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Ensemble size versus bias correction effects in subseasonal-to-seasonal (S2S) forecasts
This study explores the ensemble size effect on subseasonal-to-seasonal (S2S) forecasts of the European Center for Medium-Range Weather Forecasts...
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Evaluating Short-Range Forecasts of a 12 km Global Ensemble Prediction System and a 4 km Convection-Permitting Regional Ensemble Prediction System
Information regarding the uncertainty associated with weather forecasts, particularly when they are related to a localized area at convective scales,...
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Deterministic ensemble Kalman filter based on two localization techniques for mitigating sampling errors with a quasi-geostrophic model
In the ensemble Kalman filter (EnKF) framework for data assimilation, a limited ensemble size results in a spurious sampling error and...
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Probabilistic rainy season onset prediction over the greater horn of africa based on long-range multi-model ensemble forecasts
This works proposes a probabilistic framework for rainy season onset forecasts over Greater Horn of Africa derived from bias-corrected, long range,...
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Nonlinear Segmental Runoff Ensemble Prediction Model Using BMA
In this study, a novel nonlinear segmental runoff ensemble forecast model based on the Bayesian model averaging (BMA) algorithm (NLTM-BMA m (P-III)) is...
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Flood and Non-Flood Image Classification using Deep Ensemble Learning
Floods are one of the most frequent natural disasters, often resulting in widespread devastation. Identifying floods accurately is crucial for...
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Importance Weighting in Hybrid Iterative Ensemble Smoothers for Data Assimilation
Because it is generally impossible to completely characterize the uncertainty in complex model variables after assimilation of data, it is common to...
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Weather regimes and rainfall over Tunisia in a multi-model ensemble versus a multi-member ensemble
This study aims at investigating for the first time the links of daily rainfall over Tunisia to large-scale atmospheric conditions by establishing a...
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Marginalized iterative ensemble smoothers for data assimilation
Data assimilation is an important tool in many geophysical applications. One of many key elements of data assimilation algorithms is the measurement...
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Evaluating lightning forecasts of a convective scale ensemble prediction system over India
In this comprehensive study, we have delved into the intricate realm of lightning forecasting, a captivating yet challenging pursuit due to the...
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Runoff Forecasting of Machine Learning Model Based on Selective Ensemble
Reliable runoff forecasting plays an important role in water resource management. In this study, we propose a homogeneous selective ensemble...
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An ensemble-based data assimilation system for forecasting variability of the Northwestern Pacific ocean
An adjoint-free four-dimensional variational (a4dVar) data assimilation (DA) is implemented in an operational ocean forecast system based on an...
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Non-Gaussian Ensemble Optimization
Ensemble-based optimization (EnOpt), commonly used in reservoir management, can be seen as a special case of a natural evolution algorithm. Stein’s...
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A natural Hessian approximation for ensemble based optimization
A key challenge in reservoir management and other fields of engineering involves optimizing a nonlinear function iteratively. Due to the lack of...
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Drought index downscaling using AI-based ensemble technique and satellite data
This study introduces and validates an artificial intelligence (AI)–based downscaling method for Standardized Precipitation Indices (SPI) in the...
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The first ensemble of kilometer-scale simulations of a hydrological year over the third pole
An accurate understanding of the current and future water cycle over the Third Pole is of great societal importance, given the role this region plays...
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An ensemble method based on weight voting method for improved prediction of slope stability
This study proposes a novel ensemble method based on weighted majority voting to evaluate the slope stability. The ensemble classifier is composed of...
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An analysis of ensemble models for the water surface evaporation simulation in the Three Gorges Reservoir
The current study aims to investigate the applicability of ensemble modeling in improving the simulation of water surface evaporation ( EW ) in the...
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Improvement of ENSO simulation by the conditional multi-model ensemble method
The El Niño Southern Oscillation (ENSO) is an important interannual atmosphere–ocean interaction phenomenon in the tropical Pacific. To study ENSO,...
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Application of hybrid machine learning-based ensemble techniques for rainfall-runoff modeling
The main aim of this study was to develop hybrid machine learning (ML)-based ensemble modeling of the rainfall-runoff process in the Katar catchment,...
