On the skill of various ensemble spread estimators for probabilistic short range wind forecasting
A variety of applications ranging from civil protection associated with severe weather to economical interests are heavily dependent on meteorological information. For example, a precise planning of the energy supply with a high share of renewables requires detailed meteorological information on hig...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2012-05-01
|
| Series: | Advances in Science and Research |
| Online Access: | http://www.adv-sci-res.net/8/115/2012/asr-8-115-2012.pdf |
| Summary: | A variety of applications ranging from civil protection associated with
severe weather to economical interests are heavily dependent on
meteorological information. For example, a precise planning of the energy
supply with a high share of renewables requires detailed meteorological
information on high temporal and spatial resolution. With respect to wind
power, detailed analyses and forecasts of wind speed are of crucial interest
for the energy management. Although the applicability and the current skill
of state-of-the-art probabilistic short range forecasts has increased during
the last years, ensemble systems still show systematic deficiencies which
limit its practical use. This paper presents methods to improve the ensemble
skill of 10-m wind speed forecasts by combining deterministic information
from a nowcasting system on very high horizontal resolution with uncertainty
estimates from a limited area ensemble system. It is shown for a one month
validation period that a statistical post-processing procedure (a modified
non-homogeneous Gaussian regression) adds further skill to the probabilistic
forecasts, especially beyond the nowcasting range after +6 h. |
|---|---|
| ISSN: | 1992-0628 1992-0636 |