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Peng-Qi Huang, Yuan-Zheng Lu, and Sheng-Qi Zhou

Abstract

A new method is developed to identify the mixed layer depth (MLD) from individual temperature or density profiles. A relative variance profile is obtained that is the ratio between the standard deviation and the maximum variation of the temperature (density) from the sea surface, and the depth of the minimum relative variance is defined as the MLD. The new method is robust in finding the MLD under the influence of random noise (noise level ≤ 5%). A comparison with other available methods, which include the threshold (difference, difference interpolation, gradient, and hybrid methods) and objective (curvature and maximum angle methods) methods, is carried out using the World Ocean Circulation Experiment (WOCE) data. It is found that for a variety of depth sampling resolutions ranging from 0.04 to 25 dbar, the new method and the difference-interpolation method predict MLD values that are closer to the visually inspected ones than those by other methods. Moreover, the quality index (QI) of the MLD that is determined by the new method is the highest when compared with those of the available methods. Also, the application of the new method on the WOCE global dataset yields 94% of MLD values with , substantially higher than those (≤86%) of other methods. Ultimately, it is found that the new method determines very similar MLD values when applied to temperature or density profiles globally because it identifies the base of the mixed layer rather than the uppermost depth of the thermocline. This unique advantage makes the new method applicable in many cases, especially when the density profile is unavailable.

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Chunlüe Zhou, Kaicun Wang, and Dan Qi
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Chunlüe Zhou, Kaicun Wang, Dan Qi, and Jianguo Tan
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Wei Qi, Chi Zhang, Guangtao Fu, Huicheng Zhou, and Junguo Liu

Abstract

This study develops a new variance-based uncertainty assessment framework to investigate the individual and combined impacts of various uncertainty sources on future extreme floods. The Long Ashton Research Station Weather Generator (LARS-WG) approach is used to downscale multiple general circulation models (GCMs), and the dynamically dimensioned search approximation of uncertainty approach is used to quantify hydrological model uncertainty. Extreme floods in a region in northeastern China are studied for two future periods: near term (2046–65) and far term (2080–99). Six GCMs and three emission scenarios (A1B, A2, and B1) are used. Results obtained from this case study show that the 500-yr flood magnitude could increase by 4.5% in 2046–65 and by 6.4% in 2080–99 in terms of median values; in worst-case scenarios, it could increase by 63.0% and 111.8% in 2046–65 and 2080–99, respectively. It is found that the combined effect of GCMs, emission scenarios, and hydrological models has a larger influence on the discharge uncertainties than the individual impacts from emission scenarios and hydrological models. Further, results show GCMs are the dominant contributor to extreme flood uncertainty in both 2046–65 and 2080–99 periods. This study demonstrates that the developed framework can be used to effectively investigate changes in the occurrence of extreme floods in the future and to quantify individual and combined contributions of various uncertainty sources to extreme flood uncertainty, which can guide future efforts to reduce uncertainty.

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Chunlüe Zhou, Deliang Chen, Kaicun Wang, Aiguo Dai, and Dan Qi
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Qi Liu, Tianjun Zhou, Huiting Mao, and Congbin Fu

Abstract

The western Pacific subtropical high (WPSH) is regarded as the key circulation system that dominates the summer heat waves over eastern China, but whether the WPSH–summer heat wave connection changes with time remains unknown. In this study, decadal variations in the WPSH–heat wave connection were examined for the period 1959–2016 using daily maximum temperature data from 654 observational stations across China and global reanalysis datasets. The results show that the correlation coefficient between the WPSH intensity (WPSHI) and the number of heat-wave days (NHD) was 0.65 (>99% confidence level) during positive phases of the Pacific decadal oscillation (PDO), whereas that during negative phases of the PDO was only 0.12 (<80% confidence level). The remarkable difference in correlations is due to the more westward extension of a stronger WPSH in El Niño decaying summers during the positive phases of PDO. The stronger Indian Ocean warming in El Niño decaying-year summers for PDO positive phases in comparison to PDO negative phases is associated with enhanced convection and heating, which further drive a stronger anticyclone over the northwestern Pacific, leading to a stronger and more westward-extending WPSH, which is favorable for more heat waves over eastern China.

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Peng-Qi Huang, Xian-Rong Cen, Yuan-Zheng Lu, Shuang-Xi Guo, and Sheng-Qi Zhou

Abstract

In this study we examined the applicability of the threshold, curvature, maximum angle, and relative variance methods for identifying the oceanic bottom mixed layer (BML) thickness . Using full-depth temperature profiles along 17 WOCE sections covering the Atlantic, Indian, and Pacific Oceans, we found that the BML thicknesses determined based on the threshold, curvature, and maximum angle methods had wider 95% confidence intervals and much lower quality indexes compared with those based on the visual inspection (). The relative variance method appeared to perform better than the other methods because the 95% confidence interval and (0.60) values were closer to those determined based on the visual inspection, although differences were still present. We then proposed an integrated method by optimizing the possible values obtained from the four methods. The BML thicknesses determined using the integrated method were closest to those based on the visual inspection according to the higher (0.64) and more stations (71%) with . Compared with the results in previous studies, the integrated method determined the consistent BML thicknesses in most regions (e.g., the northern Atlantic), and it also effectively identified the BML thicknesses in some regions where the BML was considered to be not readily detectable (e.g., the Madeira Abyssal Plain).

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Shuang-Xi Guo, Xian-Rong Cen, Ling Qu, Yuan-Zheng Lu, Peng-Qi Huang, and Sheng-Qi Zhou

Abstract

Flow speed past the measuring probe is definitely needed for the estimation of the turbulent kinetic energy dissipation rates ε and temperature dissipation rates χ based on the Taylor frozen hypothesis. This speed is usually measured with current instruments. Occasional failed work of these instruments may lead to unsuccessful speed measurement. For example, low concentration of suspended particles in water could make the observed speed invalid when using acoustic measuring instruments. In this study, we propose an alternative approach for quantifying the flow speeds by only using the microstructure shear or temperature data, according to the spectral theories of the inertial and dissipation subranges. A dataset of the microstructure profiler, vertical microstructure profiler (VMP), collected in the South China Sea (SCS) during 2017, is used to describe this approach, and the inferred speeds are compared with the actual passing-probe speeds, i.e., the falling speeds of the VMP. Probability density functions (PDFs) of the speed ratios, i.e., the ratios of the speeds respectively inferred from the inertial and dissipation subranges of the shear and temperature spectra to the actual speeds, follow the lognormal distribution, with corresponding mean values of 1.32, 1.03, 1.56, and 1.43, respectively. This result indicates that the present approach for quantifying the flow speeds is valid, and the speeds inferred from the dissipation subrange of shear spectrum agree much better with the actual ones than those from the inertial subrange of shear spectrum and the inertial and dissipation subranges of temperature spectrum. The present approach may be complementary and useful in the evaluation of turbulent mixing when the directly observed speeds are unavailable.

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Chang Cao, Yichen Yang, Yang Lu, Natalie Schultze, Pingyue Gu, Qi Zhou, Jiaping Xu, and Xuhui Lee

Abstract

Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist’s smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.03°–0.05°C for temperature and of 0.18%–0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect.

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Xin Li, Guodong Cheng, Shaomin Liu, Qing Xiao, Mingguo Ma, Rui Jin, Tao Che, Qinhuo Liu, Weizhen Wang, Yuan Qi, Jianguang Wen, Hongyi Li, Gaofeng Zhu, Jianwen Guo, Youhua Ran, Shuoguo Wang, Zhongli Zhu, Jian Zhou, Xiaoli Hu, and Ziwei Xu

A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses.

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