11 research outputs found
Predictive Models for Prediction of Broad Crested Gabion Weir Aeration Performance
The gabion weirs serve the same functions that their counterpart impervious weirs do. However, they have the advantage of being eco-friendly, more stable, and economical in low to medium-head cases. Dissolved oxygen is one of the major determinants for the assessment of the purity of water. The purpose of the present work is to illustrate the comparison of multiple linear regression (MLR), neural network (NN), neuro-fuzzy system (NFS), deep neural network (DNN), and reported empirical models for the prediction of gabion weir aeration performance efficiency (APE20) with experimental results which are collected from the laboratory test. The NFS with four shaped membership functions, NN, DNN, MLR, and existing empirical models, are generated with the same input parameters, and their potentials are assessed to statistical appraisal indices. The results show that the DNN with the highest value of R2 (0.935) and NSE (0.934) and having the least errors in validating phase is the outperforming proposed model in the prediction of the APE20, which the NN model follows with R2 (0.917) and NSE (0.917). However, except trapezoidal shaped NFS model with R2 (0.873) and NSE (0.852) and MLR with R2 (0.905) and NSE (0.897), the remaining models of NFS-based and empirical relations could not perform better in validating phase. The sensitivity performance test is too conducted to find the relative relevance of the input parameter on the results of the APE20, where discharge per unit width (q) is found to be the most significant parameter, followed by the drop height (H0)
Multiscale analysis of the low-velocity impact behavior of ceramic nanoparticle-reinforced metal matrix nanocomposite beams by micromechanics and finite element approaches
Analgesic and anti-inflammatory activity of β-sitosterol isolated from Nyctanthes arbortristis leaves
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Near-global summer circulation response to the spring surface temperature anomaly in Tibetan Plateau –– the GEWEX/LS4P first phase experiment
Abstract:
Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was initiated to study the impact of springtime LST/SUBT anomalies over high mountain areas on summertime precipitation predictions. The present work explores the simulated global scale response of the atmospheric circulation to the springtime TP land surface cooling by 16 current state-of-the-art Earth System Models (ESMs) participating in the LS4P Phase I (LS4P-I) experiment. The LS4P-I results show, for the first time, that springtime TP surface anomalies can modulate a persistent quasi-barotropic Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train from the TP via the northeast Asia and Bering Strait to the western part of the North America, along with the springtime westerly jet from TP across the whole North Pacific basin. The TRC wave train modulated by the TP thermal anomaly play a critical role on the early summer surface air temperature and precipitation anomalies in the regions along the wave train, especially over the northwest North America and the southern Great Plains. The participant models that fail in capturing the TRC wave train greatly under-predict climate anomalies in reference to observations and the successful models. These results suggest that the TP LST/SUBT anomaly via the TRC wave train is the first order source of the S2S variability in the regions mentioned. Furthermore, the TP surface temperature anomaly can influence the Southern Hemispheric circulation by generating cross-equator wave trains. However, the simulated propagation pathways from the TP into the Southern Hemisphere show large inter-model differences. More dynamical understanding of the TRC wave train as well as its cross-equator propagation into the Southern Hemisphere will be explored in the newly launched LS4P phase II experiment
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Correction to: Near‑global summer circulation response to the spring surface temperature anomaly in Tibetan Plateau –– the GEWEX/LS4P first phase experiment
https://doi.org/10.1007/s00382-024-07210-5. In this article 17 references, which were wrongly moved to the Supplementary Information, need to be added. The list of added references as given below: The original article has been correcte
Altered Expression of Transmembrane Mucins, MUC1 and MUC4, in Bladder Cancer: Pathological Implications in Diagnosis
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Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the GEWEX/LS4P Phase I experiment
Abstract:
The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented