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(T. F. “Storm” Walsh III)
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Good day everyone!
Since today’s severe weather risk was only at a SLIGHT category, I wanted to touch more on hurricane season. I wanted to put something together regarding forecast models.
First, there are folks who confuse or misterm the global models (ECMWF, GFS, CMC GGEM, NAVGEM, and UKMET) as HURRICANE MODELS. This is not the case. The only TRUE Hurricane Models are the GFDL, GFDN and HWRF, which will be discussed further in this discussion.
The global models are just that..GLOBAL MODELS. Their main purpose IS NOT to forecast tropical storm or hurricane formation, but to predict the changing global pattern. Now, we’ve seen the forecast low pressure areas on the global maps, which some do eventually become tropical systems, however in the scheme of things, the models are not focusing on tropical development, rather, displaying a “solution” from the model run(s) for the meteorologist to make a determination. Based on model knowledge, the ECMWF (European Center for Medium range Weather F0recasting) is supposed to be the most accurate of the global models. Unlike the rest of the global models, the ECMWF uses 4-D technology, as well as the finer scale metric system. From past experience in past hurricane seasons, the ECMWF does have a tendency to outperform the other models, especially when a system is developed. I have noticed lately, that initialization has been below standards, thus my statement the ECMWF outperforms most of the time when a system is fully developed.
As a rating on a “personal” preference as far as accuracy, I would have to list them in the following order: ECMWF, GFS, CMC GGEM, UKMET, and NAVGEM. NAVGEM (NAVy Global Environmental Model) was previously the NOGAPS (Navy Operational Global Atmospheric Prediction System). The following document from the NHC lists the acronyms, and what each model is.
NHC TRACK AND INTENSITY MODELS
One of the other very accurate models used by the NHC is the Florida State Super Ensemble (FSSE). This is one model I do not have access to, and is owned by Florida State University.
So, in the routine of making and issuing a tropical forecast, I pour over the global models, satellite loops and stills, etc. Once we have a storm “initialized”, it’s time to track, and forecast future movement. As far as future track, I tend to look at water vapor imagery (for hurricanes or storms reaching up and being guided by the 500 mb steering layer), current steering layers, forecast steering layers, and ATCF Guidance modeling. The ATCF guidance not only uses single member models, it also utilizes what we term “consensus models”, which are listed in the NHC table above. You’ll note that a lot of folks post the “early track guidance” models when showing the projected path of a storm. These models are mostly what we term as “STATISTICAL MODELS”. These models can give a general idea of future storm track, however ARE NOT as accurate as “DYNAMIC MODELS”.
The models we look at for future storm track are the dynamic models. Here is the difference:
Statistical models are based on established relationships between storm-specific information, such as location and time of year, and the behavior of historical storms. While these models provided key forecast guidance in past decades, today these models are most often used as benchmarks of skill against which more sophisticated and accurate models and the NHC official forecast are compared. Models that are less accurate than a simple statistical model are considered “unskillful” and models that are more accurate than statistical models are considered “skillful”. Due to their simplicity, statistical models are among the quickest to run and are typically available to forecasters within minutes of initialization.
Dynamical models are the most complex and most computationally expensive numerical models used by NHC. These models make forecasts by solving the physical equations that govern the atmosphere, using a variety of numerical methods and initial conditions based on available observations.
As I attended the 2010 National Hurricane Conference, I learned the NHC forecasters generally put more weight in the consensus models, primarily the TVCA, TVCC, and TVCN for track guidance. They do make exceptions based on what they observe in initialization and the way the atmosphere is trending, and may use a blend of these, along with the FSSE, the ECMWF, and/or GFDL/HWRF models. But, for the most part, the consensus models are followed. You’ll notice these acronyms in the “spaghetti plots”.
As far as forecasting intensity, the 3 most accurate intensity models are the SHIPS (Statistical Hurricane Intensity Prediction Scheme), DSHIPS (Decay-SHIPS ) and the LGEM (Logistic Growth Equation Model). Here are descriptions of each:
The SHIPS model is a statistical-dynamical intensity model based on statistical relationships between storm behavior and environmental conditions estimated from dynamical model forecasts as well as on climatology and persistence predictors. Due to the use of the dynamical predictors, the average intensity errors from SHIPS are typically 10%-15% less than those from SHIFOR5. SHIPS has historically outperformed most of the dynamical models, including the GFDL, and SHIPS has traditionally been one of the most skillful sources of intensity guidance for NHC.
SHIPS is based on standard multiple regression techniques. The predictors for SHIPS include climatology and persistence, atmospheric environmental parameters (e.g., vertical wind shear, stability, etc.), and oceanic input such as sea surface temperature (SST) and upper-oceanic heat content. Many of the predictors are obtained from the GFS and are averaged over the entire forecast period. The developmental data from which the regression equations are derived include open ocean TCs from 1982 through the present. Each year the regression equations are re-derived based upon the inclusion of the previous year.s data. Therefore, the weighting of the predictors can change from year to year. The predictors currently found to be most statistically significant are: the difference between the current intensity and the estimated maximum potential intensity (MPI), vertical wind shear, persistence, and the upper-tropospheric temperature. SHIPS also includes predictors from satellite data such as the strength and symmetry of convection as measured from infrared satellite imagery and the heat content of the upper ocean determined from satellite altimetry observations.
Decay-SHIPS is a version of SHIPS that includes an inland decay component. Since land interactions result in weakening, the Decay-SHIPS will typically provide more accurate TC intensity forecasts when TCs encounter or interact with land. Over open water with no land interactions, the intensity forecasts from Decay SHIPS and SHIPS will be identical.
LGEM is a statistical intensity forecast model that uses the same input as SHIPS but in the framework of a simplified dynamical prediction system, instead of a multiple regression. The evolution of the intensity is determined by a logistic growth equation that constrains the solution to lie between zero and the TC’s maximum potential intensity (MPI), where the MPI is estimated from an empirical relationship with sea surface temperature (SST). The forecast of the maximum wind depends on the growth rate coefficient, which is estimated from a subset of the input to the SHIPS model. Ocean heat content and other parameters derived from geostationary satellites are also incorporated into the LGEM. An important difference from SHIPS is that the LGEM considers the variability in the environmental conditions over the length of the forecast while SHIPS does not; most of the SHIPS predictors are averaged over the entire forecast period, while the equivalent LGEM predictors are averaged only over the 24 hours prior to the forecast valid time. In addition, the MPI in the LGEM prediction is the instantaneous value, rather than the forecast period average used in SHIPS. These differences make the LGEM prediction more sensitive to environmental changes at the end of the forecast period, but also make the prediction more sensitive to track forecast errors. Since the LGEM model averages its predictors over a shorter time period, it is also better able to represent the intensity changes of storms that move from water to land and back over water relative to the SHIPS model. (Note: ALL definitions contained here are excerpts from the NHC Track and Intensity Models document).
The Hurricane Models
The true “HURRICANE MODELS” GFDL (Geophysical Fluid Dynamics Laboratory), GFDN (Geophysical Fluid Dynamics Laboratory [Navy model]), and HWRF (Hurricane Weather Research and Forecasting model) are used mainly for the shorter term forecast of tropical cyclones. From my understanding at the National Hurricane Conference, these forecast are extremely accurate out to only about 48 hours, maybe 72. The reason being, the initialization parameter of these models is only about a 6 degree square radius around the center of the storm or hurricane. The model sampling does not initialize or analyze larger areas as the global models do. The graphic below shows the area which is sampled and then computed by these models:
I hope this helped in the understanding in the role of the various models that the NHC and I use in preparing a Tropical Storm or Hurricane synopsis.
Have a blessed day!
T. F. “STORM” WALSH III
GMCS, USCG (ret)
METEOROLOGIST / HURRICANE SPECIALIST /SEVERE WEATHER SPECIALIST
MEMBER WEST CENTRAL FLORIDA AMS