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Related Concept Videos

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

4.0K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
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Types of Coprecipitation01:10

Types of Coprecipitation

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Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
Sometimes, ions in a crystal lattice can undergo isomorphous replacement by inclusions of similar charge and size. For...
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Precipitation Processes01:12

Precipitation Processes

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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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What is Weather?01:07

What is Weather?

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Overview
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Precipitation Gravimetry01:03

Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
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Correlation of Experimental Data01:23

Correlation of Experimental Data

470
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
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A Synthetic European Weather Dataset Based on Spatiotemporal Vine Copulas.

Judith N Claassen1, Elco E Koks2, Marleen C de Ruiter2

  • 1Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. j.n.claassen@vu.nl.

Scientific Data
|November 3, 2025
PubMed
Summary

A new European weather dataset, MYRIAD-SIM, simulates temperature, precipitation, and wind speed using advanced statistical models. This data aids research into compound climate events and explores scenarios beyond historical records.

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Area of Science:

  • Climate science
  • Environmental modeling
  • Statistical downscaling

Background:

  • Stochastic weather generators are crucial for simulating realistic climate data beyond historical records.
  • Accurate weather data is vital for sectors like agriculture and energy, where multiple variables interact.
  • Existing datasets may not fully capture complex spatiotemporal and multivariate dependencies.

Purpose of the Study:

  • To introduce a novel European simulated weather dataset for temperature, precipitation, and wind speed.
  • To present the MYRIAD-Stochastic vIne-copula Model (MYRIAD-SIM) for generating this dataset.
  • To provide data that captures complex weather dependencies for enhanced climate research.

Main Methods:

  • Utilized conditional vine copulas, a statistical tool, to model spatiotemporal and multivariate dependencies.
  • Generated a new European dataset for temperature, precipitation, and wind speed.
  • Ensured the generated data statistically resembles ERA5-Land while allowing for scenario exploration.

Main Results:

  • The MYRIAD-SIM dataset closely mirrors the statistical properties of ERA5-Land data.
  • The model successfully captures intricate spatiotemporal and multivariate weather patterns.
  • The simulated data exhibits sufficient variability for exploring alternative climate scenarios.

Conclusions:

  • MYRIAD-SIM offers a valuable resource for climate research, particularly for compound climate events.
  • The dataset's ability to simulate multivariate weather conditions enhances the study of climate impacts.
  • This approach facilitates deeper insights into climate variability and potential future scenarios.