Global Measurements Research Articles

Vertical structure of tropical cyclone precipitation over the North Indian Ocean: a spaceborne precipitation radar perspective

ABSTRACT Spaceborne precipitation radars provide an unprecedented opportunity to study three-dimensional structure of precipitation, particularly over the open ocean where in-situ observations are rather meagre. In this study, instantaneous surface precipitation characteristics and their vertical structures during the tropical cyclones (TCs) over the North Indian Ocean (NIO) between 2014 and 2022 have been analysed using the dual-frequency precipitation radar onboard the Global Precipitation Measurement Core Observatory. Although stratiform precipitation accounts for more than 70% of total TC surface precipitation area, convective precipitation contributes about half of the total TC surface precipitation amount over the NIO. About 90% of stratiform TC precipitation area yields surface precipitation of less than 10 mm/hour. The vertical structures of stratiform and convective TC precipitation vary with surface precipitation intensity and have nearly similar characteristics over both basins of the NIO. This preliminary quantitative TC precipitation analysis would be useful for better understanding of precipitation processes during TCs over the NIO, and for further advancement in numerical models through improved parameterization schemes for TC precipitation forecasting.

Evaluating the diagnostic performance with neurovascular segregation of the retinal nerve fibre layer in glaucoma

Aims/Purpose: To evaluate the diagnostic performance in detecting eyes with glaucoma by segregating the neuronal and vascular components in circumpapillary optical coherence tomography (OCT) and OCT angiography (OCTA) scans.Methods: In this study, 93 participants with glaucoma were age‐ and gender‐matched with normal controls with no ocular diseases. OCT and OCTA volumetric images of one eye from each participant were acquired using a prototype high resolution swept source OCT imaging system (Zeiss PlexElite) using a 6 mm x 6 mm imaging protocol centered at the optic nerve head. Circumpapillary OCT and OCTA images with a diameter of 3.46 mm were subsequently generated. Information from the circumpapillary and enface OCTA images were used to isolate and segregate the vascular components from the circumpapillary retinal nerve fibre layer (RNFL), which was obtained using a deep learning segmentation approach. Thicknesses of the RNFL with and without the vascular components were measured and diagnostic performance was evaluated using area under the receiving operating characteristic curve (AUC) analysis. Both global and quadrant (superior, inferior, nasal and temporal) measurements around the optic nerve head were considered.Results: Imaging data of one eye from 154 healthy and 143 glaucoma participants were acquired. Using only the global RNFL thickness, the detection of glaucoma achieved an AUC of 0.877 ± 0.021. With the vascular components excluded from the global RNFL thickness, an AUC of 0.890 ± 0.020 was obtained. When the vascular and non‐vascular components of the RNFL in the different quadrants were modelled separately, AUC improved to 0.927 ± 0.015, and was found to be significantly higher than the detection of glaucoma using global measures (p < 0.001).Conclusions: Segregation of vascular and non‐vascular components in the retinal nerve fibre layer led to an improvement in glaucoma detection. Further improvements were observed when the contributions of the components in the RNFL quadrants were modelled separately.

Five-Meter Nonmagnetic Telescopic Tubular Mast: Design, Test, and On-Orbit Application

Space deployable masts, as one of the most widely used branches of space deployable structures, can provide driving, positioning, and transmission functions for spacecraft in orbit, which are irreplaceable in complex space activities. The nonmagnetic telescopic tubular mast (NMTTM) is designed and manufactured by the Shenyang Institute of Automation, Chinese Academy of Sciences, aboard the SATech-01 satellite to keep the magnetic probe assembly away from magnetic interference and realize global magnetic field measurement. The NMTTM can withstand complicated vibration and shock during rocket launching in the retracted state of 0.95 m, while it can be stably released and deployed to 5.28 m in orbit. NMTTM was successfully launched into Sun-synchronous orbit on 27 July 2022, fully deployed, and generated the positioning signal after a duration of 19 min and 16 s for the deployment process on 7 November. This paper focuses on the whole process of NMTTM from mission requirements to structure design and manufacture, through to releasing, deployment, and locking technology, environmental simulation tests, up to on-orbit deployment verification, which provides valuable experience for the subsequent development and application of large-scale space deployable masts.

Multi-omics Resources for Understanding Gene Regulation in Response to ER Stress in Plants.

Proteotoxic stress of the endoplasmic reticulum (ER) is a potentially lethal condition that ensues when the biosynthetic capacity of the ER is overwhelmed. A sophisticated and largely conserved signaling, known as the unfolded protein response (UPR), is designed to monitor and alleviate ER stress. In plants, the emerging picture of gene regulation by the UPR now appears to be more complex than ever before, requiring multi-omics-enabled network-level approaches to be untangled. In the past decade, with an increasing access and decreasing costs of next-generation sequencing (NGS) and high-throughput protein-DNA interaction (PDI) screening technologies, multitudes of global molecular measurements, known as omics, have been generated and analyzed by the research community to investigate the complex gene regulation of plant UPR. In this chapter, we present a comprehensive catalog of omics resources at different molecular levels (transcriptomes, protein-DNA interactomes, and networks) along with the introduction of key concepts in experimental and computational tools in data generation and analyses. This chapter will serve as a starting point for both experimentalists and bioinformaticians to explore diverse omics datasets for their biological questions in the plant UPR, with likely applications also in other species for conserved mechanisms.

Oceanic Validation of IMERG-GMI Version 6 Precipitation Using the GPM Validation Network

Abstract NASA’s multisatellite precipitation product from the Global Precipitation Measurement (GPM) mission, the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, is validated over tropical and high-latitude oceans from June 2014 to August 2021. This oceanic study uses the GPM Validation Network’s island-based radars to assess IMERG when the GPM Core Observatory’s Microwave Imager (GMI) observes precipitation at these sites (i.e., IMERG-GMI). Error tracing from the Level 3 (gridded) IMERG V06B product back through to the input Level 2 (satellite footprint) Goddard Profiling Algorithm GMI V05 climate (GPROF-CLIM) product quantifies the errors separately associated with each step in the gridding and calibration of the estimates from GPROF-CLIM to IMERG-GMI. Mean relative bias results indicate that IMERG-GMI V06B overestimates Alaskan high-latitude oceanic precipitation by +147% and tropical oceanic precipitation by +12% with respect to surface radars. GPROF-CLIM V05 overestimates Alaskan oceanic precipitation by +15%, showing that the IMERG algorithm’s calibration adjustments to the input GPROF-CLIM precipitation estimates increase the mean relative bias in this region. In contrast, IMERG adjustments are minimal over tropical waters with GPROF-CLIM overestimating oceanic precipitation by +14%. This study discovered that the IMERG V06B gridding process incorrectly geolocated GPROF-CLIM V05 precipitation estimates by 0.1° eastward in the latitude band 75°N–75°S, which has been rectified in the IMERG V07 algorithm. Correcting for the geolocation error in IMERG-GMI V06B improved oceanic statistics, with improvements greater in tropical waters than Alaskan waters. This error tracing approach enables a high-precision diagnosis of how different IMERG algorithm steps contribute to and mitigate errors, demonstrating the importance of collaboration between evaluation studies and algorithm developers. Significance Statement Evaluation of IMERG’s oceanic performance is very limited to date. This study uses the GPM Validation Network to conduct the first extensive assessment of IMERG V06B at its native resolution over both high-latitude and tropical oceans, and traces errors in IMERG-GMI back through to the input GPROF-CLIM GMI product. IMERG-GMI overestimates tropical oceanic precipitation (+12%) and strongly overestimates Alaskan oceanic precipitation (+147%) with respect to the island-based radars studied. IMERG’s GMI estimates are assessed as these should be the optimal estimates within the multisatellite product due to the GMI’s status as calibrator of the GPM passive microwave constellation.

Analysis of Convective and Stratiform Precipitation Characteristics in Xinjiang, China Based on GPM Dual‐Frequency Precipitation Radar

The spatial distribution of precipitation in Xinjiang, China, is extremely heterogeneous due to its complex subsurface, and microphysical studies of cloud precipitation over Xinjiang are severely constrained by observational means. The Global Precipitation Measurement (GPM) dual‐frequency precipitation radar (DPR) provides improved three‐dimensional observation data of strong and weak precipitation and performs effective observations in alpine mountain regions. Therefore, this study used GPM/DPR Level‐3 data from January 2015 to December 2022 to analyze the convective and stratiform precipitation characteristics over Xinjiang. The results showed that (1) the range of maximum precipitation reflectivity factors (PRF_max) near the ground and at different heights were larger in summer and maximum PRF_max values appeared in areas along the Altai, Tianshan, and Kunlun Mountains and plains on the respective mountain slopes. In summer, the PRF_max of stratiform (convective) precipitation nearsurface ranged from 24 to 34 dBZ (28–40 dBZ). (2) The two types of precipitation exhibited the highest storm top heights in summer, with convective precipitation having higher values than stratiform precipitation and mountainous areas having higher values than the surrounding basins due to the effects of topographic uplift. (3) The value domains of the PRF, particle mass‐weighted diameter (Dm), and particle number concentration for stratiform (convective) precipitation were more concentrated (wider), that is, PRF: 14–30 dBZ (12–40 dBZ), Dm: 0.9–1.4 mm (0.7–2.1 mm), and the particle concentration: 29–35 (24–39). The height of the center of the probability density of each variable was higher in the three major mountain ranges than in the two major basins owing to the influence of topography. PRF increased and then decreased with height. Convective raindrops were in an active state of high concentration and exhibited a large scale in the lower layers, whereas the particle spectral parameters of stratiform precipitation showed a more concentrated and symmetric distribution and insignificant changes with height.

Feasibility and reliability of fetal two dimensional speckle tracking echocardiography at 16 weeks gestational age: A pilot study.

Fetal two-dimensional speckle tracking echocardiography (2D-STE) is an emerging technique for assessing fetal cardiac function by measuring global longitudinal strain. Alterations in global longitudinal strain may serve as early indicator of pregnancy complications, making 2D-STE a potentially valuable tool for early detection. Early detection can facilitate timely interventions to reduce fetal and maternal morbidity and mortality. Therefore, the aim of this study was to investigate the feasibility of performing 2D-STE at 16 weeks gestational age. This pilot study utilized 50 ultrasound clips of the fetal four-chamber view recorded between 15+5 and 16+2 weeks gestational age from a prospective cohort study. A strict protocol assessed three parameters essential for 2D-STE analysis: fetal four-chamber view ultrasound clip quality, region of interest, and frame rates. Two independent researchers measured global longitudinal strain in all adequate fetal four-chamber view ultrasound clips to determine inter- and intra-operator reliability. Out of the 50 ultrasound clips, 37 (74%) were feasible for 2D-STE analysis. The inter-operator reliability for global longitudinal strain measurements of the left and right ventricles was moderate (ICC of 0.64 and 0.74, respectively), while the intra-operator reliability was good (ICC of 0.76 and 0.79, respectively). Our findings demonstrate that fetal 2D-STE analysis at 16 weeks gestational age is feasible when adhering to a strict protocol. However, further improvements are necessary to enhance the inter- and intra-operator reliability of 2D-STE at this gestational age.

The capability of Artificial Neural Networks as a Model for Predicting Total Electron Content (TEC): A Review

The results of investigations from a complete analysis of ANN application on Total Electron Content (TEC) prediction are presented in this paper. TEC is important in defining the ionosphere and has many everyday applications, for example, satellite navigation, time delay and range error corrections for single frequency Global Positioning System (GPS) satellite signal receivers. The total electron content (TEC) in the ionosphere has been measured using GPS. GPS are not installed in every point on the earth to make global TEC measurements possible. As a result, it is crucial to have certain models that can aid to get data from places where there is not any in order to comprehend the global behavior of TEC. Neural Network (NN) models have been shown to accurately anticipate data patterns, including TEC. The capacity of neural networks to represent both linear and nonlinear relationships directly from the data being modeled is what makes them so powerful. The survey from literature reveals that, Levenberg-Marquardt algorithm is preferred and used mostly because of its speed and efficiency during learning process, and that ANN showed a good prediction of TEC compared to the IRI model. As a result, NNs are suitable for forecasting GPS TEC values at various locations if the model's input parameters are well specified.

Transboundary Livestock Network in Africa: How Circulate Pathogens and Where to Act to Prevent the Epizootics Spread?

Objectives: Transboundary animal diseases (TADs) of domestic ruminants are closely linked to livestock movements, consequently, understanding these latter provides information on the pathogen's dissemination pathways. This descriptive study, using the mapping and network analysis (NA) method, aims to characterize the cross-border mobility network of domestic ruminants on the African continent, to understand how it works, to identify the main countries controlling livestock mobility, to deduct their relationships with other countries, and finally, to highlight the articulation points of the network at which actions should be taken to stop the epizootics spread. Methodology: This is a synthetic, descriptive study, whose results make it possible to place it within the framework of epidemiological surveillance with a continental scope, aiming to guide the efforts of the concerned authorities. Based on deep documentary research, a total of 483 transhumant and commercial cross-border movements were identified. These movements were mapped by the geographic information system (GIS) to reconstruct the network of international movements between countries. The most regular movements, numbering 190 and constituting a more stable exchange network over time, were subjected to processing by the NA method, to highlight different indicators that permit the characterization of the network. The results obtained were then compared with health data on the distribution of the five main notifiable animal diseases circulating in the African continent in addition to rinderpest. All analyses were conducted using “R” software. Results: The centrality indicators enabled the identification of the main central countries, including the most active and unavoidable ones that contribute to diseases spread in Africa. They also made it possible to quantify their importance in the influence of movement, while the global measurements and network cohesion parameters showed that the latter is vulnerable to the spread of epizootics. This study revealed a strong livestock exchange relationship between 25 African countries, extending from nations on the Atlantic Ocean coasts to those of the Indian Ocean ones, which were found to be the most vulnerable to the establishment of contagious diseases. Different communities of countries whose livestock movements appear to be very cohesive and which presage significant mutual contamination have been highlighted. Certain African countries have proven to be key points in the articulation of flows between different countries and different regions and contribute significantly to the dissemination of diseases between the different regions of the continent. Accordingly, key countries where actions should be taken to stop the epizootics spread were identified. Conclusion: The results allowed a better understanding of diseases diffusion pathways through livestock movements across Africa and highlighted the main movement focal points which represent a high-risk of diseases spread, as well as the capacity to influence their diffusion through the control of the animal’s movement or the deployment of prophylactic actions at their level.

Performance of the PERSIANN Family of Products over the Mekong River Basin and Their Application for the Analysis of Trends in Extreme Precipitation Indices

Near-real-time satellite precipitation estimation is indispensable in areas where ground-based measurements are not available. In this study, an evaluation of two near-real-time products from the Center for Hydrometeorology and Remote Sensing at the University of California, Irvine—PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System) and PDIR-Now (PERSIANN-Dynamic Infrared Rain Rate near-real-time)—were compared to each other and evaluated against IMERG Final (Integrated Multi-satellite Retrievals for Global Precipitation Measurement—Final Run) from 2015 to 2020 over the Mekong River Basin and Delta (MRB) using a spatial resolution of 0.1∘ by 0.1∘ and at a daily scale. PERSIANN-CDR (PERSIANN-Climate Data Record) was also included in the evaluation but was not compared against the real-time products. In this evaluation, PDIR-Now exhibited a superior performance to that of PERSIANN-CCS, and the performance of PERSIANN-CDR was deemed satisfactory. The second part of the study entailed performing a Mann–Kendall trend test of extreme precipitation indices using 38 years of PERSIANN-CDR data over the MRB. This annual trend analysis showed that extreme precipitation over the 95th and 99th percentiles has decreased over the Upper Mekong River Basin, and the consecutive number of wet days has increased over the Lower Mekong River Basin.

Structural behaviour and resistances of high strength concrete-filled stainless steel tube (HCFSST) beam-columns

This paper reports experimental and numerical investigations into the structural behaviour and resistances of high strength concrete-filled stainless steel tube (HCFSST) beam-columns under combined compression and bending. An experimental investigation was conducted on sixteen HCFSST beam-columns specimens fabricated from stainless steel tubes with two cross-section sizes and high strength concretes with four material grades, and included concrete cylinder tests, tensile coupon tests, initial global geometric imperfection measurements and eccentric compression tests. The test setups and procedures were fully reported and the experimental observations were discussed and analysed in detail. It was found that the plane cross-section assumption was valid for eccentrically loaded HCFSST sections and the lateral deflection distribution patterns for HCFSST beam-columns were approximately half-sine wave shapes. The test results were used in a subsequent numerical investigation for the validation of finite element models, which were then employed to conduct parametric studies to generate additional numerical data over a wide range of cross-section dimensions, member lengths and loading combinations. Based on the experimental and numerical results, the relevant design rules, as set out in the European code, American specification and Australian/New Zealand standard, were evaluated for their applicability to HCFSST beam-columns. The evaluation results revealed that the European code provided accurate but scattered failure load predictions when used for HCFSST beam-columns, while the American specification and Australian/New Zealand standard resulted in conservative and scattered failure load predictions.

A Pressure Drop and Particle Image Velocimetry Investigation into Depressurized Loss-of-Coolant Accident Parameters Applied to Packed Beds with an Aspect Ratio of D/dp = 4.4

New developments in porous media modeling have allowed for a new opportunity to implement experimental data for validation and verification. This includes velocity measurements using particle image velocimetry and global pressure drop measurements that are used to produce pressure drop correlations. We conducted such experiments on two very similar facilities of packed spheres by the authors of this paper. The results from the measurements are presented in this paper as a complete experimental study of a packed bed of smooth spheres through a two-prong approach. First, a set of global pressure drop correlations are validated with experimental data and presented as a function of porous Reynolds numbers. Second, the local velocity measurements from three depths spanning 2.4 sphere diameters are presented and further analyzed through the use of a normalized probability distribution function of the time-resolved velocity field. The conclusion of this paper is a suggestion for the results to be used in the creation or validation of computational fluid dynamics porous media models in the measured flow regimes for a packed bed of smooth spheres with an aspect ratio between the sphere diameter and the empty column diameter of 4.4.

Error modeling and hierarchical Bayesian fusion for spaceborne and ground radar rainfall data

The optimal fusion of multisource rainfall data can improve the accuracy and resolution of a posteriori estimates, which is beneficial for hydrological and meteorological applications. In this study, the errors of ground-based dual-polarization radar (GR) and dual-frequency precipitation radar (DPR) on global precipitation measurement (GPM) satellite rainfall estimation were modeled, and a hierarchical Bayesian (HB) framework was developed for GR and DPR rainfall data fusion. According to the matched optimal estimated GR rainfall and rain gauge data, the GR rainfall error was analyzed, and the error variance varying with rain type and intensity was described and modeled. The rain types were classified based on disdrometer and dual-polarization radar data. By comparing the DPR rainfall product with GR rainfall, the DPR rainfall error was divided into systematic and random errors. The systematic error was linearly fitted, and the probability distributions for the random error and the variable error parameters were analyzed and modeled. Because the parameters for GR and DPR rainfall errors varied with rain type and intensity, we developed a HB fusion approach considering the varying parameters in rainfall error modeling. The performance of the fusion algorithm was evaluated using matched GR and DPR cases, which showed that the HB fusion can effectively improve the consistency between the original DPR rainfall product and rain gauge data, reducing the relative bias by an average of 30% and improving the correlation by an average of 20%. Compared with the conventional Bayesian (CB) fusion algorithm, which is based on overall error modeling, the HB fusion results can improve the root mean square error by an average of 24% and relative bias by 14%.

On the reliability of 12 high-resolution precipitation products for process-based hydrological modeling in China

Numerous satellite- and gauge-based precipitation products (SBPs/GBPs) have emerged in recent decades, providing unprecedented opportunities for process-based hydrological modeling. However, their reliability in high-resolution hydrological modeling at continental scales, especially for variables other than streamflow, remains to be investigated. Factors influencing their hydrological performance (e.g., catchment sizes, precipitation products’ spatial resolution and raw observation information) are also under debate. Here, we provide a comprehensive analysis of the hydrological reliability of 12 state-of-the-art precipitation datasets over China using a process-based land surface model at 0.125° resolution. Simulations driven by different precipitation products are evaluated across ∼ 200 basins with different catchment sizes. Results show that all simulations well reproduce the streamflow, soil moisture, evapotranspiration, and snow-depth at monthly timescale. None of the precipitation products provides best results for all variables, but the gauge-based and infrared-microwave-merged satellite products are superior to the infrared satellite products. The gauge-based regional precipitation product based on the 0.25° China precipitation dataset and the 6-km China Land Data Assimilation System (CN051_CLDAS) provides the best performance generally, followed by two global precipitation products from the Global Precipitation Climatology Centre (GPCC V2022) and the Global Precipitation Measurement Integrated Multi-satellite Retrievals (IMERGE-F V6). However, the advantages of CLDAS_CN051 and GPCC V2022 against satellite-based precipitation products are scale-dependent and tend to disappear over large-scale catchments (>106 km2). The spatial resolutions of precipitation products show no relationship with their hydrological performance, but the number of stations used to generate/bias-correct the precipitation is positively correlated with the performance of streamflow and soil moisture simulations. Differences among the climatology of terrestrial water-cycle components caused by using different precipitation products are notable and tend to increase over the dry and cold regions. Snow depth is the variable most sensitive to precipitation datasets, followed by runoff, ET, and soil moisture. This study suggests that using more station observations is more important than increasing spatial resolutions to enhance the applications of precipitation products in high-resolution hydrological modeling.

Evaluation of present-day extreme precipitation over the United States: an inter-comparison of convection and dynamic permitting configurations of E3SMv1

Accurate simulation of the present-day characteristics of mean and extreme precipitation at regional scales remains a challenge for Earth system models, which is due in part to deficiencies in model physics such as convective parameterization (CP), and coarse resolution. High horizontal resolution (HR, ∼25 km) and multiscale modeling framework (MMF, i.e. replacing conventional CP with embedded km-scale cloud-resolving models) are two promising directions that could help improve the interaction between subgrid-scale physical processes and large-scale climate. Here, we evaluate simulated extreme precipitation over the United States (US) across three configurations (i.e. low-resolution [LR], HR, and MMF) of the Energy Exascale Earth System Model (E3SMv1) and intercompare them against two gridded observation datasets (climate prediction center daily US precipitation and integrated multi-satellite retrievals for global precipitation measurement). We assess the model’s ability to simulate very heavy seasonal precipitation (illustrated by the difference between the 99th and 90th percentile values) as well as the spatial distributions of several extreme precipitation indices defined by the expert team on climate change detection and indices. Our results show that both the dry (i.e. consecutive dry days (CDD)) and wet (i.e. consecutive wet days, maximum 5 day precipitation, and very wet days) extremes evaluated herein show some improvement as well as degradation with MMF and HR relative to LR. These results vary across seasons and US subregions. For instance, only the very heavy precipitation of winter is improved with MMF and HR. Both configurations alleviate the well-known drizzling bias evident in LR across both winter and summer in many parts of the US, largely due to the overall improvement in intensity and frequency of precipitation. Additionally, our results suggest that while E3SMv1-MMF has higher intensity rates when it does rain, it has too many CDD during the summer, contributing to a low mean precipitation bias.

Design, Fabrication, and Characterization of a Novel Optical Six-Axis Distributed Force and Displacement Tactile Sensor for Dexterous Robotic Manipulation.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based six-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate the local XYZ force and displacement at ten distinct locations and provide the global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of the individual sensing units that form the overall sensor, providing distributed six-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over a local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y, and Z axes is 56.70 μm, 50.18 μm, and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5 mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty, and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm, and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task, which generated changing global forces and torques.

Global corporate reputation: a projective qualitative approach from a customer perspective

Purpose The purpose of this research is to extend the results of previous studies regarding corporate reputation scales and identify new and specific items relevant for studying global corporate reputation from a customer’s point of view. Design/methodology/approach This research was based on the qualitative projective “Album on Line” (AOL) technique. The authors used a sample of 12 French consumers distributed equally between affective and cognitive scenarios. An individual-difference multidimensional scaling approach (INDSCAL) was applied to display the overall semantic space among generated items. Findings The exploratory AOL approach generated 62 items related to both cognitive and affective orientations characterizing online and offline corporate reputation. The results uncovered six semantic clusters for each scenario. All in all, seven new items could be added in the process of building a new global corporate reputation measurement scale by adding: avant-garde, singularity, exclusivity, savings, return policy, freeness and speed. Research limitations/implications This research makes it possible to propose a new global corporate reputation measurement scale with sound psychometric properties. This scale will be adapted for click and mortars and pure players. This paper unlocks future perspectives by suggesting a causal model that integrates online corporate reputation and its main antecedents and consequences. Practical implications From a managerial perspective, this research offers insights to managers with the main orientations surrounding the components of global corporate reputation. Moreover, the AOL mappings delineate which quadrants the managers would like to be fitted into or avoid, and hence define more precisely which key elements should be stressed or discarded. Originality/value This research outlines AOL, an original qualitative projective technique that can be used to understand customers’ thoughts, which are stocked and collected as images. Moreover, this research intends to analyze the gathered data using both INDSCAL and fuzzy k-means cluster analysis to reduce conventional biases related to subjectivity.

An statistical model for the short-term albedo estimation applied to PV bifacial modules

Albedo estimation is an essential input parameter for bifacial PV modules. However, there was no clear agreement on which albedo values should be used and how they should be measured, either with satellite measurements or using onsite measurements which can be obtained from nearby meteorological stations. Since long-term measurements are not always available for new PV system locations, short-term albedo measurements are also used as input parameters in PV system performance estimation models. Short-term albedo presents high variability due to factors such as weather, seasonality or changes in the surrounding surface among others. In addition, apparently random albedo variations of 60% can be observed, even during consecutive days or within the same day. Therefore, this study presents a two-parameter exponential model that modelates the albedo data statistical distribution with an error of less than 5% in all cases and from which it is possible to determine the reliability of the obtained data. This model has been evaluated at a set of locations, with different surface types and climates, and assessed using onsite and satellite data. The impact of the methodology used to estimate the albedo data uncertainty and its reliability has also been studied as a function of several parameters such as the global horizontal irradiance and measurement time, allowing the process optimization and enhancing its reliability.

The impact of Indian radar and lightning data assimilation on the short‐range forecasts of heavy rainfall events

AbstractThe accurate prediction of high‐impact weather systems using cloud‐resolving models is still a challenge among researchers. This study evaluates the consistency of the combination of the three‐dimensional variational technique within the Gridpoint Statistical Interpolation assimilation system (GSI‐3DVAR) and nudging in the same modelling system on short‐range forecasts of three heavy rainfall events from the southwest monsoon season of 2021 over the Indian subcontinent. Three experiments have been conducted (i) control (CNTL): assimilated conventional and satellite observations; (ii) radar and lightning data assimilation (RLDA): assimilated radar reflectivity and lightning proxy reflectivity data along with all observations used in CNTL; and (iii) lightning data assimilation (LDA): same as RLDA but without the assimilation of radar data; particularly done to test the impact of assimilation of only lightning data. The model‐simulated rainfall is evaluated by using the Integrated Multi‐Satellite Retrievals (IMERG) for Global Precipitation Measurement (GPM IMERG) rainfall data. The intercomparison of LDA and RLDA for event 1 highlighted that both represent the convective regions reasonably better than CNTL, but RLDA outperforms LDA and thus further assimilation experiments are done with RLDA. RLDA provided reasonably accurate forecasts compared to CNTL, which is evident in the spatial distribution of rainfall and area‐averaged three‐hourly accumulated rainfall. Verification metrics for the three selected heavy rainfall events reveal that an optimal forecast performance (especially in the first six hours of free forecast) is obtained by the simulation with assimilation of radar and lightning data during the pre‐forecast period, through correcting the position and timing of convective centres. The probability of detection (POD) values are higher for light rainfall categories than for the heavy rain categories. POD values were higher in RLDA than CNTL throughout simulation for all three events. For all these three selected events, fractions skill scores (FSS) of RLDA are always better than CNTL with different neighbourhood sizes for different threshold values throughout the forecast period.

Aerosol effects on the three-dimensional structure of organized precipitation systems over Beijing-Tianjin-Hebei region in summer

Aerosol effects on organized precipitation systems (PSs) over Beijing-Tianjin-Hebei (BTH) region are investigated using 6 years of Global Precipitation Measurement (GPM) observations. An auto-clustering algorithm was used to identify local-scale PSs under different aerosol loading conditions and to quantify their three-dimensional structure properties. The general characteristics of PSs show a non-monotonic trend with increasing aerosol optical depth (AOD). The near surface rain rate, the maximum radar reflectivity, the horizontal precipitation area and the vertical extension of PSs decrease with increasing AOD when aerosol loading is low. However, for higher aerosol loadings, the precipitation area first increases and then decreases with increasing AOD. By constraining the variations of meteorology conditions and by calculating the partial correlations, aerosol effects rather than meteorology effects are most likely the major causes for the observed changes of PSs. One possible explanation is that the changes of proportions of different aerosol types with increasing AOD have different mechanisms for affecting the macro-physical and micro-physical properties of PSs. The findings provide a valuable insight into how aerosols affect the three-dimensional structure of local-scale PSs over a region with complex aerosol composition.