## optimal interpolation data assimilation

Ensemble Optimal Interpolation Consider the analysis equations, wa =wb +K(d −Hwb), …1 K =Pb H T (HP b H T +R)−1 …2 where w is the model state vector, d is the vector of observations, K is the gain matrix, and H is an operator that maps from model-space to observation-space – often H is simply linear interpolation. double), ClassModel is the type of the model (e.g. ��U��Mn���k��w\���o�=��x�M\p�u�8?�G�X�~���yZ�����^�F��6�:�}�ˉa^yt�tu��D�/���?�7�o��������J 1,��F����[wxP�r�� �+�斫���cI� q�IlYF�?�3�LJ�0�>\��ѭ�iZ�yez��y��$����8D��J�l^�d_J)~�o��5�F�O`=�/����'$�Q��V��w/��P���E�)��?ϼ��[�&�@ { (2003). Install it with Anaconda. Optimal Interpolation Optimal Interpolation or OI is a commonly used and fairly simple but powerful method of data assimilation. 1. The simplest data assimilation method is optimal interpolation (OI) and can be derived within both variational and sequential frameworks. Prerequisite: python>=3.6. trogen, N, phytoplankton, P, zooplankton, Z and detritus, D. Assimilation of synthetic biomass data is performed by means of the reduced-order optimal interpolation system SOFA. 12 . This procedure is purely algorithmic ; (ii) Add as information the statistical structure of the ﬁelds and use an optimal interpolation type method. This system is tested with an eddy-resolving system of the South China Sea (SCS). IEEE Xplore, delivering full text access to the world's highest quality technical literature in engineering and technology. <> PM 10 data assimilation over Europe with the optimal interpolation method M. Tombette 1,2, V. Mallet 1,2, and B. Sportisse 1,2 M. Tombette et al. data assimilation are introduced. Discuss. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. • the optimal interpolation algorithm (Section 2), • Kalman ﬁlters (ensemble – Section 3 – and RRSQRT – Section 5), • 4D-Var assimilation (Section 4). %PDF-1.4 Kalnay (2003). tions and data assimilation methods is presented. We use optimal interpolation (OI), which can be thought of as Four-dimensional variational assimilation (4D-Var) ... Data assimilation is an analysis technique in which the observed information is … stream This paper describes the application of Ensemble Optimal Interpolation (EnOI) with Monte Carlo (MC) simulation for surface currents forecasting. Data Assimilation Alan O’Neill Data Assimilation Research Centre University of Reading. %äüöß Global Data Assimilation by Local Optimum Interpolation I. Sea level anomalies (SLA) from the Ocean Topography Experiment (TOPEX)/Poseidon are assimilated with three-dimensional variational data assimilation (3DVAR) and ensemble optimal interpolation (EnOI) for the period of 1997–2001. Hµ¿nÂ0ÆÀïpc;$ØÿÄc+ÊØ)K4\À8Å1úöµ ® /lÝý¾óÝ1`ñø5År \çZæ¤ àZò\²OÂ°KjN(¤fBL÷-ÉhN¥aQ7µàÆDý ËÍ,^W0¯C OÃ`;»«íÝ#T[ÂXbd&. The sensitivity of the model error, i.e., the difference between … Optimal Interpolation ... Schematics for (a) Tibetan Plateau data assimilation, (b) general design of the DART/CLM4-based multisensor land-assimilation framework and (c) DRP-4DVar-based Coupled Data Assimilation System using FGOALS-g2. Unfortunately For the assimilation process, Direct Insertion (DI), Optimal Interpolation (OI) and Ensemble Optimal Interpolation … data assimilation. Carmichael2, S. Kulkarni [1990], and PM10 data assimilation over Europe with the optimal interpolation method M. Tombette1,2, V. Mallet2,1, and B. Sportisse1,2 1CEREA, joint laboratory ENPC – EDF R&D, Universite Paris-Est, Marne la Vall´ ee, France´ 2INRIA, Paris-Rocquencourt research center, France Received: 26 March 2008 – Published in Atmos. 3. The mix of subsystems now planned includes Under wide assumptions, OI is optimal in the sense that it is the best linear, unbiased estimator of a eld. Ensemble optimal interpolation Consider the analysis equations, wa = wb + K(d – H wb) …1 K = Pb HT (HPb HT + R)-1 …2 where w is the model state vector, d is the vector of observa-tions, K is the gain matrix, and H is an operator that maps from model-space to observation-space – often H is simply linear interpolation. The basics of data assimilation as an application of estimation theory or control theory is described and the corresponding statistical and numerical methods are introduced. 1992 ], Burgers et al were assimilated into a QG open boundary model. 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