Adaptive observations for hurricane prediction |
| |
| Authors: | Z Zhang T N Krishnamurti |
| |
| Institution: | (1) Department of Meteorology, Florida State University, Tallahassee, Florida, |
| |
| Abstract: | Summary This study proposes a method that can be used to provide guidelines to aircraft reconnaissance for hurricane observations.
The method combines numerical weather prediction (NWP) model with a statistical approach to target adaptive observations over
areas where the hurricane predictions are very sensitive to the initial analysis for the NWP-model. A single model experiment
is performed using regular initial analysis, while 50 other ensemble runs are performed from randomly perturbed initial states.
Under the perfect model assumption, the single model experiment serves as a true state. The method first computes the forecast
error variances at a certain verification time, e.g. hour 48, and then locates the maximum centers of variances. After the
locations of the maximum forecast error variances are known, various correlations of different variables between these maximum
variance points and the perturbation fields at the target time, e.g. hour 12, are calculated to identify those locations at
the target time, over where the observational errors might be responsible for the growth of forecast error variances at the
verification time. Statistically, these correlation fields indicate where the most sensitive areas are at the target time,
i.e. where the need for additional observations is suggested.
Hurricane Fran of 1996 is used to test the proposed method. The reason for choosing this case is that, during the first 48 hour
forecast, the track forecast from NWP-model was very close to the best track. Two additional experiments were designed to
examine the method. One experiment updates predicted variables at the target time (12 h) over the areas, to where the proposed
method indicates the forecast would be sensitive. The updating combines observations (or truth) with the first guess (predicted)
fields. Another experiment also modifies predicted variables at the target time (12 h), but over the areas where the method
indicates the forecast errors are less correlated to. The results show that the modification has greatly reduced the forecast
error variances at the verification time (48 h) in the first experiment, however it has a very little impact on the variance
fields at the forecast hour (48 h) in the second experiment. It is very clear from our experiments, that the proposed method
is able to identify sensitive areas, where additional observations can help to reduce hurricane forecast errors from an NWP-model.
Received July 19, 1999 Revised November 28, 1999 |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
