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NASA NTRS2022

Chapter 7: Sun Photometers

Sun photometry is an extended technique for monitoring the atmospheric composition and support satellite product validation. By measuring the direct solar irradiance, the amount and characteristics of the atmospheric aerosol particles, precipitable water vapor column, and ozone columns can be derived. Global operational networks such as the Aerosol Robotic Network (AERONET), Global Atmosphere Watch-Precision Filter Radiometer Network (GAW-PFR), Maritime Aerosol Network (MAN), or the Brewer spectrophotometer networks constitute sustained efforts for long-term monitoring of the atmosphere, with invaluable data production using cost-effective and relatively simple instrumentation. The data quality relies on the standardization of these networks, with special emphasis on the calibration as the key element in Sun photometry.

Sun photometry↗

NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2018

Ground and Satellite Based Observation Datasets for the Lower Mekong River Basin

In ‘Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability’ [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work. Moreover, land cover land use raster data that contains 18 classes that cover agriculture, urban, range and forests land cover land use classes for the basin is offered. In addition, a soil data that contains physical and chemical characteristics needed by physically based hydrological models to simulate the cycling of water and air is also provided.

Streamflow↗

DOE OSTI2020

Synergetic Use of the WSR-88D Radars, GOES-R Satellites, and Lightning Networks to Study Microphysical Characteristics of Hurricanes

Abstract This study analyzes the microphysics and precipitation pattern of Hurricanes Harvey (2017) and Florence (2018) in both the eyewall and outer rainband regions. From the retrievals by a satellite red–green–blue scheme, the outer rainbands show a strong convective structure while the inner eyewall has less convective vigor (i.e., weaker upper-level reflectivities and electrification), which may be related to stronger vertical wind shear that hinders fast vertical motions. The WSR-88D column-vertical profiles further confirm that the outer rainband clouds have strong vertical motion and large ice-phase hydrometeor formation aloft, which correlates well with 3D Lightning Mapping Array source counts in height and time. From the results from this study, it is determined that the inner eyewall region is dominated by warm rain, whereas the external rainband region contains intense mixed-phase precipitation. External rainbands are defined here as those that reside outside of the main hurricane circulation, associated with surface tropical storm wind speeds. The synergy of satellite and radar dual-polarization parameters is instrumental in distinguishing between the key microphysical features of intense convective rainbands and the warm-rain-dominated eyewall regions within the hurricanes. Substantial amounts of ice aloft and intense updrafts in the external rainbands are indicative of heavy surface precipitation, which can have important implications for severe weather warnings and quantitative precipitation forecasts. The novel part of this study is to combine ground-based radar measurement with satellite observations to study hurricane microphysical structure from surface to cloud top so as to fill in the gaps between the two observational techniques.

Meteorology & Atmospheric Sciences↗

NASA NTRS1984

Spectral characteristics of two types of low latitude aurorae

Attention is given to two types of aurorae whose low altitude emissions seem to be due to energy loss from trapped ring current ions or electrons whose energy is of the order of 1 eV. The spectral characteristics which predominate in the first type of aurora indicate direct precipitation of ring current particles as ions, and/or indirect precipitation as energetic neutrals, following charge transfer with exospheric H or O neutrals. The spectral characteristics of the second type indicate excitation by electrons and can yield brighter displays. The time variations of the emissions are found to be closely related to fluctuations of periods shorter than an hour in the magnetograms from nearby observatories.

Tinsley, B. A.↗

NASA NTRS2001

Analysis of the Performance Characteristics of the Five-Channel Microtops II Sun Photometer for Measuring Aerosol Optical Thickness and Precipitable Water Vapor

Five Microtops II sun photometers were studied in detail at the NASA Goddard Space Flight Center (GSFC) to determine their performance in measuring aerosol optical thickness (AOT or Tau(sub alphalambda) and precipitable column water vapor (W). Each derives Tau(sub alphalambda) from measured signals at four wavelengths lambda (340, 440, 675, and 870 nm), and W from the 936 nm signal measurements. Accuracy of Tau(sub alphalambda) and W determination depends on the reliability of the relevant channel calibration coefficient (V(sub 0)). Relative calibration by transfer of parameters from a more accurate sun photometer (such as the Mauna-Loa-calibrated AERONET master sun photometer at GSFC) is more reliable than Langley calibration performed at GSFC. It was found that the factory-determined value of the instrument constant for the 936 nm filter (k= 0.7847) used in the Microtops' internal algorithm is unrealistic, causing large errors in V(sub 0(936)), Tau(sub alpha936), and W. Thus, when applied for transfer calibration at GSFC, whereas the random variation of V(aub 0) at 340 to 870 nm is quite small, with coefficients of variation (CV) in the range of 0 to 2.4%, at 936 nm the CV goes up to 19%. Also, the systematic temporal variation of V(sub 0) at 340 to 870 nm is very slow, while at 936 nm it is large and exhibits a very high dependence on W. The algorithm also computes Tau(sub alpha936) as 0.91Tau(sub alpha870), which is highly simplistic. Therefore, it is recommended to determine Tau(sub alpha936) by logarithmic extrapolation from Tau(sub alpha675) and Tau(sub alpha 870. From the operational standpoint of the Microtops, apart from errors that may result from unperceived cloud contamination, the main sources of error include inaccurate pointing to the Sun, neglecting to clean the front quartz window, and neglecting to calibrate correctly. If these three issues are adequately taken care of, the Microtops can be quite accurate and stable, with root mean square (rms) differences between corresponding retrievals from clean calibrated Microtops and the AERONET sun photometer being about +/-0.02 at 340 nm, decreasing down to about +/-0.01 at 870 nm.

Ichoku, Charles↗

NASA NTRS2004

Processing of High Resolution, Multiparametric Radar Data for the Airborne Dual-Frequency Precipitation Radar APR-2

Following the successful Precipitation Radar (PR) of the Tropical Rainfall Measuring Mission, a new airborne, 14/35 GHz rain profiling radar, known as Airborne Precipitation Radar - 2 (APR-2), has been developed as a prototype for an advanced, dual-frequency spaceborne radar for a future spaceborne precipitation measurement mission. . This airborne instrument is capable of making simultaneous measurements of rainfall parameters, including co-pol and cross-pol rain reflectivities and vertical Doppler velocities, at 14 and 35 GHz. furthermore, it also features several advanced technologies for performance improvement, including real-time data processing, low-sidelobe dual-frequency pulse compression, and dual-frequency scanning antenna. Since August 2001, APR-2 has been deployed on the NASA P3 and DC8 aircrafts in four experiments including CAMEX-4 and the Wakasa Bay Experiment. Raw radar data are first processed to obtain reflectivity, LDR (linear depolarization ratio), and Doppler velocity measurements. The dataset is then processed iteratively to accurately estimate the true aircraft navigation parameters and to classify the surface return. These intermediate products are then used to refine reflectivity and LDR calibrations (by analyzing clear air ocean surface returns), and to correct Doppler measurements for the aircraft motion. Finally, the the melting layer of precipitation is detected and its boundaries and characteristics are identifIed at the APR-2 range resolution of 30m. The resulting 3D dataset will be used for validation of other airborne and spaceborne instruments, development of multiparametric rain/snow retrieval algorithms and melting layer characterization and statistics.

airborne radar↗

DOE OSTI2024

Km‐Scale Simulations of Mesoscale Convective Systems Over South America—A Feature Tracker Intercomparison

Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth's water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object-based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluate MCSs in kilometer-scale simulations with observational-based MCSs over 3 years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS characteristics is less sensitive to the tracker formulation and all trackers agree that the model can capture MCS characteristics well across different South American climate zones. Dominant sources of uncertainty are the segmentation of cloud systems in space and time and the treatment of how MCSs are linked in time. Our results highlight that comparing MCS analyses that use different tracking algorithms is challenging. We provide general guidelines on how MCS characteristics compare between trackers to facilitate a more robust assessment of MCS statistics in future studies.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

Scale Dependence of Statistics of Spatially Averaged Rain Rate Seen in TOGA COARE Comparison with Predictions from a Stochastic Model

A characteristic feature of rainfall statistics is that they in general depend on the space and time scales over which rain data are averaged. As a part of an earlier effort to determine the sampling error of satellite rain averages, a space-time model of rainfall statistics was developed to describe the statistics of gridded rain observed in GATE. The model allows one to compute the second moment statistics of space- and time-averaged rain rate which can be fitted to satellite or rain gauge data to determine the four model parameters appearing in the precipitation spectrum - an overall strength parameter, a characteristic length separating the long and short wavelength regimes and a characteristic relaxation time for decay of the autocorrelation of the instantaneous local rain rate and a certain 'fractal' power law exponent. For area-averaged instantaneous rain rate, this exponent governs the power law dependence of these statistics on the averaging length scale $L$ predicted by the model in the limit of small $L$. In particular, the variance of rain rate averaged over an $L \times L$ area exhibits a power law singularity as $L \rightarrow 0$. In the present work the model is used to investigate how the statistics of area-averaged rain rate over the tropical Western Pacific measured with ship borne radar during TOGA COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmospheric Response Experiment) and gridded on a 2 km grid depends on the size of the spatial averaging scale. Good agreement is found between the data and predictions from the model over a wide range of averaging length scales.

Kundu, Prasun K.↗

DOE OSTI2022

Bedrock Vadose Zone Storage Dynamics Under Extreme Drought: Consequences for Plant Water Availability, Recharge, and Runoff

Bedrock vadose zone water storage (i.e., rock moisture) dynamics are rarely observed but potentially key to understanding drought responses. Exploiting a borehole network at a Mediterranean blue oak savanna site—Rancho Venada—we document how water storage capacity in deeply weathered bedrock profiles regulates woody plant water availability and groundwater recharge. The site is in the Northern California Coast Range within steeply dipping turbidites. In a wet year (water year 2019; 647 mm of precipitation), rock moisture was quickly replenished to a characteristic storage capacity, recharging groundwater that emerged at springs to generate streamflow. In the subsequent rainless summer growing season, rock moisture was depleted by about 93 mm. In two drought years that followed (212 and 121 mm of precipitation) the total amount of rock moisture gained each winter was about 54 and 20 mm, respectively, and declines were documented exceeding these amounts, resulting in progressively lower rock moisture content. Oaks, which are rooted into bedrock, demonstrated signs of water stress in drought, including reduced transpiration rates and extremely low water potentials. In the 2020–2021 drought, precipitation did not exceed storage capacity, resulting in variable belowground water storage, increased plant water stress, and no recharge or runoff. Rock moisture deficits (rather than soil moisture deficits) explain these responses.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Large-Scale Influences on Atmospheric River Induced Extreme Precipitation Events Along the Coast of Washington State

Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. In order to accurately predict AR events in numerical weather prediction, subseasonal and seasonal timescales, it is important to understand the large-scale meteorological influence on extreme AR events.Here, characteristics of ARs that result in an extreme precipitation event are compared to typical ARs on the coast of WashingtonState. In addition to more intense water vapor transport, notable differences in the synoptic forcing are present during extreme precipitation events that are not present during typical AR events.In particular, a negatively tilted low pressure system is positioned to the west in the Gulf of Alaska, alongside an upper level jet streak. Subseasonal and seasonal teleconnection patterns are known to influence the weather in the Pacific Northwest. The Madden JulianOscillation (MJO) is shown to be particularly important in determining the strength of precipitation associated with in AR ont he Washington coast.

Collow, Allison↗

DOE OSTI2025

Simulation and analysis of small angle scattering (SAS) patterns of Ni-based superalloy microstructures generated by a phase-field model

This paper investigates the relationship between microstructural features and small-angle scattering (SAS) patterns in Ni-based superalloys using a combined phase-field and SAS simulation approach coupled with microstructure analyses. The simulated SAS patterns accurately capture key experimental observations previously reported in the literature, including the time-dependent transition from circular to square-shaped precipitates and the development of anisotropic SAS patterns. Importantly, our analysis reveals the correlations between characteristic length scales extracted from SAS profiles and microstructural descriptors, such as precipitate size and inter-precipitate distance. These findings provide a comprehensive understanding of the link between SAS profiles and microstructure evolution in Ni-based superalloys, offering valuable insights for materials characterization and design.

Microstructure↗

DOE OSTI2021

Raindrop Size Spectrum in Deep Convective Regions of the Americas

This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter D m , and normalized droplet concentration N w ) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader N w distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h -1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of N w in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The Role of Wind‐Moisture Characteristics in Shaping Atmospheric River Flood Hazards

Atmospheric rivers (ARs) are key drivers of extreme precipitation in the Western U.S. Using regionally downscaled thermodynamic global warming (TGW) simulations, we examine how ARs with varying wind and moisture characteristics respond to warming. We classified 812 historical AR events into Gusty-Wet, Gusty-Dry, Calm-Wet, and Calm-Dry groups to evaluate differences in precipitation behavior. ARs with stronger winds and higher moisture content exhibit higher precipitation efficiency (PE) and greater integrated water vapor (IWV). Regionally, Calm ARs show higher IWV accumulation due to slower inland transport and reduced PE. Projections indicate increases in storm-total (sub-Clausius-Clapeyron (CC) scaling) and maximum 3-hourly precipitation (super-CC scaling) across all groups, with the most pronounced changes in Gusty-Wet and Calm-Wet ARs. Spatial differences in surface runoff, PE, and inland reach highlight the importance of AR subtype in shaping future flood hazards. These results offer insights into event-level and regional-scale precipitation changes under evolving environmental conditions.

Zhou, Yang [Lawrence Berkeley National Laboratory ↗

NASA NTRSDate not supplied

The Multiplatform Precipitation Feature (MPF) Database: Synthesizing Satellite and Ground-Based Precipitation and Lightning Datasets for Convective Studies

NASA’s Lightning Imaging Sensor (LIS) and the Global Precipitation Measurement (GPM) mission have contributed a wealth of data toward global lightning and precipitation studies, respectively. Combining lightning and precipitation datasets leverages their unique insights into deep convective processes that inform about characteristics of convection and its intensity. Recent efforts to synthesize the LIS and GPM datasets prepare the opportunity for unprecedented large-scale, value-added multiplatform analyses of convection. This data synthesis proof-of-concept study elaborates on the creation of a database of reflectivity-based multiplatform precipitation features (MPFs) that capture a combination of information extracted from spatiotemporally coincident lightning and precipitation data within individual storm features. The space-based GPM Dual-frequency Precipitation Radar (DPR) provides a record of precipitation data, while the GPM Validation Network (VN) additionally incorporates ground-based polarimetric Doppler radar data to provide microphysical and kinematic context to DPR data. The LIS instrument onboard the International Space Station has contributed lightning observations since 2017. MPFs encapsulating information from these datasets are created from isolated regions of filtered, smoothed DPR reflectivity data to which ellipses are fit. Each MPF includes feature location, size, and eccentricity information as well as summary reflectivity characteristics. They also include summaries of precipitation microphysics and derived three-dimensional wind available from ground-based radar data. LIS data provides standard lightning characteristics such as flash count and density to each MPF as well as other informative metrics such as flash area and radiance. Each MPF file includes information about the original data from which the MPF and its characteristics were determined, allowing end-user reconstruction of the ellipse and deeper “level I” analysis of captured data. This database of VN-LIS MPFs enables broad statistical analysis of the relationships between the microphysical, kinematic, and electrical properties of convection. Preliminary results from a demonstration of the database will be described as well as ongoing efforts and avenues for future work.

Lightning↗

NASA NTRS2002

Characteristics of Vertical Profiles of Reflectivity and Doppler Derived From TRMM Field Campaigns

The TRMM Precipitation Radar (PR) measures the vertical profile of reflectivity from which the surface rain rate is estimated after attenuation corrections in the 2A21 algorithm. Characteristics of the vertical reflectivity profile is important for various reasons ranging from scientific to instrument algorithms. It is well known that different types of precipitation such as stratiform or convection, have different heating profiles. The vertical profile of reflectivity can provide information on precipitation classification. The vertical reflectivity structure also provides information on precipitation processes such as growth and aggregation. In terms of TRMM algorithms, an independent estimate of the vertical profiles are also extremely important since the PR returns can be attenuated in the rain layer near the surface. Corrections for attenuation are required in the lowest few kilometers, necessitating some assumptions about the rain size distributions and the reflectivity profile below the lowest measurement unaffected by the surface return. Furthermore, some assumptions about the vertical reflectivity profile are required for Ground Validation (GV) radars, since their lowest scan may be 1 or more kilometers above the surface. Statistics on the vertical reflectivity and Doppler structure are presented from the ER-2 Doppler Radar (EDOP) which participated in several TRMM field campaigns (TEFLUN-A, TEFLUN-B, and LBA) and CAMEX-3. The ER-2 aircraft overflew diverse precipitation types during these campaigns. EDOP is an X-band (9.6 GHz) radar for which returns are less attenuated than at the TRMM PR frequency. The EDOP profiles are first corrected for attenuation using the SRT method. The data from all the ER-2 campaigns are then classified by type (convection, stratiform, and other) and then statistics were performed on the vertical reflectivity and Doppler profiles in the form of CFAD's. These CFADs are compared and discussed. The computed CFAD's indicate significant differences as a function of precipitation type and location (hurricane versus non-hurricane, Brazil versus Florida). The implications of these profiles will be discussed.

Starr, David OC.↗

DOE OSTI2020

The microstructure of a selective laser melting (SLM)-fabricated NiTi shape memory alloy with superior tensile property and shape memory recoverability

A selective laser melting (SLM)-fabricated NiTi with superior tensile property and shape memory recoverability was obtained by using a unique stripe rotation scanning strategy. Here, the alloy characteristics, formation mechanisms and evolution in terms of twins, dislocations and precipitations of the alloy were systematically studied. Compared to the conventional smelting-followed-by-machining, the SLM fabrication process involves rapid solidification and repeated heating, which confer distinctive characteristics to the microstructures of SLM-fabricated NiTi alloys. Rapid solidification promotes the formation of a supersaturation solid solution matrix containing a high concentration vacancies, which in turn aggregate to generate a high density of dislocations. During subsequent repeated heating stages, these dislocations occur thermal motion along three directions of <001 > , <111> and <110 >, leading to the formation of thermal kinks, helical dislocations and wave morphology. Simultaneously, precipitated particles Ti 3 Ni 4 repeatedly nucleate and heterogeneous grow with the movement of dislocation. Such precipitation behavior, termed repeated precipitation, has not been previously reported in the conventional NiTi alloys, suggesting that it could be a unique characteristic of such alloy. After martensitic transformation, only two twins, {1 1¯ 1} type I twin and compound twin, are detected. The twinning lamellae of these two twins, where precipitation and dislocation pile-ups exist, often have uneven thickness and chaotic arrangement. Besides, the unique self-accommodated microstructures, such as secondary {1 1¯ 1} type I twin and compound twin with “herring-bone’’ lamellae, which often appear in the deformed or nanocrystalline NiTi, can also be observed. These unique microstructures may confer the distinctive properties to the SLM-fabricated NiTi.

36 MATERIALS SCIENCE↗