Improvements to feature resolution in the OSTIA sea surface temperature analysis using the NEMOVAR assimilation scheme

被引:39
作者
Fiedler, E. K. [1 ]
Mao, C. [1 ]
Good, S. A. [1 ]
Waters, J. [1 ]
Martin, M. J. [1 ]
机构
[1] Met Off, FitzRoy Rd, Exeter EX1 3PB, Devon, England
关键词
analysis; assimilation; feature resolution; L4; length-scale; NEMOVAR; OSTIA; SST; MESOSCALE VARIABILITY; NORTH-ATLANTIC; OCEAN; SST; RETRIEVALS; SPECTRA; SYSTEM; IMPACT;
D O I
10.1002/qj.3644
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The data assimilation scheme used in the Met Office's Operational Sea Surface Temperature and Ice Analysis (OSTIA) system has been updated from an Optimal Interpolation (OI)-type scheme to a variational assimilation scheme. The updated system includes a dual length-scale background error correlation operator, and a flow-dependent component to adjust the length-scale combination in favour of the short scale in regions of high sea surface temperature (SST) variability. The variational assimilation scheme improves both the analysis performance and the representation of SST features in the OSTIA analysis compared to the OI scheme of the original system. The results of spectral analysis, assessment of horizontal SST gradients and the response of an atmospheric model to the OSTIA SST analysis as a boundary condition indicate that the flow-dependent formulation successfully contributes to improvements in the feature resolution capability of the analysis. Overall, using a short length-scale of 15 km and including a flow-dependent adjustment component produces the best results compared to using either 40 km or the first Rossby radius of deformation as the short length-scale. The new system successfully captures realistic ocean variability without introducing noise into the analysis, allowing the feature resolution capability of the new system to out-perform that of other comparable SST analysis products.
引用
收藏
页码:3609 / 3625
页数:17
相关论文
共 45 条
[1]  
[Anonymous], J MARINE SCI
[2]   Assessing the quality of sea surface temperature observations from drifting buoys and ships on a platform-by-platform basis [J].
Atkinson, Christopher P. ;
Rayner, Nick A. ;
Roberts-Jones, Jonah ;
Smith, Robert O. .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2013, 118 (07) :3507-3529
[3]   A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances [J].
Bannister, R. N. .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2008, 134 (637) :1951-1970
[4]   Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts [J].
Blockley, E. W. ;
Martin, M. J. ;
McLaren, A. J. ;
Ryan, A. G. ;
Waters, J. ;
Lea, D. J. ;
Mirouze, I. ;
Peterson, K. A. ;
Sellar, A. ;
Storkey, D. .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2014, 7 (06) :2613-2638
[5]  
BLUMEN W, 1978, J ATMOS SCI, V35, P774, DOI 10.1175/1520-0469(1978)035<0774:UPVFPI>2.0.CO
[6]  
2
[7]   Assimilating Retrievals of Sea Surface Temperature from VIIRS and AMSR2 [J].
Brasnett, Bruce ;
Colan, Dorina Surcel .
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2016, 33 (02) :361-375
[8]   The impact of satellite retrievals in a global sea-surface-temperature analysis [J].
Brasnett, Bruce .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2008, 134 (636) :1745-1760
[9]   Interpreting Energy and Tracer Spectra of Upper-Ocean Turbulence in the Submesoscale Range (1-200 km) [J].
Callies, Joern ;
Ferrari, Raffaele .
JOURNAL OF PHYSICAL OCEANOGRAPHY, 2013, 43 (11) :2456-2474
[10]   Blending Sea Surface Temperatures from Multiple Satellites and In Situ Observations for Coastal Oceans [J].
Chao, Yi ;
Li, Zhijin ;
Farrara, John D. ;
Hung, Peter .
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2009, 26 (07) :1415-1426