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Papers by Wieslaw Maslowski

During the 42-year period of satellite measurements, only three winter polynyas have ever been ob... more During the 42-year period of satellite measurements, only three winter polynyas have ever been observed north of Greenland and they all occurred in the last decade, i.e. February of 2011, 2017 and 2018. The 2018 polynya was unparalleled by its magnitude and duration compared to the two previous events. Combined with the limited weather station and remotely-sensed sea ice data, a fully-coupled Regional Arctic System Model (RASM) hindcast simulation was utilized to examine the causality and evolution of these recent extreme events. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact on the development of these winter open water episodes in the study region (i.e., no significant ice melting). Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds of greater than 10 m/s) blowing persistently for at least 2 days or more, were required over the study region to mechanically redistribute some of the thickest sea ice out of the region and thus to create open water areas (a latent heat polynya). In order to assess the role of internal variability versus external forcing of such events, we additionally simulated and examined results from two RASM ensembles forced with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles, initialized 30 years apart, one in December 1985 and another in December 2015, respectively, 17 and 14 winter polynyas were produced over north of Greenland. The frequency of polynya occurrence and no apparent sensitivity to the initial sea ice thickness in the study area point to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations and probabilistic forecast of Arctic events, such as the ones being investigated here and elsewhere.

Journal Of Geophysical Research: Oceans, Apr 1, 2022

As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new se... more As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new sea-ice rheologies, and increasing model spatial resolution, ubiquitous deformation features in the Arctic sea ice are now being resolved by sea-ice models. Initiated at the Forum for Arctic Modeling and Observational Synthesis, the Sea Ice Rheology Experiment (SIREx) aims at evaluating state-of-the-art sea-ice models using existing and new metrics to understand how the simulated deformation fields are affected by different representations of sea-ice physics (rheology) and by model configuration. Part 1 of the SIREx analysis is concerned with evaluation of the statistical distribution and scaling properties of sea-ice deformation fields from 35 different simulations against those from the RADARSAT Geophysical Processor System (RGPS). For the first time, the viscous-plastic (and the elastic-viscous-plastic variant), elastic-anisotropic-plastic, and Maxwell-elasto-brittle rheologies are compared in a single study. We find that both plastic and brittle sea-ice rheologies have the potential to reproduce the observed RGPS deformation statistics, including multi-fractality. Model configuration (e.g., numerical convergence, atmospheric representation, spatial resolution) and physical parameterizations (e.g., ice strength parameters and ice thickness distribution) both have effects as important as the choice of sea-ice rheology on the deformation statistics. It is therefore not straightforward to attribute model performance to a specific rheological framework using current deformation metrics. In light of these results, we further evaluate the statistical properties of simulated Linear Kinematic Features in a SIREx Part 2 companion paper. The ice in the Arctic Ocean is not continuous: it is broken into individual pieces of ice (floes). As the winds and ocean currents continually move these ice floes, they get piled up together or pushed away from each other, forming regions of increased ice thickness (ridges) or regions of open water (leads). These leads and ridges (ice deformations) are important features of the Arctic pack ice because they control the amount of energy that can be exchanged between the atmosphere and the ocean. Current climate models cannot simulate individual ice floes and their deformations. Instead, various methods are used to represent the movement and deformation of the Arctic sea-ice cover. The goal of the Sea Ice Rheology Experiment (SIREx) is to compare these different methods and evaluate the ability of a large number of sea-ice models to reproduce observed sea-ice deformations from satellite imagery. SIREx is divided in two parts. In Part 1 (this study), we evaluate how the intensity of ice deformations varies in space and time. In Part 2 (companion paper), we track and evaluate the occurrence of specific deformation features. With this work, we show how to improve sea-ice models for realistic simulations of sea-ice deformations.

Shifts in bowhead whale distribution, behavior, and condition following rapid sea ice change in the Bering sea

Continental Shelf Research

An  Assessment of Arctic Sea Ice Intra-Annual Probabilistic Prediction Skill Using the Regional Arctic System Model

Assessment of 2019 Sub-seasonal to Intra-annual Arctic Sea Ice Forecasts

AGU Fall Meeting Abstracts, Dec 1, 2019

Advancements, Gaps, and Needs in Observing, Understanding, and Modeling the High-Latitude Earth Systems II Poster

AGU Fall Meeting 2021, Dec 17, 2021

An Evaluation of the CMIP6 Historical Simulations of the Arctic Sea Ice

AGU Fall Meeting Abstracts, Dec 1, 2020

Toward a new non-hydrostatic ice-sheet/ocean interaction model (NUMO) for Greenland fjords

AGUFM, Dec 1, 2017

A Satellite Emulator for Evaluating Sea Ice Volume in Coupled Earth System Models

The role of ice-ocean inertia in representing the impact of storms on sea ice in fully coupled Earth System Models

Modeling Ice-Ocean Interactions with Non-hydrostatic Unified Model of the Ocean (NUMO)

Importance of Sea Ice Deformations to Understanding, Modeling and Prediction of Arctic Climate Change

Evaluating simulated linear kinematic features in high-resolution sea-ice simulations of the FAMOS Sea Ice rheology experiments (SIREx)

<p>Simulating sea-ice drift and deformation in the Arctic Ocean is still a challenge becaus... more <p>Simulating sea-ice drift and deformation in the Arctic Ocean is still a challenge because of the multi-scale interaction of sea-ice floes that compose the Arctic sea ice cover. The Sea Ice Rheology Experiment (SIREx) is a model intercomparison project formed within the Forum of Arctic Modeling and Observational Synthesis (FAMOS) to collect and design skill metrics to evaluate different recently suggested approaches for modeling linear kinematic features (LKFs) and provide guidance for modeling small-scale deformation. In this contribution, spatial and temporal properties of LKFs are assessed in 33 simulations of state-of-the-art sea ice models (VP/EVP,EAP, and MEB) and compared to deformation features derived from RADARSAT Geophysical Processor System (RGPS).<br>All simulations produce LKFs, but only very few models realistically simulate at least some statistics of LKF properties such as densities, lengths, lifetimes, or growth rates. All SIREx models overestimate the angle of fracture between conjugate pairs of LKFs pointing to inaccurate model physics. The temporal and spatial resolution of a simulation and the spatial resolution of atmospheric forcing affect simulated LKFs as much as the model's sea ice rheology and numerics. Only in very high resolution simulations (≤2km) the concentration and thickness anomalies along LKFs are large enough to affect air-ice-ocean interaction processes.</p>

Winter Oceanic Response During Strong Wind Events Around Southeastern Greenland in the Regional Arctic System Model (RASM) for 1990-2010

Modeling the Arctic Atmosphere with the Regional Arctic Climate Model (RACM)

A coupled atmosphere - ocean - sea ice - land regional Arctic climate model (RACM) has recently b... more A coupled atmosphere - ocean - sea ice - land regional Arctic climate model (RACM) has recently been developed. The atmospheric model used in RACM is the Weather Research and Forecasting (WRF) model. The ocean and sea ice models are the same as those used in the NCAR Community Climate System Model (CCSM3), although used on a regional domain, and are the Los Alamos National Laboratory POP ocean model and CICE sea model. Land surface processes and hydrology are represented by the Variable Infiltration Capacity (VIC) model. These four climate system component models are coupled using the NCAR CCSM coupler CPL7. Initial results from this model will be presented that emphasize the model's ability to simulate the full annual cycle of atmosphere and land state. Results from a ten-year (1989-1999) RACM simulation will be presented and compared with uncoupled WRF-only simulations. The comparison will highlight differences between the atmosphere-land and fully coupled simulations. Future ...