no code implementations • 9 Jun 2022 • Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach, Pedram Hassanzadeh
With small ensembles, the estimated background error covariance matrix in the EnKF algorithm suffers from sampling error, leading to an erroneous estimate of the analysis state (initial condition for the next forecast cycle).
1 code implementation • 16 Mar 2021 • Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, Karthik Kashinath
These components are 1) a deep spatial transformer added to the latent space of the U-NETs to preserve a property called equivariance, which is related to correctly capturing rotations and scalings of features in spatio-temporal data, 2) a data-assimilation (DA) algorithm to ingest noisy observations and improve the initial conditions for next forecasts, and 3) a multi-time-step algorithm, which combines forecasts from DDWP models with different time steps through DA, improving the accuracy of forecasts at short intervals.
no code implementations • 11 Mar 2021 • Eviatar Bach
The optimal gain matrix of the Kalman filter is often derived by minimizing the trace of the posterior covariance matrix.
1 code implementation • 9 May 2019 • Eviatar Bach
We introduce parasweep, a free and open-source utility for facilitating parallel parameter sweeps with computational models.
Distributed, Parallel, and Cluster Computing