Pressure image assimilation for atmospheric motion estimation

The complexity of the laws of dynamics governing 3-D atmospheric flows associated with incomplete and noisy observations make the recovery of atmospheric dynamics from satellite image sequences very difficult. In this paper, we address the challenging problem of estimating physical sound and time-consistent horizontal motion fields at various atmospheric depths for a whole image sequence. Based on a vertical decomposition of the atmosphere, we propose a dynamically consistent atmospheric motion estimator relying on a multilayer dynamic model. This estimator is based on a weak constraint variational data assimilation scheme and is applied on noisy and incomplete pressure difference observations derived from satellite images. The dynamic model is a simplified vorticity-divergence form of a multilayer shallow-water model. Average horizontal motion fields are estimated for each layer. The performance of the proposed technique is assessed using synthetic examples and using real world meteorological satellite image sequences. In particular, it is shown that the estimator enables exploiting fine spatio-temporal image structures and succeeds in characterizing motion at small spatial scales.

[1]  Anne Cuzol,et al.  A Stochastic Filtering Technique for Fluid Flow Velocity Fields Tracking , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  N. Mansour.  Large-eddy simulation of a turbulent mixing layer , 1978 .

[3]  Jianhua Luo,et al.  Globally Convergent Edge-preserving Reconstruction with Contour-line Smoothing , 2011 .

[4]  Ricardo Gutierrez-Osuna,et al.  An Iterative Image Registration Technique Using a Scale-Space Model , 2011 .

[5]  Chi-Wang,et al.  ANTI-DIFFUSIVE FINITE DIFFERENCE WENO METHODS FOR SHALLOW WATER WITH TRANSPORT OF POLLUTANT , 2006 .

[6]  CLOUD PROCESSING FOR METEOSAT SECOND GENERATION (MSG) , 1999 .

[7]  P. Courtier,et al.  Variational Assimilation of Meteorological Observations With the Adjoint Vorticity Equation. I: Theory , 2007 .

[8]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[9]  Patrick Pérez,et al.  Dense estimation and object-based segmentation of the optical flow with robust techniques , 1998, IEEE Trans. Image Process..

[10]  3 D motion estimation of atmospheric layers from image sequences , 2007 .

[11]  C. Schnörr,et al.  Optical Stokes flow estimation: an imaging-based control approach , 2006 .

[12]  T. Corpetti,et al.  Fluid experimental flow estimation based on an optical-flow scheme , 2006 .

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

[14]  T. Corpetti,et al.  Pressure image assimilation for atmospheric motion estimation , 2009 .

[15]  N. Papadakis,et al.  A variational method for joint tracking of curve and motion , 2007 .

[16]  Andrew F. Bennett,et al.  Inverse Methods in Physical Oceanography: Bibliography , 1992 .

[17]  P. Courtier,et al.  Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations , 1990 .

[18]  Nicolas Papadakis,et al.  A Variational Technique for Time Consistent Tracking of Curves and Motion , 2008, Journal of Mathematical Imaging and Vision.

[19]  Kenneth Holmlund,et al.  The Utilization of Statistical Properties of Satellite-Derived Atmospheric Motion Vectors to Derive Quality Indicators , 1998 .

[20]  J. Leese,et al.  An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite Data Using Cross Correlation , 1971 .

[21]  Dmitry B. Goldgof,et al.  Fluid structure and motion analysis from multi-spectrum 2D cloud image sequences , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[22]  C. Meneveau,et al.  Scale-Invariance and Turbulence Models for Large-Eddy Simulation , 2000 .

[23]  Cloud/Hydrometeor Initialization in the 20-km RUC Using GOES and Radar Data , 2002 .

[24]  A. Bennett,et al.  The generalized inverse of a nonlinear quasigeostrophic ocean circulation model , 1992 .

[25]  P. Courtier,et al.  Extended assimilation and forecast experiments with a four‐dimensional variational assimilation system , 1998 .

[26]  Guillermo Artana,et al.  Variational assimilation of POD low-order dynamical systems , 2007 .

[27]  Étienne Mémin,et al.  Optical-Flow for 3D Atmospheric Motion Estimation , 2008, VISAPP.

[28]  Robert M. Aune,et al.  NWP Cloud Initialization Using GOES Sounder Data and Improved Modeling of Nonprecipitating Clouds , 2000 .

[29]  J. Schmetz,et al.  Satellite observations of upper tropospheric relative humidity, clouds and wind field divergence , 1995 .

[30]  Jing Yuan,et al.  Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation , 2005, Scale-Space.

[31]  E.,et al.  4D Variational Data Analysis with Imperfect Model , 2000 .

[32]  John Frederick Bailyn,et al.  Generalized Inversion , 2004 .

[33]  Patrick Pérez,et al.  Dense Estimation of Fluid Flows , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Donald Geman,et al.  Constrained Restoration and the Recovery of Discontinuities , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[36]  M. Ghil,et al.  Data assimilation in meteorology and oceanography , 1991 .

[37]  Nicolas Papadakis,et al.  Layered Estimation of Atmospheric Mesoscale Dynamics From Satellite Imagery , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Yoram Bresler,et al.  Globally convergent edge-preserving regularized reconstruction: an application to limited-angle tomography , 1998, IEEE Trans. Image Process..

[39]  C. Schnörr,et al.  Optical Stokes Flow Estimation: An Imaging‐Based Control Approach , 2006 .

[40]  Philippe Courtier,et al.  Use of cloud‐cleared radiances in three/four‐dimensional variational data assimilation , 1994 .

[41]  F. L. Dimet,et al.  Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects , 1986 .

[42]  L. Leslie,et al.  Generalized inversion of a global numerical weather prediction model , 1996 .

[43]  J. Smagorinsky,et al.  GENERAL CIRCULATION EXPERIMENTS WITH THE PRIMITIVE EQUATIONS , 1963 .

[44]  Anne Cuzol,et al.  A Low Dimensional Fluid Motion Estimator , 2007, International Journal of Computer Vision.

[45]  William L. Smith,et al.  Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS. , 1983 .

[46]  E. Tadmor,et al.  New High-Resolution Central Schemes for Nonlinear Conservation Laws and Convection—Diffusion Equations , 2000 .

[47]  Geoffrey Ingram Taylor,et al.  The transport of vorticity and heat through fluids in turbulent motion , 1932 .