Results 201 to 210 of about 18,531 (254)
Journal of Geophysical Research: Atmospheres, Volume 131, Issue 14, 28 July 2026.Abstract Climate change has caused highly uncertain precipitation regimes and associated hydrometeorological hazards over global drylands. Accurate precipitation measurements are vital for monitoring dryland ecohydrology. Satellite precipitation products (SPPs), including the Integrated Multi‐satellitE Retrievals for GPM (Global Precipitation ...
Diya Das +3 more
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Journal of Geophysical Research: Atmospheres, Volume 131, Issue 14, 28 July 2026.Abstract Pyrocumulonimbus (pyroCb) events, smoke‐infused thunderstorm clouds triggered by intense wildfires under suitable meteorological conditions, are an efficient pathway for transporting smoke to elevated altitudes. In some cases, smoke reaches the upper troposphere and lower stratosphere region, where it can persist for extended time periods and ...
Tabea Unser +3 more
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Geophysical Research Letters, Volume 53, Issue 13, 16 July 2026.Abstract This study assesses the influence of ocean–atmosphere coupling on short‐ and medium‐range forecasts of the July 2024 Indian summer monsoon using the newly configured coupled NCMRWF Unified Model (C‐NCUM). Forecasts are evaluated against the operational atmosphere–land model (NCUM) using GPM rainfall, OSTIA SSTs, and reanalysis‐derived moisture
Sumit Kumar +7 more
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Calibration of a Neural Network Ocean Closure for Improved Mean State and Variability
Geophysical Research Letters, Volume 53, Issue 13, 16 July 2026.Abstract Global ocean models exhibit biases in the mean state and variability, particularly at coarse resolution, where mesoscale eddies are unresolved. To address these biases, parameterization coefficients are typically tuned ad hoc. Here, we formulate parameter tuning as a calibration problem using Ensemble Kalman Inversion (EKI).
Pavel Perezhogin +2 more
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Kalman filter and extended Kalman filter [PDF]
, 2017 In the Bachelor’s thesis we describe the Kalman filtering algorithm for linear-Gaussian state space models and give an example of its application. We describe the extended Kalman filter for differentiable Gaussian state space models and give examples of its application.
Järvsoo, Johanna Adele
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Polynomial extended Kalman filter
IEEE Transactions on Automatic Control, 2005This work presents a polynomial version of the well-known extended Kalman filter (EKF) for the state estimation of nonlinear discrete-time stochastic systems. The proposed filter, denoted polynomial EKF (PEKF), consists in the application of the optimal polynomial filter of a chosen degree mu to the Carleman approximation of a nonlinear system. When mu
GERMANI, Alfredo +2 more
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An interlaced extended Kalman filter
IEEE Transactions on Automatic Control, 1999The aim of the paper is to propose an estimation algorithm, called Interlaced Extended Kalman Filter (IEKF), for a class of discrete-time nonlinear systems. The vector state of the system is assumed to be partitionable into \(m\) parts (subsystems), whose dynamic equations are supposed to be affine for each of the corresponding part (subsystem).
Luigi Glielmo +2 more
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Robust extended Kalman filtering
IEEE Transactions on Signal Processing, 1999Summary: Linearization errors inherent in the specification of an extended Kalman filter (EKF) can severely degrade its performance. This correspondence presents a new approach to the robust design of a discrete-time EKF by application of the robust linear design methods based on the \(H_\infty\) norm minimization criterion.
Einicke, G., White, L.
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Modified extended Kalman filtering
IEEE Transactions on Automatic Control, 1994The authors propose a modification of the extended Kalman filtering algorithm for the following system: \[ dX_ t= f(t, X_ t) dt+ \varepsilon_ 1 \sigma_ 1 (t)dV_ t, \qquad dy_ t= h(t, X_ t) dt+ \varepsilon_ 2 \sigma_ 2 (t) dW_ t, \] where \((V_ t)\) and \((W_ t)\) are independent Brownian motions, \((X_ t)\in \mathbb{R}^ n\) and \((y_ t)\in \mathbb{R ...
Nasir U. Ahmed, S. M. Radaideh
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Extended Kalman filter for extended object tracking
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017In this work, we present a novel method for tracking an elliptical shape approximation of an extended object based on a varying number of spatially distributed measurements. For this purpose, an explicit nonlinear measurement equation is formulated that relates the kinematic and shape parameters to a measurement by means of a multiplicative noise term.
Shishan Yang, Marcus Baum
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