ERS scatterometer wind data impact on ECMWF's tropical cyclone forecasts

This paper describes the positive impact of ERS scatterometer data on tropical cyclone analyses and forecasts at the European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, U.K. ERS scatterometer data is especially valuable because sparse genesis regions of tropical cyclones are available in the data, and they are available in cloudy and rainy conditions. In November 1997, ECMWF introduced a four-dimensional variational assimilation system (4D-Var) in operational use. This system benefits from a better utilization of ERS scatterometer wind data, ECMWF is using ERS-2 scatterometer wind data in the daily operational assimilation system. In order to understand and investigate the impact of ERS scatterometer wind data, assimilations with and without the use of scatterometer data have been performed for the most intense part of the 1995 Atlantic hurricane season. A comparison with the 1995 operational ECMWF optimum interpolation (OI) assimilation system's performance has also been done. Both intensity and positional errors of tropical cyclones are investigated for analyses and forecasts. The 4D-Var assimilation system show's great improvements compared to the previous OI assimilation system, and the best results are obtained when ERS scatterometer data are used in 4D-Var.

[1]  R. Daley Atmospheric Data Analysis , 1991 .

[2]  P. Courtier,et al.  A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .

[3]  Anthony Hollingsworth,et al.  The statistical structure of short-range forecast errors as determined from radiosonde data , 1986 .

[4]  David L. T. Anderson,et al.  Scatterometer Data Interpretation: Measurement Space and Inversion , 1997 .

[5]  K. Katsaros,et al.  Observation of tropical cyclones by high-resolution scatterometry , 1998 .

[6]  W. M. Gray,et al.  The formation of tropical cyclones , 1998 .

[7]  Ross N. Hoffman A preliminary study of the impact of the ERS 1 C band scatterometer wind data on the European Centre for Medium-Range Weather Forecasts global data assimilation system , 1993 .

[8]  David L. T. Anderson,et al.  Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4 , 1997 .

[9]  Robert E. McIntosh,et al.  Revised ocean backscatter models at C and Ku band under high-wind conditions , 1999 .

[10]  L. Isaksen Impact of ERS scatterometer data in the ECMWF 4D-Var assimilation system. Preliminary studies , 1997 .

[11]  A. Lorenc Optimal nonlinear objective analysis , 1988 .

[12]  P. Courtier,et al.  The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). I: Formulation , 1998 .

[13]  Ad Stoffelen,et al.  Ambiguity removal and assimilation of scatterometer data , 1997 .

[14]  Roger Saunders,et al.  Near-Surface Satellite Wind Observations of Hurricanes and Their Impact on ECMWF Model Analyses and Forecasts , 1998 .

[15]  P. Undén Tropical data assimilation and analysis of divergence , 1989 .