Johnson Mark

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  • Article
    Recent advances in Arctic ocean studies employing models from the Arctic Ocean Model Intercomparison Project
    (Oceanography Society, 2011-09) Proshutinsky, Andrey ; Aksenov, Yevgeny ; Kinney, Jaclyn Clement ; Gerdes, Rudiger ; Golubeva, Elena ; Holland, David ; Holloway, Greg ; Jahn, Alexandra ; Johnson, Mark ; Popova, Ekaterina E. ; Steele, Michael ; Watanabe, Eiji
    Observational data show that the Arctic Ocean has significantly and rapidly changed over the last few decades, which is unprecedented in the observational record. Air and water temperatures have increased, sea ice volume and extent have decreased, permafrost has thawed, storminess has increased, sea level has risen, coastal erosion has progressed, and biological processes have become more complex and diverse. In addition, there are socio-economic impacts of Arctic environmental change on Arctic residents and the world, associated with tourism, oil and gas exploration, navigation, military operations, trade, and industry. This paper discusses important results of the Arctic Ocean Model Intercomparison Project, which is advancing the role of numerical modeling in Arctic Ocean and sea ice research by stimulating national and international synergies for high-latitude research.
  • Article
    Arctic decadal variability from an idealized atmosphere-ice-ocean model: 1. Model description, calibration, and validation
    (American Geophysical Union, 2006-06-20) Dukhovskoy, Dmitry S. ; Johnson, Mark A. ; Proshutinsky, Andrey
    This paper describes a simple “multibox” model of the Arctic atmosphere-ice-ocean system. The model consists of two major modules (an Arctic module and a Greenland Sea module) and several sub-modules. The Arctic module includes a shelf box model coupled with a thermodynamic sea ice model, and an Arctic Ocean model coupled with a sea ice model and an atmospheric box model. The Greenland Sea module includes an oceanic model coupled with a sea ice model and a statistical model of surface air temperature over the Greenland Sea. The full model is forced by daily solar radiation, wind stress, river runoff, and Pacific Water inflow through Bering Strait. For validation purposes, results from model experiments reproducing seasonal variability of the major system parameters are analyzed and compared with observations and other models. The model reproduces the seasonal variability of the Arctic system reasonably well and is used to investigate decadal Arctic climate variability in Part 2 of this publication.
  • Article
    Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models
    (American Geophysical Union, 2012-03-15) Johnson, Mark ; Proshutinsky, Andrey ; Aksenov, Yevgeny ; Nguyen, An T. ; Lindsay, Ron ; Haas, Christian ; Zhang, Jinlun ; Diansky, Nikolay ; Kwok, Ron ; Maslowski, Wieslaw ; Hakkinen, Sirpa M. A. ; Ashik, Igor M. ; de Cuevas, Beverly
    Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004–2008); airborne electromagnetic measurements (2001–2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992–2008) and from submarines (1975–2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982–1986) and coastal stations (1998–2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than ∼2 m and underestimate the thickness of ice measured thicker than about ∼2 m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25–30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.
  • Technical Report
    Report on the Acoustic Network Arctic Deployment, March 1994
    (Woods Hole Oceanographic Institution, 1995-03) Johnson, Mark ; Herold, David ; Catipovic, Josko A.
    This report describes the March 1994 Arctic deployment undertaken by the Acoustic Telemetry Group of WHOI. The deployment was a part of the 1994 Sea Ice Mechanics Initiative (SIMI) project and was based at the west SIMI camp, approximately 150 nautical miles north-east of Prudhoe Bay, Alaska. The goal of the deployment was to install a network of six high-performance acoustic modems, developed at WHOI, and to obtain a data set demonstrating the communications and acoustic monitoring capabilties of the network. The six modems in the network were deployed over an area of 22 square km and communicated via radio Ethernet with a computer at the SIMI camp. Each model had a global positioning system, an acoustic source and an 8 element receiving array. The network was operated in a round-robin broadcast mode (i.e., each modem in turn transmitted a packet of data while the others received). The transmissions were 5000 bits-per-second QPSK with a 15kHz carrier. An extensive data set including raw acoustic data source localization information, and modem position was collected during the deployment. An additional function of the acoustic network was to communicate with, and track, the Odyssey, an autonomous underwater vehicle operated by the MIT group at the SIMI camp. To this end, the Odyssey was equipped with a Datasonics modem configured for periodic QPSK transmission to the network. A data set was obtained from which both the up-link communication and localization capabilties of the network can be determined.
  • Article
    Arctic decadal variability from an idealized atmosphere-ice-ocean model : 2. Simulation of decadal oscillations
    ( 2006-06-20) Dukhovskoy, Dmitry S. ; Johnson, Mark A. ; Proshutinsky, Andrey
    A simple model of the Arctic Ocean and Greenland Sea, coupled to a thermodynamic sea ice model and an atmospheric model, has been used to study decadal variability of the Arctic ice-ocean-atmosphere climate system. The motivating hypothesis is that the behavior of the modeled and ultimately the real climate system is auto-oscillatory with a quasi-decadal periodicity. This system oscillates between two circulation regimes: the Anticyclonic Circulation Regime (ACCR) and the Cyclonic Circulation Regime (CCR). The regimes are controlled by the atmospheric heat flux from the Greenland Sea and the freshwater flux from the Arctic Ocean. A switch regulating the intensity of the fluxes between the Arctic Ocean and Greenland Sea that depends on the inter-basin gradient of dynamic height is implemented as a delay mechanism in the model. This mechanism allows the model system to accumulate the “perturbation” over several years. After the perturbation has been released, the system returns to its initial state. Solutions obtained from numerical simulations with seasonally varying forcing, for scenarios with high and low interaction between the regions, reproduced the major anomalies in the ocean thermohaline structure, sea ice volume, and fresh water fluxes attributed to the ACCR and CCR.