姚恒恺

姚恒恺

讲师
Dr. Hengkai Yao (姚恒恺) is a lecturer of School of Mathmetica and Physics at the Qingdao University of Science and Technology. He got Ph.D of Physical Oceanograpy from Ocean University of China. His research interests include mesoscale eddies, ocean modeling and AI oceanography. He is member of the AI Oceanography group, which develops big data in ocean, ocean simulation, and ocean prediction. He is also a chief scientist in Qingdao Oakfull Water Technology Co., Ltd.

Physics informed neural network framework for time-varying wind stress drag coefficient identification in the Ekman model

The Ekman equation is a fundamental model for describing the wind stress response in the ocean's upper layer,with its key parameters—the vertical eddy viscosity coefficient (VEVC) …

avatar
Yitong Sun

A Dual-Attention Embedded CNN Model for Estimating Mixed Layer Depths in the Bay of Bengal

Variations in ocean mixed layer depth(MLD) show a significant impact on energy balance in the global climate systems and marine ecosystems. At present, the accuracy of modeling …

avatar
Wentao Jia
A Dual-attention Embedded CNN Model for Estimating Mixed Layer Depths in the Bay of Bengal featured image

A Dual-attention Embedded CNN Model for Estimating Mixed Layer Depths in the Bay of Bengal

Variations in ocean mixed layer depth (MLD) show a significant impact on energy balance in the global climate systems and marine ecosystems. So far, the accuracy of modeling MLD, …

avatar
Wentao Jia

Estimating Subsurface Thermohaline Structure in the Tropical Western Pacific Using DO-ResNet Model

Estimating the ocean's subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and the El Ni & ntilde;o phenomenon. This paper …

avatar
Xianmei Zhou
Estimating Subsurface Thermohaline Structure in the tropical Western Pacific using DO-ResNet model featured image

Estimating Subsurface Thermohaline Structure in the tropical Western Pacific using DO-ResNet model

Estimating ocean subsurface thermohaline information from satellite data is vital for understanding ocean dynamics and El Niño. This paper presents a double-output Residual Neural …

avatar
Xianmei Zhou

The Development of a Weather-Type Statistical Downscaling Model for Wave Climate Based on Wave Clustering

Reliable long-term wave data are significant for understanding changes and variability of ocean waves, which has important implications for coastal engineering, land erosion, and …

avatar
Wentao Jia

A Dual-Attention Embedded CNN Model for Estimating Mixed Layer Depths in the Bay of Bengal

Variations in ocean mixed layer depth(MLD) show a significant impact on energy balance in the global climate systems and marine ecosystems. At present, the accuracy of modeling …

avatar
Wentao Jia
Research on vertical structure and origin of eddies in Kuroshio-Oyashio Extension region featured image

Research on vertical structure and origin of eddies in Kuroshio-Oyashio Extension region

As a ubiquitous motion phenomenon in the ocean, mesoscale eddies play a key role in the transport and distribution of global heat, salinity, energy and marine biochemical …

avatar
姚恒恺
On the Vertical Structure of Mesoscale Eddies in the Kuroshio-Oyashio Extension featured image

On the Vertical Structure of Mesoscale Eddies in the Kuroshio-Oyashio Extension

Mesoscale eddies are swirling motions with a radius ranging from several tens to a hundred of kilometers. The mesoscale eddies can cause strong vertical displacement of isopycnals, …

avatar
姚恒恺
Introducing the New Regional Community Earth System Model, R-CESM featured image

Introducing the New Regional Community Earth System Model, R-CESM

The development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and …

dan-fu