Article
Agronomy
Andries B. Potgieter, Andrew Schepen, Jason Brider, Graeme L. Hammer
Summary: Foresight of crop yield is crucial for managing climate risks and uncertainties in the Australian agricultural industry. This study compares the skill of a wheat yield forecasting system using a statistical ENSO-analogue climate forecasting system and a dynamic GCM-derived climate forecasting system. The results show that the GCM-based approach has improved skill and provides reliable wheat yield forecasts, particularly in the early months of the season. The shift in forecast yield distributions varies by location and time, with the GCM-derived forecasts showing more widespread and earlier shifts. Overall, the GCM-based climate/crop forecasting system demonstrates significant improvement in lead time and offers potential for enhanced relevance and utility in commodity forecasting frameworks.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Geochemistry & Geophysics
Jeanne L. Hardebeck
Summary: Aftershocks do not evenly distribute around a mainshock and instead occur in spatial clusters. The spatially variable physical properties of the crust may influence the distribution of aftershocks. A study of four aftershock sequences in Southern California reveals correlations between aftershocks and various properties such as stress, fault structure, seismic velocity, and heat flow. Though improvements have been made in modeling aftershock locations, further research is needed to establish the connections between aftershock occurrence and the physical properties that cause them.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2022)
Article
Geochemistry & Geophysics
Hao Ping
Summary: This study systematically investigated the relationship between data uncertainty and the reliability of differential stress constraint using the 1992 Landers earthquake as an example. The results showed that the uncertainty of the data led to systematic deviation. Two linear relationships between the original constraint value and the true differential stress were identified, and the adjusted constraint value based on the rising segment eliminated the deviation. The analysis also revealed the variations in constraint capability at different analysis locations. Through comprehensive analysis and evaluation, the best differential stress constraint result for the Landers earthquake was obtained.
CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION
(2023)
Article
Geochemistry & Geophysics
Roby Douilly
Summary: Complex fault systems with asymmetric topography have been found in Southern California. Geometrical complexities such as stepovers can influence fault rupture. This study investigates the effect of asymmetric topography on rupture dynamics at stepovers using three different types of topography: flat, positive (mountain), and negative (basin). The results show that topography can have a significant impact on rupture propagation at stepovers, and suggest that topography should be considered in dynamic studies with geometric complexities.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2023)
Article
Multidisciplinary Sciences
Sonia Bhattacharya, Himadri Chakraborty Bhattacharyya
Summary: Severe thunderstorms, as extreme weather convective features, cause local calamities in various ways. Proper prediction is crucial in preventing these calamities and saving people. This study applies probabilistic and machine learning techniques to weather data, introducing Naive Bayes and Radial Basis Function Network (RBFN) methods with specific weather parameters. A comparative study was conducted on weather data from Kolkata, India, and the results show that the RBFN method outperforms the other two methods, achieving a correct prediction rate of 95% for severe squall-storms and 94% for no storm, with a lead time of 10-12 hours.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Kun Zhou, Wenyong Wang, Lisheng Huang, Baoyang Liu
Summary: The study evaluated the accuracy of several classical statistical methods in time series forecasting and proposed a novel decomposition method to reduce RMSE and improve forecasting accuracy. Results showed a decrease in error rate and compared traditional statistical methods with a deep generative adversarial network, finding no significant difference in forecasting accuracy for this specific time series.
KNOWLEDGE-BASED SYSTEMS
(2021)
Review
Business, Finance
H. Kent Baker, Satish Kumar, Kirti Goyal, Anuj Sharma
Summary: This study provides a comprehensive analysis of IRFA from 1992 to 2020 using bibliometrics, regression analysis, and STM. The findings show significant growth in publications, citations, and authors' collaboration network. Regression analysis identified critical predictors of IRFA's citations, while STM revealed the journal's conceptual structure with 12 major topics.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
(2021)
Article
Engineering, Electrical & Electronic
Dan Li, Guangfan Sun, Shuwei Miao, Yingzhong Gu, Yuanhang Zhang, Shuai He
Summary: This paper proposes an STLF method based on an improved sequence-to-sequence gated recurrent unit network to address the problem of poor forecast accuracy caused by neglecting the temporal dependence. The results from two real examples demonstrate significant improvements in forecast accuracy and adaptability.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Bedassa Dessalegn Kitessa, Semu Moges Ayalew, Geremew Sahilu Gebrie, Solomon Tmariam Teferi
Summary: The study predicted the water-energy supply and demand of Addis Ababa city for 2030 and 2050, determining sustainable supply methods. The results showed that future water demand will be met, but intervention is needed for energy supply-demand balance.
Article
Environmental Sciences
Yang Lyu, Xiefei Zhi, Hong Wu, Hongmei Zhou, Dexuan Kong, Shoupeng Zhu, Yingxin Zhang, Cui Hao
Summary: This study evaluated wind forecasts from different institutions in North China and found performance differences among models at different heights and lead times. The multimodel ensemble mean method effectively improved wind forecast abilities, but still had some deficiencies in reducing bias and distribution of forecast errors.
Review
Biochemical Research Methods
Stefano Castellana, Tommaso Biagini, Luca Parca, Francesco Petrizzelli, Salvatore Daniele Bianco, Angelo Luigi Vescovi, Massimo Carella, Tommaso Mazza
Summary: This study found that hundreds of human proteins interact with degenerated DNA sequences, and identifying these motifs and genomic sites is a challenging research goal in modern molecular biology and bioinformatics. Over the past twenty years, there has been an explosion of computational tools for this task, and sixteen of them were evaluated for their ability to identify known motifs in simulated sequence datasets.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Green & Sustainable Science & Technology
Marco Pierro, Damiano Gentili, Fabio Romano Liolli, Cristina Cornaro, David Moser, Alessandro Betti, Michela Moschella, Elena Collino, Dario Ronzio, Dennis van der Meer
Summary: This study investigates various aspects of regional PV power forecasting by comparing six different forecasting models, showing that forecasting accuracy is mainly affected by the algorithm and its processing, with less impact on forecasting horizon. Additionally, accuracy in irradiation prediction has less impact compared to individual plants.
Article
Endocrinology & Metabolism
Agnes Sola-Gazagnes, Catherine Pecquet, Stefano Berre, Peter Achenbach, Laure-Anne Pierson, Isabelle Virmoux-Buisson, Jocelyne M'Bemba, Fabienne Elgrably, Philippe Moguelet, Christian Boitard, Sophie Caillat-Zucman, Moussa Laanani, Joel Coste, Etienne Larger, Roberto Mallone
Summary: The study aimed to develop a management workflow for diagnosing insulin allergy and evaluate the diagnostic performance of confirmatory tests. Clinical criteria were validated as effective diagnostic guides, and the IDR test showed the best diagnostic performance.
Article
Computer Science, Information Systems
Luyao Liu, Qie Sun, Ronald Wennersten, Zhigang Chen
Summary: This study proposes a novel Stacking ensemble forecast model to improve the precision of day-ahead PV power forecasts by creating multiple sub-training sets and integrating the best performing base models.
Article
Public, Environmental & Occupational Health
Hsiang-Yu Yuan, Jingbo Liang, Md Pear Hossain
Summary: This study investigated the effects of non-pharmaceutical interventions (NPIs) and vaccine boosters on the transmission of the fifth wave of COVID-19 in Hong Kong. The findings suggest that social distancing measures alone were not effective in containing the outbreak, but the use of rapid antigen tests (RAT) and increased vaccination rates helped reduce the cumulative incidence. Additionally, the cold surge event played a temporary role in driving the outbreak.
JOURNAL OF INFECTION AND PUBLIC HEALTH
(2022)
Article
Geochemistry & Geophysics
A. M. Lombardi
Summary: This study examines three major seismic sequences in Italy and finds that the variability of the Gutenberg-Richter b-value may not be a reliable indicator of stress or a significant precursor in these examples. The findings suggest that chance, data inhomogeneities, and inefficiencies in estimation methodologies may contribute to the variability of the b-value.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Geochemistry & Geophysics
Allen Husker, Maximilian J. Werner, Jose A. Bayona, Miguel Santoyo, Raul Daniel Corona-Fernandez
Summary: The seismic gap hypothesis is widely used in Mexico to predict future earthquakes. However, no previous analysis has been done to evaluate the accuracy of these predictions in Mexico. This study analyzes a specific prediction from 1987 and finds that the seismic gap hypothesis performed poorly in predicting earthquakes in Mexico, with worse results than random chance.
BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA
(2023)
Article
Geochemistry & Geophysics
Khawaja M. Asim, Danijel Schorlemmer, Sebastian Hainzl, Pablo Iturrieta, William H. Savran, Jose A. Bayona, Maximilian J. Werner
Summary: CSEP is an international effort to evaluate earthquake forecasting models. In this study, the concept of Quadtree is proposed to create a multi-resolution grid for data-driven earthquake forecast generation and testing. The Quadtree is a hierarchical tree-based data structure used in combination with the Mercator projection, and it has numerous applications.
BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA
(2023)
Article
Geochemistry & Geophysics
A. Gualandi, D. Faranda, C. Marone, M. Cocco, G. Mengaldo
Summary: We use dynamical system tools to analyze frictional stick-slip events and investigate the underlying dynamics associated with the transition from stable sliding to unstable motion. Our analysis shows that the seismic cycle exhibits characteristics of a low-dimensional system and the local properties of the attractor require a high number of degrees of freedom. We propose that the lab seismic cycle is best explained by a random attractor based on rate- and state-dependent friction.
EARTH AND PLANETARY SCIENCE LETTERS
(2023)
Article
Geochemistry & Geophysics
Asim M. Khawaja, Sebastian Hainzl, Danijel Schorlemmer, Pablo Iturrieta, Jose A. Bayona, William H. Savran, Maximilian Werner, Warner Marzocchi
Summary: This study aims to evaluate earthquake forecast models by using a grid-based format to express earthquake forecasts and assessing the spatial distribution of seismicity through the S-test. The study found that the high resolution grid and sparse earthquake distribution affect the statistical power, and recommends the use of Quadtree-based multi-resolution grids to improve the statistical power in future experiments.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Geochemistry & Geophysics
Gert Zoeller, Sebastian Hainzl
Summary: The Groningen gas field in the Netherlands has caused increasing concerns due to induced seismic activity. This study shows that the estimated maximum possible magnitude for future earthquakes has decreased compared to previous estimates.
SEISMOLOGICAL RESEARCH LETTERS
(2023)
Article
Geochemistry & Geophysics
J. M. Holmgren, G. Kwiatek, M. J. Werner
Summary: The rupture behavior of microseismicity in fluid-injection settings is influenced by pore pressure and shows a certain degree of predictability. Through the analysis of directivity patterns and focal mechanisms, this study identifies rupture planes and directions of 10 events recorded during the 2018 St1 Deep Heat geothermal project in Finland. Unlike previous studies, the events in this project exhibit varied rupture directions, with some rupturing towards, away from, or parallel to the injection well. These findings contribute to the understanding of rupture growth in pore-pressure dominated settings.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2023)
Article
Geochemistry & Geophysics
J. N. Williams, M. J. Werner, K. Goda, L. N. J. Wedmore, R. De Risi, J. Biggs, H. Mdala, Z. Dulanya, A. Fagereng, F. Mphepo, P. Chindandali
Summary: Historical and instrumental earthquake catalogs may not accurately reflect the long-term distribution of seismicity in low strain rate regions. Therefore, probabilistic seismic hazard analysis (PSHA) should consider geologic and geodetic data to incorporate fault-based seismogenic sources. The study explores these issues in the context of a new PSHA for Malawi, which has a thick seismogenic layer and a growing exposure to seismic hazard. The results emphasize the importance of careful fault source modeling in PSHA and the need for new fault-based PSHA in the East Africa Rift.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Geochemistry & Geophysics
Behnam M. Asayesh, Sebastian Hainzl, Gert Zoeller
Summary: Current earthquake catalogs provide high-precision depth values. We extend the 3D spatiotemporal Epidemic Type Aftershock Sequence model by considering hypocentral distances. By examining different triggering functions, we find that a magnitude-dependent power-law kernel fits the earthquake data in Southern California best. The model incorporates this kernel, as well as space-dependent background activity and depth-dependent aftershock productivity, and fits the data well.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2023)
Article
Geosciences, Multidisciplinary
Bogdan Enescu, Cristian Ghita, Iren-Adelina Moldovan, Mircea Radulian
Summary: In this study, we revisited seismicity characteristics in the Vrancea region using earthquake catalog data from two time periods. The results confirmed the existence of decreased b-values in the deepest part of the seismogenic zone and statistically confirmed the seismic quiescence before the occurrence of the 1977 Vrancea earthquake.
Article
Geosciences, Multidisciplinary
Asim M. Khawaja, Behnam Maleki Asayesh, Sebastian Hainzl, Danijel Schorlemmer
Summary: Aftershock forecast models are often evaluated using a uniform spatial grid and the receiver operating characteristic (ROC) curve, but this method has flaws. This study proposes using the Matthews correlation coefficient (MCC) and the F-1 curve instead, as well as a multi-resolution test grid adapted to earthquake density. Results show that at least 8% and 5% of observed earthquakes in grid cells are needed to distinguish between a near-perfect forecast model and an informationless forecast using MCC-F1 and ROC curves respectively. Despite improved testing, the simple R model outperforms the Delta CFS model in real aftershock forecasts.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Geochemistry & Geophysics
I Spassiani, G. Falcone, M. Murru, W. Marzocchi
Summary: In this paper, the authors gather and analyze the results of the OEF system in Italy during its first 10 years of operation. The system provides real-time earthquake forecasts for the entire Italian territory based on an ensemble model. The authors evaluate the performance of the forecasts using standard tests and performance measures borrowed from other fields. The study aims to identify weaknesses in the OEF-Italy modeling, provide helpful measures for stakeholders, and uncover features of seismic activity in Italy.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Geosciences, Multidisciplinary
Domenico Giaquinto, Warner Marzocchi, Juergen Kurths
Summary: In this study, we use concepts and methods derived from complex network theory to investigate the spatial patterns and features of meteorological droughts in Europe. By analyzing the co-occurrence of drought events at different locations within a season from 1981 to 2020, we uncover robust drought continental networks and identify regional clusters characterized by the geographical propagation and source-sink systems of droughts. Our approach introduces new methodologies for climate network reconstruction and provides valuable insights into the spatial dynamics of droughts, potentially improving drought forecasting.
NONLINEAR PROCESSES IN GEOPHYSICS
(2023)