Click here for
catalog of sonde drops.
Click here for zipped post-processed sonde data.
1. Synoptic situation
Hurricane Linda developed from an easterly wave south of Mexico on 09 September, and moved westward, strengthening rapidly to become the strongest hurricane ever measured in the Eastern Pacific Ocean by 12 September. Due to the rare potential threat to the Southern California coastline, a synoptic surveillance mission was tasked for nominal time 14 September 1997 0000 UTC. At that time, Linda was embedded in the westerlies to the south of the subtropical ridge, about 900 km west southwest of Cabo San Lucas (Fig. 1). A strong trough was located just west of the U.S. west coast, and a break in the subtropical ridge to the northwest of Linda provided the opportunity for a strong, recurving hurricane to strike California.
2. General Assessment of dropwindsonde impact
A. GFDL model
Figure 2 shows the GFDL forecast tracks for Hurricane Linda, and Table 1 shows the errors and impact of the synoptic surveillance mission. The dropwindsonde data substantially improves the forecast at all times except 12 h, when all forecasts were exceptional. The upper-tropospheric data degraded the forecast at all times except 12, 36, and 84 h.
Figure 3 shows the GSM forecast tracks for Hurricane Linda, and Table 2 shows the errors and impact of the synoptic surveillance mission. The dropwindsonde data had a positive impact on the GSM forecast track at all times except 48 h, when all the forecasts showed Linda stalling in the same vicinity. The upper-tropospheric data had a mixed, though small, impact on the forecast track.
Table 3 shows the GFDL intensity forecast errors and impact of the synoptic surveillance mission. The dropwindsonde data had a positive impact on the forecast at 12 and 72 h, and the upper-tropospheric data improved the forecast at all times. Tuleya and Lord (1997) 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 4 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 correspond to Linda itself. Other large perturbations pertain to the strength of the deep-layer-mean westerly flow just to the north of the subtropical ridge axis, and to a shortwave trough about 1000 km west of Los Angeles. Only the eastern half of the second of these perturbations was sampled during the synoptic surveillance mission.
One set of model runs, the TG set, includes the dropwindsonde data taken within and around the perturbation corresponding to the strength of the westerly winds just to the north of Linda (the dropwindsonde near 31°N 122°W, and those extending from 29°N 125°W to 28°N 130°W), or a little over half the dropwindsondes released. Results are shown in Tables 1-3 and Figs. 2-3. The TG run provided better forecasts than the run including all the dropwindsonde data at all forecast times except 36 h in the GSM. The TG run provided better forecasts than the run including all the dropwindsonde data at all times except 36 and 48 h in the GFDL. However, the differences were mainly small, since only part of the area of potential large initial errors was sampled.
Figure 5 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 difference is off the coast of Baja California, Mexico, in the axis of the subtropical ridge. Other large differences are in the shortwave trough rotating around the large trough, and in the westerly winds just to the southwest of San Diego. The largest difference extends southwestward and eastward from the dropwindsonde locations nearly 1000 km, and the southwestern extension helps to explain the southern movement of Linda in the forecasts with the dropwindsonde data as compared to the forecasts without the data. However, the largest difference is in an area in which the ensemble perturbations are small, and therefore the differences are expected to decay. Figure 6 shows that, by 24 h into the forecast, the southernmost difference between the two forecasts have slowly decayed. The small perturbation initially southwest of San Diego, in the region of large ensemble perturbations in the westerly winds, has moved rapidly northeastward to Arizona and amplified. The third (westernmost) large difference was also located in an area of small ensemble perturbations, and has also decayed. These results confirm that the largest (smallest) ensemble perturbations correspond to amplifying (decaying) modes in the model. The area of large ensemble perturbation to the north of the subtropical ridge is not well-sampled during this synoptic surveillance mission. Though data taken in and around this ensemble perturbation has growing impact on the forecast fields with time, they have only a small impact on the track forecast of Linda. Sampling further to the west in the area of large ensemble perturbation north of the subtropical ridge may have had a larger positive impact on the forecast tracks.
The dropwindsonde data obtained during the synoptic surveillance mission for Hurricane Linda at nominal time 14 September 1997 0000 UTC has provided mainly positive results. The MRF ensemble forecasting system suggests that data obtained to the north of the subtropical ridge north of Linda would have the greatest impact on the Linda forecast. Dropwindsonde data obtained in this region was spread by the data assimilation to the southwest, pushing the forecasts with all dropwindsondes toward the south largely improving the forecasts. However, the western extent of this region was not sampled, suggesting that even larger improvements would have been possible.
|GFAL Error (km)|
|GFP3 Error (km)|
|GFTG Error (km)|
|24||60.||15.||( 75%)||10.||( 83%)||15.||( 75%)|
|36||128.||85.||( 34%)||85.||( 34%)||89.||( 30%)|
|48||165.||126.||( 24%)||118.||( 28%)||118.||( 28%)|
|72||334.||236.||( 29%)||215.||( 36%)||225.||( 33%)|
|84||477.||332.||( 30%)||369.||( 23%)||343.||( 28%)|
|GSAL Error (km)|
|GSP3 Error (km)|
|GSTG Error (km)|
|12||67.||56.||( 16%)||56.||( 16%)||46.||( 31%)|
|24||145.||134.||( 8%)||134.||( 8%)||134.||( 8%)|
|36||310.||290.||( 6%)||293.||( 5%)||292.||( 6%)|
|48||406.||433.||( -7%)||439.||( -8%)||434.||( -7%)|
|72||584.||512.||( 12%)||494.||( 15%)||500.||( 14%)|
|84||578.||432.||( 25%)||416.||( 28%)||425.||( 26%)|
|GFAL Error (kn)|
|GFP3 Error (kn)|
|GFTG Error (kn)|
|12||40||35||( 13%)||36||( 10%)||37||( 8%)|
|24||22||22||( 0%)||23||( -5%)||23||( -5%)|
|36||11||13||( -18%)||14||( -27%)||12||( -9%)|
|48||9||12||( -33%)||12||( -33%)||12||( -33%)|
|72||1||0||( 100%)||3||(-200%)||0||( 100%)|
Return to 1997 assessment page
Return to HRD home page