We find that the correlations of site effects between the CyberShake and empirical datasets are generally satisfactory, but the variability of site effects is slightly smaller for CyberShake datasets. There is no apparent correlation of source-specific location effects between the CyberShake and empirical datasets. Comparison of path effects shows a wide range of correlation coefficients. Finally, we investigate the source of observed differences between the CyberShake and empirical datasets. We attribute the larger median ground-motion levels in CyberShake to a combination of the homogeneous slip patterns of the earthquake ruptures, the low resolution of near-surface materials in the velocity models, and strong reflections at high-contrast boundaries in the velocity models. These factors also impact the correlations of site and path effects between the CyberShake and empirical datasets. Moreover, the leakage from location effects into site and path terms further weakens the correlations. In summary, we find that CyberShake could be improved, but it is still very useful to supplement empirical datasets for ground-motion studies, especially to inform their nonergodic components.

SoundScape learning: An automatic method for separating fish chorus in marine soundscapes.

Marine soundscapes provide the opportunity to non-invasively learn about, monitor, and conserve ecosystems. Some fishes produce sound in chorus, often in association with mating, and there is much to learn about fish choruses and the species producing them. Manually analyzing years of acoustic data is increasingly unfeasible, and is especially challenging with fish chorus, as multiple fish choruses can co-occur in time and frequency and can overlap with vessel noise and other transient sounds. This study proposes an unsupervised automated method, called SoundScape Learning (SSL), to separate fish chorus from soundscape using an integrated technique that makes use of randomized robust principal component analysis (RRPCA), unsupervised clustering, and a neural network. SSL was applied to 14 recording locations off southern and central California and was able to detect a single fish chorus of interest in 5.3 yrs of acoustically diverse soundscapes. Through application of SSL, the chorus of interest was found to be nocturnal, increased in intensity at sunset and sunrise, and was seasonally present from late Spring to late Fall. Further application of SSL will improve understanding of fish behavior, essential habitat, species distribution, and potential human and climate change impacts, and thus allow for protection of vulnerable fish species.

A 440-Year Reconstruction of Heavy Precipitation in California from Blue Oak Tree Rings

Abstract The variability of water year precipitation and selected blue oak tree-ring chronologies in California are both dominated by heavy precipitation delivered during just a few days each year. These heavy precipitation events can spell the difference between surplus or deficit water supply and elevated flood risk. Some blue oak chronologies are highly correlated with water year precipitation (r = 0.84) but are equally well correlated (r = 0.82) with heavy precipitation totals ≥25.4 mm (1 in., ≈95th percentile of daily totals, 1949–2004). The blue oak correlation with nonheavy daily totals is much weaker (<25.4 mm; r = 0.55). Consequently, some blue oak chronologies represent selective proxies for the temporal and spatial variability of heavy precipitation totals and are used to reconstruct the amount and number of days with heavy precipitation in northern California from 1582 to 2021. Instrumental and reconstructed heavy precipitation totals are strongly correlated with gridded atmospheric river–related precipitation over the western United States, especially in central California. Spectral analysis indicates that instrumental heavy precipitation totals may be dominated by high-frequency variability and the nonheavy totals by low-frequency variance. The reconstruction of heavy precipitation is coherent with instrumental heavy totals across the frequency domain and include concentrations of variance at ENSO and biennial frequencies. Return period analyses calculated using instrumental heavy precipitation totals are representative of the return periods in the blue oak reconstruction despite the large differences in series length. Decadal surges in the amount, frequency, and interannual volatility of heavy precipitation totals are reconstructed, likely reflecting episodes of elevated atmospheric river activity in the past. Significance Statement Tree-ring chronologies of blue oak are highly correlated with precipitation delivered to northern California during just the heaviest days of precipitation each year. The reconstruction of heavy precipitation indicates decadal episodes with a high frequency of extreme precipitation. These episodes of frequent heavy precipitation likely arose because of elevated atmospheric river activity and are relevant to the analysis of water supply and flood hazard in California.

Surface ozone trends and related mortality across the climate regions of the contiguous United States during the most recent climate period, 1991–2020

In this study, we leverage multiple linear regression and quantile regression combined with a novel deep learning tool (SHapley Additive exPlanations) to isolate the impact of meteorology on surface ozone pollution and to assess the effectiveness of emission reduction measures across the Contiguous United States (US) during the latest climate period (1991–2020). The findings demonstrate that all regions except the Northern Rockies and the Southwest experienced decreasing trends in median values during the warm season, with rural stations in the Southeast and urban stations in the Northeast experiencing the greatest declines of −1.29 ± 0.07 and −0.85 ± 0.08 ppb.a−1, respectively. Similar to the original data, the median values of adjusted MDA8 (Maximum Daily 8-h Average) ozone show negative trends in all regions except for Southwest urban stations, with the highest recorded in rural stations of the Southeast (−1.13 ± 0.05 ppb.a−1) and urban stations of the Northeast (−0.79 ± 0.06 ppb.a−1). In addition, the 95th percentile values of original and adjusted MDA8 ozone decreased in all regions in which Northeast urban stations had the greatest reduction (original: 3.53 ± 0.29 ppb.a−1, adjusted: 2.96 ± 0.27 ppb.a−1). Our results suggest that meteorological inter-annual variability reduces the ozone burden during the warm season in the eastern US and southern California; at the same time, it contributes to increased ozone pollution in the central US, Southwest, and northern California, indicating that efforts to reduce air pollution may be hindered by climate change. Our analysis of the impact of short-term exposure to ozone on health shows that the South was the most positively impacted by emission control policies implemented after 2000, and the Northeast had the highest number of prevented deaths (30.45 deaths prevented/million people) resulting from respiratory diseases. The results of this study should benefit air quality managers and policymakers, particularly in their efforts to update ozone mitigation strategies.

Adjoint-state traveltime tomography for azimuthally anisotropic media in spherical coordinates

SUMMARYTong has proposed an adjoint-state traveltime tomography method to determine velocity heterogeneity and azimuthal anisotropy. This method, however, ignores the Earth’s curvature when deriving the eikonal equation for azimuthally anisotropic media. Thus, further coordinate transformation or approximation is required to ensure the accuracy of traveltime prediction in large-scale tomography. To address this problem, we derive the eikonal equation for azimuthally anisotropic media in spherical coordinates, which naturally considers the Earth’s curvature. Another key ingredient is the forward modelling algorithm, whose accuracy and efficiency dominate the numerical error and computational cost of the inversion. In this study, we apply a modified fast sweeping method to solve the eikonal equation in spherical coordinates. Two approaches, including the third-order weighted essentially non-oscillatory approximation and multiplicative factorization technique, are applied to improve the accuracy. According to the numerical experiments, this new eikonal solver achieves a second-order accuracy and is about two orders of magnitude more accurate than the commonly used first-order fast sweeping method with similar runtime. Taking advantage of the two improvements, we develop a novel eikonal equation-based adjoint-state traveltime tomography method for azimuthally anisotropic media in spherical coordinates. This method is applicable for large-scale tomography, and its performance is verified by a synthetic checkerboard test and a practical seismic tomographic inversion in central California near Parkfield.

Neighborhood Deprivation, Indoor Chemical Concentrations, and Spatial Risk for Childhood Leukemia.

Leukemia is the most common childhood cancer in industrialized countries, and the increasing incidence trends in the US suggest that environmental exposures play a role in its etiology. Neighborhood socioeconomic status (SES) has been found to be associated with many health outcomes, including childhood leukemia. In this paper, we used a Bayesian index model approach to estimate a neighborhood deprivation index (NDI) in the analysis of childhood leukemia in a population-based case-control study (diagnosed 1999 to 2006) in northern and central California, with direct indoor measurements of many chemicals for 277 cases and 306 controls <8 years of age. We considered spatial random effects in the Bayesian index model approach to identify any areas of significantly elevated risk not explained by neighborhood deprivation or individual covariates, and assessed if groups of indoor chemicals would explain any elevated spatial risk areas. Due to not all eligible cases and controls participating in the study, we conducted a simulation study to add non-participants to evaluate the impact of potential selection bias when estimating NDI effects and spatial risk. The results in the crude model showed an odds ratio (OR) of 1.06 and 95% credible interval (CI) of (0.98, 1.15) for a one unit increase in the NDI, but the association became slightly inverse when adjusting for individual level covariates in the observed data (OR = 0.97 and 95% CI: 0.87, 1.07), as well as when using simulated data (average OR = 0.98 and 95% CI: 0.91, 1.05). We found a significant spatial risk of childhood leukemia after adjusting for NDI and individual-level covariates in two counties, but the area of elevated risk was partly explained by selection bias in simulation studies that included more participating controls in areas of lower SES. The area of elevated risk was explained when including chemicals measured inside the home, and insecticides and herbicides had greater effects for the risk area than the overall study. In summary, the consideration of exposures and variables at different levels from multiple sources, as well as potential selection bias, are important for explaining the observed spatial areas of elevated risk and effect estimates.

Sediment gravity flow frequency offshore central California diminished significantly following the Last Glacial Maximum

A high-resolution multibeam survey from a portion of the San Simeon Channel (offshore Morro Bay, California) captured a zone of recurring troughs and ridges adjacent to prominent submarine meander bends. Through an integrated study using surveying data, sediment core analysis, radiocarbon dating, and stable isotope measurements, we hypothesize that turbidity current event frequency was higher during the late Pleistocene than at present conditions. We speculate that the rise in sea-level following the Last Glacial Maximum sequestered sedimentation largely to the shelf during the Holocene. This work suggests that the occurrence of sediment gravity flows in this region, particularly away from any submarine channels, is appreciably lower than at times of continental shelf subaerial exposure.

Paired Synoptic and Long-Term Monitoring Datasets Reveal Decadal Shifts in Suspended Sediment Supply and Particulate Organic Matter Sources in a River-Estuarine System

The San Francisco Estuary, in central California, has several long-running monitoring programs that have been used to reveal human-induced changes throughout the estuary in the last century. Here, we pair synoptic records of particulate organic matter (POM) composition from 1990–1996 and 2007–2016 with more robust long-term monitoring program records of total suspended sediment (TSS) concentrations generally starting in the mid-1970s to better understand how POM and TSS sources and transport have shifted. Specifically, POM C:N ratios and stable isotope values were used as indicators of POM source and to separate the bulk POC pool into detrital and phytoplankton components. We found that TSS and POC sources have shifted significantly across the estuary in time and space from declines in terrestrial inputs. Landward freshwater and brackish water sites, in the Delta and near Suisun Bay, witnessed long-term declines in TSS (32 to 52%), while seaward sites, near San Pablo Bay, recorded recent increases in TSS (16 to 121%) that began to trend downwards at the end of the record considered. Bulk POM C:N ratios shifted coeval with the TSS concentration changes at nearly all sites, with mean declines of 12 to 27% between 1990–1996 and 2007–2016. The widespread declines in bulk POM C:N ratios and inferred changes in POC concentrations from TSS trends, along with the substantial declines in upstream TSS supply through time (56%), suggest measurable reductions in terrestrial inputs to the system. Changes in terrestrial TSS and POM inputs have implications for biotic (e.g., food web dynamics) and abiotic organic matter cycling (e.g., burial, export) along the estuarine continuum. This work demonstrates how human-generated environmental changes can propagate spatially and temporally through a large river-estuary system. More broadly, we show how underutilized monitoring program datasets can be paired with existing (and often imperfect) synoptic records to generate new system insight in lieu of new data collection.

Impact of Extratropical Northeast Pacific SST on U.S. West Coast Precipitation

AbstractThe rainfall over the U.S. West Coast is known to be highly influenced by large‐scale atmospheric circulation and tropical climate teleconnections. However, the role of North Pacific oceanic variability is less understood. Using high‐resolution regional atmospheric model simulations forced by sustained positive and negative phases of the extratropical Pacific Decadal Oscillation sea surface temperature anomalies (SSTa), we diagnose the precipitation changes over the U.S. West Coast during 2010–2020. We find that precipitation anomalies are up to 60% stronger (weaker) for the warm (cold) cases, especially over Northern and Central California during wintertime, and Baja California in the summertime. In both seasons, precipitation is predominantly modulated through changes in the water vapor flux, which are directed toward the coast in wintertime and away from the coast during summertime. These flux anomalies are primarily driven by large‐scale changes in the wind associated with the atmospheric adjustment to the strong ocean SSTa.