Your point about the GFS is well-taken, but at present, I'd never use the GFS or ECMWF to forecast hurricane intensity. Yes, there's value in increasing the resolution of the model. But there's also a need to improve the data assimilation to produce better initial conditions (see this NOAA white paper). The conclusion was that there are gains to be made by bumping up the resolution, but that's only one of the recommended approaches to improving the GFS. Others included better data assimilation and improving parameterizations. Much of what the public hears has been focused on the resolution of the model. Yes, it does matter, but there are other considerations that are at least equally important.
Much of the criticism of the GFS with respect to Sandy has focused on the track forecast several days out. While increasing the resolution of the model could provide some improvement to the track forecasts, I would expect better initialization to have a larger role, especially at that forecast range. I'd believe bumping up the resolution would provide much better gains in the area of forecasting intensity.
Larger atmospheric features such as air masses and mid-latitude cyclones are more predictable than smaller features. Thunderstorms are much smaller and less predictable. Also, thunderstorms are driven by instability in the atmosphere. That is, if air is nudged upward, it will accelerate upwards. This occurs when warm (or hot) moist air is beneath cold air aloft. If there's a lot of cloud cover left over from thunderstorms the previous day, for example, that makes predicting thunderstorm chances the next day much more difficult. Predicting the behavior of large air masses is done with much more skill than smaller features such as thunderstorms.
HWRF runs at a much finer grid spacing than 27 or 13 kilometers. As I recall, the grid spacing is around 3 km in the inner nest. This is done to explicitly simulate the convection at the inner core of a tropical cyclone. This nest moves with the storm, and is embedded within a much larger domain.
The upgrade from 27 to 13 kilometers actually refers to the GFS model. It's a spectral model that has a global domain. Other models that are regional (including the outer domain of the HWRF) need to know the conditions at their lateral boundaries, so they know what's moving into the domain. In the US, they typically use the GFS for their boundary conditions. I'm actually very skeptical of the need for upgrading the resolution of the GFS. That may have a role in improving GFS forecasts, but there have been studies showing that the initial conditions of the GFS are the real problem. The atmosphere is a chaotic system; that is, two similar initial states will diverge over time to produce two very different outcomes. In a study where the GFS was initialized with ECMWF initial conditions, the performance of the GFS improved. Hurricanes are typically steered by large scale features, which aren't necessarily going to be simulated better by using a finer resolution. It also doesn't address the initial conditions problem.
I'm in favor of throwing more computing power at meteorology, but I'm not convinced it will solve the problems with the GFS.
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Your point about the GFS is well-taken, but at present, I'd never use the GFS or ECMWF to forecast hurricane intensity. Yes, there's value in increasing the resolution of the model. But there's also a need to improve the data assimilation to produce better initial conditions (see this NOAA white paper). The conclusion was that there are gains to be made by bumping up the resolution, but that's only one of the recommended approaches to improving the GFS. Others included better data assimilation and improving parameterizations. Much of what the public hears has been focused on the resolution of the model. Yes, it does matter, but there are other considerations that are at least equally important.
Much of the criticism of the GFS with respect to Sandy has focused on the track forecast several days out. While increasing the resolution of the model could provide some improvement to the track forecasts, I would expect better initialization to have a larger role, especially at that forecast range. I'd believe bumping up the resolution would provide much better gains in the area of forecasting intensity.
Larger atmospheric features such as air masses and mid-latitude cyclones are more predictable than smaller features. Thunderstorms are much smaller and less predictable. Also, thunderstorms are driven by instability in the atmosphere. That is, if air is nudged upward, it will accelerate upwards. This occurs when warm (or hot) moist air is beneath cold air aloft. If there's a lot of cloud cover left over from thunderstorms the previous day, for example, that makes predicting thunderstorm chances the next day much more difficult. Predicting the behavior of large air masses is done with much more skill than smaller features such as thunderstorms.
HWRF runs at a much finer grid spacing than 27 or 13 kilometers. As I recall, the grid spacing is around 3 km in the inner nest. This is done to explicitly simulate the convection at the inner core of a tropical cyclone. This nest moves with the storm, and is embedded within a much larger domain. The upgrade from 27 to 13 kilometers actually refers to the GFS model. It's a spectral model that has a global domain. Other models that are regional (including the outer domain of the HWRF) need to know the conditions at their lateral boundaries, so they know what's moving into the domain. In the US, they typically use the GFS for their boundary conditions. I'm actually very skeptical of the need for upgrading the resolution of the GFS. That may have a role in improving GFS forecasts, but there have been studies showing that the initial conditions of the GFS are the real problem. The atmosphere is a chaotic system; that is, two similar initial states will diverge over time to produce two very different outcomes. In a study where the GFS was initialized with ECMWF initial conditions, the performance of the GFS improved. Hurricanes are typically steered by large scale features, which aren't necessarily going to be simulated better by using a finer resolution. It also doesn't address the initial conditions problem. I'm in favor of throwing more computing power at meteorology, but I'm not convinced it will solve the problems with the GFS.