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An extraordinary strong wind‐driven upwelling event occurred in Lake Superior in summer of 2010 when the lake was strongly stratified. In this paper, a detailed three‐dimensional (3‐D) investigation of the current and thermal structures during the upwelling event was conducted using in situ observations, remote sensing products, and the results of a long‐term numerical simulation. A 3‐D finite‐volume coupled ice–ocean model tailored for the Laurentian Great Lakes was employed for this purpose. The model was validated with temperature observations at National Oceanic and Atmospheric Administration buoys and mooring data from 2010. The upwelling event observed in satellite imagery and at a mooring station was reproduced by the model, showing a cooling of as much as 10°C in August 2010 along the northwestern coast. The relationship between the alongshore wind and the offshore thermocline displacement (upwelling front) derived in theoretical work (Csanady, 1977, https://doi.org/10.1029/JC082i003p00397) was used to calculate upwelling front movement offshore and found to be in in close agreement with model prediction. A significant correlation between alongshore wind stress and lake temperature change in the upwelling zone was found with a correlation coefficient of −0.87. A simple linear heat balance model explained most of variability in temperature. Plain Language Summary: An extraordinary strong upwelling event observed during summer 2010 in Lake Superior was reproduced by a numerical ocean model. A detailed three‐dimensional (3‐D) investigation of the current and thermal structures during the upwelling event was conducted using in situ observations, remote sensing products, and the results of a long‐term numerical simulation. A 4‐day long strong, persistent alongshore wind was the major driving force of this event. A significant correlation between alongshore wind stress and lake temperature change in the upwelling zone was found. A simple linear heat balance model explained most of variability in temperature measurements. The relationship between the alongshore wind and the offshore displacement of the upwelling front derived in theoretical work was used to calculate upwelling front movement offshore and found to be in in close agreement with model prediction. Key Points: An extraordinarily strong upwelling event observed during summer 2010 in Lake Superior was reproduced by a coupled ice–ocean modelStrong correlation between lake surface temperature change in the upwelling zone and alongshore wind stress was found (with a correlation coefficient of −0.87); a simple linear heat balance model explained most of time rate of change in temperatureOffshore thermocline displacement (upwelling front) in the model was in good agreement with predictions of an analytical model that employed alongshore wind and initial thermal structure [ABSTRACT FROM AUTHOR]

Efficient management and prevention of species invasions requires accurate prediction of where species of concern can arrive and persist. Species distribution models provide one way to identify potentially suitable habitat by developing the relationship between climate variables and species occurrence data. However, these models when applied to freshwater invasions are complicated by two factors. The first is that the range expansions that typically occur as part of the invasion process violate standard species distribution model assumptions of data stationarity. Second, predicting potential range of freshwater aquatic species is complicated by the reliance on terrestrial climate measurements to develop occurrence relationships for species that occur in aquatic environments. To overcome these obstacles, we combined a recently developed algorithm for species distribution modeling—range bagging—with newly available aquatic habitat-specific information from the North American Great Lakes region to predict suitable habitat for three potential invasive species: golden mussel, killer shrimp, and northern snakehead. Range bagging may more accurately predict relative suitability than other methods because it focuses on the limits of the species environmental tolerances rather than central tendency or “typical” cases. Overlaying the species distribution model output with aquatic habitat-specific data then allowed for more specific predictions of areas with high suitability. Our results indicate there is suitable habitat for northern snakehead in the Great Lakes, particularly shallow coastal habitats in the lower four Great Lakes where literature suggests they will favor areas of wetland and submerged aquatic vegetation. These coastal areas also offer the highest suitability for golden mussel, but our models suggest they are marginal habitats. Globally, the Great Lakes provide the closest match to the currently invaded range of killer shrimp, but they appear to pose an intermediate risk to the region. Range bagging provided reliable predictions when assessed either by a standard test set or by tests for spatial transferability, with golden mussel being the most difficult to accurately predict. Our approach illustrates the strength of combining multiple sources of data, while reiterating the need for increased measurement of freshwater habitat at high spatial resolutions to improve the ability to predict potential invasive species. [ABSTRACT FROM AUTHOR]

1. Hypoxia occurs seasonally in many stratified coastal marine and freshwater ecosystems when bottom dissolved oxygen (DO) concentrations are depleted below 2-3 mg O L. 2. We evaluated the effects of hypoxia on fish habitat quality in the central basin of Lake Erie from 1987 to 2005, using bioenergetic growth rate potential (GRP) as a proxy for habitat quality. We compared the effect of hypoxia on habitat quality of (i) rainbow smelt, Osmerus mordax mordax Mitchill (young-of-year, YOY, and adult), a cold-water planktivore, (ii) emerald shiner, Notropis atherinoides Rafinesque (adult), a warm-water planktivore, (iii) yellow perch, Perca flavescens Mitchill (YOY and adult), a cool-water benthopelagic omnivore and (iv) round goby Neogobius melanostomus Pallas (adult) a eurythermal benthivore. Annual thermal and DO profiles were generated from 1D thermal and DO hydrodynamics models developed for Lake Erie's central basin. 3. Hypoxia occurred annually, typically from mid-July to mid-October, which spatially and temporally overlaps with otherwise high benthic habitat quality. Hypoxia reduced the habitat quality across fish species and life stages, but the magnitude of the reduction varied both among and within species because of the differences in tolerance to low DO levels and warm-water temperatures. 4. Across years, trends in habitat quality mirrored trends in phosphorus concentration and water column oxygen demand in central Lake Erie. The per cent reduction in habitat quality owing to hypoxia was greatest for adult rainbow smelt and round goby (mean: −35%), followed by adult emerald shiner (mean: −12%), YOY rainbow smelt (mean: −10%) and YOY and adult yellow perch (mean: −8.5%). 5. Our results highlight the importance of differential spatiotemporally interactive effects of DO and temperature on relative fish habitat quality and quantity. These effects have the potential to influence the performance of individual fish species as well as population dynamics, trophic interactions and fish community structure. [ABSTRACT FROM AUTHOR]

In this paper we develop and examine several schemes for combining daily images obtained from the Sea-viewing Wide Field Spectrometer (SeaWiFS) with a two-dimensional sediment transport model of Lake Michigan. We consider two data assimilation methods, direct insertion and a kriging-based approach, and perform a forecasting study focused on a 2-month period in spring 1998 when a large storm caused substantial amounts of sediment resuspension and horizontal sediment transport in the lake. By beginning with the simplest possible forecast method and sequentially adding complexity we are able to assess the improvements offered by combining the satellite data with the numerical model. In our application, we find that data assimilation schemes that include both the data and the lake dynamics improve forecast root mean square error by 40% over purely model-based approaches and by 20% over purely data-based approaches. [ABSTRACT FROM AUTHOR]

We present a method for assimilating current observations into a two-dimensional circulation model of Lake Michigan, based on the Princeton Ocean Model (POM) and driven by observed winds. Because measurements of surface level are not available, we require that the point-wise update to the forecast horizontal current does not change the forecast surface level. This requirement makes it possible to represent the current updates by a stream function. Given an appropriate covariance model of this stream function, the current updates are calculated by kriging interpolation using the observations and the corresponding model forecast. It is further required that the current updates do not create cross-shore flows; this is represented by the stream function being constant along the coastline and is enforced by incorporating pseudo coastal data into the interpolation. This eliminates the need to construct complex spatial covariance models for the stream function. The method also accommodates observational errors. Results show that the method successfully melds observations into the model, and the influence of data assimilation propagates in space and time. [ABSTRACT FROM AUTHOR]