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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation

Remote sensing estimation of evapotranspiration (ET) directly quantifies plant water consumption and provides essential information for irrigation scheduling, which is a pressing need for California vineyards as extreme droughts become more frequent. Many ET models take satellite-derived Leaf Area Index (LAI) as a major input, but how uncertainties of LAI estimations propagate to ET and the partitioning between evaporation and transpiration is poorly understood. Here we assessed six satellite-based LAI estimation approaches using Landsat and Sentinel-2 images against ground measurements from four vineyards in California and evaluated ET sensitivity to LAI in the thermal-based two-source energy balance (TSEB) model. We found that radiative transfer modeling-based approaches predicted low to medium LAI well, but they significantly underestimated high LAI in highly clumped vine canopies (RMSE ~ 0.97 to 1.27). Cubist regression models trained with ground LAI measurements from all vineyards achieved high accuracy (RMSE ~ 0.3 to 0.48), but these empirical models did not generalize well between sites. Red edge bands and the related vegetation index (VI) from the Sentinel-2 satellite contain complementary information of LAI to VIs based on near-infrared and red bands. TSEB ET was more sensitive to positive LAI biases than negative ones. Positive LAI errors of 50% resulted in up to 50% changes in ET, while negative biases of 50% in LAI caused less than 10% deviations in ET. However, even when ET changes were minimal, negative LAI errors of 50% led to up to a 40% reduction in modeled transpiration, as soil evaporation and plant transpiration responded to LAI change divergently. These findings call for careful consideration of satellite LAI uncertainties for ET modeling, especially for the partitioning of water loss between vine and soil or cover crop for effective vineyard irrigation management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A spatial-statistical investigation of surface expressions associated with cyclic steaming in the Midway-Sunset Oil Field, California

In the Midway Sunset Oil Field in Central California, operators inject steam into the shallow diatomite formation to enhance heavy oil recovery through imbibition, wettability alteration, and viscosity reduction, among other mechanisms. The injected steam, however, does not always remain in the reservoir or return through the wells. In two zones in the study area, the steam comes out at the surface, creating sinkholes, seeps, and steam outlets. These phenomena, called “surface expressions,” pose safety and environmental hazards. Even though these surface expressions are a widespread problem in Central California, they are not well documented and understood. Possible causes of the surface expressions include: high injection pressure, structurally controlled flow patterns, leakage of steam through old improperly abandoned wells, high injection volumes, or flow along naturally occurring faults, among other possible factors. This work examines attributes of the zones with surface expressions in order to determine factors that may contribute to their occurrence. Spatial statistical analysis using logistic regression, random forests, and classification trees is used to explore the relationship between the surface expressions and geological and production-related attributes. The results point to a significant spatial correlation between the surface expressions and two predictors: concentration of plugged wells and geologic seal thickness. The results guide follow-up studies to further investigate the role of well abandonment and seal thickness in the occurrence of surface expressions.

02 PETROLEUM↗
DOE OSTI2019

Energy savings with outdoor temperature-based smart ventilation control strategies in advanced California homes

We simulated the energy performance of smart ventilation controls based on outdoor temperature in homes located in California climate regions, designed to comply with the 2016 Title 24, Part 6 California Energy Code prescriptive requirements. The smart controls shift ventilation rates in time, but ensure an annual occupant pollutant exposure equal to, or less than, what would be experienced in a home with a constant ventilation rate equal to the whole house target airflow in the ASHRAE Standard 62.2-2016. Annual simulations of previously developed prototype homes with validated ventilation models were conducted via co-simulation of EnergyPlus with CONTAM. Controller performance varied substantially by climate zone, airtightness and house prototype. Smart controls were generally ineffective in Climate Zone 1 (Arcata) due to its lack of a cooling season and low diurnal temperature swings. The most successful smart controls used parameters pre-calculated using an optimization routine. In order to better inform state energy policy, we also determined savings weighted by the amount of new home construction in each climate. The best controls averaged about one-third of ventilation-related energy savings that increased to about 48–55% when weighted. Annual average savings were about 650–700 kWh/year for the best controllers. The vast majority of site energy savings were for heating end-uses (>90% of total savings). Whole house ventilation rates increased between 0% and 42%, with typical increases in the 15–20% range. Finally, the best-performing control strategies shifted ventilation rates seasonally and modulated flows within each season. Peak concentrations during low ventilation times were kept below an exposure level of 3, well below the maximum of 5 required to avoid acute exposure issues.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A modeling comparison of deep greenhouse gas emissions reduction scenarios by 2030 in California

California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stock-turnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs), demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. Here, this paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Lastly, even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model

With the onset of climate change, regions relied upon for water supply are increasingly subject to end-member fluctuations between periods of severe drought followed by extreme precipitation. The impacts of these extreme conditions on watershed hydrodynamics in water-resource sensitive regions such as California are unknown despite their great importance for resilience and water management purposes. Understanding these impacts requires high-resolution physically based models to capture sharp variations of topography, land use, wetting fronts, etc. Here, an integrated hydrologic model was used in a high-performance computing framework to study the complex nonlinear dynamics occurring at a representative Californian watershed. The Cosumnes Watershed, one of the last major rivers in California without a dam, offers a rare opportunity to isolate the effects of water management from climate extremes. Here, we show model validation with comparisons between model outputs and local measurements in addition to various satellite-based products including (1) Snow Water Equivalent (SWE) with Snow Data Assimilation System (SNODAS) and a reconstruction method by Bair and co-authors, (2) soil moisture with Soil Moisture Active Passive (SMAP), and (3) evapotranspiration (ET) with Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC). To assess changes in hydrodynamic behavior during climate extremes and their transitions, a simulation spanning a recent drought followed by the highest precipitation year on record (2015–2017) is discussed. From these simulations, we are able to highlight regions that are the most sensitive to climate extremes, which depend on many factors including hydrologic connectivity, geology and topography. These analyses provide a better understanding of the physical phenomena occurring in the watershed, strengthening our knowledge of how the system may respond to extreme conditions which might become the “new normal.”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Identifying paleowater in California drinking water wells

Identification of paleowater in aquifers tapped for the public water supply is important both for sound water management, because paleowater is likely to be withdrawn unsustainably in high demand regions in the absence of large scale artificial recharge operations, and for contamination susceptibility assessment, because paleowater is typically isolated from contamination sources. In this study, paleowater, which herein includes pre-Holocene groundwater and also water that recharged well before the onset of significant human alteration of the hydrologic system in California, is identified using three key isotopic indicators of groundwater residence time: tritium ( 3 H), radiocarbon ( 14 C), and radiogenic helium-4 ( 4 He rad ). In this work, we compared results of these three tracers from a unique data set of more than 2000 wells that are predominantly long-screened drinking water production wells. Although considerable uncertainty is associated with calculated apparent ages for individual samples, non-parametric statistical tests indicate that the composite set of isotopic indicators support classification of samples into categories that allow identification of wells most likely to produce paleowater. Approximately 7% of the wells included in the study show strong evidence for producing paleowater, with screens extending greater than 146 m below ground surface, in which 3 H activity is less than 1 pCi/L, 14C activity is less than 40.9 pmC, and 4Herad concentration exceeds 7.4 × 10 –8 cm 3 STP/g water . An additional 22% of wells produce mixed-age water with a component of paleowater, with screens extending greater than 95 m below ground surface, in which 3 H is less than 5 pCi/L, and 14C activity is less than 95.91 pmC. Wells in desert basins of southeastern California and wells in the southwestern quadrant of the Central Valley are most likely to produce paleowater that is pre-Holocene in age. Very few wells in the northwestern portion of the state, the foothills and Sierra Nevada regions, and coastal basins with intensive artificial recharge activities are categorized as producing paleowater. Climate is the primary control on paleowater occurrence, with arid portions of the state that were wetter during the Pleistocene having the largest number of wells categorized as producing paleowater. Secondarily, paleowater is found at the end of very long flow paths in confined aquifers, e.g., in the center of the Northern Sacramento Valley. In contrast, paleowater may be masked in areas where unconfined or semi-confined conditions allow substantial mixing between modern recharge and paleowater. Modern, artificially recharged water has replaced very old groundwater on a large scale in urban coastal basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Benefits and challenges in deployment of low global warming potential R290 refrigerant for room air conditioning equipment in California

High global warming potential gases (“high GWP”) are the fastest growing sector of greenhouse gas emissions in the world and in California and are primarily used as refrigerant gases in refrigeration and cooling equipment. Hydrofluorocarbons (HFCs) refrigerants are the dominant type of high GWP gases with GWP values thousands of times larger than CO 2 on a 100-year timescale. Refrigerant-grade propane (“R290”) has a very low GWP (GWP = 3.3) with good thermodynamic properties and good cooling equipment performance but the flammability of any leaked refrigerant makes equipment design, handling, and maintenance critical factors to manage. This paper focuses on the potential climate benefits and costs of transitioning to R290 refrigerant in small room air conditioning (AC) units, specifically window AC, packaged terminal AC/heat pumps (PTAC/PTHP), and mini-split heat pumps. Overall climate impact for a transition to all three types of air conditioning units in the 2022–2051 timeframe is found to be from 15 to 64 million metric tons of greenhouse gas (GHG) savings in California with a cost of saved CO 2 eq that ranges from $14.50 per ton of CO 2 eq saved to -$50.30 per ton of CO 2 eq saved (net savings) depending on whether the baseline refrigerant is R32 or R410A and depending on the relative energy efficiency for R290 units compared to baseline units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Cross-biome assessment of gross soil nitrogen cycling in California ecosystems

Microbial transformations of nitrogen (N) largely determine whether N is retained in ecosystems via net primary productivity or lost via gaseous emissions and leaching. The controls on soil N cycling are often studied at single locales, making it difficult to predict N cycling at regional to global scales. We hypothesized that contemporary soil properties exhibit consistent relationships with instantaneous gross N cycling rates across diverse biomes that create a continuum in these properties. We measured ex situ gross N cycling rates and soil properties at 33 study sites representing five biome classifications in California including deserts, grasslands, shrublands, forest, and wetlands. Desert soils had significantly lower total N, organic carbon (C), microbial biomass N, and soil moisture as well as higher pH than all other biomes, whereas forests and wetlands had significantly lower soil nitrate ($NO_3^-$) concentrations (P < 0.001 for all). Gross mineralization rates were best predicted by the combination of soil moisture and soil C:N ratios (R 2 = 0.46), which exerted positive and negative controls, respectively. Grasslands exhibited marginally higher gross mineralization than all other biomes, whereas deserts had the lowest rates due to low soil moisture (P = 0.09). Gross nitrification rates were positively correlated to soil $NO_3^-$ concentrations (R 2 = 0.34) and negatively correlated to soil C:N ratios (R 2 = 0.31). The negative relationship between gross nitrification and soil C:N ratios was driven by forest soils, which had significantly higher C:N ratios and lower gross nitrification than all other biomes (P < 0.05). Dissimilatory $NO_3^-$- reduction to $NH_4^+$ (DNRA) occurred in soils from all biomes. The strong positive correlation between DNRA rates and soil $NO_3^-$ (R 2 = 0.41) suggests $NO_3^-$ limitation of DNRA. Predictable patterns in gross N cycling across biomes in California suggest that contemporary soil properties are important drivers of instantaneous soil N cycling rates that integrate over differences in vegetation type, atmospheric N deposition rates, and local climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Capacity contributions of Southern Oregon offshore wind to the Pacific Northwest and California

Variable renewable energy generation poses unique capacity challenges, which increasingly depend on weather events at varying timescales. Facilitated by transmission planning, geographic and technological diversity of the generation fleet may provide a mitigation to capacity shortfalls. In this work, offshore wind (OSW) energy is sited in the areas off the West Coast between Coos Bay, Oregon, and Crescent City, California. Three generation and transmission scenarios are modeled within the Western Interconnection: (i) 3.4 gigawatts (GW) of installed OSW capacity connected to Southern Oregon through a High Voltage Alternating Current (HVAC) Radial Topology in 2030; (ii) 12.9 GW of installed OSW capacity connected to Washington, Oregon, and California through a High Voltage Direct Current (HVDC) Radial Topology post-2030, and (iii) the same 12.9 GW connected to the same locations through a Multi-terminal DC (MTDC) Backbone Topology post-2030. Zonal dispatch simulations assuming coincident wind, solar, and hydropower production and loads over 18 meteorological years, accounting for temperature-dependent equipment derating and forced outages, serve as inputs to the Associated System Capacity Contribution (ASCC) methodology. The capacity credit is 33%, 25% and 34% for the 2030 HVAC Radial Topology, 2030+ HVDC Radial Topology, and 2030+ MTDC Backbone Topology, respectively. Transmission design is shown to mitigate the typical erosion of marginal capacity contribution as more OSW is developed, underscoring the opportunity for grid modernization while decarbonizing the generation mix.

17 WIND ENERGY↗
DOE OSTI2016

Quantifying Cr(VI) Production and Export from Serpentine Soil of the California Coast Range

Here, hexavalent chromium (Cr(VI)) is generated in serpentine soils and exported to surface and groundwaters at levels above health-based drinking water standards. Although Cr(VI) concentrations are elevated in serpentine soil pore water, few studies have reported field evidence documenting Cr(VI) production rates and fluxes that govern Cr(VI) transport from soil to water sources. We report Cr speciation (i) in four serpentine soil depth profiles derived from the California Coast Range serpentinite belt and (ii) in local surface waters. Within soils, we detected Cr(VI) in the same horizons where Cr(III)-minerals are colocated with biogenic Mn(III/IV)-oxides, suggesting Cr(VI) generation through oxidation by Mn-oxides. Water-extractable Cr(VI) concentrations increase with depth constituting a 7.8 to 12 kg/km 2 reservoir of Cr(VI) in soil. Here, Cr(VI) is produced at a rate of 0.3 to 4.8 kg Cr(VI)/km 2 /yr and subsequently flushed from soil during water infiltration, exporting 0.01 to 3.9 kg Cr(VI)/km 2 /yr at concentrations ranging from 25 to 172 μg/L. Although soil-derived Cr(VI) is leached from soil at concentrations exceeding 10 μg/L, due to reduction and dilution during transport to streams, Cr(VI) levels measured in local surface waters largely remain below California’s drinking water limit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Source-Resolved Inversion of Elemental Carbon Emissions in California Using Log-Space Bayesian Inference

Elemental carbon (EC), operationally quantified by thermal-optical analysis, is widely used as a proxy for black carbon (BC) relevant to short-term climate forcing and public health. Current EC emission inventories remain highly uncertain, with persistent discrepancies between bottom-up and top-down estimates. In this study, we develop a source-resolved, log-space Bayesian inversion framework applied to estimate California’s statewide EC emissions in 2019. By integrating surface EC measurements from the EPA’s Air Quality System network with high-resolution source contributions simulated by a chemical transport model, we identify a one-third underestimation in the existing statewide EC inventory, requiring an increase of the total from a prior of 8.58 [5.49–13.75] Gg year–1 to a posterior estimate of 12.78 [10.71–15.37] Gg year–1. This discrepancy is primarily driven by substantial underestimations in the power and industrial and off-road mobile sectors. Furthermore, population-weighted exposure analysis reveals a marked sectoral divergence between emission mass and health burden: off-road mobile sources dominate both emissions and exposure, accounting for 31% of statewide exposure, while residential wood combustion contributes 26% of total exposure despite comprising only 19% of total emissions, due to its source proximity to population. These findings underscore the need to update sector-specific EC speciation profiles and demonstrate that mitigation strategies targeting off-road mobile sources and residential wood combustion are critical for reducing EC-related health impacts in California.

Zhang, Jie↗
DOE OSTI2018

Future Projections of the Large-Scale Meteorology Associated with California Heat Waves in CMIP5 Models

Previous work showed that climate models capture historical large-scale meteorological patterns (LSMPs) associated with California Central Valley heat waves including both ways these heat waves form. This work examines what models predict under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios. Model performance varies, so a multimodel average weights each model based on its historical performance in four parameters. An LSMP index (LSMPi) defined using upper atmosphere variables captures dates of past extreme surface temperature maxima. LSMPi correlates well with all values of California Central Valley-average surface maximum temperature. LSMPi distributions in future simulations shift ~0.6 standard deviations higher between 1961–2000 and 2061–2100 for RCP8.5 data. Based on the historical climatology, future scenarios show a large increase in the frequency and duration of heat waves in every model. Four times as many heat waves occur and their median duration doubles, using historical thresholds. Of the two ways heat waves form, Type 1 has similar frequency in the future. But, Type 2 becomes much more common because Type 2 has a preexisting hot anomaly in Southwestern Canada, much like the historical to future climatological change in that region (a “global warming” signal). The 20-year return value anomaly increases by 30–40%. The average of the 50 hottest temperatures increases 3.5–6 K depending on the scenario. When extreme values are defined using the future climatology, the models and their average have no consistent increase or decrease of distribution properties such as shape, scale, and return values of the extremes compared to historical values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Semiquantitative Estimates of Rainfall Variability During the 8.2 kyr Event in California Using Speleothem Calcium Isotope Ratios

A multiproxy record from a fast-growing stalagmite reveals variable hydroclimate on the California coast across the 8.2 kyr event and a precursor event likely caused by initial drainage of proglacial Lake Agassiz. Using speleothem δ 44 Ca, we develop the first semiquantitative estimates of paleorainfall variability for California through calibration with measurements of the modern climate and cave environment. We find that the magnitude of rainfall variability during the 8.2 kyr event approached the multiyear variability observable in the recent past (1950–2019) and the magnitude of variability during the precursor event likely exceeded this range. Additionally, we observe other instances of multidecadal variability comparable in magnitude to the precursor event during the record. Finally, our work suggests that speleothem calcium isotope ratios are a powerful semiquantitative means to reconstruct paleorainfall, although numerous factors must be assessed in each cave system before applying this approach.

58 GEOSCIENCES↗
DOE OSTI2021

Winter precipitation changes in California under global warming: Contributions of CO2, uniform SST warming, and SST change patterns

Climate models project a wetting winter over California, distinct from the drying in all other Mediterranean climate regions under warming. Dynamic effect via an eastward extension of the westerly jet stream over the North Pacific is the root cause for the wetting California. Utilizing four sets of prescribed-SST (sea surface temperature) simulations, the relative effects of direct CO2 radiative forcing, uniform SST warming, and SST change pattern are investigated. The wetting winter is dominated by uniform SST warming mainly through its effect on the jet extension. As a fundamental response to the enhanced upper-tropospheric warming in the tropics, the jet extension in coupled simulations is well reproduced under uniform SST warming and robust among models. An El Niño-like SST warming pattern has a secondary contribution to the jet extension via atmospheric teleconnection, but with large inter-model spread. Relative to the SST forcing, the direct CO2 radiative effect is negligible.

Dong, Lu↗
DOE OSTI2020

Variations of Stress Parameters in the Southern California Plate Boundary Around the South Central Transverse Ranges

We examine the stress field in Southern California with a focus on the region near the South Central Transverse Ranges (SCTR), using a refined stress inversion methodology. We independently invert declustered and aftershocks focal mechanisms from the years 1981 to 2017. Comparisons between the stress field orientations and the stress ratios from these inversions provide information on local sources of the stress field. Regionally, the SHmax tends to be toward NNE and the stress ratios vary from transtensional stress regime near the Eastern California Shear Zone (ECSZ), to strike-slip faulting near the SCTR, and toward transpression near the Western Transverse Ranges. Detailed analysis of stress parameters near the SCTR indicates deviations from the regional strike-slip faulting including the following: (1) The San Bernardino Mountain area shows S Hmax direction toward NNW and transpressional stress components likely associated with the motions of the San Andreas Fault and ECSZ; (2) the Cajon Pass and San Gorgonio Pass show transpressional stress regime near the bottom of the seismogenic zone likely associated with the elevated topography; and (3) in Crafton Hills, rotation of the principal stress plunges and SHmax direction and transtensional stress regime below ~10 km, along with lower estimated apparent friction coefficient, suggest a weak fault possibly associated with deep creep. The performed multiscale analysis resolves effects of regional and local loadings. The average stress parameters in the analyzed 37 years do not show significant temporal variations of stress field near the SCTR region.

58 GEOSCIENCES↗
DOE OSTI2020

Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling

Abstract We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Contributions of Climate Change and ENSO Variability to Future Precipitation Extremes Over California

The El Niño/Southern Oscillation (ENSO) affects the occurrence frequency and intensity of extreme precipitation through modulations of regional heat and moisture fluxes. California experiences particularly strong ENSO influences and models project different to its extreme precipitation. It remains unclear how diverse projections of future precipitation extremes relate to inter-model differences for those changing signals. Here, we use “large ensemble” simulations with multiple climate models along with the Coupled Model Intercomparison Project Phase 5 to investigate the range of precipitation extreme changes over California and the influences from ENSO-related teleconnections. We found that precipitation amount increases are much larger during El Niño relative to La Niña years, mainly caused by the differences in frequency of extreme events during different phases. The ENSO-driven effect is even larger than the overall climate change signal for the most extreme events, implying uncertainties from inter-model differences in ENSO-related SST variability for extreme precipitation changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CANVAS: An Adjoint Waveform Tomography Model of California and Nevada

Abstract We present the California‐Nevada Adjoint Simulations (CANVAS) model, an adjoint waveform tomography model of the crust and uppermost mantle of the states of California and Nevada. We used WUS256 (Rodgers et al., 2022, https://doi.org/10.1029/2022jb024549 ) as the starting model and iteratively decreased the minimum period of CANVAS from 30 to 12 s. CANVAS was iterated in two distinct stages: the first stage with source mechanisms from the Global Centroid Moment Tensor (GCMT) catalog and the second stage with inverted moment tensors (MT) using the CANV_WUS model (Doody et al., 2023, https://doi.org/10.1029/2023jb026463 ). We show that updating the MTs with 3D Green's functions improved waveform fits and azimuthal coverage of windowed data used to calculate the gradients. As for the model itself, we improved waveform fits over WUS256, particularly in the dispersed surface waves. CANVAS resolved tectonic features seen in other models and accurately defined the depth to basement of major basins, including the Central Valley and the Ventura Basin. We propose CANVAS as a starting model for crustal tomography models on smaller scales.

58 GEOSCIENCES↗