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Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

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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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Precipitation Gravimetry01:03

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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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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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Types of Coprecipitation01:10

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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.
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Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

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In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
In the Volhard method, a standard excess of AgNO3 is first added to the...
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Severe Hail Fall and Hailstorm Detection Using Remote Sensing Observations.

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Radar observations are most effective for identifying severe hailstorms and hail occurrence, outperforming satellite data. Combining single- and dual-polarization radar metrics offers the greatest skill in hail detection and size estimation.

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Area of Science:

  • Atmospheric Science
  • Meteorology
  • Remote Sensing

Background:

  • Severe hail events cause significant property damage in the U.S.
  • Ground-based radar (NEXRAD) and geostationary satellites are key tools for severe storm detection.
  • Recent upgrades to radar and satellite technology necessitate an updated assessment of their capabilities.

Purpose of the Study:

  • To compare the effectiveness of radar and satellite data in identifying hailstorms and hail occurrence.
  • To assess the ability of different radar types (single- vs. dual-polarization) to discriminate hail sizes.
  • To propose improvements to the Maximum Expected Size of Hail (MESH) metric.

Main Methods:

  • Analyzed over 10,000 storms identified via radar echo-top tracking.
  • Utilized nearly 6,000 hail reports from 30 severe weather days (2013-present).
  • Compared radar (single- and dual-polarization) and satellite observational products.

Main Results:

  • Radar observations demonstrated the highest skill in discriminating severe from non-severe hailstorms and identifying hail occurrence.
  • Single- and dual-polarization radar performed similarly, but combining metrics yielded the greatest skill.
  • Proposed revisions to the MESH metric improved comparisons between reported and estimated hail sizes.

Conclusions:

  • Radar remains the most skillful tool for real-time severe hail detection and characterization.
  • Combining radar polarization metrics enhances hail detection capabilities.
  • Improvements to the MESH metric are crucial for accurate hail size estimation.