Wieslaw Maslowski - Academia.edu (original) (raw)

Papers by Wieslaw Maslowski

GEM - International Journal on Geomathematics

PLOS ONE

The Bering Sea experiences a seasonal sea ice cover, which is important to the biophysical enviro... more The Bering Sea experiences a seasonal sea ice cover, which is important to the biophysical environment found there. A pool of cold bottom water (<2°C) is formed on the shelf each winter as a result of cooling and vertical mixing due to brine rejection during the predominately local sea ice growth. The extent and distribution of this Cold Pool (CP) is largely controlled by the winter extent of sea ice in the Bering Sea, which can vary considerably and recently has been much lower than average. The cold bottom water of the CP is important for food security because it delineates the boundary between arctic and subarctic demersal fish species. A northward retreat of the CP will likely be associated with migration of subarctic species toward the Chukchi Sea. We use the fully-coupled Regional Arctic System Model (RASM) to examine variability of the extent and distribution of the CP and its relation to change in the sea ice cover in the Bering Sea during the period 1980–2018. RASM resul...

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition ex... more The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition explored the coupled central arctic climate system from late September 2019 to late September 2020. The project was based on and around the icebreaker Polarstern, as it was frozen into, and drifted with, the arctic sea ice from the Siberian sector of the Arctic, past the North Pole, and on towards the Fram Strait. The expedition was designed as a "sea ice Lagrangian" experiment, wherein a specific region of sea ice was passively followed over the course of a year, serving as an integrator of thermodynamic, dynamic, chemical, and biological interactions with the atmosphere and ocean. The overall scientific goal for the mission was to understand the processes driving the ongoing rapid decline of sea ice as well as the implications of those changes on the regional and global climate systems. In particular, the expedition was constructed in a way to observe and understand the physical, chemical, and biological processes that serve to couple and link the arctic atmosphere, sea ice, ocean, and ecosystem. Guiding science questions for the mission include: 1. What are the seasonally varying energy sources, mixing processes, and interfacial fluxes that affect the heat and momentum budgets of the arctic atmosphere, ocean, and sea ice?

American Geophysical Union eBooks, Feb 1, 2016

EGU General Assembly Conference Abstracts, Apr 1, 2015

EGU General Assembly Conference Abstracts, May 1, 2014

Bulletin of the American Meteorological Society, 2022

Climate observations inform about the past and present state of the climate system. They underpin... more Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surfac...

ABSTRACT The Arctic is experiencing changes never before seen in historic times. The physical, ch... more ABSTRACT The Arctic is experiencing changes never before seen in historic times. The physical, chemical, biological, and social components of the Arctic System are interrelated, and therefore a holistic perspective is needed to understand and quantify their connections and predict future system changes. A regional Arctic System Model (ASM) will strengthen our understanding of these components. It will advance scientific investigations and provide a framework for improving predictive capabilities, thereby helping society to prepare for environmental change and its impacts on humans, ecosystems, and the global climate system. It will be a vehicle for harnessing the resources of the many sub-disciplines of arctic research for the benefit of planners and policymakers. An ASM will build on previous modeling and observations, and it will benefit from ongoing studies of component models that are in varying stages of development. The initial core model will include atmosphere, ocean, sea ice, and selected land components and will be constructed in a manner that allows investigators to add or exchange components as the ASM project progresses. These will include ice sheets, mountain glaciers, dynamic vegetation, biogeochemistry, terrestrial and marine ecosystems, coastal systems, atmospheric chemistry, and human and social dimension modules. The core focus of the proposed ASM program will be to understand complexity and adaptation in the Arctic System as well as society’s role and response in the evolution of that system. The program is designed to complement and work with global Earth System Modeling programs to create reliable probabilistic forecasts of the state of the Arctic on seasonal to decadal timescales. Therefore, the modeling program must work toward quantifying and reducing uncertainties related to variability of the Arctic System, uncertainty in the models themselves, and uncertainty in society’s response and adaptation to arctic change. Basic model development within the ASM program should be focused on improving simulations of the arctic biosphere and anthroposphere. The ASM program will require coordination of diverse segments of the research community and support for computing infrastructure and software. The coordination function should be guided by a number of working groups and a scientific steering committee. A central facility will fulfill the functions of a project office, data center, and point of international liaison to be shaped and overseen by the steering committee. Dedicated personnel at this facility should provide documentation, testing, and support for the ASM. Proposals for providing these core functions should be sought at the outset of the program. The program should be approached in stages to make sure it is meeting the overarching goals mentioned above. Stage One will be to fund small pilot projects that allow researchers to demonstrate the capacity of limited-area coupled models to improve understanding of the role of the Arctic in global environmental change. These projects would use high-resolution, Arctic-focused simulations to understand the physics, chemistry, and biology of the Arctic as it undergoes rapid change. If successful, this stage will be expanded to construct a basic regional ASM climate model core. Stage Two incorporates coupled biogeochemical and ecological components into the ASM. Stage Three targets the coupling of those components least ready for integration into the ASM; these include components related to human interaction with the environment. Each stage requires close interaction between ASM model developers and the global modeling and observation communities, and each should be focused on understanding the Arctic as a complex adaptive system.

Elem Sci Anth, 2022

Year-round observations of the physical snow and ice properties and processes that govern the ice... more Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability...

• An international and interdisciplinary team made comprehensive observations of the atmosphere, ... more • An international and interdisciplinary team made comprehensive observations of the atmosphere, sea ice, ocean, ecosystem, and biogeochemistry over an annual cycle in the Central Arctic. • The MOSAiC year was characterized, above all, by a thin and dynamic sea ice pack, reflecting the impact of the multi-decadal warming trend in global air temperatures on the Arctic region. • The unprecedented data set will foster cross-cutting, process-based research that will advance understanding, bolster observational techniques from the surface and satellites, and enable improved modeling and predictive capabilities.

Substantial amounts of nutrients and carbon enter the Arctic Ocean from the Pacific Ocean through... more Substantial amounts of nutrients and carbon enter the Arctic Ocean from the Pacific Ocean through the Bering Strait, distributed over three main pathways. Water with low salinities and nutrient concentrations takes an eastern route along the Alaskan coast, as Alaskan Coastal Water. A central pathway exhibits intermediate salinity and nutrient concentrations, while the most nutrient-rich water enters the Bering Strait on its western side. Towards the Arctic Ocean, the flow of these water masses is subject to strong topographic steering within the Chukchi Sea with volume transport modulated by the wind field. In this contribution, we use data from several sections crossing Herald Canyon collected in 2008 and 2014 together with numerical modelling to investigate the circulation and transport in the western part of the Chukchi Sea. We find that a substantial fraction of water from the Chukchi Sea enters the East Siberian Sea south of Wrangel Island and circulates in an anticyclonic direction around the island. This water then contributes to the highnutrient waters of Herald Canyon. The bottom of the canyon has the highest nutrient concentrations, likely as a result of addition from the degradation of organic matter at the sediment surface in the East Siberian Sea. The flux of nutrients (nitrate, phosphate, and silicate) and dissolved inorganic carbon in Bering Summer Water and Winter Water is computed by combining hydrographic and nutrient observations with geostrophic transport referenced to lowered acoustic Doppler current profiler (LADCP) and surface drift data. Even if there are some general similarities between the years, there are differences in both the temperature-salinity and nutrient characteristics. To assess these differences, and also to get a wider temporal and spatial view, numerical modelling results are applied. According to model results, high-frequency variability dominates the flow in Herald Canyon. This leads us to conclude that this region needs to be monitored over a longer time frame to deduce the temporal variability and potential trends.

On the cover: Top left: Multi-timescale simulation of a single protein. A phosphoglycerate kinase... more On the cover: Top left: Multi-timescale simulation of a single protein. A phosphoglycerate kinase protein was subjected to MD simulations on various supercomputing architectures. The relative motions of the red and blue domains of the proteins are highly complex and can be described in terms of the motion of a configurational point on a rough energy landscape (illustrated). The transitions of the structure between energy minima on the landscape can be described in terms of a network (illustrated), which was found to be fractal (self-similar) over 13 decades of time (Image credit: Thomas Splettstoesser, scistyle.com). Top middle: Ocean currents and eddies in a high-resolution global ocean simulation. Colors show speed, where white is faster. Detailed turbulent structures are visible throughout the Southern Ocean, where the Antarctic circumpolar current flows eastward around the globe. Large eddies are particularly visible in the Agulhas current at the southern tip of Africa. These ocean simulations are validated against satellite and shipboard observations. The domain includes 100 vertical layers and 1.5 million horizontal grid cells ranging from 10 to 30 km in diameter, and was run on 8000 processors. (Image credit: The Model for Prediction Across Scales-Ocean [MPAS-Ocean], a component of the U.S. Department of Energy's new Accelerated Climate Model for Energy [ACME] and developed at Los Alamos National Laboratory [LANL]. Image by Phillip Wolfram and Mark Petersen of the MPAS-Ocean team, which also includes Todd Ringler, Xylar Asay-Davis, Mathew Maltrud, Luke Van Roekel, Milena Veneziani, and Jon Wolfe, all of LANL.) Top right: Model of the cellulase synthase enzyme, CesA, derived by integrating neutron scattering and high-performance computing (Image credit: Thomas Splettstoesser, scistyle.com). Bottom: The paint-like swirls of this visualization depict global watersurface temperatures, with the surface texture driven by vorticity. Cool temperatures are designated by blues and warmer temperatures by reds. Trapped regions of warmer water (red) adjacent to the Gulf Stream off the eastern coast of the United States indicate the model's ability to simulate eddy transport of heat within the ocean, a key component necessary to accurately simulating global climate variability. (Image credit: The Model for Prediction Across Scales-Ocean [MPAS-Ocean], a component of the U.S. Department of Energy's new Accelerated Climate Model for Energy [ACME] and developed at Los Alamos National Laboratory [LANL]. Image by Phillip Wolfram and Mark Petersen of the MPAS-Ocean team, which also includes Todd Ringler,