Jove
Visualize
Contact Us

Related Concept Videos

Precipitation Processes01:12

Precipitation Processes

4.7K
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...
4.7K
Precipitation Gravimetry01:03

Precipitation Gravimetry

13.8K
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...
13.8K
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...
4.0K
Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

4.7K
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...
4.7K
Types of Coprecipitation01:10

Types of Coprecipitation

5.0K
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...
5.0K
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

36
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
36

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Interoperable Traceability in Agrifood Supply Chains: Enhancing Transport Systems Through IoT Sensor Data, Blockchain, and DataSpace.

Sensors (Basel, Switzerland)·2025
Same author

Deep Learning for Opportunistic Rain Estimation via Satellite Microwave Links.

Sensors (Basel, Switzerland)·2024
Same author

ZPD Retrieval Performances of the First Operational Ship-Based Network of GNSS Receivers over the North-West Mediterranean Sea.

Sensors (Basel, Switzerland)·2024
Same author

Environmental Temperature, Other Climatic Variables, and Cardiometabolic Profile in Acute Myocardial Infarction.

Journal of clinical medicine·2024
Same author

A machine learning approach to assess Sustainable Development Goals food performances: The Italian case.

PloS one·2024
Same author

Use of Sentinel-3 OLCI Images and Machine Learning to Assess the Ecological Quality of Italian Coastal Waters.

Sensors (Basel, Switzerland)·2023
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jan 13, 2026

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.2K

A Two-Step Machine Learning Approach Integrating GNSS-Derived PWV for Improved Precipitation Forecasting.

Laura Profetto1, Andrea Antonini2, Luca Fibbi2,3

  • 1Dipartimento Ingegneria dell'Informazione e Scienze Matematiche (DIISM), Universitá di Siena, 53100 Siena, Italy.

Entropy (Basel, Switzerland)
|October 28, 2025
PubMed
Summary
This summary is machine-generated.

Global Navigation Satellite System (GNSS) meteorology enhances precipitation nowcasting using Precipitable Water Vapor (PWV). A novel machine learning approach improves short-term weather forecasts, especially during extreme events.

Keywords:
GNSS meteorologyPrecipitable Water Vapor (PWV)machine learningprecipitation nowcastingshort-term weather forecasting

More Related Videos

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.4K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

11.0K

Related Experiment Videos

Last Updated: Jan 13, 2026

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.2K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.4K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

11.0K

Area of Science:

  • Atmospheric Science
  • Meteorology
  • Geophysics

Background:

  • Global Navigation Satellite System (GNSS) meteorology offers high-resolution, near-real-time atmospheric data.
  • Precipitable Water Vapor (PWV) derived from GNSS is a crucial indicator of atmospheric moisture.
  • Accurate short-term precipitation forecasting is vital for various applications.

Purpose of the Study:

  • To enhance short-term precipitation forecasting by integrating GNSS-derived PWV with traditional meteorological data.
  • To develop and evaluate a novel two-step machine learning framework for precipitation nowcasting.
  • To improve the accuracy of precipitation forecasts, particularly during extreme weather events.

Main Methods:

  • A hybrid machine learning framework combining Random Forest (RF) and Long Short-Term Memory (LSTM) neural networks was developed.
  • The RF model estimated current precipitation using PWV, surface weather, and auxiliary atmospheric variables.
  • The LSTM network predicted subsequent hour precipitation by analyzing temporal data dependencies.

Main Results:

  • The proposed hybrid RF-LSTM model demonstrated improved precipitation forecasting accuracy.
  • The model showed particular effectiveness in predicting extreme weather events like intense rainfall and thunderstorms.
  • Performance surpassed conventional precipitation nowcasting models.

Conclusions:

  • Integrating GNSS meteorology with advanced machine learning provides a powerful tool for precipitation nowcasting.
  • The developed framework offers a promising solution for meteorological services, early warning systems, and disaster risk management.
  • GNSS-based nowcasting has significant potential for real-time decision-making in weather-sensitive applications.