Correction Process Research Articles

Modeling, analysis, and optimization of random error in indirect time-of-flight camera

For indirect time-of-flight (iToF) cameras, we proposed a modeling approach focused on addressing random error. Our model characterizes random error comprehensively by detailing the propagation of error introduced by signal light, ambient light, and dark noise through phase calculation and system correction processes. This framework leverages correlations between incident light and tap responses to quantify noise impacts accurately. We then experimentally validated the theoretical model, confirming its predictive accuracy. Additionally, from a waveform design perspective, we recommend selecting an optimal duty cycle for the light waveform based on the relative intensities of ambient and signal light to effectively reduce random error.

Development of an image quality evaluation system for bedside chest X-ray images using scatter correction processing.

In plain radiography, scattered X-ray correction processing (Virtual Grid: VG) is used to estimate and correct scattered rays in images. We developed an objective evaluation system for bedside chest X-ray images using VG and investigated its usefulness. First, we trained the blind/referenceless image spatial quality evaluator (BRISQUE) on 200 images obtained by portable chest radiography. We then evaluated optimal chest phantom VG images as well as those that deviated from the VG setting conditions using BRISQUE. Furthermore, we conducted a subjective evaluation using the mean opinion score (MOS) and established an objective evaluation system for VG images. Finally, the degree of agreement between the MOS subjectively evaluated by 14 radiological technologists and that determined by the objective evaluation system for 100 clinical images obtained by portable chest radiography was calculated using Cohen's kappa coefficient. The correlation coefficient between the BRISQUE score and MOS for chest phantom images was - 0.96 (p < 0.05). The two scores showed a very high linear correlation, indicating the potential of the BRISQUE score as an alternative to MOS. The Cohen's kappa coefficient for the objective evaluation system using the optimal conversion table was 0.42. Conversely, there was a very high detection rate of 82.86% for poor-quality images. An objective evaluation system for bedside chest X-ray images using VG that uses no-reference image quality evaluation helps provide proper image quality. Furthermore, such a system can be constructed with a small amount of training data, which increases the possibility of introducing it to a variety of facilities.

Research on Key Technologies of 260 °C/210 MPa Ultra-Deep Logging Equipment

Deep and ultra-deep oil, which are unconventional oil reservoirs have become an important field for increasing reserves and production in China’s oil and gas exploration and development, and pose higher requirements for ultra-deep logging technology and equipment. For addressing the technical challenges faced in the development of 260 °C/210 MPa ultra-high temperature and high-pressure logging equipment, based on the CPLog fast and imaging series instruments, this article originally proposes key core technologies and solutions such as 260 °C/210 MPa electromechanical sensors, 13,000 m cable communication, and large borehole correction processing. Through the design indoor testing of a BS-PT-based ultra-high temperature acoustic transducer, 260 °C/210 MPa instrument pressure-bearing housing components, and field testing of large borehole environment testing and 13,000-m cable 8000-m deep well data transmission, it will help develop a prototype of 260 °C/210 MPa ultra-high temperature and high pressure logging equipment. The key technology research of 260 °C/210 MPa logging equipment has laid the foundation for the development of ultra-deep logging equipment and provided technical support for the exploration and development of ultra-deep oil and gas at a depth of 10,000 m.

Baseline correction for infrared spectra using relative absorbance-based independent component analysis

Infrared spectroscopy has important applications in fields such as materials analysis and chemical detection, while baseline correction is a key step in ensuring the accurate interpretation of spectral data. Uncorrected baselines can lead to deviations in absorption peaks, which affects the accuracy of both quantitative and qualitative analysis. When the absorption peaks of various components in a mixed gas overlap, the lack of reference baseline information in the continuous absorption band can result in significant errors during the baseline correction process. In this paper, we propose a relative absorbance-based independent component analysis (RA-ICA) algorithm to address this challenge. The algorithm first calculates the relative absorbance spectrum that excludes baseline information. Subsequently, based on the Beer-Lambert law and independent component analysis, it extracts independent components containing the absorption peak information of the components, allowing for fitting spectra that require baseline correction. Finally, a baseline model that combines polynomial curves and residuals is used to reconstruct the hidden baseline of the absorption band. Simulation and experimental results demonstrate that the baseline reconstructed using the RA-ICA method exhibits a significantly lower error compared to five other commonly used baseline correction methods and accurately preserves the detailed characteristics of the baseline.

The cerebellum is involved in implicit motor sequence learning.

Implicit motor sequence learning (IMSL) is a cognitive function that allows us to execute multiple movements in a specific sequential order and plays a crucial role in our daily functional activities. Although the role of the basal ganglia network in IMSL is well-established, the exact involvement of the cerebellar network is less clear. Here, we aimed to address this issue by investigating the effects of cerebellar transcranial direct-current stimulation (tDCS) on IMSL. In this sham-controlled, crossover study in 45 healthy young adults, we used mixed-effects models to analyze sequence-specific (primary outcome) and general learning effects (secondary outcome) in the acquisition (during tDCS), short- (five minutes post-tDCS) and long-term consolidation (one week post-tDCS) phases of IMSL, as measured by the serial reaction time (SRT) task. Analyses based on response times (RTs) revealed that anodal tDCS over the cerebellum significantly increased sequence-specific learning during acquisition, compared to sham (anodal: M = 38.24 ms, sham: M = 26.78 ms, p = 0.032); did not affect general learning; and significantly slowed overall RTs (anodal: M = 362.03 ms, sham: M = 356.37 ms, p = 0.049). Accuracy-based analyses revealed that anodal tDCS reduced the probability of correct responses occurring in random trials versus sequential trials by 1.17%, p = 0.009, whereas sham tDCS had no effect, p = 0.999. Our finding of enhanced sequence-specific learning, but not general learning, suggests that the cerebellar network not only plays a role in error correction processes, but also serves a sequence-specific function within the integrated motor learning network that connects the basal ganglia and cerebellum.

BDS-3/GNSS Undifferenced Pseudorange and Phase Time-Variant Mixed OSB Considering the Receiver Time-Variant Biases and Its Benefit on Multi-Frequency PPP

The legacy Global Navigation Satellite System (GNSS) satellite clock offsets obtained by the dual-frequency undifferenced (UD) ionospheric-free (IF) model absorb the code and phase time-variant hardware delays, which leads to the inconsistency of the precise satellite clock estimated by different frequencies. The dissimilarity of the satellite clock offsets generated by different frequencies is called the inter-frequency clock bias (IFCB). Estimates of the IFCB typically employ epoch-differenced (ED) geometry-free ionosphere-free (GFIF) observations from global networks. However, this method has certain theoretical flaws by ignoring the receiver time-variant biases. We proposed a new undifferenced model coupled with satellite clock offsets, and further converted the IFCB into the code and phase time-variant mixed observable-specific signal bias (OSB) to overcome the defects of the traditional model and simplify the bias correction process of multi-frequency precise point positioning (PPP). The new model not only improves the mixed OSB performance, but also avoids the negative impact of the receiver time-variant biases on the satellite mixed OSB estimation. The STD and RMS of the original OSB can be improved by 7.5–60.9% and 9.4–66.1%, and that of ED OSB (it can reflect noise levels) can be improved by 50.0–87.5% and 60.0–88.9%, respectively. Similarly, the corresponding PPP performance for using new mixed OSB is better than that of using the traditional IFCB products. Thus, the proposed pseudorange and phase time-variant mixed OSB concept and the new undifferenced model coupled with satellite clock offsets are reliable, applicable, and effective in multi-frequency PPP.

An Optimized SVR Algorithm for Pulse Pile-Up Correction in Pulse Shape Discrimination.

Pulse pile-up presents a significant challenge in nuclear radiation measurements, particularly in neutron-gamma pulse shape discrimination, as it causes pulse distortion and diminishes identification accuracy. To address this, we propose an optimized Support Vector Regression (SVR) algorithm for correcting pulse pile-up. Initially, the Dung Beetle Optimizer (DBO) and Whale Optimization Algorithm (WOA) are integrated to refine the correction process, with performance evaluated using charge comparison methods (CCM) for pulse shape discrimination. Leveraging prior knowledge from simulated data, we further analyze the relationships between various types of pulse pile-ups, including their combinations, inter-peak distances, and the accuracy of corrections. Extensive experiments conducted in a mixed neutron-gamma radiation field using plastic scintillators demonstrate that the proposed method effectively corrects pulse pile-up and accurately discriminates between neutron and gamma. Moreover, our approach significantly improves the fidelity of pulse shape discrimination and enhances the overall reliability of radiation detection systems in high-interference environments.

NEUROPSYCHOLOGICAL INTERVENTION IN DEVELOPMENTAL DISORDERS

There is an increase of children identifi ed with developmental disorders, which is why it is necessary to have knowledge of the neuropsychological and cultural-historical psychological approach, which will allow the specialist to approach the cause of different alterations, expand the diagnostic possibilities and to create intervention programmes. The neuropsychological diagnosis obtained from a qualitative analysis makes it possible for the neuropsychological assessment to consider not only the causes of the clinical picture but also to determine the objectives and methods for neuropsychological correction. One of the main challenges of child neuropsychology consists in elaborating and not selecting the methods of intervention (Solovieva and Quintanar, ). The remediation and teaching programmes are personalized, as they are aimed at functional integration of weak neuropsychological mechanisms by relying on strong mechanisms. The programme contains a particular sequence of stages, in the initial phase the objectives to be developed through the different tasks are explained to the parents, the work agreement is presented and rapport with the child is established. In each of the stages, the child’s motivation, desire and willingness to work on different activities is guaranteed. During the therapy sessions, neuropsychologist provides the child with the necessary physical and verbal guidance. The participation of the family and the social context is fundamental throughout the process of neuropsychological correction, with the objective of improving the child’s quality of life and his or her integral development.

A day-ahead wind speed correction method: Enhancing wind speed forecasting accuracy using a strategy combining dynamic feature weighting with multi-source information and dynamic matching with improved similarity function

Forecasting error of day-ahead wind speed (WS) seriously affects wind power integration and power system security and stability. In this regard, this paper fully considers the spatiotemporal correlation of wind farms (WFs) in different geographical locations, and proposes a day-ahead WS combined correction method that integrates multi-source station dynamic information weighting. Different from the previous WS correction methods, this paper fully considers the dynamic correlation of WS between the WFs, introduces an improved weighted similarity function to screen and dynamically weight the information of WFs with dynamic correlation, and introduces the dynamic weighting feature into the WS correction process. A combined decomposition mechanism is proposed, which combines sequential variational mode decomposition (SVMD) and feature mode decomposition (FMD) models to extract the most relevant trend components and non-stationary components of forecasted and measured WS. A combined correction model is introduced, and a combined architecture of Non-stationary Transformer combined with bidirectional long short-term memory network (Ns-Transformer-BILSTM) is used to correct the stationary WS component. A dynamic matching mechanism of fluctuation components considering improved similarity is proposed for the correction of non-stationary components. The proposed method is applied to several regional WFs in China. The experimental results show that the average correction of NRMSE, NMAE and R can reach 2.4 % ∼ 3.7 %, 2.0 % ∼ 3.0 % and 3.3 % ∼ 9.7 %, respectively. The NRMSE and NMAE corresponding to the corrected WS of certain individual WFs can be reduced by 10 % and 9 %, respectively, and R can be increased by 33 %.

Impact of altimeter-buoy data-pairing methods on the validation of Sentinel-3A coastal significant wave heights

Sea state information is critical for a broad range of human activities (e.g. shipping, marine energy, marine engineering) most of them being concentrated along the coastal zone. Satellite altimeter records of significant wave heights (SWH) represent the largest source of sea state observations available to date. However, the quality of altimeter observations is reduced in the coastal zone due to surface heterogeneity within the radar signal footprint. Major difficulties to assess the performance of coastal altimetry in the coastal zone are the reduced number of valid altimeter records and the increased sea state variability, which have recently fostered the development of new methods to pair and compare nearby altimeter and buoy data. In this study, we use a high-resolution numerical wave model implemented over the European coastal waters in order to characterize the spatial variability of sea states in the proximity of coastal in situ buoys, we explore different model-based data-pairing methods to account for coastal sea state variability and we assess their impact on the validation of Sentinel-3A 20Hz SWH measurements. Three Sentinel-3A processing modes are considered: the pseudo low rate mode processing, the SAR processing and the Low Resolution with Range Migration Correction (LR-RMC) processing. Our results indicate major impacts of data-pairing methods on the Sentinel-3A coastal validation and reveals the contribution of more frequent low SWH conditions, poorly resolved by radar altimeters, in the coastal zone as an additional source of errors in coastal altimetry.

The use of concept maps in nursing/midwifery exam papers and their examination on their feasibility and reliability as assessment tools

BackgroundConcept maps demonstrate relationships between concepts visually, allowing connections to develop the learner's cognition. Despite studies that demonstrate the value of this method, it has still not been adopted in mainstream nursing education as an assessment tool. AimThe aim of this study is to evaluate the use of the concept map as an assessment tool in nursing education. MethodsThis study was conducted following the one-shot experimental design. One exam paper was designed to be given to participants at the final examination of a core shared undergraduate nursing/midwifery module. The target sample of the study were undergraduate first year students (N = 185). Following initial exposure of student nurses/midwives, during the Autumn semester, concept maps were included into the final exam. These were evaluated and compared with another of the most traditional assessment methods, the multiple-choice question type (MCQ). Quantitative statistical analysis of the concept map and MCQ grades were conducted. Statistical tests were used to compare all pairs of both types of papers. ResultsAll paired t-test results were found to be statistically significant and effect size results also supported the statistically significant results. Concept maps' structure allows the assessment of the totality of concepts of a specific area/section of the material. MCQs can assess one aspect/detail of a concept at a time without the limitation to draw material from a specific area/section. When used together, educators can use these different features in assessing student's knowledge/understanding on the totality of taught material. Additional advantage of the concept map is its straightforward, objective and quick correction process. ConclusionThe study provides evidence that the concept map can be a trusted assessment tool for identifying the nursing students' gaps in knowledge and comprehension.

INVESTIGATIONS ON THERMAL PERFORMANCE OF AN ELECTRONIC BOARD USING CONDUCTION-BASED FINITE ELEMENT METHOD WITH A NEW MODELING APPROACH

Electronic systems are used in almost all areas of industry, with an increasing power consumption rate. This trend makes thermal management of electronics compulsory in order for proper operation. Several methods can be employed to examine electronics’ thermal behavior. Conduction-based Finite Element Method (FEM) for heat transfer analysis is one of them; providing accurate solutions within short solution times is one of its outstanding advantages. Nevertheless, the fluid inside or around the system, usually air for electronic systems, is not included directly in the conduction-based FEM analysis model. This is an essential deficiency in terms of solution accuracy. If this drawback is overcome, conduction-based FEM will become a preferred analysis method, especially for transient problems under natural convection. In this study, a conduction-based FEM analysis model of an electronic board with two heat-dissipating components inside an enclosure under transient natural convection was developed. The procedure of the model involves the correction of unknown input parameters. An experimental investigation was performed, the results of which were used as reference values for the correction process. These unknown parameters were determined iteratively. The iteration was continued until the results of the analysis and those of the experiment matched. The difference between the results of the analysis and those of the experiment was less than 2-3°C. Some parametrical thermal investigations were performed on the electronic board using the final analysis model.

Research on signal enhancement and flow rate calculation methods of multi-channel ultrasonic flowmeter

Abstract In the field of drilling, accurate measurement of mud flow helps detect potential leaks or abnormal situations, thereby improving overall safety and preventing accidents from occurring. Traditional contact flow meters require breaking the pipeline before installation, making them difficult to install in underground environments. In addition, the complex composition of underground fluids and their corrosive nature can also lead to unsatisfactory measurement results. Therefore, as a non-invasive flow measurement tool, ultrasonic flowmeter is a better choice. However, the ultrasonic echo signals of current ultrasonic flow meters are susceptible to external interference in actual testing, resulting in a decrease in signal quality and making it impossible to perform accurate detection. This article focuses on the research of ultrasound echo signal processing model, designs a four channel ultrasound transceiver model, improves the wavelet denoising algorithm, designs signal reconstruction and baseline correction processing methods, and proposes a pipeline flow calculation algorithm based on Gaussian numerical integration. This method can greatly improve the quality of ultrasound echo signals and the average accuracy of flow measurement. Finally, relevant testing experiments were conducted, and the results of the final performance measurement showed that the method proposed in this paper improved the average accuracy of the measurement by 5.07%, and the relative error remained at around 2%, with a significant improvement in error rate. Therefore, the method proposed in this article has extremely high accuracy in mud flow measurement.

AI versus human effectiveness in essay evaluation

The evaluation of student essay corrections has become a focal point in understanding the evolving role of Artificial Intelligence (AI) in education. This study aims to assess the accuracy, efficiency, and cost-effectiveness of ChatGPT's essay correction compared to human correction, with a primary focus on identifying and rectifying grammatical errors, spelling, sentence structure, punctuation, coherence, relevance, essay structure, and clarity. The research involves collecting essays from 100 randomly selected university students, covering diverse themes, with anonymity maintained and no prior corrections by humans or AI. An analysis sheet, outlining linguistic and informational elements for evaluation, serves as a benchmark for assessing the quality of corrections made by ChatGPT and humans. The study reveals that ChatGPT excels in fundamental language mechanics, demonstrating superior performance in areas like grammar, spelling, sentence structure, relevance, and supporting evidence. However, thematic consistency remains an area where human evaluators outperform the AI. The findings emphasize the potential for a balanced approach, leveraging both human and AI strengths, for a comprehensive and effective essay correction process.

Feature Vector Effectiveness Evaluation for Pattern Selection in Computational Lithography

Pattern selection is crucial for optimizing the calibration process of optical proximity correction (OPC) models in computational lithography. However, it remains a challenge to achieve a balance between representative coverage and computational efficiency. This work presents a comprehensive evaluation of the feature vectors’ (FVs’) effectiveness in pattern selection for OPC model calibration, leveraging key performance indicators (KPIs) based on Kullback–Leibler divergence and distance ranking. Through the construction of autoencoder-based FVs and fast Fourier transform (FFT)-based FVs, we compare their efficacy in capturing critical pattern features. Validation experimental results indicate that autoencoder-based FVs, particularly augmented with the lithography domain knowledge, outperform FFT-based counterparts in identifying anomalies and enhancing lithography model performance. These results also underscore the importance of adaptive pattern representation methods in calibrating the OPC model with evolving complexities.

Research on the Recognition Method of Tobacco Flue-Curing State Based on Bulk Curing Barn Environment

Curing modulation is one of the important processes in tobacco production, so it is crucial to recognize tobacco flue-curing states effectively and accurately. This study created a dataset of the complete tobacco flue-curing process in a bulk curing barn environment and proposed a lightweight recognition model based on a feature skip connections module. Firstly, the image data was enhanced using a color correction matrix, which was used to recover the true color of the tobacco leaf in order to reduce the misidentification of adjacent states. Secondly, the convolutional neural network model proposed in this paper introduced Spatially Separable convolution to enhance the extraction of tobacco leaf texture features. Then, the standard convolution in Short-Term Dense Concatenate (STDC) was replaced with Depthwise Separable Convolutional blocks with different expansion rates to reduce the number of model parameters and FLOPs (Floating Point Operations Per Second). Finally, the Tobacco Flue-Curing State Recognition Network (TFSNet) was constructed by combining the SimAm attention mechanism. The experimental results showed that the model accuracy was improved by 1.63 percentage points after the color correction process. The recognition accuracy of TFSNet for the seven states of tobacco flue-curing was as high as 98.71%. The number of params and the FLOPs of the TFSNet model were 203,058 and 172.39 M, which were 98.18% and 90.55% lower than that of the ResNet18 model, respectively. The size of the model was 0.78 mb, and the time consumed per frame was only 21 ms. Compared with the mainstream model, TFSNet significantly improved the detection speed while maintaining high accuracy, and it provided effective technical support for the intelligentization of the tobacco flue-curing process.

Phase diagram of the three-dimensional subsystem toric code

Subsystem quantum error-correcting codes typically involve measuring a sequence of noncommuting parity check operators. They can sometimes exhibit greater fault tolerance than conventional codes, which use commuting checks. However, unlike subspace codes, it is unclear if subsystem codes—in particular their advantages—can be understood in terms of ground-state properties of a physical Hamiltonian. In this paper, we address this question for the three-dimensional subsystem toric code (3D STC), as recently constructed by Kubica and Vasmer [], which exhibits single-shot error correction. Motivated by a conjectured relation between single-shot properties and thermal stability, we study the zero- and finite-temperature phases of an associated noncommuting Hamiltonian. By mapping the Hamiltonian model to a pair of 3D Z2 gauge theories coupled by a kinetic constraint, we find various phases at zero temperature, all separated by first-order transitions: There are 3D toric code-like phases with deconfined point-like excitations in the bulk, and there are phases with a confined bulk supporting a 2D toric code on the surface when appropriate boundary conditions are chosen. The latter is similar to the surface topological order present in 3D STC. However, the similarities between the single-shot correction in 3D STC and the confined phases are only partial: they share the same sets of degrees of freedom, but they are governed by different dynamical rules. Instead, we argue that the process of single-shot error correction can more suitably be associated with a path (rather than a point) in the zero-temperature phase diagram, a perspective, which inspires alternative measurement sequences enabling single-shot error correction. Moreover, since none of the above-mentioned phases survives at nonzero temperature, the single-shot error-correction property of the code does not imply thermal stability of the associated Hamiltonian phase. Published by the American Physical Society 2024

The Effectiveness of Temporary Hemiepiphysiodesis for Non-idiopathic Coronal Angular Deformity of the Knee in Children: A Comparison of Hinge Eight-Plate and Traditional Eight-Plate.

Temporary hemiepiphysiodesis (TH) is a very common technique for coronal angular deformity of the knee in children, especially non-idiopathic. However, there is currently a dearth of comparative research on the hinge eight-plate (HEP) and traditional eight-plate (TEP). This study aimed to assess the clinical effectiveness and implant-related complication rates of TH using TEP and HEP for non-idiopathic coronal angular deformity, as well as to identify clinical factors affecting correction velocity. We retrospectively observed a consecutive series of patients with non-idiopathic coronal angular deformity of the knee who underwent TH using HEP or TEP and completed the deformity correction process from July 2016 to July 2022. According to the kind of eight plates, we divided those patients into the HEP group and the TEP treatment group. Relevant clinical factors, including the mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), screw divergence angle (SDA), angle of plate and screw (APS), hinge angle of HEP (HA), and the knee zone location of the lower extremity mechanical axis, were documented. Additionally, deformity correction velocity, complications, and clinical efficacy were assessed. Categorical variables were analyzed using the chi-squared test, Fisher exact test, or Wilcoxon test, while continuous variables were evaluated using the t-test or analysis of variance (ANOVA). There were 29 patients in the HEP treatment group (seven girls and 22 boys) and 33 patients (12 girls and 21 boys) in the TEP treatment group. In all, 91.86% (79/86 knees) of the genu angular deformities were completely corrected, 6.98% (6/86 knees) had the overcorrection condition, and 10.47% (9/86 knees) had screw loosening. The swayback HEP rate was 11.29% (7/62 HEPs), which was related to the screw loosening in the HEP group (p < 0.001). The overall correction velocities and screw divergence angle change speeds in the HEP group were all significantly faster than those in the TEP group (p < 0.05). The initial APS of the HEP implanted was higher than that of TEP (p < 0.01), and multisite changes of APS during deformity correction of the HEP group were smaller than that of the TEP group. HEP proved to be an appropriate device for TH for non-idiopathic coronal angular deformities of the knee with high correction velocity in children. Avoiding the occurrence of the swayback phenomenon may reduce the complications of HEP.

Estimating the rate of failure to notice functionword errors in natural reading.

Skilled readers sometimes fail to notice seemingly obvious errors in text, such as the repetition or omission of a function word or the transposition of two words, suggesting that linguistic knowledge can override bottom-up input at either a perceptual or postperceptual level. The present study investigates the role of this top-down process of error correction in natural reading of extended texts. In previous research, critical sentences have been presented one at a time, and subjects were explicitly tasked with detecting errors. In the present study, each participant read a full newspaper article or pair of articles, with their comprehension tested by multiple choice questions. As a secondary task, participants were also instructed that they should make a mouse click on any errors in the text, without any instruction as to the frequency or nature of any such errors. Each article contained nine intentionally inserted errors involving function words: three repetitions, three omissions, and three transpositions. After removing subjects who did not click on the text at all (leaving n = 165), the median subject made seven clicks, but detected only one of the nine inserted errors. Neither error type nor article type (highly professional vs. amateur) clearly modulated the rate of error detection, though subjects clicked more often overall on the amateur articles. We conclude that previous research has dramatically underestimated the rate at which readers fail to notice these function word errors; in natural reading, they are noticed only rarely. No existing reading model can account for this phenomenon.

Optical Characterization of Coastal Waters with Atmospheric Correction Errors: Insights from SGLI and AERONET-OC

This study identifies the characteristics of water regions with negative normalized water-leaving radiance (nLw(λ)) values in the satellite observations of the Second-generation Global Imager (SGLI) sensor aboard the Global Change Observation Mission–Climate (GCOM-C) satellite. SGLI Level-2 data, along with atmospheric and in-water optical properties measured by the sun photometers in the AErosol RObotic NETwork-Ocean Color (AERONET-OC) from 26 sites globally, are utilized in this study. The focus is particularly on Tokyo Bay and the Ariake Sea, semi-enclosed water regions in Japan where previous research has pointed out the occurrence of negative nLw(λ) values due to atmospheric correction with SGLI. The study examines the temporal changes in atmospheric and in-water optical properties in these two regions, and identifies the characteristics of regions prone to negative nLw(λ) values due to atmospheric correction by comparing the optical properties of these regions with those of 24 other AERONET-OC sites. The time series results of nLw(λ) and the single-scattering albedo (ω(λ)) obtained by the sun photometers at the two sites in Tokyo Bay and Ariake Sea, along with SGLI nLw(λ), indicate the occurrence of negative values in SGLI nLw(λ) in blue band regions, which are mainly attributed to the inflow of absorptive aerosols. However, these negative values are not entirely explained by ω(λ) at 443 nm alone. Additionally, a comparison of in situ nLw(λ) measurements in Tokyo Bay and the Ariake Sea with nLw(λ) values obtained from 24 other AERONET-OC sites, as well as the inherent optical properties (IOPs) estimated through the Quasi-Analytical Algorithm version 5 (QAA_v5), identified five sites—Gulf of Riga, Long Island Sound, Lake Vanern, the Tokyo Bay, and Ariake Sea—as regions where negative nLw(λ) values are more likely to occur. These regions also tend to have lower nLw(λ) values at shorter wavelengths. Furthermore, relatively high light absorption by phytoplankton and colored dissolved organic matter, plus non-algal particles, was confirmed in these regions. This occurs because atmospheric correction processing excessively subtracts aerosol light scattering due to the influence of aerosol absorption, increasing the probability of the occurrence of negative nLw(λ) values. Based on the analysis of atmospheric and in-water optical measurements derived from AERONET-OC in this study, it was found that negative nLw(λ) values due to atmospheric correction are more likely to occur in water regions characterized by both the presence of absorptive aerosols in the atmosphere and high light absorption by in-water substances.