Hristo G. Chipilski
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View article: On the sensitivity of different ensemble filters to the type of assimilated observation networks
On the sensitivity of different ensemble filters to the type of assimilated observation networks Open
Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods …
View article: Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations
Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations Open
Data assimilation plays a pivotal role in understanding and predicting turbulent systems within geoscience and weather forecasting, where data assimilation is used to address three fundamental challenges, i.e., high-dimensionality, nonline…
View article: Nonlinear ensemble filtering with diffusion models: Application to the surface quasi-geostrophic dynamics
Nonlinear ensemble filtering with diffusion models: Application to the surface quasi-geostrophic dynamics Open
The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here we explore another promising solution in which diffusion models are used to formula…
View article: Exact nonlinear state estimation
Exact nonlinear state estimation Open
The majority of data assimilation (DA) methods in the geosciences are based on Gaussian assumptions. While these assumptions facilitate efficient algorithms, they cause analysis biases and subsequent forecast degradations. Non-parametric, …
View article: Toward the Application of Nonlinear Ensemble Data Assimilation Methods to Convective-Scale Parameter Estimation
Toward the Application of Nonlinear Ensemble Data Assimilation Methods to Convective-Scale Parameter Estimation Open
Recent work has demonstrated that convective-scale model parameters, such as those related to cloud microphysical schemes, are nonlinearly related to dynamic/thermodynamic variables in forecasts and observations. This leads to errors when …
View article: Progress, challenges, and future steps in data assimilation for convection‐permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021
Progress, challenges, and future steps in data assimilation for convection‐permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021 Open
In November 2021, the Royal Meteorological Society Data Assimilation (DA) Special Interest Group and the University of Reading hosted a virtual meeting on the topic of DA for convection‐permitting numerical weather prediction. The goal of …
View article: Bridging linear state estimation and machine learning
Bridging linear state estimation and machine learning Open
<p>Recent years have seen active efforts within the geophysical community to combine traditional Data Assimilation (DA) methods with emerging Machine Learning (ML) techniques. However, most of this past theoretical work has been cent…
View article: Comment on gmd-2020-303
Comment on gmd-2020-303 Open
Abstract. TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets on either rectilinear or unstructured/native grids. Version 2.1 of the TE fram…
View article: Analysis of a Case of Supercellular Convection over Bulgaria: Observations and Numerical Simulations
Analysis of a Case of Supercellular Convection over Bulgaria: Observations and Numerical Simulations Open
A long-lived supercell developed in Northwest Bulgaria on 15 May 2018 and inflicted widespread damage along its track. The first part of this article presents a detailed overview of the observed storm evolution. Doppler radar observations …
View article: Object-Based Algorithm for the Identification and Tracking of Convective Outflow Boundaries in Numerical Models
Object-Based Algorithm for the Identification and Tracking of Convective Outflow Boundaries in Numerical Models Open
A novel object-based algorithm capable of identifying and tracking convective outflow boundaries in convection-allowing numerical models is presented in this study. The most distinct feature of the proposed algorithm is its ability to seam…