Oxygen uptake and vertical transport during deep convection events in the Labrador Sea and its interannual variability

Dissolved oxygen (DO) is essential for marine life and biogeochemical cycling. To a first order approximation, DO is determined by the competition between ocean ventilation and biological productivity. Approximately 21% of the atmospheric gases is oxygen, and the waters at the ocean surface are enriched in oxygen. Ventilation occurs through a suite of physical processes that brings the DO-rich surface waters into the interior ocean. This dissertation combines two works that closely examine the ventilation of oxygen in the region of deep water formation, and explore the relationship between air-sea oxygen flux and surface forcing aiming at deepening our understanding of the processes that regulate he DO inventory. Through these analyses we develop a framework to understand the oxygen to ocean heat content (O2-OHC) ratio in the ocean interior. Both works focus on the Labrador Sea and include a theoretical development and its validation using a suite of numerical sensitivity experiments. The first work leads to two main conclusions. 1) Both the duration and the intensity of the winter-time cooling are important to the total O2 uptake for a convective event. Stronger cooling leads to deeper convection and brings oxygen into deeper depths. Longer duration of the cooling period increases the total amount of oxygen uptake over the convective season. 2) The bubble-mediated influx of oxygen can increase oxygen uptake, but part of the contribution is compensated by the weakening the diffusive influx because the air-sea disequilibrium of oxygen is shifted towards supersaturation. The degree of compensation between the diffusive and bubble-mediated gas exchange depends on the relative strength of oceanic vertical mixing and the gas transfer velocity. Strong convective mixing reduces the degree of compensation so that the two components of gas exchange together drive exceptionally strong oceanic oxygen uptake. A numerical model with idealized domain and non-hydrostatic dynamics is used to test the hypotheses in this work. The second work explores what controls the O2-OHC ratio during deep convection. Models of different complexities ranging from 1-D convective adjustment model to a regional ocean circulation model that includes a complex biogeochemical module are used. The bubble injection increases the oxygen flux and the magnitude of the O2-OHC ratio under intense convective events. Longer cooling duration leads to a larger magnitude of the O2-OHC ratio. The pre-conditioning of the vertical gradients in oxygen and temperature are important for the O2-OHC ratio under different climate scenarios. With these two works, we highlight a few key mechanisms that are important to regulate the DO inventory in the ocean interior, but further efforts are needed to understand the global DO variability and to constrain the deoxygenation potential under a warming climate.Ph.D

Deep convection simulation from the MITgcm (MIT General Circulation Model) (IVOMLS project)

Dataset: Deep convection simulation using MITgcmAll experiments are preformed using the MIT General Circulation Model (MITgcm). The model is configured to allow non-hydrostatic dynamics to explicitly resolve deep convection. The model domain is a box with periodic boundary conditions in the x and y directions of 32 x 32 km with horizontal resolution of 250 m. The box has a uniform depth of 2 km with 41 z-levels whose thicknesses increases from 10 m at surface to 100 m near the bottom. The linear equation of state is used throughout this study. 16 sensitivity experiments are designed to explore the behavior of oxygen uptake during the deep convection events under different cooling conditions. Two validation runs are also applied by forcing the model using observational data from Argo. In this data set, horizontally averaged profiles and vertical transport of dissolved oxygen and temperature from all experiments are included. A few transect of dissolved oxygen and temperature are also included to demonstrate the evolution of the convection event. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/706167NSF Division of Ocean Sciences (NSF OCE) OCE-135737

A new flywheel energy storage system for distributed generation

ABSTRACT It is necessary to install flywheel energy storage (FES) system in distributed generation, which can improve the quality and the reliability of electric power. The proposed system is composed of four parts: flywheel, magnetic bearing, motor/generator, and power converter. A permanent magnet motor-generator is incorporated in a composite flywheel, running at high speed in a vacuum containment to minimize air friction losses. The flywheel is to be suspended on magnet bearings. A 3-phase, switch mode bridge inverter, driven by a pulse width modulation board, achieves the variable speed control for the motor/generator and the control for the DC bus voltage. The presentation will explain the schematics of the flywheel battery, control diagram, power electronics and motor/generator. The overall operation will be described

Ocean response offshore of Taiwan to super typhoon Nepartak (2016) based on multiple satellite and buoy observations

Multi-satellite and buoy observation data were used to systematically analyze the ocean response offshore of Taiwan to Super Typhoon Nepartak in 2016. The satellite data showed that a high sea surface temperature combined with a thick warm water layer and deep mixed layer provided a good thermal environment for continuous intensification of the typhoon. Two high-resolution buoys (NTU1 and NTU2) moored 375 and 175 km offshore of southeastern Taiwan were used to clarify the typhoon–ocean interaction as the typhoon approached Taiwan. The ocean conditions were similar at the two buoys before the typhoon, and both buoys were on the left side of the typhoon track and suffered similar typhoon factors (e.g., typhoon intensity and translation speed) during its passage. However, the ocean response differed significantly at the two buoys. During the forced period, the entire upper ocean was cooled at NTU1. In contrast, there was a clear three-layer vertical structure at NTU2 consisting of cool surface and deep layers with a warmer layer between the two cool layers. These responses can be attributed to strong upwelling of a cold eddy at NTU1 and vertical mixing at NTU2. These results indicate that, under similar preexisting conditions and typhoon factors, the movement of ocean eddies under typhoon forcing is an unexpected mechanism that results in upwelling and thus needs to be considered when predicting changes in the ocean environment and typhoon intensity

The role of freshwater forcing on surface predictability in the Gulf of Mexico

The predictability of fields at the ocean surface in the northern Gulf of Mexico (GoM) is investigated through five ensembles of regional ocean simulations between 2014 and 2016. The ensembles explore two horizontal resolutions and different representations of the riverine inflow, and focus on the Loop Current system (LCS) and the Mississippi-Atchafalaya River System (MARS) interactions. The predictability of the surface fields is high in the northern GoM if the atmospheric forcing and the flow at Yucatan Channel are known, and the ensembles simulate similar LCS behavior up to 5 months. In terms of LCS-MARS interactions, the ensembles confirm that they are strongly modulated by the LC mesoscale variability. The relationship is two-ways, with the LCS being influenced by - and not only influencing - the freshwater plume. Whenever the freshwater flux is strong, the northward extension of the LCS is constrained. The ensemble simulations also indicate that this influence is stronger if the riverine inflow is simulated in an active fashion with a meridional velocity component proportional to the flux. Sea surface temperature (SST) and salinity (SSS) predictability have opposite seasonality in their signal, with the SST (SSS) field being more predictable in summer (winter). Partially resolving submesoscale instabilities and improving the accuracy of the riverine fluxes' representation causes the spread to increase, especially in SST. Finally, the predictability of surface relative vorticity decreases in amplitude when increasing resolution due to feedbacks between the mesoscale and submesoscale circulations, but retains most of its intraseasonal and interannual signal.Comment: 24 pages, 13 figures, submitted to JGR: ocean

Towards Homogeneous Modality Learning and Multi-Granularity Information Exploration for Visible-Infrared Person Re-Identification

Visible-infrared person re-identification (VI-ReID) is a challenging and essential task, which aims to retrieve a set of person images over visible and infrared camera views. In order to mitigate the impact of large modality discrepancy existing in heterogeneous images, previous methods attempt to apply generative adversarial network (GAN) to generate the modality-consisitent data. However, due to severe color variations between the visible domain and infrared domain, the generated fake cross-modality samples often fail to possess good qualities to fill the modality gap between synthesized scenarios and target real ones, which leads to sub-optimal feature representations. In this work, we address cross-modality matching problem with Aligned Grayscale Modality (AGM), an unified dark-line spectrum that reformulates visible-infrared dual-mode learning as a gray-gray single-mode learning problem. Specifically, we generate the grasycale modality from the homogeneous visible images. Then, we train a style tranfer model to transfer infrared images into homogeneous grayscale images. In this way, the modality discrepancy is significantly reduced in the image space. In order to reduce the remaining appearance discrepancy, we further introduce a multi-granularity feature extraction network to conduct feature-level alignment. Rather than relying on the global information, we propose to exploit local (head-shoulder) features to assist person Re-ID, which complements each other to form a stronger feature descriptor. Comprehensive experiments implemented on the mainstream evaluation datasets include SYSU-MM01 and RegDB indicate that our method can significantly boost cross-modality retrieval performance against the state of the art methods.Comment: 15 pages, 9figure

Research of Deicing and Melting Snow on Airport Asphalt Pavement by Carbon Fiber Heating Wire

In the paper, the method of deicing and melting snow by the carbon fiber heating wire (CFHW) embedded in the airport asphalt pavement is proposed to improve the security of airport operation. The field experiment of deicing and melting snow on the airport asphalt pavement is conducted. Deicing and melting snow, asphalt pavement temperature, ice-free area ratio, and snow-free area ratio are analyzed. Electrical power with 350 W/m2 is input to the airport asphalt pavement for deicing and melting snow by the CFHW. In the experiment, 3 mm ice can be melted, and the average infrared ray temperature (IRT) of the airport asphalt pavement surface can achieve an increment of 13.0°C in 2.5 hours when the air temperature is from −7.5°C to −2.2°C. Snow with 3.2 mm precipitation can be melted in 2 hours when the air temperature is from −4.8°C to −3.5°C, and the asphalt pavement temperature can achieve an increment of 5.9°C at the depth of 0.5 cm. The results show that the method of deicing and melting snow on the airport asphalt pavement by the CFHW is practicable in the cold zone

Central-Pacific El Niño-Southern Oscillation less predictable under greenhouse warming

Abstract El Niño-Southern Oscillation (ENSO) is the dominant mode of interannual climate variability in the tropical Pacific, whose nature nevertheless may change significantly in a warming climate. Here, we show that the predictability of ENSO may decrease in the future. Across the models in the Coupled Model Intercomparison Project Phase 6 (CMIP6), we find a robust decrease of the persistence and predictability for the Central Pacific (CP) ENSO under global warming, notably in passing through the boreal spring. The strength of spring predictability barrier will be increased by 25% in the future. The reduced predictability of CP ENSO is caused by the faster warming over surface ocean in tropical Pacific and, in turn, the enhanced thermodynamical damping rate on CP ENSO in response to global warming. In contrast, the predictability of Eastern Pacific ENSO will not change. Our results suggest that future greenhouse warming will make the prediction of CP ENSO more challenging, with far-reaching implications on future climate predictions