ECMWF Activities for Improved Hurricane Forecasts

被引：62

作者：

Magnusson, L. ^{[1
]}

Bidlot, J-R ^{[1
]}

Bonavita, M. ^{[1
]}

Brown, A. R. ^{[1
]}

Browne, P. A. ^{[1
]}

De Chiara, G. ^{[1
]}

Dahoui, M. ^{[1
]}

Lang, S. T. K. ^{[1
]}

Mcnally, T. ^{[1
]}

Mogensen, K. S. ^{[1
]}

Pappenberger, F. ^{[1
]}

Prates, F. ^{[1
]}

Rabier, F. ^{[1
]}

Richardson, D. S. ^{[1
]}

Vitart, F. ^{[1
]}

Malardel, S. ^{[1
,2
]}

机构：

[1] European Ctr Medium Range Weather Forecasts, Reading, Berks, England

[2] Meteo France, Lab Atmosphere & Cyclones, St Denis, Reunion, France

来源：

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY | 2019年 / 100卷 / 03期

关键词：

JULIAN OSCILLATION; PREDICTABILITY; ASSIMILATION; ENSEMBLE; MODEL; TELECONNECTIONS; SENSITIVITY; PREDICTION; IMPACT; MADDEN;

D O I：

10.1175/BAMS-D-18-0044.1

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Tropical cyclones are some of the most devastating natural hazards and the three beastsHarvey, Irma, and Mariaduring the Atlantic hurricane season 2017 are recent examples. The European Centre for Medium-Range Weather Forecasts (ECMWF) is working on fulfilling its 2016-25 strategy in which early warnings for extreme events will be made possible by a high-resolution Earth system ensemble forecasting system. Several verification reports acknowledge deterministic and probabilistic tropical cyclone tracks from ECMWF as world leading. However, producing reliable intensity forecasts is still a difficult task for the ECMWF global forecasting model, especially regarding maximum wind speed. This article will put the ECMWF strategy into a tropical cyclone perspective and highlight some key research activities, using Harvey, Irma, and Maria as examples. We describe the observation usage around tropical cyclones in data assimilation and give examples of their impact. From a model perspective, we show the impact of running at 5-km resolution and also the impact of applying ocean coupling. Finally, we discuss the future challenges to tackle the errors in intensity forecasts for tropical cyclones.

引用

页码：445 / 458

页数：14

共 49 条

[21] THE HURRICANE FORECAST IMPROVEMENT PROJECT
Gall, Robert
Franklin, James
Marks, Frank
Rappaport, Edward N.
Toepfer, Frederick
[J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2013, 94 (03) : 329 - 343
[22] Haiden T., 2017, 817 ECMWF
[23] Met Office Unified Model Tropical Cyclone Performance Following Major Changes to the Initialization Scheme and a Model Upgrade
Heming, Julian T.
[J]. WEATHER AND FORECASTING, 2016, 31 (05) : 1433 - 1449
[24] Holm E. V., 2018, 21 INT C INF FUS CAM, P92, DOI [10.23919/ICIF.2018.8455209, DOI 10.23919/ICIF.2018.8455209]
[25] Janssen P. A. E. M., 2018, S WIND WAV LOND UK I
[26] Predictability and Dynamics of Tropical Cyclone Rapid Intensification Deduced from High-Resolution Stochastic Ensembles
Judt, Falko
Chen, Shuyi S.
[J]. MONTHLY WEATHER REVIEW, 2016, 144 (11) : 4395 - 4420
[27] Choosing a Boundary Layer Parameterization for Tropical Cyclone Modeling
Kepert, Jeffrey D.
[J]. MONTHLY WEATHER REVIEW, 2012, 140 (05) : 1427 - 1445
[28] Impact of perturbation methods in the ECMWF ensemble prediction system on tropical cyclone forecasts
Lang, S. T. K.
Leutbecher, M.
Jones, S. C.
[J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2012, 138 (669) : 2030 - 2046
[29] On the impact of re-centring initial conditions for ensemble forecasts
Lang, Simon T. K.
Bonavita, Massimo
Leutbecher, Martin
[J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2015, 141 (692) : 2571 - 2581
[30] Ensemble forecasting
Leutbecher, M.
Palmer, T. N.
[J]. JOURNAL OF COMPUTATIONAL PHYSICS, 2008, 227 (07) : 3515 - 3539

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