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Jinlun Zhang

Senior Principal Oceanographer

Email

zhang@apl.washington.edu

Phone

206-543-5569

Biosketch

Dr. Zhang is interested in understanding how air-ice-ocean interaction in polar oceans affects polar and global climate. He investigates properties of polar air-ice-ocean systems using large- scale sea ice and ocean models. His recent work has focused on examining the evolution of the sea ice cover and the upper ocean in the Arctic in response to a significant climate change recently observed in the northern polar ocean.

He has developed a coupled global ice-ocean model to study the responses of sea ice to different conditions of surface heat fluxes and the effects of sea ice growth/decay on oceanic thermohaline circulation. He is also interested in developing next-generation sea ice models which capture anisotropic nature of ice dynamics. Dr. Zhang joined the Laboratory in 1994

Department Affiliation

Polar Science Center

Education

B.S. Shipbuilding & Ocean Engineering, Harbin Shipbuilding Engineering Institute, China, 1982

M.S. Ship Fluid Dynamics & Ocean Engineering, China Ship Scientific Research Center, 1984

Ph.D. Ice and Ocean Dynamics, Thayer School of Engineering, Dartmouth College, 1993

Projects

Changing Sea Ice and the Bering Sea Ecosystem

Part of the BEST (Bering Sea Ecosystem Study) Project, this study will use high-resolution modeling of Bering Sea circulation to understand past change in the eastern Bering climate and ecosystem and to predict the timing and scope of future change.

 

The Arctic Ocean Model Intercomparison Project (AOMIP): Synthesis and Integration

The AOMIP science goals are to validate and improve Arctic Ocean models in a coordinated fashion and investigate variability of the Arctic Ocean and sea ice at seasonal to decadal time scales, and identify mechanisms responsible for the observed changes. The project's practical goals are to maintain and enhance the established AOMIP international collaboration to reduce uncertainties in model predictions (model validation and improvements via coordinated experiments and studies); support synthesis across the suite of Arctic models; organize scientific meetings and workshops; conduct collaboration with other MIPs with a special focus on model improvements and analysis; disseminate findings of AOMIP effort to broader communities; and train a new generation of ocean and sea-ice modelers.

 

The Impact of Changes in Arctic Sea Ice on the Marine Planktonic Ecosystem- Synthesis and Modeling of Retrospective and Future Conditions

This work will investigate the historical and contemporary changes of arctic sea ice, water column, and aspects of the marine ecosystem as an integrated entity, and project future changes associated with a diminished arctic ice cover under several plausible warming scenarios.

 

More Projects

Publications

2000-present and while at APL-UW

Evidence of an increasing role of ocean heat in Arctic winter sea ice growth

Ricker, R., F. Kauker, A. Schweiger, S. Hendricks, J. Zhang, and S. Paul, "Evidence of an increasing role of ocean heat in Arctic winter sea ice growth," J. Clim., EOR, doi:10.1175/JCLI-D-20-0848.1, 2021.

More Info

24 Mar 2021

We investigate how sea ice decline in summer and warmer ocean and surface temperatures in winter affect sea ice growth in the Arctic. Sea ice volume changes are estimated from satellite observations during winter from 2002 to 2019 and partitioned into thermodynamic growth and dynamic volume change. Both components are compared to validated sea ice-ocean models forced by reanalysis data to extend observations back to 1980 and to understand the mechanisms that cause the observed trends and variability. We find that a negative feedback driven by the increasing sea ice retreat in summer yields increasing thermodynamic ice growth during winter in the Arctic marginal seas eastward from the Laptev Sea to the Beaufort Sea. However, in the Barents and Kara Seas, this feedback seems to be overpowered by the impact of increasing oceanic heat flux and air temperatures, resulting in negative trends in thermodynamic ice growth of –2 km3month-1yr-1 on average over 2002–2019 derived from satellite observations.

Benthic hotspots on the northern Bering and Chukchi continental shelf: Spatial variability in production regimes and environmental drivers

Feng, X., R. Ji, C. Ashjian, J. Zhang, R. Campbell, and J.M. Grebmeier, "Benthic hotspots on the northern Bering and Chukchi continental shelf: Spatial variability in production regimes and environmental drivers," Prog. Oceanogr., 191, doi:10.1016/j.pocean.2020.102497, 2021.

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1 Feb 2021

Benthic biological hotspots with persistently high macrofaunal biomass exist on the highly advective continental shelf that extends from the northern Bering Sea to the northeast Chukchi Sea. Environmental factors that influence carbon export to the benthos, a key driver for hotspot formation and persistence, remain uncertain. Multiple modeling approaches were used to better understand the combined effects of biological production and physical transport processes on supplying biogenic materials to those biological hotspots. Large data sets of benthic and environmental observations were synthesized, outputs from a pan-arctic ice-ocean-biogeochemical model were analyzed, and particle tracking modeling experiments and statistical analyses were conducted. Two different biophysical mechanisms of biogenic material supply to five benthic hotspot subdomains over a latitudinal range were identified using models and verified using data synthesis. Two hotpots to the south and the north of Bering Strait and the third one in southern Barrow Canyon heavily rely on carbon supplied from upstream biological production. In contrast, the St. Lawrence Island Polynya, southwest of St. Lawrence Island in the northern Bering Sea, and the Northeast Chukchi Sea hotspots are mostly fueled by local production. Spatial statistical modeling of benthic biomass distribution generally recaptured known hotspots but also suggested the likelihood of other probable hotspots in subregions of the biologically productive Gulf of Anadyr and of the topographically controlled Herald Canyon where limited sampling has occurred. The study provides new mechanistic understandings of the oceanographic processes and biophysical interactions that produce organic matter in sea ice and in the water column that subsequently is exported to underlying benthic communities. Combining data synthesis with process-based modeling was critical in understanding the dynamics of these sympagic-pelagic-benthic ecosystems and the potential climate-change-induced ecosystem response in the Pacific Arctic region.

Sea ice properties in high-resolution sea ice models

Zhang, J., "Sea ice properties in high-resolution sea ice models," J. Geophys. Res., 126, doi:10.1029/2020JC016686, 2021.

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13 Jan 2021

An Arctic sea ice-ocean model is run with three uniform horizontal resolutions (6, 4, and 2 km) and identical sea ice and ocean model parameterizations, including an isotropic viscous-plastic sea ice rheology, a mechanical ice strength parameterization, and an ice ridging parameterization. Driven by the same atmospheric forcing, the three model versions all produce similar spatial patterns and temporal variations of ice thickness and motion fields, resulting in almost identical magnitude and seasonal evolution of total ice volume and mean ice concentration, ice speed, and fractions of ice of various thickness categories over the Arctic Ocean. Increasing model resolution from 6 to 2 km does not significantly improve model performance when compared to NASA IceBridge ice thickness observations. This suggests that the large-scale sea ice properties of the model are insensitive to varying high resolutions within the multifloe scale (2–10 km), and it may be unnecessary to adjust model parameters constantly with increasingly high resolutions. This is also true with models within the aggregate scale (10–75 km), indicating that model parameters used at coarse resolution may be used at high or multiscale resolution. However, even though the three versions all yield similar mean state of sea ice, they differ in representing anisotropic properties of sea ice. While they produce a basic pattern of major sea ice leads similar to satellite observations, their leads are distributed differently in space and time. Without changing model parameters and sea ice spatiotemporal variability, the 2-km resolution model tends to capture more leads than the other two models.

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In The News

February's big patch of open water off Greenland? Not global warming, says new analysis

UW News, Hannah Hickey

In February 2018, a vast expanse of open water appeared in the sea ice above Greenland, a region that normally has sea ice well into the spring. The big pool of open water in the middle of the ice, known as a polynya, was a scientific puzzle.

18 Dec 2018

Arctic sea ice volume, now tracking record low, stars in data visualization

UW News and Information, Hannah Hickey

The Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) combines weather observations, sea-surface temperature and satellite pictures of ice coverage to compute ice volume and then compares that with on-the-ground measurements. PIOMAS ice numbers starred in an animated graphic posted this week by a climate scientist at the University of Reading.

7 Jul 2016

UW researchers attend sea ice conference — above the Arctic Circle

UW News and Information, Hannah Hickey

University of Washington polar scientists are on Alaska’s North Slope this week for the 2016 Barrow Sea Ice Camp. Supported by the National Science Foundation, the event brings together U.S.-based sea ice observers, satellite experts and modelers at various career stages to collect data and discuss issues related to measuring and modeling sea ice. The goal is to integrate the research community in order to better observe and understand the changes in Arctic sea ice.

1 Jun 2016

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