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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Effects of proton irradiation on nanocluster precipitation in ferritic steel containing fcc alloying additions

Newly-developed precipitate-strengthened ferritic steels with and without pre-existing nanoscale precipitates were irradiated with 4 MeV protons to a dose of ~5 mdpa at 50 C and subsequently examined by nanoindentation and atom probe tomography (APT). Irradiation-enhanced precipitation and coarsening of pre-existing nanoscale precipitates were observed. Copper partitions to the precipitate core along with a segregation of Ni, Al and Mn to the precipitate/matrix interface after both thermal aging and proton irradiation. Proton irradiation induces the precipitation reaction and coarsening of pre-existing nanoscale precipitates, and these results are similar to a thermal aging process. The precipitation and coarsening of nanoscale precipitates are responsible for the changes in hardness. The observation of the radiation-induced softening is essentially due to the coarsening of the pre-existing Cu-rich nanoscale precipitates. The implication of the precipitation on the embrittlement of reactor-pressure-vessel steels after irradiation is discussed.

Zhang, Zhongwu↗
DOE OSTI2022

Contribution of Tibetan Plateau ecosystems to local and remote precipitation through moisture recycling

The ecosystems of the Tibetan Plateau (TP) provide multiple important ecosystem services that benefit both local populations and those beyond, such as through climate regulation services on precipitation for East Asia and China. However, the precipitation regulation service of the TP ecosystems for supplying moisture and maintaining precipitation is yet to be evaluated. In this study, we used the moisture recycling framework and a moisture tracking model to quantify the precipitation regulation services of TP ecosystems for their contribution to precipitation. We found TP ecosystems contributed substantially to local and downwind precipitation, with a declined contribution from 221 mm/year for the TP and neighboring areas, to <10 mm/year for eastern China and other surrounding countries. Among ecosystem types, grassland contributed most to precipitation, followed by barren and snow lands, forests, and shrublands. In terms of seasonality, precipitation contribution from TP ecosystems was greater in summer months than in non-summer months for western China, while the opposite was true for eastern China – though the magnitude was much smaller. Over the past two decades, the significant evapotranspiration increases in TP translated to a widespread increase in precipitation contribution for TP and downwind beneficiary regions from 2000 to 2020. Our study provides a quantitative way to understand the precipitation regulation services of TP ecosystems through moisture recycling, substantiating their key role to safeguard precipitation and the water cycle for downwind regions– effectively acting as an ecological security shelter that could be perceived by the public.

Li, Yan↗
DOE OSTI2015

Stress transfer during different deformation stages in a nano-precipitate-strengthened Ni-Ti shape memory alloy

Understanding the role of fine coherent precipitates in the micromechanical behavior of precipitate-strengthened shape memory alloys (SMAs), which still remains a mystery heretofore, is of crucial importance to the design of advanced SMAs with optimal functional and mechanical properties. Here, we investigate the lattice strain evolution of, and the stress partition between the nanoscale Ni{sub 4}Ti{sub 3} precipitates and the matrix in a precipitate-strengthened Ni-Ti SMA during different deformation stages by in-situ synchrotron high-energy X-ray diffraction technique. We found that, during R-phase reorientation and stress-induced martensitic transformation, which both involve the shear deformation process, the lattice strain of the nanoscale precipitates drastically increases by a magnitude of 0.5%, which corresponds to an abrupt increase of ∼520 MPa in internal stress. This indicates that stress repartition occurs and most of the stress is transferred to the precipitates during the shear deformation of the matrix. It is further revealed that the nanoscale precipitates which only have a low volume fraction bear a considerable amount of applied stress during all deformation stages investigated, implying that the nanoscale precipitates play an important role in the deformation behavior of the precipitate-strengthened Ni-Ti SMAs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Fine precipitation scenarios of AlZnMg(Cu) alloys revealed by advanced atomic-resolution electron microscopy study Part II: Fine precipitation scenarios in AlZnMg(Cu) alloys

Although they are among the most important precipitation-hardened materials for industry applications, the high-strength AlZnMg(Cu) alloys have thus far not yet been understood adequately about their underlying precipitation scenarios in relation with the properties. This is partly due to the fact that the structures of a number of different precipitates involved in the alloys are unknown, and partly due to the complexity that the precipitation behaviors of the alloys may be closely related to the alloy's composition. In Part I of the present study, we have determined all the unknown precipitate structures in the alloys. Here in Part II, using atomic-resolution electron microscopy in association with the first principles energy calculations, we further studied and correlated the phase/structure transformation/evolution among these hardening precipitates in relation with the alloy's composition. It is shown that there are actually two coexisting classes of hardening precipitates in these alloys: the first class includes the η′-precipitates and their early-stage Guinier–Preston (GP-η′) zones; the second class includes the precursors of the equilibrium η-phase (referred to η{sub p}, or η-precursor) and their early-stage Guinier–Preston (GP-η{sub p}) zones. The two coexisting classes of precipitates correspond to two precipitation scenarios. - Highlights: • We determine and verify all the key precipitate structures in AlMgZn(Cu) alloys. • We employ aberration-corrected scanning transmission electron microscopy (STEM). • We use aberration-corrected high-resolution TEM (HRTEM) for the investigations. • We obtain atomic-resolution images of the precipitates and model their structures. • We refine all precipitate structures with quantitative image simulation analysis. • The hardening precipitates in AlZnMg alloys shall be classified into two groups. • Two precipitation scenarios coexist in the alloys. • The precipitation behavior of such an alloy depends on the alloy's composition. • Very detailed phase/structure transformations among the precipitates are revealed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. Here, we used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. Finally, this highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Evaluating Precipitation Events Using GPM IMERG 30-Minute Near Real-Time Precipitation Estimates

Accurately detecting and estimating precipitation at near–real time (NRT) is of utmost importance for the early detection and monitoring of hydrometeorological hazards. The precipitation product, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), provides NRT 0.1° and 30-min precipitation estimates across the globe with only a 4-h latency. This study was an evaluation of the GPM IMERG version 6 level-3 early run 30-min precipitation product for precipitation events from 2014 through 2020. The purpose of this research was to identify when, where, and why GPM IMERG misidentified and failed to detect precipitation events in California, Nevada, Arizona, and Utah in the United States. Precipitation events were identified based on 15-min precipitation from gauges and 30-min precipitation from the IMERG multisatellite constellation. False-positive and false-negative precipitation events were identified and analyzed to determine their characteristics. Precipitation events identified by gauges had longer duration and had higher cumulative precipitation than those identified by GPM IMERG. GPM IMERG had many false event detections during the summer months, suggesting possible virga event detection, which is when precipitation falls from a cloud but evaporates before it reaches the ground. The frequency and timing of the merged passive microwave (PMW) product and forward propagation were responsible for IMERG overestimating cumulative precipitation during some precipitation events and underestimating others. This work can inform experts that are using the GPM IMERG NRT product to be mindful of situations where GPM IMERG–estimated precipitation events may not fully resolve the hydrometeorological conditions driving these hazards.

Jessica R P Sutton↗
DOE OSTI2018

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 experiment

This study summarizes the precipitation properties collected during the GoAmazon2014/5 campaign near Manaus in central Amazonia, Brazil. Precipitation breakdowns, summary radar rainfall relationships and self-consistency concepts from a coupled disdrometer and radar wind profiler measurements are presented. The properties of Amazon cumulus and associated stratiform precipitation are discussed, including segregations according to seasonal (Wet/Dry regime) variability, 5 cloud echo-top height and possible aerosol influences on the apparent oceanic characteristics of the precipitation drop size distributions. Overall, we observe that the Amazon precipitation straddles behaviors found during previous U.S. Department of Energy Atmospheric Radiation Measurements program (ARM) tropical deployments, with distributions favoring higher concentrations of smaller drops than ARM continental examples. Oceanic type precipitation characteristics are predominantly observed during the Amazon Wet seasons. An exploration of the controls on Wet season precipitation properties reveals that 10 wind direction, as compared with other standard radiosonde thermodynamic parameters or aerosol count/regime classifications performed at the ARM site, provides a good indicator for those Wet season Amazon events having an oceanic character for their precipitation drop size distributions.

aerosol influences↗
DOE OSTI2020

Investigating the linkage between simulated precipitation climatology and ENSO-related precipitation anomaly based on multi-model and perturbed parameter ensembles

It remains a challenge for climate models to correctly capture the relationship between precipitation and ENSO. This studyexamines the linkage between the simulated precipitation climatology and ENSO-related precipitation anomaly during borealwinter based on the multi-model ensemble from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) and perturbedparameter ensemble (PPE) with the Beijing Climate Center (BCC) atmospheric model. The AMIP5 models have large biases insimulating the tropical precipitation anomaly during El Niño, such as the shifts of the Inter-Tropical Convergence Zone (ITCZ)and South Pacific Convergence Zone (SPCZ). The inter-model differences show that the precipitation change in response to seasurface temperature (SST) change increases with enhanced precipitation climatology. The ENSO-related precipitation anomalycan also be related to the spatial distribution of the mean-state precipitation. The simulated ITCZ/SPCZ displacements aresignificantly correlated with the spatial precipitation-SST relationship in the mean state. Models with stronger mean-stateprecipitation-SST relationship also produce stronger SPCZ/ITCZ displacements. The mean-state tropical precipitation also hasstrong impacts on the ENSO-related precipitation anomalies over East Asia. In the BCC PPE, the connection between the mean-state precipitation and ENSO-related precipitation anomaly is overall consistent with that in AMIP5. Parameters associated withthe low-cloud and deep convection processes are the most influential ones for the precipitation simulations in BCC. Comparedwith the version in AMIP5, the new BCC model can better simulate the precipitation climatology and the relationship betweenENSO and precipitation over southern China. These results have important implications for model development and model-basedclimate predictions.

Yang, Ben↗
DOE OSTI2021

The Relationship between Precipitation and Precipitable Water in CMIP6 Simulations and Implications for Tropical Climatology and Change

It is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pw nc . This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pw nc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a ‘‘double ITCZ’’ feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in lowintensity drizzle precipitation in the PERSIANN precipitation dataset.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

We extend and enhance the concept of the Cloud Regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), by adding precipitation information in order to better understand cloud-precipitation relationships. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, cloud-precipitation “hybrid” regimes are derived by implementing the k-means clustering algorithm with advanced initialization and objective measures to determine the most optimal clusters. By expressing precipitation rates within 1-degree grid cell as histograms and making choices on the relative weight of cloud and precipitation, we could obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics. In the deep tropics, when precipitation is weighted weakly, the cloud part of the hybrid entroids resembles the centroid of cloud-only regimes, but still tightens the cloud-precipitation relationship by decreasing the precipitation variability of each regime. As precipitation weight progressively increases, the shape of the cloudy part of the hybrid centroids becomes blunter, while the precipitation part of the centroids sharpens. In the case where cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct features in the precipitation parts of the centroids, which allows us to project them onto the 30-minly IMERG domain. Such a projection can be used to overcome the temporal sparseness of MODIS cloud observations, which leads to great application potential for various convection-focused studies, including diurnal cycle analysis.

cloud-precipitation↗
DOE OSTI2017

Radiation-induced swelling and radiation-induced segregation & precipitation in dual beam irradiated Ferritic/Martensitic HT9 steel

Highlights: • The depth-dependence of radiation-induced cavities was characterized in self-ion irradiated HT9 co-implanted with He. • The injected interstitial effect was revealed to suppress cavity swelling in the vicinity of the damage peak. • ChemiSTEM elemental maps revealed the segregation of Ni at cavity surfaces and its possible synergistic influence on swelling was discussed. - Abstract: Ferritic/Martensitic HT9 steel was irradiated at 432 °C to 16.6 displacements per atom (dpa) (at the depth of 600 nm) using a defocused beam of 5 MeV Fe{sup ++} ions, while co-implanted with 3.22 appm He at the same depth. The helium concentration profile was designed so to follow the damage curve with a 0.22 appm He/dpa ratio at the depth from 300 to 1000 nm in the material. The depth-dependence of the cavity size and number density were characterized by both transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) imaging methods. A comparison between the two techniques was done showing good agreement. Cavity number density and the resulting swelling were found to be suppressed by the injected interstitial effect in the vicinity of the ion induced damage peak. The region between 300 and 750 nm depth which excludes the injected interstitial effect was thus proposed for improved cavity swelling analysis. The swelling ratio in this region was found to be ~(0.86–1.02) × 10{sup − 2}%/dpa. In addition, ChemiSTEM characterization revealed radiation-induced segregation occurring throughout the irradiated region and precipitation of G-phase particles. Segregation of Ni to cavity surfaces was also observed and its possible synergistic influence on swelling was discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Fine precipitation scenarios of AlZnMg(Cu) alloys revealed by advanced atomic-resolution electron microscopy study Part I: Structure determination of the precipitates in AlZnMg(Cu) alloys

Although they are among the most important precipitation-hardened materials for industry applications, the high-strength AlZnMg(Cu) alloys have thus far not yet been understood adequately about their underlying precipitation scenarios in relation with the properties. This is partly due to the fact that the structures of a number of different precipitates involved in electron microscopy in association with quantitative image simulations have to be employed; a systematic study of these hardening precipitates in different alloys is also necessary. In Part I of the present study, it is shown that there are five types of structurally different precipitates including the equilibrium η-phase precipitate. Using two state-of-the-art atomic-resolution imaging techniques in electron microscopy in association with quantitative image simulations, we have determined and clarified all the unknown precipitate structures. It is demonstrated that atomic-resolution imaging can directly suggest approximate structure models, whereas quantitative image analysis can refine the structure details that are much smaller than the resolution of the microscope. This combination is crucially important for solving the difficult structure problems of the strengthening precipitates in AlZnMg(Cu) alloys. - Highlights: Part I: • We determine and verify all the key precipitate structures in AlMgZn(Cu) alloys. • We employ aberration-corrected scanning transmission electron microscopy (STEM). • We use aberration-corrected high-resolution TEM (HRTEM) for the investigations. • We obtain atomic-resolution images of the precipitates and model their structures. • We refine all precipitate structures with quantitative image simulation analysis. Part II: • The hardening precipitates in AlZnMg alloys shall be classified into two groups. • Two precipitation scenarios coexist in the alloys. • The precipitation behavior of such an alloy depends on the alloy's composition. • Very detailed phase/structure transformations among the precipitates are revealed.

36 MATERIALS SCIENCE↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
DOE OSTI2011

A micro-alloyed ferritic steel strengthened by nanoscale precipitates

A ferritic steel with finely dispersive precipitates was investigated to reveal the fundamental strengthening mechanisms. The steel has a yield strength of 760 MPa, approximately three times higher than that of conventional Ti-bearing high strength hot-rolled sheet steels, and its ultimate tensile strength reaches 850 MPa with an elongation-to-failure value of 18%. Using energy dispersive X-ray spectroscopy (EDXS) and transmission electron microscope (TEM), fine carbides TiC with an average diameter of 10 nm were observed in the ferrite matrix of the 0.08%Ti steel, and some cubic M23C6 precipitates were also observed at the grain boundaries and the interior of the grains. The finely dispersive TiC precipitates in the matrix provide matrix strengthening. The estimated magnitude of precipitation strengthening is around 458 MPa, depending on the average size of the nanoscale precipitates. Dislocation densities increased from 3.42×1013 m-2 to 1.69 × 1014 m-2, respectively, with increasing tensile strain from 5.5% to 22%. The measured work-hardening behavior can be related to the observed dislocation accumulations resulting from the dispersive nano-scale precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Midlatitude Oceanic Cloud and Precipitation Properties as Sampled By the ARM Eastern North Atlantic Observatory

Marine low clouds are critical to the climate system because of their extensive coverage and associated controls on boundary layer dynamics and radiative energy balance. The primary foci for this study are marine low cloud observations over a heavily instrumented site on the Azores archipelago in the eastern North Atlantic (ENA) and their associated raindrop size distribution (DSD) properties, relative low-cloud contributions to the precipitation, and additional sampling (instrument, environmental) considerations. The contribution from low clouds (e.g., cloud top < 4 km) to the overall precipitation over midlatitude oceans is poorly understood, in part because of the lack of coupled, high-quality measurements of precipitation and low-cloud properties. Cloud regime and precipitation breakdowns performed for a multi-year record emphasize the diurnal precipitation cycle and DSD characteristics for both low and deeper clouds. Results demonstrate that marine low clouds over this ENA location account for a significant (45%) contribution to the total rainfall and exhibit a diurnal cycle in cloud (thickness, top, base) and precipitation characteristics similar to satellite records. Additional controls on observed surface rainfall characteristics of low clouds allowed by the extended ground-based facility datasets are also explored. From those analyses, it is suggested that the synoptic state exerts a significant control on low-cloud and surface precipitation properties.

Giangrande, Scott↗
DOE OSTI2015

High-resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America

This study performs high-spatial-resolution (12 km) Weather Research and Forecasting (WRF) simulations over a very large domain (7200 km × 6180 km, covering much of North America) to explore changes in mean and extreme precipitation in the mid and late 21st century under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). We evaluate WRF model performance for a historical simulation and future projections, applying the Community Climate System Model version 4 (CCSM4) as initial and boundary conditions with and without a bias correction. WRF simulations using boundary and initial conditions from both versions of CCSM4 show smaller biases versus evaluation data sets than does CCSM4 over western North America. WRF simulations also improve spatial details of precipitation over much of North America. However, driving the WRF with the bias-corrected CCSM4 does not always reduce the bias. WRF-projected changes in precipitation include decreasing intensity over the southwestern United States, increasing intensity over the eastern United States and most of Canada, and an increase in the number of days with heavy precipitation over much of North America. Projected precipitation changes are more evident in the late 21st century than the mid 21st century, and they are more evident under RCP 8.5 than under RCP 4.5 in the late 21st century. Uncertainties in the projected changes in precipitation due to different warming scenarios are non-negligible. Differences in summer precipitation changes between WRF and CCSM4 are significant over most of the United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Impacts of aerosols on seasonal precipitation and snowpack in California based on convection-permitting WRF-Chem simulations

Here, a version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42° N, 117–124° W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about –0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation, 3 % for SWE, and 7 % for surface runoff for the whole domain, while the corresponding numbers are 12, 10, and 10 % for the mountaintops. The reduction in SWE is more significant in a dry year, with 9 % for the whole domain and 16 % for the mountaintops. The maximum reduction of ~20 % in precipitation occurs in May and is associated with the maximum aerosol loading, leading to the largest decrease in SWE and surface runoff over that period. It is also found that dust aerosols can cause early snowmelt on the mountaintops and reduced surface runoff after April.

54 ENVIRONMENTAL SCIENCES↗