TY - GEN
T1 - Comparison of Mesoscale Model Setups for Offshore Wind Resource Assessment: A New Jersey Case Study
AU - Optis, Michael
AU - Kumler, Andrew
AU - Moriarty, Patrick
AU - Scott, George
AU - Musial, Walter
AU - Draxl, Caroline
AU - Brodie, Joseph
AU - Miles, Travis
PY - 2019
Y1 - 2019
N2 - As the offshore wind energy industry begins to emerge on the U.S. northeast coast, there is an urgent need for an accurate characterization of the offshore wind resource. The offshore regime features various resource characteristics not seen onshore, including frequent coastal low-level jets, non-steady surface conditions (e.g. waves), complex air-sea and land-sea interactions, and coastal mesoscale circulations (e.g. sea breeze). An accurate characterization of these phenomena in mesoscale models is critical to support accurate energy production estimates and forecasting for future offshore wind farms. However, a robust validation of mesoscale model performance in the offshore U.S. has been limited due to sparse data and difficulty obtaining offshore measurements. Consequently, it is unclear how mesoscale models perform offshore and which suite of parameterizations and input data are best suited for accurate resource characterization. To begin addressing this knowledge gap, the National Renewable Energy Laboratory, in collaboration with the Rutgers Center for Ocean Observing Leadership, conducted a mesoscale model validation campaign in the offshore environment. The Weather Research and Forecasting (WRF) model was assessed and the New Jersey offshore coastal area served as the validation domain. An ensemble of WRF simulations conducted over a one-year period sampled from a range of model setups, including different reanalysis and forecast data inputs, sea surface temperature data inputs, planetary boundary layer parameterizations, and WRF versions. The performance of each ensemble member was validated against a network of observations including offshore floating lidars, coastal met towers, offshore platform measurements, and offshore buoys. Model performance was assessed on annual, seasonal, and diurnal scales with particular emphasis on the vertical wind speed profile and temperature stratification. Preliminary results from this validation work will be presented here. The key WRF inputs and parameters driving changes in the modeled wind resource will be discussed and preliminary recommendations on WRF setups for offshore wind resource modeling will be proposed. The application of this validation exercise to other proposed offshore wind energy areas in the U.S. will also be discussed. mesoscale circulations (e.g. sea breeze). An accurate characterization of these phenomena in mesoscale models is critical to support accurate energy production estimates and forecasting for future offshore wind farms. However, a robust validation of mesoscale model performance in the offshore U.S. has been limited due to sparse data and difficulty obtaining offshore measurements. Consequently, it is unclear how mesoscale models perform offshore and which suite of parameterizations and input data are best suited for accurate resource characterization. To begin addressing this knowledge gap, the National Renewable Energy Laboratory, in collaboration with the Rutgers Center for Ocean Observing Leadership, conducted a mesoscale model validation campaign in the offshore environment. The Weather Research and Forecasting (WRF) model was assessed and the New Jersey offshore coastal area served as the validation domain. An ensemble of WRF simulations conducted over a one-year period sampled from a range of model setups, including different reanalysis and forecast data inputs, sea surface temperature data inputs, planetary boundary layer parameterizations, and WRF versions. The performance of each ensemble member was validated against a network of observations including offshore floating lidars, coastal met towers, offshore platform measurements, and offshore buoys. Model performance was assessed on annual, seasonal, and diurnal scales with particular emphasis on the vertical wind speed profile and temperature stratification. Preliminary results from this validation work will be presented here. The key WRF inputs and parameters driving changes in the modeled wind resource will be discussed and preliminary recommendations on WRF setups for offshore wind resource modeling will be proposed. The application of this validation exercise to other proposed offshore wind energy areas in the U.S. will also be discussed.
AB - As the offshore wind energy industry begins to emerge on the U.S. northeast coast, there is an urgent need for an accurate characterization of the offshore wind resource. The offshore regime features various resource characteristics not seen onshore, including frequent coastal low-level jets, non-steady surface conditions (e.g. waves), complex air-sea and land-sea interactions, and coastal mesoscale circulations (e.g. sea breeze). An accurate characterization of these phenomena in mesoscale models is critical to support accurate energy production estimates and forecasting for future offshore wind farms. However, a robust validation of mesoscale model performance in the offshore U.S. has been limited due to sparse data and difficulty obtaining offshore measurements. Consequently, it is unclear how mesoscale models perform offshore and which suite of parameterizations and input data are best suited for accurate resource characterization. To begin addressing this knowledge gap, the National Renewable Energy Laboratory, in collaboration with the Rutgers Center for Ocean Observing Leadership, conducted a mesoscale model validation campaign in the offshore environment. The Weather Research and Forecasting (WRF) model was assessed and the New Jersey offshore coastal area served as the validation domain. An ensemble of WRF simulations conducted over a one-year period sampled from a range of model setups, including different reanalysis and forecast data inputs, sea surface temperature data inputs, planetary boundary layer parameterizations, and WRF versions. The performance of each ensemble member was validated against a network of observations including offshore floating lidars, coastal met towers, offshore platform measurements, and offshore buoys. Model performance was assessed on annual, seasonal, and diurnal scales with particular emphasis on the vertical wind speed profile and temperature stratification. Preliminary results from this validation work will be presented here. The key WRF inputs and parameters driving changes in the modeled wind resource will be discussed and preliminary recommendations on WRF setups for offshore wind resource modeling will be proposed. The application of this validation exercise to other proposed offshore wind energy areas in the U.S. will also be discussed. mesoscale circulations (e.g. sea breeze). An accurate characterization of these phenomena in mesoscale models is critical to support accurate energy production estimates and forecasting for future offshore wind farms. However, a robust validation of mesoscale model performance in the offshore U.S. has been limited due to sparse data and difficulty obtaining offshore measurements. Consequently, it is unclear how mesoscale models perform offshore and which suite of parameterizations and input data are best suited for accurate resource characterization. To begin addressing this knowledge gap, the National Renewable Energy Laboratory, in collaboration with the Rutgers Center for Ocean Observing Leadership, conducted a mesoscale model validation campaign in the offshore environment. The Weather Research and Forecasting (WRF) model was assessed and the New Jersey offshore coastal area served as the validation domain. An ensemble of WRF simulations conducted over a one-year period sampled from a range of model setups, including different reanalysis and forecast data inputs, sea surface temperature data inputs, planetary boundary layer parameterizations, and WRF versions. The performance of each ensemble member was validated against a network of observations including offshore floating lidars, coastal met towers, offshore platform measurements, and offshore buoys. Model performance was assessed on annual, seasonal, and diurnal scales with particular emphasis on the vertical wind speed profile and temperature stratification. Preliminary results from this validation work will be presented here. The key WRF inputs and parameters driving changes in the modeled wind resource will be discussed and preliminary recommendations on WRF setups for offshore wind resource modeling will be proposed. The application of this validation exercise to other proposed offshore wind energy areas in the U.S. will also be discussed.
KW - mesoscale model uncertainty
KW - mesoscale models
KW - New Jersey
KW - offshore development
KW - offshore wind resource assessment
KW - Rutgers University
M3 - Presentation
T3 - Presented at the AMS Annual Meeting, 6-10 January 2019, Phoenix, Arizona
ER -