Using the knowledge and techniques developed in prior studies as well as in the Modeling System, Validation, and Cloud Computing Tasks in this project, we have developed a plan for implementing the unstructured SWAN wave model in an operational mode to provide multi-day forecasts of wave conditions at the site. There are several components to a robust operational system, including skillful numerical models for wind and wave forcing and high-resolution wave responses, file and data management techniques, and compute resources that are available on demand and with sufficient speed to ensure near real-time forecasting capability. The above-described validation study demonstrates that the model is configured appropriately, which results in and good wave hindcast predictions. The validation simulations were carried out using Amazon EC2 compute resources, with deployment methods and scripts that will be directly used in the real-time operational implementation. The primary task in implementing the operational system is thus in coordinating the various needed real-time inputs to the SWAN wave model, including the operational NOAA NCEP WAVEWATCH III wave spectra output and the wind fields computed by the WeatherFlow weather forecasting system.
The overall workflow plan for the operational system is shown in Figure 7.1, and is based on our experiences detailed above in the forecast demonstration section. Generally, each forecast period (e.g., at 0, 6, 12, and 18Z) will begin by checking for the availability of external data sources (NCEP and WeatherFlow forecast output). When both data sources for the current forecast period are available, the data fields will be processed into the specific formats required for SWAN. A package containing the complete simulation (model executables, configuration files, and pre-processing input files) will then be created, compute resources on Amazon EC2 provisioned, and the package deployed for execution. The system will then wait until the results are available, transfer the results back to the host machine for
verification and validation, and then send the output files for wave heights, periods, and directions to the project’s data server.
Details of the processing steps are not shown, but many of the needed steps have already been developed in the course of the validation study (such as converting WAVEWATCH III spectra format to SWAN format and reformatting of wind and pressure fields into SWAN format). Additionally, our team (Blanton and Gamiel, in particular) have extensive experience in developing automated software systems that manage environmental and earth sciences computations.
We anticipate that, initially, the time between the start of a forecast period and the availability of the detailed SWAN forecast products will be approximately 9-11 hours. This is largely dependent on the availability of the Weather Flow wind and pressure fields, which are available approximately 8 hours after the forecast period start time, due to the high resolution of the WRAMS model. Each SWAN forecast simulation will take approximately 1.7 hours on 32 EC2 cores, with subsequent post-processing of about 1 hour. This results in the 9-11 hour estimate of the project’s wave forecast information. Details of the operational wave and wind data sources are given next.
Figure 7.1: Workflow for planned operational forecast system. Arrows with dotted lines indicate connections to external data servers. The lower level steps operate on the project’s Amazon host machine, transfer files to and from external servers, and deploy simulations to the provisioned EC2 resource.
7.1 Real-time data sources
The SWAN model is configured to apply wave spectra along the domain’s open boundary and apply 10- meter, 10-minute wind velocity at the surface. In the validation study, we used high-quality wind fields from Oceanweather, Inc. to drive the offshore (WAVEWATCH III) and nearshore (SWAN) wave models, with WAVEWATCH III simulations providing wave energy along the regional model boundary. In the operational forecasting context, we will replace the winds with operational winds from the WeatherFlow Regional Atmospheric Modeling System, and replace the oceanic wave energy spectra with the operational WAVEWATCH III output from NCEP.
Offshore wave boundary conditions
NCEP operates the WAVEWATCH III wave model on several different spatial domains, including the Northwest Atlantic area, shown in Figure 7.2. This figure also shows the VA DMME regional model domain and the locations of the WAVEWATCH III output points for the “Wakefield” area. NCEP WAVEWATCH III output is posted to a production file server2, accessible by FTP. A component of the VA DMME forecasting system will look at the NCEP FTP server for new files, acquire them as they become available, and interpolate the WAVEWATCH III wave energy spectra to the SWAN open boundary locations.
Figure 7.2: Left) Snapshot of the operational NCEP Western North Atlantic WAVEWATCH III model domain, at the 111th hour forecast from 30 July 2014. This shows the wave height and peak wave direction. The WAVEWATCH III forecast simulations are driven by the NCEP Global Forecast System (GFS) model output. Right) Location of the VA DMME forecast domain and operational NCEP WAVEWATCH III output points (blue dots).
Wind forcing for operational wave forecasting
There are several sources of operational meteorological model products available, including NCEP’s NAM and Global Forecast System (GFS) model output. We will use NCEP meteorological products while we develop the fully operational wave model system, since it is easily available and we have methods that handle the GRIB23 format on Lambert Conformal coordinate systems.
2
ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/wave/prod/wave.YYYYMMDD/bulls.tCCz/
, where CC is the cycle (00, 06, 12, 18). The Wakefield output spectra are in files named multi_1.NW-AKQ51.spec.
3
GRIB2 is the GRidded In Binary format typically used for meteorological model output. Version 2 is the most recent format and metadata standard for GRIB, and is easily converted to other formats such as NetCDF.
However, these large-scale model implementations are not configured to run at resolutions that resolve important gradients in winds that occur during intense storm systems, due to the large spatial regions that the continental-scale models cover. This is particularly true for tropical systems, where cyclone winds are typically concentrated in narrow bands about the vortex center. We will, therefore, use a commercial, high resolution meteorological product operated by our WeatherFlow partners. Based on the Regional Atmospheric Modeling System (RAMS), WeatherFlow has developed a customized, proprietary version called WRAMS that is used extensively for operational forecasting along much of the U.S. coastline. Detailed descriptions of RAMS model physics, strengths and weaknesses, and common applications are available in Pielke et al (1992) and Cotton et al (2003). Walko et al (2000) and Walko et al (2005) describe the RAMS surface scheme and its most recent updates. Tremback et al (2014) provide the most recent operational summary for RAMS.
For this VA DMME project, WeatherFlow will construct the surface wind and pressure forecast product from a combination of WeatherFlow and NOAA/NCEP model output. Higher resolution models (2-4 km) will be the primary forecast source used in the first few forecast days, with coarser models providing forecast fields out to 5-7 days. Table 7.1 describes the primary model sources at each forecast period. WeatherFlow will develop a process that creates a smooth (in space and time) wind and pressure field data set that blends the various model output, and onto a 2 km spatial grid for use in the wave model forecast system. The spatial domain for the RAMS 2 km grid will extend from 35.31 deg N to 39.90 deg N latitude and 76.988 deg W to 74.000 deg W longitude at a resolution of 0.018 deg (~2km).
Table 7.1. Meteorological Model Data Sources for Operational Wind Forecast Product Development.
Forecast Period (hours)
Model Provider Spatial Resolution
Available Output Frequency
Model Run Times
0-36 WRAMS WeatherFlow 2/4 km 1 hour 00, 06, 12, 18Z
36-60 NAM NOAA/NCEP 4km 3 hour 00, 06, 12, 18Z
60-84 NAM NOAA/NCEP 12km 3 hour 00, 06, 12, 18Z
84-120 GFS NOAA/NCEP ~27km 3 hour 00, 06, 12, 18Z
The hierarchy of operational wind field products is shown in Figure 7.3, including the operational NCEP NAM (North American Mesoscale) model. The wind field from the WRAMS 2km domain along the Virginia coastline is shown in Figure 7.3 (middle). Within the designated 2km output Grid (Figure 7.3, right), WeatherFlow will provide either WRAMS 2km data or will interpolate data from the coarser
models indicated above to the same 2km spatial and 1-hour temporal resolution. This data set will also be used to provide a backup forcing data set in situations where a cycle of a finer scale model is unavailable. The transition in time between models will be smoothed with a weighted 3-hour temporal filter.
The combined model forecast fields will be transferred to a WeatherFlow FTP site in a GRIB2 file containing hourly forecast fields, 0-120 hour, of 10-meter wind velocity and atmospheric pressure reduced to mean sea level. The operational VA DMME forecast system will look at the WeatherFlow FTP site for updated wind files and retrieve the files to start the SWAN forecast model process.
7.2 Higher resolution wave model grid
In the SWAN grid described above, the resolution in the VA DMME area is about 5-10 km. To resolve features with spatial scales at or below the separation of the potential tower locations, it is necessary to have grid nodes that are much closer together. We have developed an SWAN grid that has substantially higher resolution in the tower area. This grid, shown in Figure 7.4, has twice as many nodes as the above-described grid, but all of the new nodes are packed into the tower area, focusing incrementally down to a nominal length scale of about 300 m. This is one of the major benefits of using models formulated in finite elements; specific areas can be highly resolved without over-resolution of other areas, with very smooth grading of the resolution.
Figure 7.3. Left) Operational NOAA NCEP NAM domain, used for initial and boundary conditions for the WeatherFlow RAMS model, as well as potential forecast data for the blended wind and pressure field needed for wave forecasting. Middle) WeatherFlow RAMS (WRAMS) 2km wind output example for wave forecasting. The wind barbs are not shown at the 2 km resolution, for clarity. Right) The sequence of WRAMS domains plus 2km Output Grid (in yellow). The Output Grid is tailored to the wave forecasting model application.
We note that this grid has not been fully validated, although initial tests have shown that this grid is robust with respect to numerical stability at a necessarily smaller time step. Computations using this grid would impact the total computation time and resource costs. However, there may be benefits to the much higher resolution grid and bathymetry, including more accurate wave propagation directions. This grid is available for future uses by the VA DMME project, including using it in the forecasting system should the need arise.