Editorial Type:
Article
Article Type:
Research Article

Improved Hurricane Track Forecasting from the Continuous Assimilation of High Quality Satellite Wind Data

L. M. Leslie School of Mathematics, University of New South Wales, Sydney, New South Wales, Australia

Search for other papers by L. M. Leslie in
Current site
Google Scholar
PubMed Close
,
J. F. LeMarshall Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia

Search for other papers by J. F. LeMarshall in
Current site
Google Scholar
PubMed Close
,
R. P. Morison School of Mathematics, University of New South Wales, Sydney, New South Wales, Australia

Search for other papers by R. P. Morison in
Current site
Google Scholar
PubMed Close
,
C. Spinoso Royal Melbourne Institute of Technology, Melbourne, Victoria, Australia

Search for other papers by C. Spinoso in
Current site
Google Scholar
PubMed Close
,
R. J. Purser National Centers for Environmental Prediction, Washington, D.C.

Search for other papers by R. J. Purser in
Current site
Google Scholar
PubMed Close
,
N. Pescod Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia

Search for other papers by N. Pescod in
Current site
Google Scholar
PubMed Close
, and
R. Seecamp Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia

Search for other papers by R. Seecamp in
Current site
Google Scholar
PubMed Close
Print Publication:
01 May 1998
DOI:
https://doi.org/10.1175/1520-0493(1998)126<1248:IHTFFT>2.0.CO;2
Page(s):
1248–1258
Restricted access

Abstract

Despite recent improvements in the accuracy of hurricane track forecasts, mean position errors still remain unacceptably large. For example, recurvature is captured poorly by forecast models and can produce excessively large position errors. This study addresses the problem of hurricane track forecasting in three ways. First, the initial conditions for the forecast model are augmented by a dense coverage of high spatial and temporal resolution satellite-derived wind vectors. Second, to gauge the extent to which this additional four-dimensional detail of the atmospheric structure can be exploited, three distinct types of data assimilation methods are examined. These are 1) conventional (intermittent, cycled) 6-h assimilation, 2) nudging over a 12- or 24-h period up to the initial time, and 3) recently developed barotropic and four-dimensional variational assimilation schemes, also over a 12- or 24-h period. The nudging and variational methods are continuous assimilation procedures and incorporate satellite-derived winds, typically at 6-h frequencies, but up to hourly frequencies in trials over the Australian region. Over the Atlantic basin, only a 6-h frequency of high-density satellite-derived wind vectors was available for the 1995 season. Third, a very high-resolution (15 km) semi-implicit, semi-Lagrangian model provided forecasts out to 72 h.

The present study describes the direct application to the Atlantic basin, for the specific case of Hurricane Opal, of data assimilation and prediction procedures developed for tropical cyclones over the Australian Pacific basin. A series of forecasts was made, from the two initial times 0000 and 1200 UTC 2 October 1995, respectively. In these cases, where CLIPER (climatology and persistence) and other conventional forecast guidance was poor, the nudging and variational assimilation procedures, which were those that best utilized the high spatial and temporal resolution satellite-derived winds, produced greatly improved forecasts.

Corresponding author address: L. M. Leslie, School of Mathematics, University of New South Wales, Sydney 2052, Australia.

Abstract

Despite recent improvements in the accuracy of hurricane track forecasts, mean position errors still remain unacceptably large. For example, recurvature is captured poorly by forecast models and can produce excessively large position errors. This study addresses the problem of hurricane track forecasting in three ways. First, the initial conditions for the forecast model are augmented by a dense coverage of high spatial and temporal resolution satellite-derived wind vectors. Second, to gauge the extent to which this additional four-dimensional detail of the atmospheric structure can be exploited, three distinct types of data assimilation methods are examined. These are 1) conventional (intermittent, cycled) 6-h assimilation, 2) nudging over a 12- or 24-h period up to the initial time, and 3) recently developed barotropic and four-dimensional variational assimilation schemes, also over a 12- or 24-h period. The nudging and variational methods are continuous assimilation procedures and incorporate satellite-derived winds, typically at 6-h frequencies, but up to hourly frequencies in trials over the Australian region. Over the Atlantic basin, only a 6-h frequency of high-density satellite-derived wind vectors was available for the 1995 season. Third, a very high-resolution (15 km) semi-implicit, semi-Lagrangian model provided forecasts out to 72 h.

The present study describes the direct application to the Atlantic basin, for the specific case of Hurricane Opal, of data assimilation and prediction procedures developed for tropical cyclones over the Australian Pacific basin. A series of forecasts was made, from the two initial times 0000 and 1200 UTC 2 October 1995, respectively. In these cases, where CLIPER (climatology and persistence) and other conventional forecast guidance was poor, the nudging and variational assimilation procedures, which were those that best utilized the high spatial and temporal resolution satellite-derived winds, produced greatly improved forecasts.

Corresponding author address: L. M. Leslie, School of Mathematics, University of New South Wales, Sydney 2052, Australia.

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Bennett, A. F., L. M. Leslie, C. R. Hagelberg, and P. E. Powers, 1993:Tropical cyclone prediction using a barotropic model initialized by a generalized inverse method. Mon. Wea. Rev.,121, 1714–1729.

  • ——, B. S. Chua, and L. M. Leslie, 1996: Generalised inversion of a global numerical weather prediction model. Meteor. Appl. Phys.,60, 165–178.

  • Davidson, N. E., and B. J. McAvaney, 1981: The ANMRC tropical analysis scheme. Mon. Wea. Rev.,109, 155–228.

  • Elsberry, R. L., 1990: International experiments to study tropical cyclones in the western North Pacific. Bull. Amer. Meteor. Soc.,71, 1305–1316.

  • Haltiner, G. J., and R. T. Williams, 1980: Numerical Prediction and Dynamic Meteorology. Wiley, 477 pp.

  • Le Marshall, J. F., W. Smith, and G. Callan, 1985: Hurricane Debby—An illustration of the complementary nature of VAS soundings and cloud and water vapor motion winds. Bull. Amer. Meteor. Soc.,66, 258–263.

  • ——, L. J. Stirling, R. F. Davidson, and M. J. Hassett, 1987: The Australian region McIDAS. Aust. Meteor. Mag.,35, 55–64.

  • ——, N. R. Pescod, G. A. Mills, and P. K. Stewart, 1992: Cloud drift winds in the Australian Bureau of Meteorology: An operational note. Aust. Meteor. Mag.,40, 247–250.

  • ——, ——, R. S. Seaman, G. A. Mills, and P. K. Stewart, 1994: An operational system for generating cloud drift winds in the Australian region and their impact on numerical weather prediction. Wea. Forecasting,9, 361–370.

  • ——, L. M. Leslie, and C. Spinoso, 1996a: The impact of spatial and temporal distribution of satellite observations on tropical cyclone data assimilation: Preliminary results. Meteor. Atmos. Phys.,60, 157–163.

  • ——, ——, and A. F. Benett, 1996b: Tropical Cyclone Beti—An example of the benefits of assimilating hourly satellite wind data. Aust. Meteor. Mag.,45, 275–279.

  • ——, ——, ——, C. Spinoso, and N. R. Pescod 1996c: Assimilation of direct readout satellite observations from polar and geostationary satellites in sub-synoptic scale meteorology. Adv. Space Res.,19, 413–422.

  • Leslie, L. M., and R. J. Purser, 1995: Three-dimensional mass-conserving semi-Lagrangian scheme employing forward trajectories. Mon. Wea. Rev.,123, 2551–2566.

  • Mills, G. A., G. M. Callan, and B. M. Goodman, 1986: A mesoscale data assimilation scheme for real time use in the McIDAS environment. CIMSS Tech. Rep., 86 pp. [Available from CIMSS, Space Science and Engineering Center, University of Wisconsin, 1225 West Dayton St., Madison, WI 53706.].

  • Morison, R. P., 1993: Statistical tropical cyclone forecasting. M.S. thesis, Dept. of Mathematics, Monash University, 98 pp. [Available from Monash University, Dept. of Mathematics, Clayton, Victoria 3168, Australia.].

  • Puri, K., N. E. Davidson, L. M. Leslie, and L. W. Logan, 1992: The BMRC tropical limited-area model. Aust. Meteor. Mag.,40, 81–104.

  • Velden, C. S., C. M. Hayden, W. P. Menzel, J. L. Franklin, and J. S. Lynch, 1992. The impact of satellite-derived winds on numerical hurricane track forecasts. Wea. Forecasting,7, 107–118.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 455 155 18
PDF Downloads 144 34 2