Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models

被引:254
作者
Chelton, DB [1 ]
Freilich, MH [1 ]
机构
[1] Oregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USA
关键词
D O I
10.1175/MWR-2861.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Wind measurements by the National Aeronautics and Space Administration (NASA) scatterometer (NSCAT) and the SeaWinds scatterometer on the NASA QuikSCAT satellite are compared with buoy observations to establish that the accuracies of both scatterometers are essentially the same. The scatterometer measurement errors are best characterized in terms of random component errors, which are about 0.75 and 1.5 m s(-1) for the along-wind and crosswind components, respectively. The NSCAT and QuikSCAT datasets provide a consistent baseline from which recent changes in the accuracies of 10-m wind analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the U.S. National Centers for Environmental Prediction (NCEP) operational numerical weather prediction (NWP) models are assessed from consideration of three time periods: September 1996-June 1997, August 1999-July 2000, and February 2002-January 2003. These correspond, respectively, to the 9.5-month duration of the NSCAT mission, the first 12 months of the QuikSCAT mission, and the first year after both ECMWF and NCEP began assimilating QuikSCAT observations. There were large improvements in the accuracies of both NWP models between the 1997 and 2000 time periods. Though modest in comparison, there were further improvements in 2002, at least partly attributable to the assimilation of QuikSCAT observations in both models. There is no evidence of bias in the 10-m wind speeds in the NCEP model. The 10-m wind speeds in the ECMWF model, however, are shown to be biased low by about 0.4 m s(-1). While it is difficult to eliminate systematic errors this small, a bias of 0.4 in s(-1) corresponds to a typical wind stress bias of more than 10%. This wind stress bias increases to nearly 20% if atmospheric stability effects are not taken into account. Biases of these magnitudes will result in significant systematic errors in ocean general circulation models that are forced by ECMWF winds.
引用
收藏
页码:409 / 429
页数:21
相关论文
共 48 条
[1]  
[Anonymous], J GEOPHYS RES
[2]   Physically based modeling of QuikSCAT SeaWinds passive microwave measurements for rain detection [J].
Boukabara, SA ;
Hoffman, RN ;
Grassotti, C ;
Leidner, SM .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2002, 107 (D24)
[3]   Scatterometer observations of wind variations induced by oceanic islands: Implications for wind-driven ocean circulation [J].
Chavanne, C ;
Flament, P ;
Lumpkin, R ;
Dousset, B ;
Bentamy, A .
CANADIAN JOURNAL OF REMOTE SENSING, 2002, 28 (03) :466-474
[4]   Satellite measurements reveal persistent small-scale features in ocean winds [J].
Chelton, DB ;
Schlax, MG ;
Freilich, MH ;
Milliff, RF .
SCIENCE, 2004, 303 (5660) :978-983
[5]  
Chelton DB, 2000, MON WEATHER REV, V128, P1993, DOI 10.1175/1520-0493(2000)128<1993:SOOTWJ>2.0.CO
[6]  
2
[7]  
CHELTON DB, 2005, IN PRESS J CLIMATE
[8]   Warm core ring velocities inferred from NSCAT [J].
Cornillon, P ;
Park, KA .
GEOPHYSICAL RESEARCH LETTERS, 2001, 28 (04) :575-578
[9]   RADAR SCATTERING AND EQUILIBRIUM RANGES IN WIND-GENERATED WAVES WITH APPLICATION TO SCATTEROMETRY [J].
DONELAN, MA ;
PIERSON, WJ .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 1987, 92 (C5) :4971-5029
[10]   Revised ocean backscatter models at C and Ku band under high-wind conditions [J].
Donnelly, WJ ;
Carswell, JR ;
McIntosh, RE ;
Chang, PS ;
Wilkerson, J ;
Marks, F ;
Black, PG .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 1999, 104 (C5) :11485-11497