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  • 1
    Online Resource
    Online Resource
    Structure of a Low-Level Jet over Lower Cook Inlet, Alaska
    American Meteorological Society ; 1990
    In:  Monthly Weather Review Vol. 118, No. 12 ( 1990-12), p. 2568-2578
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 118, No. 12 ( 1990-12), p. 2568-2578
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/1520-0493(1990)118〈2568:SOALLJ〉2.0.CO;2
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 1990
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  • 2
    Online Resource
    Online Resource
    Evaluating the performance of Gulf of Alaska walleye pollock (Theragra chalcogramma) recruitment forecasting models using a Monte Carlo resampling strategy
    Canadian Science Publishing ; 2009
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 66, No. 3 ( 2009-03), p. 367-381
    Details
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 66, No. 3 ( 2009-03), p. 367-381
    Abstract: Multiple linear regressions (MLRs), generalized additive models (GAMs), and artificial neural networks (ANNs) were compared as methods to forecast recruitment of Gulf of Alaska walleye pollock ( Theragra chalcogramma ). Each model, based on a conceptual model, was applied to a 41-year time series of recruitment, spawner biomass, and environmental covariates. A subset of the available time series, an in-sample data set consisting of 35 of the 41 data points, was used to fit an environment-dependent recruitment model. Influential covariates were identified through statistical variable selection methods to build the best explanatory recruitment model. An out-of-sample set of six data points was retained for model validation. We tested each model’s ability to forecast recruitment by applying them to an out-of-sample data set. For a more robust evaluation of forecast accuracy, models were tested with Monte Carlo resampling trials. The ANNs outperformed the other techniques during the model fitting process. For forecasting, the ANNs were not statistically different from MLRs or GAMs. The results indicated that more complex models tend to be more susceptible to an overparameterization problem. The procedures described in this study show promise for building and testing recruitment forecasting models for other fish species.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    URL: Article
    DOI: 10.1139/F08-203
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2009
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  • 3
    Online Resource
    Online Resource
    Comparative analysis of statistical tools to identify recruitment–environment relationships and forecast recruitment strength
    Oxford University Press (OUP) ; 2005
    In:  ICES Journal of Marine Science Vol. 62, No. 7 ( 2005-01-01), p. 1256-1269
    Details
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 62, No. 7 ( 2005-01-01), p. 1256-1269
    Abstract: Many of the factors affecting recruitment in marine populations are still poorly understood, complicating the prediction of strong year classes. Despite numerous attempts, the complexity of the problem often seems beyond the capabilities of traditional statistical analysis paradigms. This study examines the utility of four statistical procedures to identify relationships between recruitment and the environment. Because we can never really know the parameters or underlying relationships of actual data, we chose to use simulated data with known properties and different levels of measurement error to test and compare the methods, especially their ability to forecast future recruitment states. Methods examined include traditional linear regression, non-linear regression, Generalized Additive Models (GAM), and Artificial Neural Networks (ANN). Each is compared according to its ability to recover known patterns and parameters from simulated data, as well as to accurately forecast future recruitment states. We also apply the methods to published Norwegian spring-spawning herring (Clupea harengus L.) spawner–recruit–environment data. Results were not consistently conclusive, but in general, flexible non-parametric methods such as GAMs and ANNs performed better than parametric approaches in both parameter estimation and forecasting. Even under controlled data simulation procedures, we saw evidence of spurious correlations. Models fit to the Norwegian spring-spawning herring data show the importance of sea temperature and spawning biomass. The North Atlantic Oscillation (NAO) did not appear to be an influential factor affecting herring recruitment.
    Type of Medium: Online Resource
    ISSN: 1095-9289 , 1054-3139
    URL: Article
    DOI: 10.1016/j.icesjms.2005.05.018
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2005
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  • 4
    Online Resource
    Online Resource
    Sustaining the marine ecosystem of the Pribilof Domain
    Elsevier BV ; 2008
    In:  Deep Sea Research Part II: Topical Studies in Oceanography Vol. 55, No. 16-17 ( 2008-8), p. 1698-1700
    Details
    In: Deep Sea Research Part II: Topical Studies in Oceanography, Elsevier BV, Vol. 55, No. 16-17 ( 2008-8), p. 1698-1700
    Type of Medium: Online Resource
    ISSN: 0967-0645
    URL: Article
    DOI: 10.1016/j.dsr2.2008.04.023
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2008
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  • 5
    Online Resource
    Online Resource
    A comparison of gradient and observed over‐the‐water winds along a mountainous coast
    American Geophysical Union (AGU) ; 1993
    In:  Journal of Geophysical Research: Oceans Vol. 98, No. C9 ( 1993-09-15), p. 16555-16569
    Details
    In: Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), Vol. 98, No. C9 ( 1993-09-15), p. 16555-16569
    Abstract: Surface winds measured from April 11, 1987, through August 16, 1987, at five locations off the southeastern coast of the Alaska Peninsula indicate the complexity of coastal wind structure as a function of proximity to a mountainous coast. Proxy winds were computed for the same five locations from digitized sea level pressure fields using a simple geotriptic wind model. Shoreward of the Rossby deformation radius, the friction parameters of the geotriptic model vary from their open‐ocean values, slowing the winds and rotating them farther counterclockwise. These changing friction parameters account for the effect of the mountains on the surface wind distribution. Proxy winds and observed surface winds are coherent for periods longer than about 2 days and are better correlated farther seaward from the coast and for northeasterly alongshore winds and southeasterly onshore winds. Estimates of numbers of storms, regional wind stress, and regional vorticity determined from proxy winds are qualitatively accurate.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    URL: Article
    DOI: 10.1029/93JC01506
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 1993
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    SSG: 16,13
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  • 6
    Online Resource
    Online Resource
    Contributions of FOCI research to forecasts of year‐class strength of walleye pollock in Shelikof Strait, Alaska
    Wiley ; 1996
    In:  Fisheries Oceanography Vol. 5, No. s1 ( 1996-03), p. 189-203
    Details
    In: Fisheries Oceanography, Wiley, Vol. 5, No. s1 ( 1996-03), p. 189-203
    Abstract: NOAA's Fisheries Oceanography Coordinated Investigations (FOCI) contributes information to help forecast year‐class strength of walleye pollock (Theragra chalcogramma ) in the Gulf of Alaska. Quantitative estimates of recruitment are obtained from models of stock assessment and stock projection employing information supplied by FOCI. To generate its information, FOCI convenes specialists in marine biology, physical and fisheries oceanography, meteorology, and statistics to assemble and analyse relevant biological and physical time series with respect to recruitment and processes hypothesized to influence fish survival. Statistical methods encompass linear and nonlinear regression, stochastic simulation modelling, transfer function time series modelling, and tree‐modelling regression. The current database consists of 31 years of data, and analyses have identified factors that affect ocean stratification and circulation during spring and summer of the fish's birth year as being important to recruitment. A conceptual model of the recruitment process serves as the framework for a recruitment forecast scheme. A stochastic mathematical simulation model of the conceptual model produces similarities between simulated and observed recruitment time series. FOCI has successfully forecast recruitment observed over the past several years.
    Type of Medium: Online Resource
    ISSN: 1054-6006 , 1365-2419
    URL: Issue
    URL: Article
    DOI: 10.1111/fog.1996.5.issue-s1
    DOI: 10.1111/j.1365-2419.1996.tb00092.x
    Language: English
    Publisher: Wiley
    Publication Date: 1996
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  • 7
    Online Resource
    Online Resource
    Wind drag coefficient over first‐year sea ice in the Bering Sea
    American Geophysical Union (AGU) ; 1983
    In:  Journal of Geophysical Research: Oceans Vol. 88, No. C5 ( 1983-03-30), p. 2845-2852
    Details
    In: Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), Vol. 88, No. C5 ( 1983-03-30), p. 2845-2852
    Abstract: Profiles of relative wind speed and temperature were collected from four levels over rough sea ice in the marginal ice zone of the Bering Sea and used to compute surface wind drag coefficients. Based upon 138 profiles for near‐constant ice conditions, northeast winds of 3–15 m s −1 , and near‐neutral stability, the mean, near‐neutral, 10‐m drag coefficient was 0.00309±0.00049. This is among the largest drag coefficients measured for neutral atmospheric conditions over sea ice. Sixty‐five percent of the variance of this estimate is explained by orientation of the ice floe to the wind; an additional 5% of the variance is explained by wind‐speed dependence. Provided that diabatic atmospheric stability over the Bering Sea ice pack is well correlated with low wind speed, the significant ice‐advecting wind stress on the ice is determined from the neutral value of the drag coefficient, a function of ice roughness length alone. The ice forecaster thus may use remote measurements or estimates of wind speed and surface roughness to assess the wind component of ice advection.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    URL: Article
    DOI: 10.1029/JC088iC05p02845
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 1983
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    detail.hit.zdb_id: 3094181-7
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    detail.hit.zdb_id: 2220777-6
    detail.hit.zdb_id: 3094197-0
    SSG: 16,13
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  • 8
    Online Resource
    Online Resource
    Physical forcing and nutrient conditions associated with patterns of Chl a and phytoplankton productivity in the southeastern Bering Sea during summer
    Elsevier BV ; 2008
    In:  Deep Sea Research Part II: Topical Studies in Oceanography Vol. 55, No. 16-17 ( 2008-8), p. 1745-1760
    Details
    In: Deep Sea Research Part II: Topical Studies in Oceanography, Elsevier BV, Vol. 55, No. 16-17 ( 2008-8), p. 1745-1760
    Type of Medium: Online Resource
    ISSN: 0967-0645
    URL: Article
    DOI: 10.1016/j.dsr2.2008.03.003
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2008
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    detail.hit.zdb_id: 1500312-7
    SSG: 14
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  • 9
    Online Resource
    Online Resource
    Aircraft Observations of Offshore-directed Flow near Wide Bay, Alaska
    American Meteorological Society ; 1993
    In:  Monthly Weather Review Vol. 121, No. 1 ( 1993-01), p. 150-161
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 121, No. 1 ( 1993-01), p. 150-161
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/1520-0493(1993)121〈0150:AOOODF〉2.0.CO;2
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 1993
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    SSG: 14
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  • 10
    Online Resource
    Online Resource
    Offshore-Directed Winds in the Vicinity of Prince William Sound, Alaska
    American Meteorological Society ; 1988
    In:  Monthly Weather Review Vol. 116, No. 6 ( 1988-06), p. 1289-1301
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 116, No. 6 ( 1988-06), p. 1289-1301
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/1520-0493(1988)116〈1289:ODWITV〉2.0.CO;2
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 1988
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    detail.hit.zdb_id: 202616-8
    SSG: 14
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