# optimal interpolation data assimilation

data assimilation. ,, 1 CEREA, joint laboratory ENPC – EDF R&D, Université Paris-Est, Marne la Vallée, France; 2 INRIA, Paris-Rocquencourt research center, France [1990], and Data Assimilation Alan O’Neill Data Assimilation Research Centre University of Reading. … : 27 May 2008 Optimal Interpolation We now describe the OI method. (2003). ROMS has a comprehensive four-dimensional variational (4D-Var) data assimilation algorithm for the ocean com- Optimal interpolation (OI) has been used to produce analyses of quasi‐geostrophic (QG) stream function over a 59‐day period in a 150‐km‐square domain off northern California. <> !e��v�Fp�vd-��'AOdTI�~�\�YڮR����2*z�q��u!ke��2X���� Install it with Anaconda. The basic concept of statistical interpolation will be introduced and the pursued goals will be clari ed. ERA-40 precipitation data include large-scale rain rate, convective rain rate and snowfall rate. Phys. Data assimilation is a mathematical discipline that seeks to optimally combine theory with observations. 3. double), ClassModel is the type of the model (e.g. Three-dimensional variational analysis (3D-Var) 14 . raw data using one of the following families of several methods: (i) Perform a simple interpolation, no information is added to the data. Introduction Over the past decade, the planners of the First GARP Global Experiment (FGGE)-have labored to assure that the meteoroloqical observing system extant during the Experiment would provide truly global coveraqe on a nearly continuous basis. • the optimal interpolation algorithm (Section 2), • Kalman ﬁlters (ensemble – Section 3 – and RRSQRT – Section 5), • 4D-Var assimilation (Section 4). Optimal interpolation (OI) has been used to produce analyses of quasi-geostrophic (QG) stream function over a 59-day period in a 150-km-square domain off northern California. 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. Prerequisite: python>=3.6. Bouttier and Courtier, 1999). Under wide assumptions, OI is optimal in the sense that it is the best linear, unbiased estimator of a eld. Most weather centers around the world used OI for operational numerical weather forecasts throughout the 1970s and 80s. [1992], Thomas [1988], Janssen et al. Optimal interpolation (OI) has been used to produce analyses of quasi-geostrophic (QG) stream function over a 59-day period in a 150-km-square domain off northern California. 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. This system is tested with an eddy-resolving system of the South China Sea (SCS). tions and data assimilation methods is presented. Venkataraman , 2G.R. The ensemble optimal interpolation (EnOI) is applied to the regional ocean modeling system (ROMS) with the ability to assimilate the along-track sea level anomaly (TSLA). The article proposes parallel implementation of the Ensemble Optimal Interpolation (EnOI) data assimilation (DA) method in eddy-resolving World Ocean circulation model. 3. Data assimilation provides a framework to combine the large area coverage of GHI estimates derived from satellite imagery with the more accurate data of ground sensors. with the Ensemble Optimal Interpolation scheme (En OI) and it is shown that it has several advantages, in particular, it provides a better forecast and requires less computational cost. The matrix Pb is the background error This procedure is purely algorithmic ; (ii) Add as information the statistical structure of the ﬁelds and use an optimal interpolation type method. The optimal interpolation is a sequential data assimilation method. 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. Discuss. 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. Note that the black and orange arrow lines in (b) indicate the forecast and analysis steps, respectively. Works on Linux/Windows/Mac. These tools are closely related to those of estimation theory and to those of optimal control. Under certain conditions, statistical interpolation becomes the so-called optimal interpolation, that entirely relies It is implemented in OptimalInterpolation.hxx and OptimalInterpolation.cxx.The class OptimalInterpolation is a template class: OptimalInterpolation

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