Peter Jan van Leeuwen
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View article: Adaptive Correlation- and Distance-Based Localization for Iterative Ensemble Smoothers in a Coupled Nonlinear Multiscale Model
Adaptive Correlation- and Distance-Based Localization for Iterative Ensemble Smoothers in a Coupled Nonlinear Multiscale Model Open
This paper extends the 2024 study of iterative ensemble smoothers by Evensen et al., who used a sizeable 1000-member ensemble configuration, to now using smaller, more affordable ensemble sizes with localization. As is well known, localiza…
View article: Comment on egusphere-2025-2420
Comment on egusphere-2025-2420 Open
View article: Introducing non‐Gaussian observation errors into incremental variational data assimilation methods
Introducing non‐Gaussian observation errors into incremental variational data assimilation methods Open
The probability density function (pdf) of the observation error can be non‐Gaussian, with causes including representation error, bounded observables, or nonlinearity. However, it has been assumed to be Gaussian in most data assimilation ap…
View article: A Regimes‐Based Approach to Identifying Seasonal State‐Dependent Prediction Skill
A Regimes‐Based Approach to Identifying Seasonal State‐Dependent Prediction Skill Open
Subseasonal‐to‐decadal atmospheric prediction skill attained from initial conditions is typically limited by the chaotic nature of the atmosphere. However, for some atmospheric phenomena, prediction skill on subseasonal‐to‐decadal timescal…
View article: Model and observation‐error covariance matrix information in the physical nudging equations
Model and observation‐error covariance matrix information in the physical nudging equations Open
In this work we show how to extend the deterministic physical nudging scheme in order to include two important ingredients, the model and observation‐error covariance matrices, which are common features of classical data‐assimilation schem…
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: Ensemble Kalman, adaptive Gaussian mixture, and particle flow filters for optimized earthquake occurrence estimation
Ensemble Kalman, adaptive Gaussian mixture, and particle flow filters for optimized earthquake occurrence estimation Open
View article: P094 Recurrence patterns in pathological node-positive prostate cancer: Insights from preoperative and occurrence-based PSMA-PET/CT imaging
P094 Recurrence patterns in pathological node-positive prostate cancer: Insights from preoperative and occurrence-based PSMA-PET/CT imaging Open
View article: P095 Management in robot-assisted radical prostatectomy patients with recto-urethral fistulas: The York-Mason technique
P095 Management in robot-assisted radical prostatectomy patients with recto-urethral fistulas: The York-Mason technique Open
View article: Ensemble Kalman, Adaptive Gaussian Mixture, and Particle Flow Filters for Optimized Earthquake Forecasting
Ensemble Kalman, Adaptive Gaussian Mixture, and Particle Flow Filters for Optimized Earthquake Forecasting Open
Probabilistic forecasts are regarded as the highest achievable goal when predicting earthquakes, but limited information on stress, strength, and governing parameters of the seismogenic sources affects their accuracy. Ensemble data-assimil…
View article: Uncertainty Quantification for Deep Learning
Uncertainty Quantification for Deep Learning Open
We present a critical survey on the consistency of uncertainty quantification used in deep learning and highlight partial uncertainty coverage and many inconsistencies. We then provide a comprehensive and statistically consistent framework…
View article: Online state and time‐varying parameter estimation using the implicit equal‐weights particle filter
Online state and time‐varying parameter estimation using the implicit equal‐weights particle filter Open
A method is proposed for resilient and efficient estimation of the states and time‐varying parameters in nonlinear high‐dimensional systems through a sequential data assimilation process. The importance of estimating time‐varying parameter…
View article: A non‐parametric way to estimate observation errors based on ensemble innovations
A non‐parametric way to estimate observation errors based on ensemble innovations Open
Previous studies that inferred the observation error statistics from the innovation statistics can only provide the second moment of the error probability density function (pdf). However, the observation errors are sometimes non‐Gaussian, …
View article: Unbiased fully nonlinear data assimilation: the Stochastic Particle Flow Filter
Unbiased fully nonlinear data assimilation: the Stochastic Particle Flow Filter Open
Nonlinearities in numerical models for the geosciences and in observation operators that map model states to observation space have become so strong that they can no longer be ignored. The particle flow filter (PFF) is a fully nonlinear an…
View article: Data assimilation approaches with iterative ensemble smoothers in coupled nonlinear multiscale models
Data assimilation approaches with iterative ensemble smoothers in coupled nonlinear multiscale models Open
Iterative ensemble smoothers, originally developed for parameter estimation in petroleum applications, are effective data assimilation methods in coupled, unstable dynamical systems. In this study, we demonstrate this using a coupled multi…
View article: Uncertainty Quantification for Deep Learning
Uncertainty Quantification for Deep Learning Open
Many processes in the geosciences are highly complex and computationally challenging or not well known. In those cases, Machine Learning, especially Deep Learning, is becoming increasingly popular to either replace expensive numerica…
View article: Data Assimilation with Biases & Random Errors
Data Assimilation with Biases & Random Errors Open
Assimilating dynamic models and observations, along with their errors using Bayesian estimation method are challenged when the model has both aleatoric and epistemic errors. We devised a diffusion map technique that can filter an observati…
View article: Iterative Ensemble Smoothers for Data Assimilation in Coupled Nonlinear Multiscale Models
Iterative Ensemble Smoothers for Data Assimilation in Coupled Nonlinear Multiscale Models Open
This paper identifies and explains particular differences and properties of adjoint-free iterative ensemble methods initially developed for parameter estimation in petroleum models. The aim is to demonstrate the methods’ potential for sequ…
View article: A Cold Lid on a Warm Ocean: Indian Ocean Surface Rain Layers and Their Feedbacks to the Atmosphere
A Cold Lid on a Warm Ocean: Indian Ocean Surface Rain Layers and Their Feedbacks to the Atmosphere Open
Ocean surface rain layers (RLs) form when relatively colder, fresher, less dense rain water stably stratifies the upper ocean. RLs cool sea surface temperature (SST) by confining surface evaporative cooling to a thin near‐surface layer, an…
View article: The probability of metastases within different Prostate-Specific Antigen (PSA) ranges using Prostate-Specific Membrane Antigen (PSMA) positron emission tomography in patients with newly diagnosed prostate cancer
The probability of metastases within different Prostate-Specific Antigen (PSA) ranges using Prostate-Specific Membrane Antigen (PSMA) positron emission tomography in patients with newly diagnosed prostate cancer Open
View article: The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system
The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system Open
In the past decade groundbreaking new satellite observations of the Arctic sea ice cover have been made, allowing researchers to understand the state of the Arctic sea ice system in greater detail than before. The derived estimates of sea …
View article: Noise calibration for the stochastic rotating shallow water model
Noise calibration for the stochastic rotating shallow water model Open
Stochastic partial differential equations have been used in a variety of contexts to model the evolution of uncertain dynamical systems. In recent years, their applications to geophysical fluid dynamics has increased massively. For a judic…
View article: A satellite era reanalysis of the Arctic sea ice cover utilising year-round observations of sea ice thickness
A satellite era reanalysis of the Arctic sea ice cover utilising year-round observations of sea ice thickness Open
<p><span data-ogsc="rgb(36, 36, 36)" data-ogsb="white">Over the last decade, there have been a number of new observational records of Arctic sea ice thickness produced, with improved spatiotemporal coverage,…
View article: Using the (Iterative) Ensemble Kalman Smoother to Estimate the Time Correlation in Model Error
Using the (Iterative) Ensemble Kalman Smoother to Estimate the Time Correlation in Model Error Open
Numerical weather prediction systems contain model errors related to missing and simplified physical processes, and limited model resolution. While it has been widely recognized that these model errors need to be included in the data assim…
View article: Particle Filtering and Gaussian Mixtures – On a Localized Mixture Coefficients Particle Filter (LMCPF) for Global NWP
Particle Filtering and Gaussian Mixtures – On a Localized Mixture Coefficients Particle Filter (LMCPF) for Global NWP Open
In a global numerical weather prediction (NWP) modeling framework we study the implementation of Gaussian uncertainty of individual particles into the assimilation step of a localized adaptive particle filter (LAPF). We obtain a local repr…
View article: Comment on egusphere-2022-982
Comment on egusphere-2022-982 Open
Abstract. In the past decade groundbreaking new satellite observations of the Arctic sea ice cover have been made, allowing researchers to understand the state of the Arctic sea ice system in greater detail than before. Th…
View article: The true diagnostic accuracy of PSMA PET/CT for staging lymph node metastases in primary prostate cancer
The true diagnostic accuracy of PSMA PET/CT for staging lymph node metastases in primary prostate cancer Open
View article: Correlation of claims based and patient reported pad use for incontinence one year after radical prostatectomy
Correlation of claims based and patient reported pad use for incontinence one year after radical prostatectomy Open
View article: Using optics to detect positive surgical margins intraoperatively during prostate cancer surgery
Using optics to detect positive surgical margins intraoperatively during prostate cancer surgery Open
View article: Diagnostic value of sentinel lymph node biopsy for nodal staging before radiotherapy in prostate cancer patients with clinically localized disease on PSMA PET/CT versus conventional imaging
Diagnostic value of sentinel lymph node biopsy for nodal staging before radiotherapy in prostate cancer patients with clinically localized disease on PSMA PET/CT versus conventional imaging Open