The etymology of modern English vocabulary explores words of native Anglo-Saxon origin, Germanic borrowings, and English elements, examining their characteristics and assimilation into the language. It delves into the ways borrowing occurs, criteria for assimilation, and the distinct layers comprisi

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NCI Data Collections BARPA & BARRA2 serve as critical enablers of big data science and analytics in Australia, offering a vast research collection of climate, weather, earth systems, environmental, satellite, and geophysics data. These collections include around 8PB of regional climate simulations a

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Delve into the discussion on regressive voice assimilation, challenging traditional views of laryngeal phonology. Explore the intricate phonetic cues and contrasts that go beyond Voice Onset Time (VOT), examining the complexities of active [-voice] in voicing languages. Discover the prevalence of re

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The integration of NLP into data pipelines represents a paradigm shift in data engineering, offering companies a powerful tool to reinvent their data workflows and unlock the full potential of their data. By automating data processing tasks, handling diverse data sources, and fostering a data-driven

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The integration of NLP into data pipelines represents a paradigm shift in data engineering, offering companies a powerful tool to reinvent their data workflows and unlock the full potential of their data. By automating data processing tasks, handling diverse data sources, and fostering a data-driven

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In today's data-driven world, organizations rely on robust data engineering pipelines to collect, process, and analyze vast amounts of data efficiently. At the heart of these pipelines lies data wrangling, a critical process that involves cleaning, transforming, and preparing raw data for analysis.

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In current data world, businesses thrive on their ability to harness and interpret vast amounts of data. This data, however, often comes in raw, unstructured forms, riddled with inconsistencies and errors. To transform this chaotic data into meaningful insights, organizations need robust data wrangl

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Public sector organizations are increasingly investing in Business Intelligence Solutions (BIS) to leverage data for decision-making. This study by Modiketse Tshehla explores the factors affecting BIS adoption, incorporating concepts like assimilation, adoption, diffusion, and infusion. Through rese

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The NOAA Unified Forecast System (UFS) is a comprehensive Earth system model designed for regional to global predictive time scales, covering various domains such as ocean, land, cryosphere, atmosphere, and more. The system involves research and operational components like data assimilation, forecas

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Data Governance and Data Analytics play crucial roles in transforming data into knowledge and insights for generating positive impacts on various operational systems. They help bring together disparate datasets to glean valuable insights and wisdom to drive informed decision-making. Managing data ma

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Joint project by USBR, USACE, and NCAR focusing on improving streamflow forecasting using automated over-the-loop approaches. Key challenges include model calibration, data assimilation, and real-time forcings. Objectives involve building an automated system for short- to long-term flow predictions

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Chemawa Indian School, established in 1880 in Forest Grove, played a significant role in the federal government's assimilation efforts towards Native American youth. The school later relocated to Salem with the labor of American Indian students. Explore its history through a series of steps includin

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Explore the impact and role of data utilization in organizations through the investigation of data collection methods, data quality, decision-making processes, reliability of collection methods, factors affecting data quality, and privacy considerations. Two scenarios are presented: data collection

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Hybrid Variational/Ensemble Data Assimilation combines features from the Ensemble Kalman Filter and Variational assimilation methods to improve the NCEP Global Forecast System. It incorporates ensemble perturbations into the variational cost function, leading to more accurate forecasts. The approach

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SCRUM2 project aims to enhance CMEMS through regional/coastal ocean-biogeochemical uncertainty modelling, ensemble consistency verification, probabilistic forecasting, and data assimilation. The research team plans to contribute significant advancements in ensemble techniques and reliability assessm

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Discussion at the Climate Modelling User Group meeting highlighted the use of Ocean ECVs, with a focus on organic carbon production and model comparisons. Key topics included increasing resolution, biogeochemistry predictions, and validation using OC CCI data. Various WP projects were also discussed

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In a series of talks, we delve into using the JEDI data assimilation system for forecast models and grids via Model.Space interface classes. Discover the importance of interface classes, the power they hold, and their implementation for specific models. Explore how these classes facilitate code inst

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This study explores the optimal ocean sampling strategy for Hurricane Isaac (2012) using high-resolution in-situ observations. It investigates the sensitivity of tropical cyclone intensity change through assimilation of AXBT, AXCTD, and AXCP observations. Results show significant impact areas along

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Study on the rapid intensification of Super Typhoon Usagi in 2013, focusing on the role of moisture, ensemble forecasting, data assimilation, and factors affecting intensity forecasts. The research explores the impact of environmental and internal factors on intensity divergence and timing variation

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Explore the future of hydrologic modeling with a focus on distributed models, data assimilation, ensemble forecasts, and verification. Discover the potential benefits of continued research in physically based models for more accurate forecasts in various conditions. Uncover challenges facing hydrolo

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Valid data from JPL was filtered and processed, resulting in the assimilation of all 41889 data points across 14 levels. The assimilated levels were detailed, with specific data points removed and quality control checks applied. Discrepancies in the center location were observed between the analysis

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The NOAA hurricane forecasting models include HWRF, POM, HYCOM, HMON, covering regions like the Pacific, Indian Ocean, North Atlantic, and Gulf of Mexico. These models utilize a combination of climatology data, feature models, and real-time RTOFS inputs for initialization and forecasting. Various co

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This presentation by Dr. Rolf H. Langland explores the concept of adaptive observing in atmospheric applications, focusing on the methodology, field programs, challenges, and objectives of targeted observing. It delves into the optimization problem of determining locations for special atmospheric ob

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The Joint Center for Satellite Data Assimilation (JCSDA) operates as a multi-agency research center aimed at enhancing the use of satellite data for weather, ocean, climate, and environmental analysis. Organized under key projects like JEDI and CRTM, JCSDA focuses on algorithm development and observ

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Explore the innovative Data Assimilation techniques and the Unified Forecast System for high-resolution regional modeling at NOAA. The suite aims to simplify operational Earth modeling, combining local and global domains, with an emphasis on observation processing, data assimilation, and verificatio

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This content provides an overview of various operational ocean modeling and forecasting systems, including data assimilation processes, glider data, surface and subsurface data sources, forecasting models for hurricanes, and NOAA's hurricane forecasting models. It covers a range of technologies and

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Explore the evolution and challenges faced in cloud-resolving Numerical Weather Prediction (NWP) models over the past 50 years. Discover key milestones, such as the development of climate models and data assimilation systems, alongside persistent issues in predicting warm season phenomena and tropic

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Explore the utilization of radiance data in global data assimilation at NOAA/NCEP, focusing on the integration of various satellite instruments like AMSU-A, ATMS, MHS, and more. Recent and upcoming enhancements to the global data assimilation system are discussed, with an emphasis on changes to the

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Preparation and assimilation of aerosol optical depth data from NPP VIIRS into a global aerosol model, including product descriptions, data requirements, processed observations, and conclusions on VIIRS aerosol products. Details on AOT, APSP, SM classification, and environmental data records are cov

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Key observations and advancements in operational air quality forecasting and data assimilation were highlighted in sessions featuring prominent experts from various organizations like ECMWF/CAMS, GAFIS, NOAA, and ECCC. Topics discussed ranged from progress and challenges in air quality forecasting i

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The 2014 NCEP Production Suite Review highlighted the significant implementation of the 13 km Global Forecast System (GFS). This major update involved substantial enhancements in resolution, observations, analysis, and physics, impacting various NCEP models and centers. The improved 13 km GFS brough

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This study delves into the exploration of strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. It discusses the challenges, benefits, and methods involved in transitioning towards coupled data assimilation systems, particularly focusing on the imbalance at the i

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Explainable AI (XAI) addresses the need for human-understandable AI models, contrasting with black box approaches. Intelligent gap filling for CCI ECV data is crucial but lacks efficient methods. Machine Learning can enhance EO data analysis with XAI insights, necessitating collaboration between dom

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This study explores data assimilation strategies for coupled atmosphere-ocean systems using an Ensemble Kalman Filter (EnKF) and a low-order analogue of the climate system. Motivated by the growing interest in near-term climate predictions, the challenges of interacting slow and fast components of t

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Thermoacoustic instabilities, a challenge for gas turbine manufacturers, are addressed through a low-order nonlinear thermoacoustic model. The model is discretized with natural acoustic modes, allowing for the quantitative accuracy of the qualitative model through data assimilation with Lagrangian o

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This research explores using machine learning as the observation operator for satellite radiance data assimilation, aiming to improve the efficiency of the process. By training the machine learning model with model output and observations, the study investigates reducing the need for a physically-ba

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Explore the structure and evolution of the Low-Level Jet (LLJ) phenomenon through combined observations and numerical models. The focus is on the LLJ across the PECAN domain, spatial and temporal variability, heterogeneity with height, continuity across cases, and evening transition effects. Efforts

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Utilizing a range of radiance data sources, NOAA/NCEP has implemented significant upgrades to its Global Data Assimilation System. Recent and upcoming changes focus on improving model levels, introducing new observation errors, and expanding all-sky assimilation capabilities. The future direction in

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Ensemble Data Assimilation system implemented in ICON-IT for pre-operational runs using IFS LBC and ICON-KENDA DA cycle. Observations such as RAOB, PILOT, SYNOP, SHIP, BUOY, Wind Profilers/Radars, etc., are assimilated. Analysis comparison with COSMO-IT includes statistical observations from May to

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Assimilating satellite observations into Numerical Weather Prediction models improves forecast accuracy and provides valuable information for various users. Key takeaways include the benefits of incorporating more satellite data, enhancing decision support for government agencies and citizens, and t

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