Generation of Three-Dimensional Lake Model Forecasts for Lake Erie*

Abstract

A one-way coupled atmospheric-lake modeling system was developed to generate short-term, mesoscale lake circulation, water level, and temperature forecasts for Lake Erie. The coupled system consisted of the semioperational versions of the Pennsylvania State University-National Center for Atmospheric Research threedimensional, mesoscale meteorological model (MM4), and the three-dimensional lake circulation model of the Great Lakes Forecasting System (GLFS). The coupled system was tested using archived MM4 36-h forecasts for three cases during 1992 and 1993. The cases were chosen to demonstrate and evaluate the forecasts produced by the coupled system during severe lake conditions and at different stages in the lake's annual thermal cycle. For each case, the lake model was run for 36 h using surface heat and momentum fluxes derived from MM4's hourly meteorological forecasts and surface water temperatures from the lake model. Evaluations of the lake forecasts were conducted by comparing forecasts to observations and lake model hindcasts. Lake temperatures were generally predicted well by the coupled system. Below the surface, the forecasts depicted the evolution of the lake's thermal structure, although not as rapidly as in the hindcasts. The greatest shortcomings were in the predictions of peak water levels and times of occurrence. The deficiencies in the lake forecasts were related primarily to wind direction errors and underestimation of surface wind speeds by the atmospheric model. The three cases demonstrated both the potential and limitations of daily high-resolution lake forecasts for the Great Lakes. Twice daily or more frequent lake forecasts are now feasible for Lake Erie with the operational implementation of mesoscale atmospheric models such as the U.S. National Weather Service's Eta Model and Rapid Update Cycle.

Coastline change detection using remote sensing

“…This can be achieved, for example, by histogram thresholding on one of the infrared bands of TM or ETM+ imagery. Experience has shown that of the six reflective TM bands, midinfrared band 5 is the best for extracting the land-water interface (Kelley, et al, 1998). Band 5 exhibits a strong contrast between land and water features due to the high degree of absorption of mid-infrared energy by water (even turbid water) and strong reflectance of midinfrared by vegetation and natural features in this range.…”

A multi-temporal remote sensing approach for monitoring changes in spatial extent of freshwater lake of Deepor Beel Ramsar Site, a major wetland of Assam

“…r wetland identification is band 5 because of its ability to discriminate land-water interface (Kelley et al 1998). Landsat TM bands 3, 4, and 5 are usually the best combination of bands he three bands data of Landsat TM is used and is density sliced interactively with the study rea FCC, such that the pixels having gray values corresponding only water bodies are identified.…”

A three-dimensional model of water circulation and temperature structure in the Caspian Sea

“…The process is chosen from 0 to 6 o'clock, 6 to 12 in time steps ∆t=3600 second. The distribution function is measured and the horizontal velocity, when repeated, can be measured by equation (8). As the explicit method has been used, all the location properties are approximated through the central difference method.…”

“…Casandy (1971-73) and Bennet and Simins (1979), present an understanding of the limitations and stability of these models in large scales. The presentation was done through the analytical studies upon which the later researches on the lake modeling were conducted [1,2,4,6,8,10]. These models were mostly utilized for Michigan, Ontario, Erie, lakes.…”