On the simulation of Laurentian Great Lakes water levels under projections of global climate change

Mackay, Murray; Seglenieks, Frank

doi:10.1007/s10584-012-0560-z

Cited by 38 publications

(26 citation statements)

References 23 publications

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“…Studies based on Bchange factor^method applied to a suite of models generally lead to the conclusion that Great Lake water levels may significantly decline in future climate. However, RCM based studies suggest small decrease or even increase in the future levels (MacKay and Seglenieks 2013;Lofgren 2004). The present study complements existing efforts to quantify present and future Great Lakes NBS using RCMs.…”

Section: Discussionmentioning

confidence: 99%

“…Studies by Manabe et al (2004) and Milly et al (2005) based on GCM output suggest an increase in Great Lakes net outflow and consequently increasing water supply. Lofgren (2004) and MacKay and Seglenieks (2013), who promoted the use of Regional Climate Models (RCMs) in evaluating potential changes in the Great Lakes NBS, project less dramatic declines in water levels compared to Bchange factor^based studies. This study is a contribution to regional climate modeling effort over the Great Lakes region.…”

Section: Introductionmentioning

confidence: 99%

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Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

et al. 2015

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Regional climate modelling represents an appealing approach to projecting Great Lakes water supplies under a changing climate. In this study, we investigate the response of the Great Lakes Basin to increasing greenhouse gas and aerosols emissions using an ensemble of sixteen climate change simulations generated by three different Regional Climate Models (RCMs): CRCM4, HadRM3 and WRFG. Annual and monthly means of simulated hydrometeorological variables that affect Great Lakes levels are first compared to observation-based estimates. The climate change signal is then assessed by computing differences between simulated future (2041-2070) and present (1971-1999) climates. Finally, an analysis of the annual minima and maxima of the Net Basin Supply (NBS), derived from the simulated NBS components, is conducted using Generalized Extreme Value distribution. Results reveal notable model differences in simulated water budget components throughout the year, especially for the lake evaporation component. These differences are reflected in the resulting NBS. Although uncertainties in observation-based estimates are quite large, our analysis indicates that all three RCMs tend to underestimate NBS in late summer and fall, which is related to biases in simulated runoff, lake evaporation, and over-lake precipitation. The climate change signal derived from the total ensemble mean indicates no change in future mean annual NBS. However, our analysis suggests an amplification of the NBS annual cycle and an intensification of the annual NBS minima in future climate. This emphasizes the need for an adaptive management of water to minimize potential negative implications associated with more severe and frequent NBS minima.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

et al. 2015

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“…The intense convection and the strong local atmospheric respond through lake-effect precipitation [25]. The climate teleconnection patterns, such as the North Atlantic Oscillation (NAO), the Arctic Oscillation (AO), and the El Niño-Southern Oscillation (ENSO) might also impact on the Great Lakes ice cover [26][27][28][29][30][31][32]. Many studies show the significant impacts of the ENSO including the increasing gustiness of winds (e.g., Li et al [31]; Enloe et al [30]) and ice cover (e.g., Bix et al [27], Assel and Rodionov [26].…”

Section: The Great Lakes Turbulent Fluxesmentioning

confidence: 99%

The Estimation of the North American Great Lakes Turbulent Fluxes Using Satellite Remote Sensing and MERRA Reanalysis Data

Moukomla

Blanken

2017

Remote Sensing

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Abstract:This study provides the first technique to investigate the turbulent fluxes over the Great Lakes from July 2001 to December 2014 using a combination of data from satellite remote sensing, reanalysis data sets, and direct measurements. Turbulent fluxes including latent heat flux (Q E ) and sensible heat flux (Q H ) were estimated using the bulk aerodynamic approach, then compared with the direct eddy covariance measurements from the rooftop of three lighthouses-Stannard Rock Lighthouse (SR) in Lake Superior, White Shoal Lighthouse (WS) in Lake Michigan, and Spectacle Reef Lighthouse (SP) in Lake Huron. The relationship between modeled and measured Q E and Q H were in a good statistical agreement, for Q E , R 2 varied from 0.41 (WS), 0.74 (SR), and 0.87 (SP) with RMSE of 5.68, 6.93, and 4.67 W·m −2 , respectively, while Q H , R 2 ranged from 0.002 (WS), 0.8030 (SP) and 0.94 (SR) with RMSE of 6.97, 4.39 and 4.90 W·m −2 respectively. Both monthly mean Q E and Q H were highest in January for all lakes except Lake Ontario, which was highest in early December. The turbulent fluxes then sharply drop in March and are negligible during June and July. The evaporation processes continue again in August.

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“…Simulation-based schemes provide a basis to move forward; however, modifications are required to relax prognostic inputs and to represent the thermal and evap-78 A. Nazemi and H. S. Wheater: On inclusion of water resource management in Earth system models -Part 2 orative functions of reservoirs for online applications. Modeling schemes have already been developed for representing energy balance of natural lakes at sub-grid scale (e.g., MacKay, 2011;MacKay and Seglenieks, 2013) and can be merged with improved simulationbased reservoir operation algorithms to simultaneously characterize reservoir release, storage and evaporation as well as land-atmospheric feedbacks. However, an important question remains in how to address substantial biases in estimation of reservoir release due to the uncertainty in estimation of reservoir inflows, particularly in online simulations.…”

Section: Water Resource Management Algorithmsmentioning

confidence: 99%

On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling

Nazemi

Wheater

2015

Hydrol. Earth Syst. Sci.

114

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Abstract. Human water use has significantly increased during the recent past. Water withdrawals from surface and groundwater sources have altered terrestrial discharge and storage, with large variability in time and space. These withdrawals are driven by sectoral demands for water, but are commonly subject to supply constraints, which determine water allocation. Water supply and allocation, therefore, should be considered together with water demand and appropriately included in Earth system models to address various large-scale effects with or without considering possible climate interactions. In a companion paper, we review the modeling of demand in large-scale models. Here, we review the algorithms developed to represent the elements of water supply and allocation in land surface and global hydrologic models. We note that some potentially important online implications, such as the effects of large reservoirs on land-atmospheric feedbacks, have not yet been fully investigated. Regarding offline implications, we find that there are important elements, such as groundwater availability and withdrawals, and the representation of large reservoirs, which should be improved. We identify major sources of uncertainty in current simulations due to limitations in data support, water allocation algorithms, host large-scale models as well as propagation of various biases across the integrated modeling system. Considering these findings with those highlighted in our companion paper, we note that advancements in computation and coupling techniques as well as improvements in natural and anthropogenic process representation and parameterization in host large-scale models, in conjunction with remote sensing and data assimilation can facilitate inclusion of water resource management at larger scales. Nonetheless, various modeling options should be carefully considered, diagnosed and intercompared. We propose a modular framework to develop integrated models based on multiple hypotheses for data support, water resource management algorithms and host models in a unified uncertainty assessment framework. A key to this development is the availability of regional-scale data for model development, diagnosis and validation. We argue that the time is right for a global initiative, based on regional case studies, to move this agenda forward.

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On the simulation of Laurentian Great Lakes water levels under projections of global climate change

Cited by 38 publications

References 23 publications

Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

The Estimation of the North American Great Lakes Turbulent Fluxes Using Satellite Remote Sensing and MERRA Reanalysis Data

On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling

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