Contributed by Mark Stoelinga, Arcvera Renewables
The lack of complex terrain in the offshore environment may intuitively steer project developers away from mesoscale modeling to assess the project wind energy resource. However, there are compelling technical reasons indicating that this is not the right course of action. Here is why.
The wind industry has long recognized the technical value of mesoscale numerical weather prediction (“mesoscale modeling”) for wind energy resource assessment. Mesoscale models simulate all atmospheric processes that impact wind farm performance, including transient storm systems and weather fronts, land surface processes, boundary layer heating and turbulence, thermal flows, gravity waves, air-sea interaction, and clouds and precipitation.
For wind energy resource application purposes, when run with a grid of high spatial resolution (
However, the wind industry is also rapidly advancing offshore development and requires accurate wind resource and site suitability estimates in this unique environment. Does the absence of underlying topography and land surface variability in the offshore environment preclude the applicability of mesoscale modeling? The answer is an unequivocal “no”.
There are three critical aspects of the marine environment for which mesoscale modeling offers unique capabilities that lower the uncertainty of wind resource and site suitability estimates in the offshore environment:
1. The stability of the marine environment
Over land, the diurnal cycle of solar heating and nocturnal radiative cooling of the land surface produces large daily oscillations in atmospheric stability, especially in the warm season. Compared to onshore, offshore diurnal heating and cooling are muted, yet stability can vary significantly if the air flowing over the sea is notably warmer or colder than the sea surface temperature. This can often occur, in part due to the seasonal lag of sea-surface warming and cooling compared to land. For example, a warm continental air mass flowing over cold water in the spring and early summer can stabilize the air mass, whereas an arctic air mass flowing southward over warm water in the fall and early winter can destabilize it. Mesoscale models have been designed by the atmospheric research community to properly represent air-sea energy exchange processes and marine boundary layers and have long been used to predict the weather over both land and sea. They are well suited to simulate the evolution of atmospheric stability, turbulence, and wind shear associated with evolving air-sea thermal contrasts in the offshore environment. A critical phenomenon that must be modeled to reasonable accuracy, that is present in mesoscale models but not in CFD or linear models, is the stable marine inversion. The stable marine inversion is critical because of its role in modulating wind farm-atmospheric interaction (WFAI) and wake propagation.
2. The uniqueness of the coastal zone
Offshore wind is economically more feasible when the depth is relatively shallow, a constraint that often focuses on development nearshore rather than over the open ocean. This coastal zone environment is unique because its meteorology is constantly in transition, with air streams adjusting to the abrupt change in underlying surface roughness, heating, and moisture. A ubiquitous feature is a significant mean wind speed gradient from the coast extending tens of kilometers offshore, with lower speeds nearer the coast. With the high cost of offshore wind measurement campaigns, often only one measurement site is deployed within the project area, which is insufficient to establish this gradient observationally. Mesoscale models include physical algorithms that the atmospheric research community has developed to represent the unique and highly contrasting surface characteristics and processes of both the land and water environments. As such, the models are exceptionally well suited to simulate this coastal gradient accurately.
3. The storm track
Many regions of offshore wind development are within, or on the flanks of, a “storm track”, or a region where large-scale weather systems (low-pressure centers and fronts) repeatedly develop and pass through. A storm track can superimpose another gradient in mean wind speed on the project site. Because mesoscale models include all of the physical processes that affect the life cycles of such weather systems, a climatology built from retrospective mesoscale model simulations will typically quantify the storm track accurately. As with the coastal zone gradient, this is important when there are too few observations to establish the gradient across the wind project site.
In addition to long-term mean wind resource estimates, outputs from mesoscale models can be used to estimate turbulence intensity, extreme winds, and other parameters relevant to site suitability. And when run continuously for a period of a year or more, the models provide time-series output across the wind project, increasingly recognized as important for accurate loss estimates and financial modeling. With more accurate characterization of the site-specific evolution of the marine inversion, and with the use of wind farm parameterization, WFAI and wake propagation is more accurately modeled, enabling more accurate wind farm optimization and energy capture.
Our key takeaway
To summarize, the lack of complex terrain in the offshore environment may intuitively steer project developers away from mesoscale modeling to assess the project wind energy resource. However, there are compelling technical reasons why this is not the case. The benefits of mesoscale modeling are not limited to capturing interactions of weather-induced wind flows with the underlying terrain. They also include a wide array of atmospheric processes that are key to simulating wind evolution in offshore marine environments and should be considered an essential component in the offshore wind project developer’s toolbox.
About the author
Mark currently serves as Lead, Atmospheric Science Innovation and Applications, at ArcVera Renewables. Mark received a B.S. in Physics from the University of Illinois at Urbana, and a Ph.D. in Atmospheric Sciences from the University of Washington at Seattle. Mark became a recognized research expert in meteorology, numerical weather prediction, and climate change impacts, while working as a research scientist at the National Center for Atmospheric Research (1993-1995) and the University of Washington (1995-2009). Since then he has been at 3TIER, Vaisala, and ArcVera, where he has worked on developing, improving, and testing advanced techniques for assessment and forecasting of renewable energy, including wake modeling, time series loss modeling, remote sensing applications in complex terrain, and benchmarking of end-to-end wind energy assessment.