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1. Synoptic situation
Hurricane Georges developed from an easterly wave that moved off the coast of Africa 13 September, and developed into a tropical depression two days later. The system moved westward, strengthening rapidly into a hurricane by 17 September. Due to the potential threat to Florida, a synoptic surveillance mission was tasked for nominal time 22 September 1998 0000 UTC, with a follow-on mission the next day. At that time, Georges was moving west-northwestward and was located over Hispaniola, to the south the subtropical ridge (Fig. 1). A strong cold low was located in the Caribbean Sea to the south of western Cuba. The circulation to the northeast of Bermuda was a subtropical system which eventually developed into Tropical Storm Karl.
2. General Assessment of dropwindsonde impact
A. GFDL model
Figure 2 shows the GFDL forecast tracks for Hurricane Georges, and Table 1 shows the errors and impact of the synoptic surveillance mission. The results are mainly negative, with improvements only at 12 h. The upper-tropospheric data improved the forecasts at all times except 36 h.
Georges made landfall twice during the forecast. The first was 21.5 h into the forecast near Imias, Guantanamo, Cuba. Both GFDL forecasts which incorporated the dropwindsonde data failed to foecast landfall in Cuba, instead forecasting impact in the southern Bahama Islands.
The forecast without the dropwindsonde data was the only one to forecast the second landfall 63.5 h into the forecast near Key West, FL. That run forecast landfall at Fort Lauderdale, FL. The run with all and that with only the lower-level dropwindsonde data predicted landfall at High Rock, Grand Bahama Island, and at Cooper's Town, Abaco Island, both in the Bahama Islands, and both substantially further from the landfall point than the other run.
Figure 3 shows the VICBAR forecast tracks for Hurricane Georges, and Table 2 shows the errors and impact of the synoptic surveillance mission. The dropwindsonde data improved the forecasts at all times, and the upper-tropospheric data provided a better forecast than the run with all these data through 48 h.
Georges made landfall twice during the forecast. The first, near Imias, Guantanamo, Cuba, 21.5 h into the forecast, was well-forecast by all VBAR runs. The forecast was degraded slightly by the addition of the dropwindsonde data, though even the forecast with all the dropwindsonde data was excellent.
The runs with the dropwindsonde data performed better than the run without the data at the third landfall point at Key West, Florida, 63.5 h into the forecast, though all three forecasts were similar. The runs without and with all the dropwindsonde data forecast landfall at Tavernier, Fl, and the run with only the lower-level dropwindsonde data predicted landfall at Islamorada, FL.
Figure 4 shows the GSM forecast tracks for Hurricane Georges, and Table 3 shows the errors and impact of the synoptic surveillance mission. The dropwindsonde data improved the GSM forecast track during the first day. All forecasts were good, though the forecast without the dropwindsondes was particularly exceptional through five days. The upper-tropospheric data improved the forecast at all forecast times except 24 h.
Georges made landfall twice during the forecast. The first was 21.5 h into the forecast near Imias, Guantanamo, Cuba. The forecast without the dropwindsondes made landfall near Imias, whereas the two runs with the dropwindsonde data forecast landfall near Boqueron, Guantanamo, Cuba. The forecasts with the dropwindsonde data were slightly degraded compared to that without the dropwindsonde data.
Though substantially better at the landfall point, the forecast without the dropwindsonde data was slightly to the left of the best track, and so did not predict the landfall at Key West, Florida, 63.5 h into the forecast. The forecast with all the dropwindsonde data predicted landfall near Islamorada, FL, and that with only the lower-level dropwindsonde data predicted landfall at Key Largo, FL, both substantially to the east of the landfall point.
Table 4 shows the GFDL intensity forecast errors and impact of the synoptic surveillance mission. The dropwindsonde data had a positive impact at 24 h and after 48 h, and the upper-tropospheric data improved the forecasts at 24 h, and 72 to 96 h. Tuleya and Lord (1997) also showed modest improvements to GFDL model intensity forecasts in the HRD synoptic flow cases.
The atmosphere has long been recognized as a chaotic system (Lorenz 1963), e.g. very small perturbations to initial conditions result in increasingly large differences in the evolution of the atmosphere with time. Since the exact state of the atmosphere can never be measured, all analyses contain errors whose magnitudes can only be estimated. An indeterminate number of initial conditions consistent with the observational data can therefore be used in numerical weather prediction, and single model runs at any synoptic time only give one possible solution to the evolution of the atmosphere. Many operational forecast centers around the world, therefore, now employ ensemble forecasting as a means of quantifying the uncertainty in the evolution of the atmospheric system. Small perturbations from a best "control" state are calculated and added to and subtracted from this control to allow for different integrations starting from theoretically equally likely initial states. These perturbations are designed so as to mimic the fastest growing modes in the model and to create the largest envelope of possibilities in the forecast. Therefore, they generally correspond to locations where large analysis errors will most impact the forecast. Those features corresponding to perturbations which most impact the tracks of tropical cyclones must be found, properly sampled, and thoroughly tested, to prove the efficacy of targeting techniques.
Figure 5 shows the variance of the size of the perturbations in the National Centers for Environmental Prediction (NCEP) global model ensemble forecasting system (Toth and Kalnay 1993). The largest perturbations are associated with Hurricane Georges. Another large perturbation is centered over southern Ontario, and is associated with a vorticity maximum in the midlatitude westerly flow. Another maximum is associated with the cold low over western Cuba, and another with the ridging between Georges and this cold low. Another maximum is associated with the vortex that developed into Tropical Storm Ivan, and another with Hurricane Jeanne in the eastern Atlantic.
Figure 6 shows the difference in the 850 - 200 hPa averaged winds between the runs in which all the dropwindsonde data and none of the dropwindsonde data are included. The largest differences form a ring around Hurricane Georges. The difference maximum is located to the south, and is contained solely between locations where dropwindsonde data were obtained. This region also extends eastward a considerable distance away from the flight pattern. Other difference maxima are located in the subtropical ridge to the north of Georges, and in the southwestern Caribbean Sea. Since some of the impact extends more than 1000 km away from the location of dropwindsonde observations, and since the maximum difference is actually between dropwindsonde observations, the data assimilation may have spread the data from the observation locations into surrounding data-void regions.
Figure 7 shows that, by 24 h into the forecast, the difference maximum between the forecasts with and without the dropwindsonde data originally to the south of Georges in an area of large ensemble spread have amplified. The maximum originally to the north of Georges, also in an area of large ensemble spread, has moved eastward and also amplified. The maximum further to the north in the subtropical ridge, on the edge of an area of large perturbation, has moved northeastward to combine with the perturbation associated with the circulation that later developed into Tropical Storm Ivan, and has also amplified. The difference maximum in the southwestern Caribbean Sea, initially in an area of small ensemble spread, has moved northward and decayed slightly. An extension of the differences in the vicinity of the cold low over western Cuba has amplified. These results generally confirm that the largest (smallest) ensemble perturbations correspond to amplifying (decaying) modes in the model.
The dropwindsonde data obtained during the synoptic surveillance mission for Hurricane Georges at nominal time 23 September 1998 0000 UTC has provided mainly negative results throughout the five day forecast of Hurricane Georges in the GFDL and GSM models, and positive results in the VBAR model. However, even the forecasts with the dropwindsonde data were relatively good in this case.
|GFAL Error (km)|
|GFP3 Error (km)|
|12||64.||46.||( 28%)||49.||( 23%)|
|36||94.||252.||( -168%)||247.||( -163%)|
|48||125.||320.||( -156%)||326.||( -161%)|
|72||356.||582.||( -63%)||620.||( -74%)|
|84||451.||701.||( -55%)||767.||( -70%)|
|96||518.||788.||( -52%)||848.||( -64%)|
|120||833.||966.||( -16%)||1019.||( -22%)|
|Landfall#1||74.||----||( und%)||-----||( und%)|
|Landfall#2||264.||455.||( -72%)||512.||( -94%)|
|VBAL Error (km)|
|VBP3 Error (km)|
|12||77.||47.||( 39%)||47.||( 39%)|
|24||146.||106.||( 27%)||109.||( 25%)|
|36||207.||153.||( 26%)||168.||( 19%)|
|48||244.||195.||( 20%)||210.||( 14%)|
|72||344.||301.||( 13%)||296.||( 14%)|
|84||472.||407.||( 14%)||407.||( 14%)|
|96||569.||499.||( 12%)||490.||( 14%)|
|108||665.||594.||( 11%)||575.||( 14%)|
|120||697.||659.||( 5%)||630.||( 4%)|
|Landfall#2||147.||133.||( 10%)||129.||( 12%)|
|GSAL Error (km)|
|GSP3 Error (km)|
|12||107.||47.||( 56%)||61.||( 43%)|
|24||109.||56.||( 49%)||44.||( 60%)|
|36||70.||106.||( -51%)||106.||( -51%)|
|108||158.||256.||( -62%)||278.||( -76%)|
|120||189.||253.||( -34%)||304.||( -61%)|
|Landfall#1||31.||57.||( -84%)||43.||( -39%)|
|Landfall#2||----||129.||( und%)||170.||( und%)|
|GFAL Error (kn)|
|GFP3 Error (kn)|
|24||13||8||( 38%)||9||( 31%)|
|72||9||6||( 33%)||8||( 11%)|
|84||17||5||( 71%)||6||( 65%)|
|96||29||13||( 55%)||18||( 38%)|
|120||31||17||( 45%)||16||( 48%)|
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