Search Results for "data assimilation"

Model for the simulation of atmospheric tracer transport & chemistry. Allows Zooming. 4D-variational data-assimilation is possible based on the adjoint of the transport code (including zoom).

***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. ...

Generic data-assimilation toolbox written in java, with native (c and fortran) libraries for high performance computing. Provides tools to couple to your own model and a wide range of algorithms, ranging from parameter calibration to Kalman filters.

...Two scripting languages (PCRcalc and Python) include a rich set of spatial operations for manipulating and analysing raster maps. A Python framework supports Monte Carlo simulations and data assimilation (Ensemble Kalman Filter and Particle Filter). The Aguila tool allows for the interactive visualisation of stochastic spatio-temporal data.

The latest ESMF development is happening in GitHub: https://github.com/esmf-org/esmf https://earthsystemmodeling.org The Earth System Modeling Framework provides high-performance software infrastructure and superstructure for the construction and coupling of climate, weather, and data assimilation applications.

A coupled dual porosity Stokes model implemented with FEniCS. References: 1. C. Douglas, X. Hu, B. Bai, X. He, M. Wei and J. Hou, "A Data Assimilation Enabled Model for Coupling Dual Porosity Flow with Free Flow," 2018 17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), Wuxi, 2018, pp. 304-307. doi: 10.1109/DCABES.2018.00085 2. Hu X., Douglas C.C. (2019) An Implementation of a Coupled Dual-Porosity-Stokes Model with FEniCS. ...

Development of new data assimilation techniques for ocean models

Pheno Analysis is a sequential data assimilation framework for use with prognostic phenology models. It uses MODIS satellite data to constrain model parameters and states.

PANDA (Passing Attributes between Networks for Data Assimilation), is a message-passing model to gene regulatory network reconstruction. PANDA integrates multiple sources of biological data, including protein-protein interaction, gene expression, and sequence motif information, in order to reconstruct genome-wide, condition-specific regulatory networks. PANDA is also available in other programming languages, including: MATLAB/Octave: (1) https://drive.google.com/a/channing.harvard.edu/file/d/0BwVdzX3nIj6RamtmNVdKYVk1N2c/view?...

Data Assimilation (DA) is a computational approach that estimates unknown parameters in a pathway model using time-course data. Here, we developed a Java software with an intuitive interface to allow users to carry out parameters estimation using DA.

Problem Solving Environment (PSE) for Data Assimilation and Model Calibration

The Land Information System (LIS) is a high performance land surface modeling and data assimilation system, based on GSFC's Land Data Assimilation Systems. This site provides LIS source codes and data to registered users.

The Inverse Ocean Model (IOM) is a software system for developing customized data-assimilation systems for numerical ocean models. It has also been used with general purpose hydrodynamic and geodynamic models.