Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China

This study evaluated and intercompared seven near-real-time (NRT) versions of satellite-based precipitation products (SPPs) with latencies of less than one day, including GSMaP-NRT, GSMaP-Gauge-NRT, GSMaP-NOW, IMERG-Early, IMERG-Late, TMPA 3B42RT, and PERSIANN-CCS for wet seasons from 2008 to 2019 in a typical middle–high latitude temperate monsoon climate basin, namely, the Nierji Basin in China, in four aspects: flood sub-seasons, rainfall intensities, precipitation events, and hydrological utility. Our evaluation shows that the cell-scale and area-scale intercomparison ranks of NRT SPPs are similar in these four aspects. The performances of SPPs at the areal scale, at the event scale, and with light magnitude are better than those at the cell scale, at the daily scale, and with heavy magnitude, respectively. Most SPPs are similar in terms of their Pearson Correlation Coefficient (CC). The main difference between SPPs is in terms of their root-mean-square error (RMSE). The worse performances of TMPA 3B42RT are mainly caused by the poor performances during main flood seasons. The worst performances of PERSIANN-CCS are primarily reflected by the lowest CC and the underestimation of precipitation. Though GSMaP-NOW has the highest RMSE and overestimates precipitation, it can reflect the precipitation variation, as indicated by the relatively high CC. The differences among SPPs are more significant in pre-flood seasons and less significant in post-flood seasons. These results can provide valuable guidelines for the selection, correction, and application of NRT SPPs and contribute to improved insight into NRT-SPP retrieval algorithms.

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A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0070.1 ◽

2019 ◽

Vol 20 (5) ◽

pp. 999-1014 ◽

Cited By ~ 9

Author(s):

Stephen B. Cocks ◽

Lin Tang ◽

Pengfei Zhang ◽

Alexander Ryzhkov ◽

Brian Kaney ◽

...

Keyword(s):

Real Time ◽

Heavy Precipitation ◽

Estimation Algorithm ◽

Differential Phase ◽

Specific Attenuation ◽

Quantitative Precipitation Estimation ◽

Precipitation Estimation ◽

Bias Ratio ◽

Using Data ◽

Precipitation Events

Abstract The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.

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An Improved Multipath Mitigation Method and Its Application in Real-Time Bridge Deformation Monitoring

Remote Sensing ◽

10.3390/rs13122259 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2259

Author(s):

Ruicheng Zhang ◽

Chengfa Gao ◽

Qing Zhao ◽

Zihan Peng ◽

Rui Shang

Keyword(s):

Real Time ◽

Sampling Rate ◽

Threshold Value ◽

Deformation Monitoring ◽

Success Rates ◽

Multipath Mitigation ◽

Mode Decomposition ◽

Observation Noise ◽

Original Observation ◽

Better Than

A multipath is a major error source in bridge deformation monitoring and the key to achieving millimeter-level monitoring. Although the traditional MHM (multipath hemispherical map) algorithm can be applied to multipath mitigation in real-time scenarios, accuracy needs to be further improved due to the influence of observation noise and the multipath differences between different satellites. Aiming at the insufficiency of MHM in dealing with the adverse impact of observation noise, we proposed the MHM_V model, based on Variational Mode Decomposition (VMD) and the MHM algorithm. Utilizing the VMD algorithm to extract the multipath from single-difference (SD) residuals, and according to the principle of the closest elevation and azimuth, the original observation of carrier phase in the few days following the implementation are corrected to mitigate the influence of the multipath. The MHM_V model proposed in this paper is verified and compared with the traditional MHM algorithm by using the observed data of the Forth Road Bridge with a seven day and 10 s sampling rate. The results show that the correlation coefficient of the multipath on two adjacent days was increased by about 10% after residual denoising with the VMD algorithm; the standard deviations of residual error in the L1/L2 frequencies were improved by 37.8% and 40.7%, respectively, which were better than the scores of 26.1% and 31.0% for the MHM algorithm. Taking a ratio equal to three as the threshold value, the fixed success rates of ambiguity were 88.0% without multipath mitigation and 99.4% after mitigating the multipath with MHM_V. The MHM_V algorithm can effectively improve the success rate, reliability, and convergence rate of ambiguity resolution in a bridge multipath environment and perform better than the MHM algorithm.

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Validation of CHIRPS Precipitation Estimates over Taiwan at Multiple Timescales

Remote Sensing ◽

10.3390/rs13020254 ◽

2021 ◽

Vol 13 (2) ◽

pp. 254 ◽

Cited By ~ 1

Author(s):

Jie Hsu ◽

Wan-Ru Huang ◽

Pin-Yi Liu ◽

Xiuzhen Li

Keyword(s):

Annual Cycle ◽

Interannual Variation ◽

Winter Precipitation ◽

Monthly Precipitation ◽

Precipitation Estimation ◽

Precipitation Estimates ◽

Precipitation Variation ◽

Global Precipitation ◽

Multiple Timescale ◽

Better Than

The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which incorporates satellite imagery and in situ station information, is a new high-resolution long-term precipitation dataset available since 1981. This study aims to understand the performance of the latest version of CHIRPS in depicting the multiple timescale precipitation variation over Taiwan. The analysis is focused on examining whether CHIRPS is better than another satellite precipitation product—the Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM) final run (hereafter IMERG)—which is known to effectively capture the precipitation variation over Taiwan. We carried out the evaluations made for annual cycle, seasonal cycle, interannual variation, and daily variation during 2001–2019. Our results show that IMERG is slightly better than CHIRPS considering most of the features examined; however, CHIRPS performs better than that of IMERG in representing the (1) magnitude of the annual cycle of monthly precipitation climatology, (2) spatial distribution of the seasonal mean precipitation for all four seasons, (3) quantitative precipitation estimation of the interannual variation of area-averaged winter precipitation in Taiwan, and (4) occurrence frequency of the non-rainy grids in winter. Notably, despite the fact that CHIRPS is not better than IMERG for many examined features, CHIRPS can depict the temporal variation in precipitation over Taiwan on annual, seasonal, and interannual timescales with 95% significance. This highlights the potential use of CHIRPS in studying the multiple timescale variation in precipitation over Taiwan during the years 1981–2000, for which there are no data available in the IMERG database.

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Age Prediction of Human Based on DNA Methylation by Blood Tissues

Genes ◽

10.3390/genes12060870 ◽

2021 ◽

Vol 12 (6) ◽

pp. 870

Author(s):

Jiansheng Zhang ◽

Hongli Fu ◽

Yan Xu

Keyword(s):

Dna Methylation ◽

Pearson Correlation ◽

Close Correlation ◽

Gradient Boosting ◽

Tissue Samples ◽

Regression Methods ◽

Cpg Sites ◽

Testing Dataset ◽

Age Related ◽

Better Than

In recent years, scientists have found a close correlation between DNA methylation and aging in epigenetics. With the in-depth research in the field of DNA methylation, researchers have established a quantitative statistical relationship to predict the individual ages. This work used human blood tissue samples to study the association between age and DNA methylation. We built two predictors based on healthy and disease data, respectively. For the health data, we retrieved a total of 1191 samples from four previous reports. By calculating the Pearson correlation coefficient between age and DNA methylation values, 111 age-related CpG sites were selected. Gradient boosting regression was utilized to build the predictive model and obtained the R2 value of 0.86 and MAD of 3.90 years on testing dataset, which were better than other four regression methods as well as Horvath’s results. For the disease data, 354 rheumatoid arthritis samples were retrieved from a previous study. Then, 45 CpG sites were selected to build the predictor and the corresponded MAD and R2 were 3.11 years and 0.89 on the testing dataset respectively, which showed the robustness of our predictor. Our results were better than the ones from other four regression methods. Finally, we also analyzed the twenty-four common CpG sites in both healthy and disease datasets which illustrated the functional relevance of the selected CpG sites.

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The Effectiveness of Multi-Label Classification and Multi-Output Regression in Social Trait Recognition

Sensors ◽

10.3390/s21124127 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4127

Author(s):

Will Farlessyost ◽

Kelsey-Ryan Grant ◽

Sara R. Davis ◽

David Feil-Seifer ◽

Emily M. Hand

Keyword(s):

Social Interactions ◽

First Impressions ◽

Social Traits ◽

Judicial Proceedings ◽

Facial Attributes ◽

Future Work ◽

Automated Methods ◽

Insight Into ◽

Social Trait ◽

Better Than

First impressions make up an integral part of our interactions with other humans by providing an instantaneous judgment of the trustworthiness, dominance and attractiveness of an individual prior to engaging in any other form of interaction. Unfortunately, this can lead to unintentional bias in situations that have serious consequences, whether it be in judicial proceedings, career advancement, or politics. The ability to automatically recognize social traits presents a number of highly useful applications: from minimizing bias in social interactions to providing insight into how our own facial attributes are interpreted by others. However, while first impressions are well-studied in the field of psychology, automated methods for predicting social traits are largely non-existent. In this work, we demonstrate the feasibility of two automated approaches—multi-label classification (MLC) and multi-output regression (MOR)—for first impression recognition from faces. We demonstrate that both approaches are able to predict social traits with better than chance accuracy, but there is still significant room for improvement. We evaluate ethical concerns and detail application areas for future work in this direction.

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Acoustic-Prosodic and Lexical Cues to Deception and Trust: Deciphering How People Detect Lies

Transactions of the Association for Computational Linguistics ◽

10.1162/tacl_a_00311 ◽

2020 ◽

Vol 8 ◽

pp. 199-214

Author(s):

Xi (Leslie) Chen ◽

Sarah Ita Levitan ◽

Michelle Levine ◽

Marko Mandic ◽

Julia Hirschberg

Keyword(s):

Deception Detection ◽

Human Perception ◽

Lie Detection ◽

Challenging Problem ◽

Cues To Deception ◽

Lexical Cues ◽

Insight Into ◽

Large Corpus ◽

Better Than

Humans rarely perform better than chance at lie detection. To better understand human perception of deception, we created a game framework, LieCatcher, to collect ratings of perceived deception using a large corpus of deceptive and truthful interviews. We analyzed the acoustic-prosodic and linguistic characteristics of language trusted and mistrusted by raters and compared these to characteristics of actual truthful and deceptive language to understand how perception aligns with reality. With this data we built classifiers to automatically distinguish trusted from mistrusted speech, achieving an F1 of 66.1%. We next evaluated whether the strategies raters said they used to discriminate between truthful and deceptive responses were in fact useful. Our results show that, although several prosodic and lexical features were consistently perceived as trustworthy, they were not reliable cues. Also, the strategies that judges reported using in deception detection were not helpful for the task. Our work sheds light on the nature of trusted language and provides insight into the challenging problem of human deception detection.

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Exploring genomes with a game engine

Faraday Discussions ◽

10.1039/c3fd00152k ◽

2014 ◽

Vol 169 ◽

pp. 443-453 ◽

Cited By ~ 3

Author(s):

Jeremiah J. Shepherd ◽

Lingxi Zhou ◽

William Arndt ◽

Yan Zhang ◽

W. Jim Zheng ◽

...

Keyword(s):

Real Time ◽

Video Game ◽

Linear Structure ◽

Structural Data ◽

Game Engine ◽

3D Genome ◽

Genome Viewer ◽

A Genome ◽

Visualization Techniques ◽

Insight Into

More and more evidence indicates that the 3D conformation of eukaryotic genomes is a critical part of genome function. However, due to the lack of accurate and reliable 3D genome structural data, this information is largely ignored and most of these studies have to use information systems that view the DNA in a linear structure. Visualizing genomes in real time 3D can give researchers more insight, but this is fraught with hardware limitations since each element contains vast amounts of information that cannot be processed on the fly. Using a game engine and sophisticated video game visualization techniques enables us to construct a multi-platform real-time 3D genome viewer. The game engine-based viewer achieves much better rendering speed and can handle much larger amounts of data compared to our previous implementation using OpenGL. Combining this viewer with 3D genome models from experimental data could provide unprecedented opportunities to gain insight into the conformation–function relationships of a genome.

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Assessment of Near-Real-Time Satellite Precipitation Products from GSMaP in Monitoring Rainfall Variations over Taiwan

Remote Sensing ◽

10.3390/rs13020202 ◽

2021 ◽

Vol 13 (2) ◽

pp. 202

Author(s):

Wan-Ru Huang ◽

Pin-Yi Liu ◽

Jie Hsu ◽

Xiuzhen Li ◽

Liping Deng

Keyword(s):

Real Time ◽

Complex Terrain ◽

Daily Rainfall ◽

Rainfall Estimation ◽

Rainfall Events ◽

Satellite Precipitation ◽

Different Seasons ◽

Daily Scale ◽

Rainfall Variations ◽

Southwestern Taiwan

This study assessed four near-real-time satellite precipitation products (NRT SPPs) of Global Satellite Mapping of Precipitation (GSMaP)—NRT v6 (hereafter NRT6), NRT v7 (hereafter NRT7), Gauge-NRT v6 (hereafter GNRT6), and Gauge-NRT v7 (hereafter GNRT7)— in representing the daily and monthly rainfall variations over Taiwan, an island with complex terrain. The GNRT products are the gauge-adjusted version of NRT products. Evaluations for warm (May–October) and cold months (November–April) were conducted from May 2017 to April 2020. By using observations from more than 400 surface gauges in Taiwan as a reference, our evaluations showed that GNRT products had a greater error than NRT products in underestimating the monthly mean rainfall, especially during the warm months. Among SPPs, NRT7 performed best in quantitative monthly mean rainfall estimation; however, when examining the daily scale, GNRT6 and GNRT7 were superior, particularly for monitoring stronger (i.e., more intense) rainfall events during warm and cold months, respectively. Spatially, the major improvement from NRT6 to GNRT6 (from NRT7 to GNRT7) in monitoring stronger rainfall events over southwestern Taiwan was revealed during warm (cold) months. From NRT6 to NRT7, the improvement in daily rainfall estimation primarily occurred over southwestern and northwestern Taiwan during the warm and cold months, respectively. Possible explanations for the differences between the ability of SPPs are attributed to the algorithms used in SPPs. These findings highlight that different NRT SPPs of GSMaP should be used for studying or monitoring the rainfall variations over Taiwan for different purposes (e.g., warning of floods in different seasons, studying monthly or daily precipitation features in different seasons, etc.).

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Evaluation of IMERG Level-3 Products in Depicting the July to October Rainfall over Taiwan: Typhoon Versus Non-Typhoon

Remote Sensing ◽

10.3390/rs13040622 ◽

2021 ◽

Vol 13 (4) ◽

pp. 622

Author(s):

Wan-Ru Huang ◽

Pin-Yi Liu ◽

Ya-Hui Chang ◽

Cheng-An Lee

Keyword(s):

Real Time ◽

Tropical Rainfall Measuring Mission ◽

Temporal Variations ◽

Rain Gauge ◽

Advantages And Disadvantages ◽

Level 3 ◽

Spatio Temporal ◽

Typhoon Season ◽

Early Late ◽

Better Than

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.

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The Military Physician in Captivity

International Review of the Red Cross ◽

10.1017/s0020860400062720 ◽

1969 ◽

Vol 9 (99) ◽

pp. 295-303

Author(s):

E. Reginato

Keyword(s):

Medical Officer ◽

Red Cross ◽

Prisoner Of War ◽

Geneva Conventions ◽

Peace And Justice ◽

In Captivity ◽

Military Physician ◽

The Military ◽

Insight Into ◽

Better Than

In his introductory address at the third International Refresher Course for Junior Medical Officers, Dr. H. Meuli, member of the ICRC, said “No one knows war better than the military medical officer, nor measures its horror, nor hates it more. No one has greater insight into war to enable him to take a stand for peace and against war”. From its very beginnings the Red Cross has been linked to medicine; it was the ICRC which obtained for doctors the means of exercising their profession in war, which are laid down in the Geneva Conventions.It therefore seems appropriate to quote extensively from a communication submitted at the Course by an Italian doctor, bearing moving testimony to the difficulties facing the medical officer, the noble character of his mission and the principles underlying his activity in the prisoner of war camp. These principles were summed up in his conclusion : “Like peace and justice, medicine loses its significance if not accompanied by charity. If it is to stay universal, it must not lose its humanity”. (Ed.).

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