Article
Geochemistry & Geophysics
Jiazheng Liu, Weifu Li, Jiangtao Peng, Lijun Shen, Hua Han, Peng Zhang, Lei Yang
Summary: The study improves upon the coastline inflection point method by utilizing a nonrigid point set registration method to enhance the geolocation accuracy of MWRI observations. The comparison analysis demonstrates that the proposed method can provide more accurate estimation of geolocation bias and achieve good results in long-term data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geosciences, Multidisciplinary
Grey S. Nearing, Daniel Klotz, Jonathan M. Frame, Martin Gauch, Oren Gilon, Frederik Kratzert, Alden Keefe Sampson, Guy Shalev, Sella Nevo
Summary: Ingesting real-time observation data is crucial for many hydrological forecasting systems. This paper compares two strategies, autoregression and variational data assimilation, for incorporating real-time streamflow observations into LSTM rainfall-runoff models. The results show that autoregression is both more accurate and computationally efficient, but it is sensitive to missing data. However, this can be mitigated by using an appropriate training strategy in data assimilation.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Robotics
Riccardo Polvara, Sergi Molina, Ibrahim Hroob, Alexios Papadimitriou, Konstantinos Tsiolis, Dimitrios Giakoumis, Spiridon Likothanassis, Dimitrios Tzovaras, Grzegorz Cielniak, Marc Hanheide
Summary: Achieving a robust long-term deployment with mobile robots in agriculture is challenging due to the continuously changing environment. In this study, an ongoing effort in the long-term deployment of an autonomous mobile robot in a vineyard is reported, with the objective of acquiring a data set for testing mapping and localization algorithms. The data set covers a total of 7 months and captures the canopy growth from March to September. An initial study on long-term localization using different sessions belonging to different months and plant stages is also presented.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Forestry
John Turner
Summary: Long-term studies in forestry are crucial for maintaining and improving forest management. However, the success rate of such studies is low, with a limited number of them achieving the stated long-term objectives and a large portion of collected information being inaccessible.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Geosciences, Multidisciplinary
Martin G. Mlynczak, B. Thomas Marshall, Rolando R. Garcia, Linda Hunt, Jia Yue, V. Lynn Harvey, Manuel Lopez-Puertas, Chris Mertens, James Russell III
Summary: The accuracy of long-term atmospheric temperature observations by satellite instruments relies on various factors, such as measurement accuracy, instrument calibration stability, satellite orbit stability, and numerical algorithm stability. A recent example of algorithm instability in the temperature data from the SABER instrument on the NASA TIMED satellite is presented. This instability resulted in significantly colder temperatures than anticipated for a period from mid-December 2019 to mid-2022. The paper emphasizes the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth's mesosphere and lower thermosphere, and introduces a corrected version (Version 2.08) of the SABER temperatures.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Optics
Jian Xing, Pengyu Yan, Wenchao LI, Shuanglong Cui
Summary: This article proposes a method that combines the generalized inverse matrix (GIM) with the long short-term memory (LSTM) neural network algorithm for data processing of multi-wavelength pyrometry. The method completely eliminates the influence of emissivity and demonstrates superior accuracy and efficiency compared to traditional methods.
Article
Environmental Sciences
Xingchuan Yang, Chuanfeng Zhao, Yikun Yang, Hao Fan
Summary: The spatiotemporal distributions of aerosol optical properties and major aerosol types over Australia show strong seasonal variations and spatial heterogeneity. Most sites exhibit increasing trends in aerosol optical depth (AOD) and decreasing trends in Angstrom exponent (AE). Different regions in Australia have distinct characteristics in terms of major aerosol types, with mixed aerosols dominating all seasons.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2021)
Article
Computer Science, Artificial Intelligence
D. Fister, J. Perez-Aracil, C. Pelaez-Rodriguez, J. Del Ser, S. Salcedo-Sanz
Summary: In this paper, three customised AI frameworks for longterm summer air temperature prediction are proposed. The frameworks consider Deep Learning, Machine Learning algorithms, and data reduction techniques. The results show that these frameworks have achieved excellent prediction skill for seasonal climate prediction problems in both Paris and Cordoba regions.
APPLIED SOFT COMPUTING
(2023)
Article
Multidisciplinary Sciences
Qibin Duan, Clare A. McGrory, Glenn Brown, Kerrie Mengersen, You-Gan Wang
Summary: Many studies have examined global temperature trends, but there is a lack of in-depth analysis of latent trends. Using a joint model, this study analyzes Australian data and finds that daily maximum temperature is warming at a rate of about 0.21 degrees C per decade, while daily minimum temperature is warming at a rate of about 0.13 degrees C per decade. The study also reveals nuanced patterns of change based on location, season, and the percentiles of the temperature series.
Article
Construction & Building Technology
Aksel Fenerci, Knut Andreas Kvale, Oyvind Wiig Petersen, Anders Ronnquist, Ole Oiseth
Summary: This data paper describes a large data set of wind and acceleration data collected through long-term monitoring of the Hardanger Bridge in Norway. The data set includes both raw and organized data, published in an open-access data repository. The paper discusses the monitoring system used, methods of signal processing and data adjusting, as well as the organization and summary of the data set.
JOURNAL OF STRUCTURAL ENGINEERING
(2021)
Article
Construction & Building Technology
Pei Jie Zhang, Chun Sheng Wang, Gen Shu Wu, Yu Wang
Summary: This study conducted long-term monitoring on a composite girder, investigated the temperature distribution patterns under typical weather conditions, and provided standard values for the most critical temperature gradient. By comparing with current specifications, it was proven that the proposed models can better represent the thermal loads on the test girder model.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2022)
Article
Construction & Building Technology
Sabarigirivasan Lakshmi Narayanan, Umamaheswari Nambiappan
Summary: This article investigates an experimental steel I-girder section encased in concrete and its instrumentation to analyze temperature distributions in concrete bridges. The study aims to examine the effect of varying air temperatures and thermal loads from solar radiation. Structural health monitoring sensors, including temperature sensors, were connected to the girder to constantly monitor structural performance. The experimental data collection occurred during an exceptionally cold season, and the results revealed the lateral and vertical distribution of thermal gradients, as well as the fluctuations over time. Empirical equations were suggested based on accumulated thermal data to forecast peak lateral and vertical temperature gradients according to the girder's highest daily and lowest mean temperatures. This temperature variation may cause longitudinal expansion and contraction in the structure during seasonal variations.
Article
Geosciences, Multidisciplinary
Colin Goldblatt, Victoria L. McDonald, Kelly E. McCusker
Summary: The research indicates that the early Earth had a dimmer Sun and rare glaciation in the Precambrian, known as the 'faint young Sun problem'. Through climate model experiments, it was found that systematic changes to low clouds have played a major role in stabilizing Earth's climate throughout its history, highlighting the importance of physical feedbacks in long-term climate stabilization, with a smaller role for geochemical feedbacks.
Article
Meteorology & Atmospheric Sciences
Ole Einar Tveito
Summary: When analyzing long-term climate trends and variability, it is important to use undisturbed data and consistent data series. This paper presents an approach to construct long-term homogenized climate series, which leads to better and more reliable gridded datasets for analyzing climate trends and variability.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Infectious Diseases
Chloe C. H. Smit, Kris Rogers, Hamish Robertson, Katja Taxis, Lisa G. Pont
Summary: This study examines trends in antibiotic use among long-term care residents using real-world data. The findings reveal patterns of antibiotic use and highlight the need for quality treatment guidelines in this vulnerable population.