Fangjie Yu

An objective algorithm for estimating maximum oceanic mixed layer depth using seasonality indices derived from Argo temperature/salinity profiles

In this study, we propose a new algorithm for estimating the annual maximum mixed layer depth (M2LD) analogous to a full range of local “ventilation” depth, and corresponding to the deepest surface to which atmospheric influence can be “felt.” Two “seasonality indices” are defined, respectively, for temperature and salinity through Fourier analysis of their time series using Argo data, on the basis of which a significant local minimum of the index corresponding to a maximum penetration depth can be identified. A final M2LD is then determined by maximizing the thermal and haline effects. Unlike most of the previous schemes which use arbitrary thresholds or subjective criteria, the new algorithm is objective, robust, and property adaptive provided a significant periodic geophysical forcing such as annual cycle is available. The validity of our methodology is confirmed by the spatial correlation of the tropical dominance of saline effect (mainly related to rainfall cycle) and the extratropical dominance of thermal effect (mainly related to solar cycle). It is also recognized that the M2LD distribution is characterized by the coexistence of basin-scale zonal structures and eddy-scale local patches. In addition to the fundamental buoyancy forcing caused mainly by latitude-dependent solar radiation, the impressive two-scale pattern is found to be primarily attributable to (1) large-wave climate due to extreme winds (large scale) and (2) systematic eddy shedding as a result of persistent winds (mesoscale). Moreover, a general geographical consistency and a good quantitative agreement are found between the new algorithm and those published in the literature. However, a major discrepancy in our result is the existence of a constantly deeper M2LD band compared with other results in the midlatitude oceans of both hemispheres. Given the better correspondence of our M2LDs with the depth of the oxygen saturation limit, it is argued that there might be a systematic underestimation with existing criteria in these regions. Our results demonstrate that the M2LD may serve as an integrated proxy for studying the coherent multidisciplinary variabilities of the coupled ocean–atmosphere system.

Illumination-robust area-based stereo matching with improved census transform

This paper presents a novel area-based stereo matching algorithm based on improved census transform under changing illumination. For the traditional census-based stereo matching, the result is not robust under variant illumination, because the intensity value of center pixel in the mask is affected by the noise to cause distortion. In order to solve this problem, we propose the improved census transform method, which takes the standard deviation of census mask as the base point instead of the center pixel, comparing with the difference of per neighborhood pixel and the mean intensity of the mask to build the sparse census transform. The experiments show that the stereo matching algorithm is robust even if the illumination changes.

i4OilSpill, an operational marine oil spill forecasting model for Bohai Sea

Oil spill models can effectively simulate the trajectories and fate of oil slicks, which is an essential element in contingency planning and effective response strategies prepared for oil spill accidents. However, when applied to offshore areas such as the Bohai Sea, the trajectories and fate of oil slicks would be affected by time-varying factors in a regional scale, which are assumed to be constant in most of the present models. In fact, these factors in offshore regions show much more variation over time than in the deep sea, due to offshore bathymetric and climatic characteristics. In this paper, the challenge of parameterizing these offshore factors is tackled. The remote sensing data of the region are used to analyze the modification of wind-induced drift factors, and a well-suited solution is established in parameter correction mechanism for oil spill models. The novelty of the algorithm is the self-adaptive modification mechanism of the drift factors derived from the remote sensing data for the targeted sea region, in respect to empirical constants in the present models. Considering this situation, a new regional oil spill model (i4OilSpill) for the Bohai Sea is developed, which can simulate oil transformation and fate processes by Eulerian-Lagrangian methodology. The forecasting accuracy of the proposed model is proven by the validation results in the comparison between model simulation and subsequent satellite observations on the Penglai 19-3 oil spill accident. The performance of the model parameter correction mechanism is evaluated by comparing with the real spilled oil position extracted from ASAR images.

Design and implementation of atmospheric multi-parameter sensor for UAV-based aerosol distribution detection

Purpose In this paper, a light-weight, low-power atmospheric multi-parameter sensor (AMPS), which could be mounted on small flying platforms such as a tethered balloon, a quad-rotor unmanned aerial vehicle (UAV), a UAV helicopter, etc., is implemented and integrated to sample vertical distribution of aerosols with integrated parameters of aerosol particle concentration, temperature, relative humidity and atmospheric pressure. Design/methodology/approach The AMPS integrates three kinds of probes in an embedded system. A synchronous method based on GPS is proposed to drive the laser aerosol particle sensor, the temperature and humidity probe and the pressure probe to sample four channels approximately simultaneously. Different kinds of housing are designed to accommodate various flying platforms, and the weight is controlled to adapt the payload of each platform. Findings A series of validation tests show that while the AMPS achieves high precision, its power consumption is less than 1.3 W, which is essential for light flying platforms. The AMPS was mounted on different flying platforms and the difference was evaluated. For three times every five days, vertical profiles of PM2.5 and PM10 concentrations were observed by the AMPS mounted on a quad-rotor UAV, which revealed the significant correlation between the aerosol particle concentration and atmospheric parameters. Originality/value A new light-weight and low-power AMPS for small flying platforms is designed and tested, which provides an effective way to explore the properties of aerosol vertical distribution, and to monitor pollutants flexibly.

A Novel Cross-Platform Architecture Design for Oil Spill Forecasting Model

In recent years, the expansion of marine oil and gas transport has led to the increase of oil spill accidents. Both accidents occurring in deep sea and coastal regions can bring huge financial losses. As the development of ocean model, oil spill model has been proposed and became a valid countermeasure to simulate the process of transport, diffusion and transformation of the surface oil in seawater. This paper presents an oil spill model with a novel cross-platform (Windows/Linux) architecture. This model can not only compute oil concentration mathematically and numerically, but also can draw oil spill concentration maps with pseudo color, by using computer visualization technique. The tendency of transport, diffusion and transformation of oil could be illustrated in chronological order by the concentration maps. Furthermore, an oil spill simulation case has been accomplished, and the simulation results is discussed in this paper. Results showed that this model could simulate oil slick motions effectively and had friendly user interface.

A Novel High Accuracy Sub-Pixel Corner Detection Algorithm for Camera Calibration

This paper presents a novel sub-pixel corner detection algorithm for camera calibration. In order to achieve high accuracy and robust performance, the pixel level candidate regions are firstly identified by Harris detector. Within these regions, the center of gravity (COG) method is used to gain sub-pixel corner detection. Instead of using the intensity value of the regions, we propose to use corner response function (CRF) as the distribution of the weights of COG. The results of camera calibration experiments show that the proposed algorithm is more accurate and robust than traditional COG sub-pixel corner detection methods.

Risk assessment of oil spills in the Chinese Bohai Sea for prevention and readiness

Oil spill accidents occur with increasing frequency in the Chinese Bohai Sea because of the presence of extensive number of oil platforms and oil pipelines the Chinese Bohai region. An appropriate risk assessment for oil spill prevention and readiness is necessary. Risk assessment for the entire Chinese Bohai Sea based on a quantitative method is proposed. We created a hypothetical simulation of oil spill trajectories based on an oil spill model for 28 oil platforms in the Chinese Bohai region in 2010. Then, we mapped a risk index in the study areas based on a combination of oil spill trajectories and shoreline susceptibility data. Five high-risk areas were identified in the entire Chinese Bohai Sea. Detailed suggestions for prevention and readiness are described here. These results can help in developing a risk assessment of oil spills in the Chinese Bohai Sea and serve as a useful analytic tool for slick-related emergencies.

A Correction Method for UAV Helicopter Airborne Temperature and Humidity Sensor

This paper presents a correction method for UAV helicopter airborne temperature and humidity including an error correction scheme and a bias-calibration scheme. As rotor downwash flow brings measurement error on helicopter airborne sensors inevitably, the error correction scheme constructs a model between the rotor induced velocity and temperature and humidity by building the heat balance equation for platinum resistor temperature sensor and the pressure correction term for humidity sensor. The induced velocity of a spatial point below the rotor disc plane can be calculated by the sum of the induced velocities excited by center line vortex, rotor disk vortex, and skew cylinder vortex based on the generalized vortex theory. In order to minimize the systematic biases, the bias-calibration scheme adopts a multiple linear regression to achieve a systematically consistent result with the tethered balloon profiles. Two temperature and humidity sensors were mounted on “Z-5” UAV helicopter in the field experiment. Overall, the result of applying the calibration method shows that the temperature and relative humidity obtained by UAV helicopter closely align with tethered balloon profiles in providing measurements of the temperature profiles and humidity profiles within marine atmospheric boundary layers.

Lossless Data Compression Based on Adaptive Linear Predictor for Embedded System of Unmanned Vehicles

AbstractUnmanned vehicles represent a significant technical improvement for ocean and atmospheric monitoring. With the increasing number of sensors mounted on the unmanned mobile platforms, the data volume and its rapid growth introduce a new challenge relative to the limited transmission bandwidth. Data compression provides an effective approach. However, installing a lossless compression algorithm in an embedded system, which is in fact limited in computing resources, scale, and energy consumption, is a challenging task. To address this issue, a novel self-adaptive lossless compression algorithm (SALCA) that is focused on the dynamic characteristics of multidisciplinary ocean and atmospheric observation data is proposed that is the extended work of two-model transmission theory. The proposed method uses a second-order linear predictor that can be changed as the input data vary and can achieve better lossless compression performance for dynamic ocean data. More than 200 groups of conductivity–temperature...

MDIS cloth system: virtual reality technology for firefighter training

Fire accidents can cause numerous casualties and heavy property losses, especially, in petrochemical industry, such accidents are likely to cause secondary disasters. However, common fire drill training would cause loss of resources and pollution. We designed a multi-dimensional interactive somatosensory (MDIS) cloth system based on virtual reality technology to simulate fire accidents in petrochemical industry. It provides a vivid visual and somatosensory experience. A thermal radiation model is built in a virtual environment, and it could predict the destruction radius of a fire. The participant position changes are got from Kinect, and shown in virtual environment synchronously. The somatosensory cloth, which could both heat and refrigerant, provides temperature feedback based on thermal radiation results and actual distance. In this paper, we demonstrate the details of the design, and then verified its basic function. Heating deviation from model target is lower than 3.3 °C and refrigerant efficiency is approximately two times faster than heating efficiency.