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In this work, a 1550-nm full-fiber Doppler lidar via software-defined platform is built to realize flexible and low-cost contactless vibration measurement of high-voltage power equipment. A 1550-nm fiber layout is designed to generate optical interference between vibration signal and carrier wave. The reflected vibration signal is collected by an optical transceiver and the carrier wave is generated by an acousto-optic modulator (AOM). The optical beat signal is collected by a balanced detector (BD) then sent into a general software defined radio (SDR) receiver. By GNU developing platform, the target mechanical vibration signal is demodulated and several flexible functions such as speed-acceleration trans, harmonic component analysis and fault diagnosis is realized. Performance of Doppler lidar is first verified on mechanical vibration source by PZT vibration actuator, results show that the designed lidar could retrieve 50 Hz–20 kHz mechanical vibration signals within the working distance is up to 20 m. Further case application scenarios on the power transformer and gas-insulated switchgear (GIS) are also conducted to verify the feasibility of proposed lidar.

Antiarcha data are essential to quantitative studies of basal jawed vertebrates. The absence of structured data on key groups of early vertebrates, such as Antiarcha, has lagged in understanding their diversity and distribution patterns. Previous works of early vertebrates usually focused on anatomy and phylogeny, given their significant impacts on the evolution of key characters, but lacked comprehensive structured data. Here, we contribute an unprecedented open-access Antiarcha dataset covering 60 genera of 6025 specimens from the Ludfordian to the Famennian globally. We have organized an expert team to collect and curate 142 publications spanning from 1939 to 2021. Additionally, we have two-stage quality controls in the process: domain experts examined the literature and senior experts reviewed the results. In this paper, we give details of the data storage structure and visualize these antiarch fossil sites on the paleogeographic map. The novel Antiarcha dataset has tremendous research potential, including testing previous qualitative hypotheses in biodiversity changes, spatiotemporal distribution, evolution, and community composition. It is now an essential part of the DeepBone database and will be updated with the latest publication, also available on https://doi.org/10.5281/zenodo.6536446 (Pan and Zhu, 2021).

Studies on the hydrological response to continuous extreme and asymptotic climate change can improve our ability to cope with intensified water-related problems. Most of the literature focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change. First, the time-varying parameter is derived to reflect the ACWSC periodic and abrupt variations in both drought and non-drought periods. Second, the change points and varying patterns of the ACWSC are analyzed based on the Bayesian change point analysis with multiple evaluation criteria. Finally, various catchment properties and climate characteristics are used to explore the possible relationship between these variables and the temporal variation characteristics of the ACWSC. The catchments that suffered from a prolonged meteorological drought in southeast Australia were selected as the case study. Results indicate that: (1) the increase in amplitude change in the ACWSC is observed in 83/92 catchments during the prolonged drought period, and significant shifts in the mean value of the ACWSC are detected in 77/92 catchments; (2) the average response time of the ACWSC for all 92 catchments with significant changes is 641.3 d; (3) the values of the ACWSC changed significantly in the catchments with small areas, low elevations, small slope ranges, large forest coverage, and high soil water-holding capacities. This study could enhance our understanding of the variations in catchment property under climate change.

We forecast constraints on cosmological parameters enabled by three surveys conducted with SPT-3G, the third-generation camera on the South Pole Telescope. The surveys cover separate regions of 1500, 2650, and 6000 deg ^2 to different depths, in total observing 25% of the sky. These regions will be measured to white noise levels of roughly 2.5, 9, and $12\ \mu {\rm{K}}$ -armin, respectively, in cosmic microwave background (CMB) temperature units at 150 GHz by the end of 2024. The survey also includes measurements at 95 and 220 GHz, which have noise levels a factor of ∼1.2 and 3.5 times higher than 150 GHz, respectively, with each band having a polarization noise level $\sim \sqrt{2}$ times higher than the temperature noise. We use a novel approach to obtain the covariance matrices for jointly and optimally estimated gravitational lensing potential band powers and unlensed CMB temperature and polarization band powers. We demonstrate the ability to test the ΛCDM model via the consistency of cosmological parameters constrained independently from SPT-3G and Planck data, and consider the improvement in constraints on ΛCDM extension parameters from a joint analysis of SPT-3G and Planck data. The ΛCDM cosmological parameters are typically constrained with uncertainties up to ∼2 times smaller with SPT-3G data, compared to Planck, with the two data sets measuring significantly different angular scales and polarization levels, providing additional tests of the standard cosmological model.

We present a flare star catalog from 4 yr of nontargeted millimeter-wave survey data from the South Pole Telescope (SPT). The data were taken with the SPT-3G camera and cover a 1500 deg ^2 region of the sky from 20 ^h 40 ^m 0 ^s to 3 ^h 20 ^m 0 ^s in right ascension and from −42° to −70° in declination. This region was observed on a nearly daily cadence from 2019 to 2022 and chosen to avoid the plane of the galaxy. A short-duration transient search of this survey yields 111 flaring events from 66 stars, increasing the number of both flaring events and detected flare stars by an order of magnitude from the previous SPT-3G data release. We provide cross-matching to Gaia DR3, as well as matches to X-ray point sources found in the second ROSAT all-sky survey. We have detected flaring stars across the main sequence, from early-type A stars to M dwarfs, as well as a large population of evolved stars. These stars are mostly nearby, spanning 10–1000 pc in distance. Most of the flare spectral indices are constant or gently rising as a function of frequency at 95/150/220 GHz. The timescale of these events can range from minutes to hours, and the peak ν L _ν luminosities range from 10 ^27 to 10 ^31 erg s ^−1 in the SPT-3G frequency bands.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Aerosols significantly affect the Earth–atmosphere energy balance and climate change by acting as cloud condensation nuclei. Specifically, the susceptibility of cloud and precipitation to aerosols is stronger when aerosols are faint but tends to be saturated in polluted conditions. However, previous methodologies generally miss these faint aerosols based on instantaneous observations because they are too optically thin to be detected and are therefore usually unretrieved. This result in a large underestimation when quantifying aerosol climate impacts. Here, we focus on retrieving and verifying the instantaneous extinction of undetected faint aerosol by the CALIPSO layer detection algorithm on a global scale. Using the observations during the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) as constraints, the lidar ratios of undetected faint aerosol are estimated with a global median of 42.2 and 24.5 sr at the stratosphere and the troposphere, respectively. The retrieved extinction of undetected aerosol during night-time shows good agreement with the independent 12-month SAGE III/ISS product on a 1∘ average. The corresponding correlation coefficient and averaged normalized root-mean-square error are 0.66 % and 100.6 %, respectively. The minimum retrieved extinction coefficients can be extended to 10−3 and 10−4 km−1 with an uncertainty of 35 % and 125 % during night-time, respectively. The CALIPSO retrieval during daytime has a positive bias and relatively low agreement with SAGE III/ISS due to the low signal-to-noise ratio caused by sunlight. This study has great potential for improving the understanding of aerosol variations and the quantification of aerosol impacts on global climate change.

Climate warming has significantly changed the hydrological cycle in cold regions, especially in areas with permafrost or seasonal frost. Groundwater flow and its interactions with surface water are essential components of the hydrological process. However, few studies or modeling works have been based on long-term field observations of groundwater level, temperature, hydrogeochemistry, or isotopic tracers from boreholes due to obstacles such as remote locations, limited infrastructure, and harsh work conditions. In the Hulugou catchment, an alpine catchment in the headwater region of the Heihe River on the northern Qinghai–Tibet Plateau (QTP), we drilled four sets of depth-specific wells and monitored the groundwater levels and temperatures at different depths. Surface water (including river water, glacier meltwater, and snow meltwater), precipitation, groundwater from boreholes, spring water, and soil water were sampled to measure the abundances of major and minor elements, dissolved organic carbon (DOC), and stable and radioactive isotopes at 64 sites. This study provides a dataset of these groundwater parameters spanning 6 consecutive years of monitoring/measurements. These data can be used to investigate groundwater flow processes and groundwater–surface water interactions on the QTP under global climate change. The dataset provided in this paper can be obtained at https://doi.org/10.5281/zenodo.6296057 (Ma et al., 2021b) and will be subject to further updates.

Satellite-based cloud base and top height (CBH and CTH) and cloud geometrical thickness (CGT) are validated against ground-based lidar measurements and provide new scientific insights. The satellite measurements are done by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The retrieval methodology is built on the 333 m resolution low-level water cloud data obtained from the Vertical Feature Mask product of CALIPSO. The methodology is based on the definition that CBH of boundary layer clouds is the lowest cloud base over an area of several tens of kilometers. This allows taking the CBH of the neighboring penetrable shallower cloud as having CBH representative for the entire cloud field. The methodology over the ocean was validated based on observations from two surface-based ceilometer measurements in the islands of Barbados and the Azores, with an error standard deviation of ±115 m. Validation over land was based on 4 years data of 138 terrestrial ceilometer sites with an error standard deviation of ±220 m. The unprecedented accurate CBH allows us to obtain CGT, which is an essential parameter in the understanding of the aerosol–cloud interaction. Based on this newly developed methodology, we retrieved the annual, seasonal, and diurnal distributions of global CBH, CTH, and CGT for two years and analyzed the variations of CBH and CTH over the ocean and land. Climatology of the annual mean cloud geometrical properties shows the following. (1) The lowest CBH occurs over the eastern margins of the subtropical oceans and increases westward from 300–400 to 800–900 m. The CGT increases from 300 to 1200 m, respectively. In the western part of the tropical oceans, CBH is 500–600 m and CGT is ∼ 1500 m. (2) A narrow band of lower CBH and CGT occurs over the Equator, especially over the eastern parts of the oceans. (3) CBH and CGT over the tropical rain forests (Amazon and Congo) are 1200 and 1500 m, respectively. CBH over the drier tropical land is 1500–2000 m, with CGT of 800–1000 m. (4) CBH decreases towards Antarctica in the Southern Ocean, while CGT deepens. (5) Seasonally, the mid-latitude global oceans have the lowest CBH (mostly below 500 m) and CGT in summer seasons and the highest values in winter. (6) There is just an obvious difference between day and night for the maximum CTH and CGT over the tropics. Over the ocean, there is no discernible difference in CBH, but during night CTH is higher by ∼ 300 m.

The objective of this study was to assess the genetic diversity and phylogenetic relationship of nine sheep populations, including two famous high prolific populations and seven popular mutton populations raised in China. Overall, these sheep populations in this study exhibited a rich genetic diversity. Both the expected heterozygosity and Nei's unbiased gene diversity ranged from 0.64 to 0.75, with the lowest value found in Dorset sheep (DST) and the highest in Hu sheep (HUS) and Ba Han sheep (BAS). The polymorphic information content (PIC) varied between 0.59 in DST and 0.71 in HUS and BAS. Specifically, for individual breeds, the small-tail Han sheep (STH) and the four introduced populations did not display the expected diversity; therefore more attention should be paid to the maintenance of diversity during management of these populations. The results of un-weighted pair-group method (UPGMA) phylogenetic tree and structure analysis indicated that the nine investigated populations can be divided into two groups. Suffolk (SUF) and DST were clustered in one group, and the other group can be further divided into three clusters: German Mutton Merino (GMM)–BAS–Bamei Mutton sheep (BAM), HUS–STH and Du Han (DOS)–Dorper (DOP). This clustering result is consistent with sheep breeding history. TreeMix analysis also hinted at the possible gene flow from GMM to SUF. Together, an in-depth view of genetic diversity and genetic relationship will have important implications for breed-specific management.

Understanding the propagation of prolonged meteorological drought helps solve the problem of intensified water scarcity around the world. Most of the existing literature studied the propagation of drought from one type to another (e.g., from meteorological to hydrological drought) with statistical approaches; there remains difficulty in revealing the causality between meteorological drought and potential changes in the catchment water storage capacity (CWSC). This study aims to identify the response of the CWSC to the meteorological drought by examining the changes of hydrological-model parameters after drought events. Firstly, the temporal variation of a model parameter that denotes that the CWSC is estimated to reflect the potential changes in the real CWSC. Next, the change points of the CWSC parameter were determined based on the Bayesian change point analysis. Finally, the possible association and linkage between the shift in the CWSC and the time lag of the catchment (i.e., time lag between the onset of the drought and the change point) with multiple catchment properties and climate characteristics were identified. A total of 83 catchments from southeastern Australia were selected as the study areas. Results indicated that (1) significant shifts in the CWSC can be observed in 62.7 % of the catchments, which can be divided into two subgroups with the opposite response, i.e., 48.2 % of catchments had lower runoff generation rates, while 14.5 % of catchments had higher runoff generation rate; (2) the increase in the CWSC during a chronic drought can be observed in smaller catchments with lower elevation, slope and forest coverage of evergreen broadleaf forest, while the decrease in the CWSC can be observed in larger catchments with higher elevation and larger coverage of evergreen broadleaf forest; (3) catchments with a lower proportion of evergreen broadleaf forest usually have a longer time lag and are more resilient. This study improves our understanding of possible changes in the CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system under climate change.

A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s ^−1 ) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s ^−1 and ≈70 km s ^−1 , respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

Reactive oxygen species (ROS) mediate multiple physiological functions; however, the over-accumulation of ROS causes premature aging and/or death and is associated with various inflammatory conditions. Nevertheless, there are limited clinical treatment options that are currently available. The good news is that owing to the considerable advances in nanoscience, multiple types of nanomaterials with unique ROS-scavenging abilities that influence the temporospatial dynamic behaviors of ROS in biological systems have been developed. This has led to the emergence of next-generation nanomaterial-controlled strategies aimed at ameliorating ROS-related inflammatory conditions. Accordingly, herein we reviewed recent progress in research on nanotherapy based on ROS scavenging. The underlying mechanisms of the employed nanomaterials are emphasized. Furthermore, important issues in developing cross-disciplinary nanomedicine-based strategies for ROS-based inflammatory conditions are discussed. Our review of this increasing interdisciplinary field will benefit ongoing studies and clinical applications of nanomedicine based on ROS scavenging.

Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. Many existing studies model the time-varying parameters as functions of physically based covariates; however, a major challenge remains in finding effective information to control the large uncertainties that are linked to the additional parameters within the functions. This paper formulated the time-varying parameters for a lumped hydrological model as explicit functions of temporal covariates and used a hierarchical Bayesian (HB) framework to incorporate the spatial coherence of adjacent catchments to improve the robustness of the projection performance. Four modeling scenarios with different spatial coherence schemes and one scenario with a stationary scheme for model parameters were used to explore the transferability of hydrological models under contrasting climatic conditions. Three spatially adjacent catchments in southeast Australia were selected as case studies to examine the validity of the proposed method. Results showed that (1) the time-varying function improved the model performance but also amplified the projection uncertainty compared with the stationary setting of model parameters, (2) the proposed HB method successfully reduced the projection uncertainty and improved the robustness of model performance, and (3) model parameters calibrated over dry years were not suitable for predicting runoff over wet years because of a large degradation in projection performance. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.

While dust aerosols emitted from major Asian sources such as Taklimakan and Gobi deserts have been shown to have strong effect on Asian monsoon and climate, the role of dust emitted from Tibetan Plateau (TP) itself, where aerosols can directly interact with the TP heat pump because of their physical proximity both in location and elevation, has not been examined. This study uses the dust-coupled RegCM4.1 regional climate model (RCM) to simulate the spatiotemporal distribution of dust aerosols originating within the TP and their radiative effects on the East Asian summer monsoon (EASM) during both heavy and light dust years. Two 20-year simulations with and without the dust emission from TP showed that direct radiative cooling in the mid-troposphere induced by the TP locally produced dust aerosols resulted in an overall anticyclonic circulation anomaly in the low troposphere centered over the TP region. The northeasterly anomaly in the EASM region reduces its strength considerably. The simulations found a significant negative correlation between the TP column dust load produced by local emissions and the corresponding anomaly in the EASM index (r = −0.46). The locally generated TP dust can cause surface cooling far downstream in Bohai Gulf and the China–North Korea border area through stationary Rossby wave propagation. Although dust from within TP (mainly Qaidam Basin) is a relatively small portion of total Asian aerosols, its impacts on Asian monsoon and climate seems disproportionately large, likely owning to its higher elevation within TP itself.

ZY-3 has been acquiring high quality imagery since its launch in 2012 and its tri-stereo (three-view or three-line-array) imagery has become one of the top choices for extracting DSM (Digital Surface Model) products in China over the past few years. The ZY-3 tri-stereo sensors offer users the ability to capture imagery over large regions including an entire territory of a country, such as China, resulting in a large volume of ZY-3 tri-stereo scenes which require timely (e.g., near real time) processing, something that is not currently possible using traditional photogrammetry workstations. This paper presents a high performance computing solution which can efficiently and automatically extract DSM products from ZY-3 tri-stereo imagery. The high performance computing solution leverages certain parallel computing technologies to accelerate computation within an individual scene and then deploys a distributed computing technology to increase the overall data throughput in a robust and efficient manner. By taking advantage of the inherent efficiencies within the high performance computing environment, the DSM extraction process can exploit all combinations offered from a set of tri-stereo images (forward-backword, forward-nadir and backword-nadir). The DSM results merged from all of the potential combinations can minimize blunders (e.g., incorrect matches) and also offer the ability to remove potential occlusions which may exist in a single stereo pair, resulting in improved accuracy and quality versus those that are not merged. Accelerated performance is inherent within each of the individual steps of the DSM extraction workflow, including the collection of ground control points and tie points, image bundle adjustment, the creation of epipolar images, and computing elevations. Preliminary experiments over a large area in China have proven that the high performance computing system can generate high quality and accurate DSM products in a rapid manner.

The Chinese satellites HJ-1 A/B, CBERS-02C and ZY-3 have been recently launched and are considered as the main space platforms on orbit to acquire optical images for monitoring the Earth for various applications in China. The commercially distributed products (Level 1 or 2) of those satellites usually lack sufficient information (about platform, sensor and ephemeris) that is the key to geometrically correct the acquired images. It is therefore always a challenging issue and the first step to assess the geometric accuracy, which is a key part of qualities in spatial data, of the images from those satellites before generation of geometrically accurate image products. This paper first describes an operational methodology to assess the geometric accuracy of those satellite images. The methodology automatically collects dense and spatially well distributed ground control points (GCP) against reference imagery and then fits those GCPs to the given geometric math model. The geometric accuracy of an image can then be assessed from the overall fitness of those GCPs and their distribution of geometric errors along and across track. The residual mean square (RMS) parameter is used to indicate the degree of overall fitness of the GCPs to the photogrammetric system. The distribution of geometric errors may be random or approximated by a second or higher order polynomial functions; the latter case is generally considered as a systematic error that was not removed completely in the Level 1 or 2 data product. In order to draw solid conclusions, a significant number of samples are selected for each of those satellites by taking variations of landscapes into consideration. The assessment experiments demonstrate that the accuracy of HJ-1 A/B is often very poor, that of CBERS-02C is better than the situation of HJ-1 A/B but records poor accuracy for most samples, and that of ZY-3 is the best among all satellites under investigation and has few samples with poor accuracy. According to the assessment results, this paper suggests an operational correction methodology to improve the accuracy for those satellites, particularly for the HJ-1 A/B and CBERS-02C. Operational production proves that the proposed correction methodology is capable of achieving much higher accuracy than traditional ones and the achieved accuracy meets high standard product requirements for such applications as mapping.

Optical fiber communications continued to advance at a rapid pace in 2010. This paper presents a brief overview of the most exciting technological advances of 2010, eking out record capacity out of optical fiber through enhancing spectral efficiency and shrinking power consumption using modern optical fiber communication system designs.

DNA barcoding is an effective technique to identify species and analyze phylogenesis and evolution. However, research on and application of DNA barcoding in Canis have not been carried out. In this study, we analyzed two species of Canis, Canis lupus (n = 115) and Canis latrans (n = 4), using the cytochrome c oxidase subunit I (COI) gene (1545 bp) and COI barcoding (648 bp DNA sequence of the COI gene). The results showed that the COI gene, as the moderate variant sequence, applied to the analysis of the phylogenesis of Canis members, and COI barcoding applied to species identification of Canis members. Phylogenetic trees and networks showed that domestic dogs had four maternal origins (A to D) and that the Tibetan Mastiff originated from Clade A; this result supports the theory of an East Asian origin of domestic dogs. Clustering analysis and networking revealed the presence of a closer relative between the Tibetan Mastiff and the Old English sheepdog, Newfoundland, Rottweiler and Saint Bernard, which confirms that many well-known large breed dogs in the world, such as the Old English sheepdog, may have the same blood lineage as that of the Tibetan Mastiff.

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from −19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result. Furthermore, it is found that neither a decrease in cloud droplet coalescence nor a decrease in riming necessarily implies a decrease in precipitation due to compensation effects by other microphysical pathways. The simulations suggest that mixed-phase conditions play an important role in buffering the effect of aerosol perturbations on cloud microphysics and reducing the overall susceptibility of clouds and precipitation to changes in the aerosol number concentrations. As a consequence the aerosol effect on precipitation is suggested to be less pronounced or even inverted in regions with high terrain (e.g., the Alps or Rocky Mountains) or in regions where mixed-phase microphysics is important for the climatology of orographic precipitation.