Abstract
The ability of ensemble prediction systems to predict the probability that a tropical cyclone will fall within a certain area is evaluated. Ensemble forecasts of up to 5 days issued by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Met Office (UKMET) were evaluated for the 2008 Atlantic and western North Pacific seasons. In the Atlantic, the ECMWF ensemble mean was comparable in skill to a consensus of deterministic models. Dynamic "probability circles" that contained 67% of the ECMWF ensemble captured the best track in ~67% of all cases for 24-84-h forecasts, and were slightly underdispersive beyond 96 h. In contrast, the Goerss predicted consensus error (GPCE) was overdispersive. The addition of the UKMET ensemble yielded improvements in the short range and degradations for longer-range forecasts. The ECMWF ensemble performed similarly when the size was reduced from 50to 20.On average, it produced a lower measure of independence between its members than an ensemble comprising different deterministic models. The 67% circles normally captured the best track during straight-line motion, but less so for sharply turning tracks. In contrast to the Atlantic, the ECMWF ensemble (and GPCE) was unable to capture sufficient verifications within the 67% probability circles in the western North Pacific, in part because of a less skillful ensemble mean (and consensus). Though further evaluations are necessary, the results demonstrate the potential for ensemble prediction systems to enhance probabilistic forecasts, and for The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) to be embraced by the operational and research communities.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 659-680 |
| Number of pages | 22 |
| Journal | Weather and Forecasting |
| Volume | 25 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2010 |
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Keywords
- Ensembles
- Forecasting techniques
- Tropical cyclones
ASJC Scopus subject areas
- Atmospheric Science
Cite this
On the ability of global ensemble prediction systems to predict tropical cyclone track probabilities. / Majumdar, Sharanya J; Finocchio, Peter M.
In: Weather and Forecasting, Vol. 25, No. 2, 04.2010, p. 659-680.Research output: Contribution to journal › Article
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TY - JOUR
T1 - On the ability of global ensemble prediction systems to predict tropical cyclone track probabilities
AU - Majumdar, Sharanya J
AU - Finocchio, Peter M.
PY - 2010/4
Y1 - 2010/4
N2 - The ability of ensemble prediction systems to predict the probability that a tropical cyclone will fall within a certain area is evaluated. Ensemble forecasts of up to 5 days issued by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Met Office (UKMET) were evaluated for the 2008 Atlantic and western North Pacific seasons. In the Atlantic, the ECMWF ensemble mean was comparable in skill to a consensus of deterministic models. Dynamic "probability circles" that contained 67% of the ECMWF ensemble captured the best track in ~67% of all cases for 24-84-h forecasts, and were slightly underdispersive beyond 96 h. In contrast, the Goerss predicted consensus error (GPCE) was overdispersive. The addition of the UKMET ensemble yielded improvements in the short range and degradations for longer-range forecasts. The ECMWF ensemble performed similarly when the size was reduced from 50to 20.On average, it produced a lower measure of independence between its members than an ensemble comprising different deterministic models. The 67% circles normally captured the best track during straight-line motion, but less so for sharply turning tracks. In contrast to the Atlantic, the ECMWF ensemble (and GPCE) was unable to capture sufficient verifications within the 67% probability circles in the western North Pacific, in part because of a less skillful ensemble mean (and consensus). Though further evaluations are necessary, the results demonstrate the potential for ensemble prediction systems to enhance probabilistic forecasts, and for The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) to be embraced by the operational and research communities.
AB - The ability of ensemble prediction systems to predict the probability that a tropical cyclone will fall within a certain area is evaluated. Ensemble forecasts of up to 5 days issued by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Met Office (UKMET) were evaluated for the 2008 Atlantic and western North Pacific seasons. In the Atlantic, the ECMWF ensemble mean was comparable in skill to a consensus of deterministic models. Dynamic "probability circles" that contained 67% of the ECMWF ensemble captured the best track in ~67% of all cases for 24-84-h forecasts, and were slightly underdispersive beyond 96 h. In contrast, the Goerss predicted consensus error (GPCE) was overdispersive. The addition of the UKMET ensemble yielded improvements in the short range and degradations for longer-range forecasts. The ECMWF ensemble performed similarly when the size was reduced from 50to 20.On average, it produced a lower measure of independence between its members than an ensemble comprising different deterministic models. The 67% circles normally captured the best track during straight-line motion, but less so for sharply turning tracks. In contrast to the Atlantic, the ECMWF ensemble (and GPCE) was unable to capture sufficient verifications within the 67% probability circles in the western North Pacific, in part because of a less skillful ensemble mean (and consensus). Though further evaluations are necessary, the results demonstrate the potential for ensemble prediction systems to enhance probabilistic forecasts, and for The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) to be embraced by the operational and research communities.
KW - Ensembles
KW - Forecasting techniques
KW - Tropical cyclones
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UR - http://www.scopus.com/inward/citedby.url?scp=77955522550&partnerID=8YFLogxK
U2 - 10.1175/2009WAF2222327.1
DO - 10.1175/2009WAF2222327.1
M3 - Article
AN - SCOPUS:77955522550
VL - 25
SP - 659
EP - 680
JO - Weather and Forecasting
JF - Weather and Forecasting
SN - 0882-8156
IS - 2
ER -