Thermophysical properties of Almahata Sitta meteorites (asteroid 2008 TC 3 ) for high‐fidelity entry modeling
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Stefan Loehle↗
SEARCH · Engineering Papers
Results for “TC”
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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Reducing TC Position Uncertainty in an Ensemble Data Assimilation and Prediction System: A Case Study of Typhoon Fanapi (2010)
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Kuan-Jen Lin↗
Correlating Tc and Crystallographic Parameters in UTe2
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Material Science↗
Incorporation of marine energy classification systems into relevant IEC TC 114 technical specifications.
Abstract not provided.
Neary, Vincent Sinclair↗
Magic gap ratio for optimally robust superfluidity and high-Tc superconductivity
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High Magnetic Field Science↗
DOE Zero Energy Ready Home Case Study HIA 2021: TC Legend Homes, Neohouse, Bellevue, WA
Case study of a DOE 2021 Housing Innovation Award winning custom home in a marine climate that got a HERS -22 with PV, with 2,614 square feet, triple-pane windows, LED lighting, and heat recovery ventilator with a HEPA filter and CO2 sensor.
Building America, residential construction, home b↗
DOE Zero Energy Ready Home Case Study HIA 2020: TC Legend Homes, Everson Net Positive, Everson, WA
Case study of a DOE 2020 Housing Innovation Award winning custom home in a cold climate that got a HERS -19 with PV, with 2,538 square feet and a large south-facing roof, which is designed to hold over 80 solar panels, and the large south-facing windows, bringing in sunlight to warm the concrete floors and provide passive solar heating.
Building America, residential construction, home b↗
Materials Data on Tc3Pd by Materials Project
Tc3Pd crystallizes in the trigonal R-3m space group. The structure is three-dimensional. there are seven inequivalent Tc+0.67- sites. In the first Tc+0.67- site, Tc+0.67- is bonded to nine Tc+0.67- and three equivalent Pd2+ atoms to form a mixture of edge, face, and corner-sharing TcTc9Pd3 cuboctahedra. There are three shorter (2.72 Å) and six longer (2.74 Å) Tc–Tc bond lengths. All Tc–Pd bond lengths are 2.81 Å. In the second Tc+0.67- site, Tc+0.67- is bonded to twelve Tc+0.67- atoms to form TcTc12 cuboctahedra that share corners with six equivalent TcTc12 cuboctahedra, edges with eighteen TcTc9Pd3 cuboctahedra, and faces with eighteen TcTc9Pd3 cuboctahedra. All Tc–Tc bond lengths are 2.74 Å. In the third Tc+0.67- site, Tc+0.67- is bonded to nine Tc+0.67- and three equivalent Pd2+ atoms to form a mixture of edge, face, and corner-sharing TcTc9Pd3 cuboctahedra. There are three shorter (2.72 Å) and six longer (2.74 Å) Tc–Tc bond lengths. All Tc–Pd bond lengths are 2.81 Å. In the fourth Tc+0.67- site, Tc+0.67- is bonded to sixteen Tc+0.67- atoms to form a mixture of edge, face, and corner-sharing TcTc16 cuboctahedra. There are a spread of Tc–Tc bond distances ranging from 2.72–5.48 Å. In the fifth Tc+0.67- site, Tc+0.67- is bonded to nine Tc+0.67- and three equivalent Pd2+ atoms to form TcTc9Pd3 cuboctahedra that share corners with seventeen TcTc9Pd3 cuboctahedra, edges with sixteen TcTc9Pd3 cuboctahedra, and faces with fifteen TcTc16 cuboctahedra. All Tc–Tc bond lengths are 2.74 Å. All Tc–Pd bond lengths are 2.81 Å. In the sixth Tc+0.67- site, Tc+0.67- is bonded to twelve Tc+0.67- atoms to form TcTc12 cuboctahedra that share corners with eleven TcTc13Pd3 cuboctahedra, edges with sixteen TcTc9Pd3 cuboctahedra, and faces with twenty-one TcTc13Pd3 cuboctahedra. There are six shorter (2.72 Å) and six longer (2.74 Å) Tc–Tc bond lengths. In the seventh Tc+0.67- site, Tc+0.67- is bonded to thirteen Tc+0.67- and three equivalent Pd2+ atoms to form TcTc13Pd3 cuboctahedra that share corners with seventeen TcTc9Pd3 cuboctahedra, edges with twenty TcTc9Pd3 cuboctahedra, and faces with twenty-five TcTc13Pd3 cuboctahedra. There are a spread of Tc–Tc bond distances ranging from 2.74–5.48 Å. All Tc–Pd bond lengths are 2.81 Å. There are two inequivalent Pd2+ sites. In the first Pd2+ site, Pd2+ is bonded in a 6-coordinate geometry to six equivalent Tc+0.67- atoms. In the second Pd2+ site, Pd2+ is bonded in a 6-coordinate geometry to six Tc+0.67- atoms.
36 MATERIALS SCIENCE↗
Materials Data on Zn7Tc by Materials Project
TcZn7 crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Tc is bonded to twelve Zn atoms to form TcZn12 cuboctahedra that share corners with twelve equivalent TcZn12 cuboctahedra, edges with twenty-four ZnZn10Tc2 cuboctahedra, and faces with eighteen ZnZn10Tc2 cuboctahedra. All Tc–Zn bond lengths are 2.74 Å. There are twenty-five inequivalent Zn sites. In the first Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the second Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the third Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the fourth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn12 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the fifth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the sixth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the seventh Zn site, Zn is bonded to twelve Zn atoms to form ZnZn12 cuboctahedra that share corners with twelve equivalent ZnZn12 cuboctahedra, edges with twenty-four ZnZn10Tc2 cuboctahedra, faces with six equivalent TcZn12 cuboctahedra, and faces with twelve ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the eighth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the ninth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the tenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn12 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the eleventh Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twelfth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. Both Zn–Zn bond lengths are 2.74 Å. In the thirteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. Both Zn–Zn bond lengths are 2.74 Å. In the fourteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the fifteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the sixteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the seventeenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. All Zn–Zn bond lengths are 2.74 Å. In the eighteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the nineteenth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twentieth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twenty-first Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twenty-second Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn12 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twenty-third Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Tc bond lengths are 2.74 Å. All Zn–Zn bond lengths are 2.74 Å. In the twenty-fourth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Zn bond lengths are 2.74 Å. In the twenty-fifth Zn site, Zn is bonded to two equivalent Tc and ten Zn atoms to form ZnZn10Tc2 cuboctahedra that share corners with twelve ZnZn10Tc2 cuboctahedra, edges with four equivalent TcZn12 cuboctahedra, edges with twenty ZnZn10Tc2 cuboctahedra, faces with two equivalent TcZn12 cuboctahedra, and faces with sixteen ZnZn10Tc2 cuboctahedra. Both Zn–Zn bond lengths are 2.74 Å.
36 MATERIALS SCIENCE↗
Identification and Quantification of Technetium Species in Hanford Waste Tank AN-102
Technetium-99 (Tc) generated from the fission of 235U and 239Pu in high yields is one of the most difficult contaminants to be addressed at the U.S. Department of Energy Hanford Site. In strongly alkaline solutions typifying Hanford tank waste, Tc exists as pertechnetate (TcO4-) (oxidation state VII) as well as in reduced forms (oxidation state < VII) collectively known as non-pertechnetate species. Designing strategies for effective Tc management, including separation and immobilization, necessitates understanding the molecular structure of the non- pertechnetate species and their identification in the actual tank waste samples, which would facilitate development of new treatment technologies effective for dissimilar Tc species. Toward this objective, a spectroscopic library of the Tc(I) [fac-Tc(CO)3]+ and Tc(IV, VII) compounds was generated using a range of techniques and applied to the characterization of the actual tank waste supernatant collected from the tank 241-AN-102 at Hanford, WA. A sample of the 241-AN-102 tank waste supernatant was processed to adjust Na concentration to about 5.6 M and remove 137Cs by spherical resorcinol-formaldehyde (sRF) ion exchange resin. Cesium-loaded sRF column was eluted with 0.5 M HNO3. As received AN-102, Cs-depleted AN-102 effluent, and sRF eluate fractions were comprehensively characterized for chemical composition and speciation of Tc using 99Tc nuclear magnetic resonance spectroscopy and X-ray absorption spectroscopy. It was demonstrated for the first time that non-pertechnetate Tc present in the 241-AN-102 tank waste is composed of several low-valent Tc species, including the Tc(I) [fac-Tc(CO)3]+ and Tc(IV) compounds. This is the second experimental observation of the [fac-Tc(CO)3]+ species in the Hanford tank waste and the first demonstration of multiple forms of non-pertechnetate species existing simultaneously in the waste, cumulatively highlighting their importance for the waste processing.
Low Activity Waste (LAW), High Level Waste, nuclea↗
Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data
Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.
Landsat↗
Structural Investigation of Technetium Dibutylphosphate Species Using X-ray Absorption Fine Structure Spectroscopy
The speciation of Tc after the extraction of Tc(IV) from H 2 O and 1 M HNO 3 by dibutylphosphoric acid (HDBP) in dodecane has been studied by X-ray absorption fine structure (XAFS) spectroscopy. Results show the formation of dimeric species with Tc 2 O 2 and Tc 2 O units, and the formulas [Tc 2 O 2 (DBP·HDBP) 4 ] (1) and [Tc 2 O(NO 3 ) 2 (DBP) 2 (DBP·HDBP) 2 ] (2) were, respectively, proposed for the species extracted from H 2 O and 1 M HNO 3 . The interatomic Tc–Tc distances found in the Tc 2 O 2 and Tc 2 O units [2.55(3) and 3.57(4) Å, respectively] are similar to the ones found in Tc(IV) dinuclear species. It is likely that the speciation of Tc(IV) in dodecane is due to the extraction of a species with a Tc 2 O unit for (2) and to the redissolution of a Tc(IV)-DBP solid for (1). The XAFS results for (1) and (2) were compared to that obtained for the extraction of Tc(IV) with TBP/HDBP/dodecane from 0.5 M HNO 3 , (3) which highlight the formation of Tc mononuclear nitrate species {i.e. [Tc(NO 3 ) 3 (DBP)] or [Tc(NO 3 ) 2 (DBP·HDBP)]}. These results confirm the importance of the preparation and speciation of the Tc(IV) aqueous solutions prior to extraction and how much this influences and drives the final Tc speciation in organic extraction. Here, these studies outline the complexity of Tc separation chemistry and provide insights into the behavior of Tc during the reprocessing of used nuclear fuel.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Materials Data on Tc4Br7O by Materials Project
Tc4OBr7 crystallizes in the monoclinic P2_1/c space group. The structure is zero-dimensional and consists of four Tc4OBr7 clusters. there are four inequivalent Tc+2.25+ sites. In the first Tc+2.25+ site, Tc+2.25+ is bonded in a 3-coordinate geometry to three Br1- atoms. There are a spread of Tc–Br bond distances ranging from 2.55–2.80 Å. In the second Tc+2.25+ site, Tc+2.25+ is bonded in a distorted T-shaped geometry to three Br1- atoms. There are a spread of Tc–Br bond distances ranging from 2.53–2.58 Å. In the third Tc+2.25+ site, Tc+2.25+ is bonded in a distorted T-shaped geometry to three Br1- atoms. There are one shorter (2.51 Å) and two longer (2.53 Å) Tc–Br bond lengths. In the fourth Tc+2.25+ site, Tc+2.25+ is bonded in a 4-coordinate geometry to three Br1- atoms. There are a spread of Tc–Br bond distances ranging from 2.53–2.90 Å. O2- is bonded in a distorted single-bond geometry to one Br1- atom. The O–Br bond length is 1.74 Å. There are seven inequivalent Br1- sites. In the first Br1- site, Br1- is bonded in a 1-coordinate geometry to two Tc+2.25+ atoms. In the second Br1- site, Br1- is bonded in a water-like geometry to one Tc+2.25+ and one O2- atom. In the third Br1- site, Br1- is bonded in a distorted single-bond geometry to one Tc+2.25+ atom. In the fourth Br1- site, Br1- is bonded in a 2-coordinate geometry to two Tc+2.25+ atoms. In the fifth Br1- site, Br1- is bonded in a 2-coordinate geometry to two Tc+2.25+ atoms. In the sixth Br1- site, Br1- is bonded in a 2-coordinate geometry to two Tc+2.25+ atoms. In the seventh Br1- site, Br1- is bonded in a 2-coordinate geometry to two Tc+2.25+ atoms.
36 MATERIALS SCIENCE↗
Multidecadal Fluctuations in the Observed ENSO‐Tropical Cyclone Teleconnection
Abstract El Niño‐Southern Oscillation (ENSO) is a skillful predictor for seasonal tropical cyclone (TC) activity in most TC basins. This study examines recent changes in the observed ENSO‐TC teleconnection strength, as measured by ENSO modulation of hurricane frequency. We find that the ENSO‐North Atlantic TC teleconnection fluctuated over time, with the strongest relationship occurring from the 1980s to the mid‐2000s. In the western and eastern North Pacific, the ENSO‐TC teleconnection has strengthened in recent decades. Periods with a strong ENSO‐TC teleconnection are associated with more favorable environmental conditions for TCs, with higher values of genesis potential indices. Positive phases of the Atlantic Multidecadal Oscillation coincided with periods of strong ENSO‐TC teleconnections in the Atlantic and North Pacific basins. A weaker Atlantic ENSO‐TC relationship was associated with negative phases of the Pacific Decadal Oscillation and the North Atlantic Oscillation. This research reveals climate conditions that modulate ENSO's utility for seasonal TC prediction. Plain Language Summary El Niño‐Southern Oscillation (ENSO) is a useful predictor for seasonal tropical cyclone (TC) activity in many basins. Here we found that the strength of the ENSO‐TC teleconnection, represented as the correlation between ENSO and the number of hurricanes and accumulated cyclone energy, has changed in the historical record. The ENSO‐TC teleconnection in the North Atlantic fluctuated over time, with a weak relationship during the 1960s and 1970s and a strong relationship during the 1980s to mid‐2000s. Meanwhile, the ENSO‐TC teleconnection strengthened in the North Pacific in recent decades, with strong teleconnections after the 1980s in the western North Pacific and after the 2000s in the eastern North Pacific. Periods of strong ENSO‐TC teleconnections are associated with more favorable environmental conditions for TCs, including higher values of genesis potential indices and higher mid‐tropospheric humidity, as well as positive phases of the Atlantic Multidecadal Oscillation. Additionally, the negative phase of the Pacific Decadal Oscillation leads to strong/weak ENSO‐TC teleconnections in the eastern North Pacific and North Atlantic, respectively. Furthermore, a negative North Atlantic Oscillation is associated with a weak ENSO‐North Atlantic TC teleconnection. This research highlights variations in ENSO's effectiveness for seasonal TC prediction. Key Points The observed impact of ENSO on tropical cyclone (TC) activity exhibits multidecadal fluctuations The ENSO‐TC teleconnection was strong in the Atlantic from the 1980s to mid‐2000s and strengthened over the North Pacific in recent decades The ENSO‐TC teleconnection is stronger in the Atlantic and North Pacific basins during a positive Atlantic Multidecadal Oscillation
ENSO↗
The Role of Radiative Interactions in Tropical Cyclone Development under Realistic Boundary Conditions
Abstract The impact of radiative interactions on tropical cyclone (TC) climatology is investigated using a global, TC-permitting general circulation model (GCM) with realistic boundary conditions. In this model, synoptic-scale radiative interactions are suppressed by overwriting the model-generated atmospheric radiative cooling rates with their monthly varying climatological values. When radiative interactions are suppressed, the global TC frequency is significantly reduced, indicating that radiative interactions are a critical component of TC development even in the presence of spatially varying boundary conditions. The reduced TC activity is primarily due to a decrease in the frequency of pre-TC synoptic disturbances (“seeds”), whereas the likelihood that the seeds undergo cyclogenesis is less affected. When radiative interactions are suppressed, TC genesis shifts toward coastal regions, whereas TC lysis locations stay almost unchanged; together the distance between genesis and lysis is shortened, reducing TC duration. In a warmer climate, the magnitude of TC reduction from suppressing radiative interactions is diminished due to the larger contribution from latent heat release with increased sea surface temperatures. These results highlight the importance of radiative interactions in modulating the frequency and duration of TCs.
Meteorology & Atmospheric Sciences↗
Materials Data on Tc2As3 by Materials Project
Tc2As3 crystallizes in the triclinic P-1 space group. The structure is three-dimensional. there are four inequivalent Tc+0.50+ sites. In the first Tc+0.50+ site, Tc+0.50+ is bonded to six As+0.33- atoms to form a mixture of distorted edge, face, and corner-sharing TcAs6 octahedra. The corner-sharing octahedra tilt angles range from 40–60°. There are a spread of Tc–As bond distances ranging from 2.47–2.71 Å. In the second Tc+0.50+ site, Tc+0.50+ is bonded to six As+0.33- atoms to form a mixture of distorted edge, face, and corner-sharing TcAs6 octahedra. The corner-sharing octahedra tilt angles range from 40–59°. There are a spread of Tc–As bond distances ranging from 2.48–2.60 Å. In the third Tc+0.50+ site, Tc+0.50+ is bonded to six As+0.33- atoms to form a mixture of edge, face, and corner-sharing TcAs6 octahedra. The corner-sharing octahedra tilt angles range from 40–60°. There are a spread of Tc–As bond distances ranging from 2.46–2.58 Å. In the fourth Tc+0.50+ site, Tc+0.50+ is bonded to six As+0.33- atoms to form a mixture of edge, face, and corner-sharing TcAs6 octahedra. The corner-sharing octahedra tilt angles range from 40–59°. There are a spread of Tc–As bond distances ranging from 2.45–2.58 Å. There are six inequivalent As+0.33- sites. In the first As+0.33- site, As+0.33- is bonded in a 5-coordinate geometry to four Tc+0.50+ and one As+0.33- atom. The As–As bond length is 2.49 Å. In the second As+0.33- site, As+0.33- is bonded in a 5-coordinate geometry to four Tc+0.50+ and one As+0.33- atom. In the third As+0.33- site, As+0.33- is bonded in a distorted rectangular see-saw-like geometry to four Tc+0.50+ atoms. In the fourth As+0.33- site, As+0.33- is bonded in a 4-coordinate geometry to four Tc+0.50+ atoms. In the fifth As+0.33- site, As+0.33- is bonded in a 5-coordinate geometry to four Tc+0.50+ and one As+0.33- atom. The As–As bond length is 2.82 Å. In the sixth As+0.33- site, As+0.33- is bonded in a 5-coordinate geometry to four Tc+0.50+ and one As+0.33- atom. The As–As bond length is 2.70 Å.
36 MATERIALS SCIENCE↗
Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai
This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.
Jana Kolassa↗
Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai
This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.
Jana Kolassa↗