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Your search keyword '"JOHN, G. W."' showing total 9 results
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9 results on '"JOHN, G. W."'

4. Inland lake temperature initialization via coupled cycling with atmospheric data assimilation

Author

Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley

Subjects
General Medicine
Abstract

Application of lake models coupled within earth-system prediction models, especially for predictions from days to weeks, requires accurate initialization of lake temperatures. Commonly used methods to initialize lake temperatures include interpolation of global sea-surface temperature (SST) analyses to inland lakes, daily satellite-based observations, or model-based reanalyses. However, each of these methods have limitations in capturing the temporal characteristics of lake temperatures (e.g., effects of anomalously warm or cold weather) for all lakes within a geographic region and/or during extended cloudy periods. An alternative lake-initialization method was developed which uses two-way-coupled cycling of a small-lake model within an hourly data assimilation system of a weather prediction model. The lake model simulated lake temperatures were compared with other estimates from satellite and in situ observations and interpolated-SST data for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake surface temperature from as much as 5–10 K vs. interpolated-SST data to about 1–2 K compared to available in situ and satellite observations.

Published
2022

6. Inland lake temperature initialization via cycling with atmospheric data assimilation

Author

Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley

Abstract

Application of lake models coupled within earth-system prediction models, especially for short-term predictions from days to weeks, requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within an hourly updated weather prediction model to constrain lake temperature evolution. We compare these simulated lake temperature values with other estimates from satellite and in situ and interpolated-SST data sets for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake temperature from as much as 5–10 K (using interpolated-SST data) to about 1–2 K (comparing with available in situ and satellite observations.

Published
2022

8. Inland lake temperature initialization via cycling with atmospheric data assimilation.

Author

Benjamin, Stanley G., Smirnova, Tatiana G., James, Eric P., Anderson, Eric J., Fujisaki-Manome, Ayumi, Kelley, John G. W., Mann, Greg E., Gronewold, Andrew D., Chu, Philip, and Kelley, Sean G. T.

Subjects
WATER temperature, WEATHER forecasting, PREDICTION models
Abstract

Application of lake models coupled within earth-system prediction models, especially for short-term predictions from days to weeks, requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within an hourly updated weather prediction model to constrain lake temperature evolution. We compare these simulated lake temperature values with other estimates from satellite and in situ and interpolated-SST data sets for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake temperature from as much as 5-10 K (using interpolated-SST data) to about 1-2 K (comparing with available in situ and satellite observations. [ABSTRACT FROM AUTHOR]

Published
2022
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9. Improving Flood Forecast Guidance for Ports in the Great Lakes Using a Linked Hydrologic-Hydrodynamic Framework.

Author

Fitzpatrick, Lindsay, Titze, Dan, Beletsky, Dmitry, Anderson, Eric J., and Kelley, John G. W.

Subjects
GREAT Lakes (North America), UNITED States. National Oceanic & Atmospheric Administration
Abstract

The NOAA Great Lakes Operational Forecast System (GLOFS), based on the Finite-Volume Community Ocean Model (FVCOM), provides water forecast guidance across the Great Lakes, however, it does not include harbors and navigational ports. While GLOFS does include inflow from some gauged streams, large volumes of water entering the lakes through tributaries are not being accounted for. To examine the benefits of including model coverage over marine infrastructures, a linked hydrologic-hydrodynamic framework was developed for the Twin Ports of Duluth-Superior in western Lake Superior. Simulated streamflow from the National Water Model (NWM) was injected into an extended wet-dry FVCOM grid that covered the harbor and surrounding floodplain. Test cases were conducted for severe flooding events caused by heavy rainfall and/or storm surges to see if the one-way coupled models could capture coastal flooding. Model results compared well against time-series of water level, with root mean square error (RMSE) and bias values small relative to the typical fluctuations. Inclusion of streamflow for NWM-simulated tributaries improved the accuracy of modeled water levels in the harbor and increased simulated current speeds in navigational channels by up to 0.4 ms-1. Modeled inundation and flood extent in the floodplain closely matched surveys conducted in response to a record flood event in 2012. The results demonstrate the capability of the modeling framework to provide flood guidance in a complex coastal setting in the Great Lakes region. [ABSTRACT FROM AUTHOR]

Published
2023

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