Search for: All records

The present topography of the northern Tibetan Plateau is characterized by the northwest-trending Eastern Kunlun Range, Qaidam Basin, and Qilian Shan, which figure importantly into the evolution and mechanism of Tibetan plateau development during Cenozoic Indo-Asian convergence. Understanding the Cenozoic deformation history and the source-to-sink relationship through time has significant implications for deciphering the growth history of the northern Tibetan Plateau. Despite decades of study, the timing, pattern, and mechanisms of deformation across the northern Tibetan Plateau are still vigorously debated. The North Qaidam thrust belt, located between the Qaidam Basin and Qilian Shan thrust belt, provides a valuable record of Cenozoic deformation in the northern Tibetan Plateau. Here, we present the results of new geologic mapping, structural and sedimentology analysis, and apatite fission track thermochronology to constrain the Cenozoic evolution history and reconstruct the paleogeomorphology of the eastern domain of the North Qaidam thrust belt and its foreland, the Wulan Basin. Our analyses reveal the North Qaidam thrust belt experienced multi-phase exhumation since the Cretaceous. A period of Eocene localized thrust-related uplift of the North Qaidam thrust belt initiated shortly after India-Asia collision, and lower erosion rates in the Oligocene allowed the thrust belt to expand along-strike eastward. Localmore »uplift shed sediments to the southwest, directly into the Qaidam Basin. Reactivation of the proximal thrust faults and initiation of the northwest-striking right-slip Elashan fault at ca. 15−10 Ma drove the final accelerated mid-Miocene cooling and denudation to the surface. This phase of deformation established the overall framework morphology of the northeastern margin of the Tibetan Plateau, including the overall structure of the basins and ranges.« less

Lecture-based teaching paired with laboratory-based exercises is most commonly used in cybersecurity instruction. However, it focuses more on theories and models but fails to provide learners with practical problem-solving skills and opportunities to explore real-world cybersecurity challenges. Problem-based Learning (PBL) has been identified as an efficient pedagogy for many disciplines, especially engineering education. It provides learners with real-world complex problem scenarios, which encourages learners to collaborate with classmates, ask questions and develop a deeper understanding of the concepts while solving real-world cybersecurity problems. This paper describes the application of the PBL methodology to enhance professional training-based cybersecurity education. The authors developed an online laboratory environment to apply PBL with Knowledge-Graph (KG) based guidance for hands-on labs in cybersecurity training.Learners are provided access to a virtual lab environment with knowledge graph guidance to simulated real-life cybersecurity scenarios. Thus, they are forced to think independently and apply their knowledge to create cyber-attacks and defend approaches to solve problems provided to them in each lab. Our experimental study shows that learners tend to gain more enhanced learning outcomes by leveraging PBL with knowledge graph guidance, become more aware of cybersecurity and relevant concepts, and also express interest in keep learning of cybersecurity usingmore »our system.« less

Abstract An unprecedented extreme positive Indian Ocean Dipole event (pIOD) occurred in 2019, which has caused widespread disastrous impacts on countries bordering the Indian Ocean, including the East African floods and vast bushfires in Australia. Here we investigate the causes for the 2019 pIOD by analyzing multiple observational datasets and performing numerical model experiments. We find that the 2019 pIOD is triggered in May by easterly wind bursts over the tropical Indian Ocean associated with the dry phase of the boreal summer intraseasonal oscillation, and sustained by the local atmosphere-ocean interaction thereafter. During September-November, warm sea surface temperature anomalies (SSTA) in the central-western tropical Pacific further enhance the Indian Ocean’s easterly winds, bringing the pIOD to an extreme magnitude. The central-western tropical Pacific warm SSTA is strengthened by two consecutive Madden Julian Oscillation (MJO) events that originate from the tropical Indian Ocean. Our results highlight the important roles of cross-basin and cross-timescale interactions in generating extreme IOD events. The lack of accurate representation of these interactions may be the root for a short lead time in predicting this extreme pIOD with a state-of-the-art climate forecast model.

Abstract Following the interdecadal shift of El Niño–Southern Oscillation (ENSO) properties that occurred in 1976/77, another regime shift happened in 1999/2000 that featured a decrease of variability and an increase in ENSO frequency. Specifically, the frequency spectrum of Niño-3.4 sea surface temperature shifted from dominant variations at quasi-quadrennial (~4 yr) periods during 1979–99 to weaker fluctuations at quasi-biennial (~2 yr) periods during 2000–18. Also, the spectrum of warm water volume (WWV) index had almost no peak in 2000–18, implying a nearly white noise process. The regime shift was associated with an enhanced zonal gradient of the mean state, a westward shift in the atmosphere–ocean coupling in the tropical Pacific, and an increase in the static stability of the troposphere. This shift had several important implications. The whitening of the subsurface ocean temperature led to a breakdown of the relationship between WWV and ENSO, reducing the efficacy of WWV as a key predictor for ENSO and thus leading to a decrease in ENSO prediction skill. Another consequence of the higher ENSO frequency after 1999/2000 was that the forecasted peak of sea surface temperature anomaly often lagged that observed by several months, and the lag increased with the lead time. The ENSOmore »regime shift may have altered ENSO influences on extratropical climate. Thus, the regime shift of ENSO in 1999/2000 as well as the model default may account for the higher false alarm and lower skill in predicting ENSO since 1999/2000.« less