Jove
Visualize
Contact Us
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 Concept Videos

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

2.0K
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...
2.0K
Precipitation Processes01:12

Precipitation Processes

578
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...
578
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

182
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
182
Precipitation Gravimetry01:03

Precipitation Gravimetry

7.2K
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...
7.2K
Multiple Regression01:25

Multiple Regression

3.2K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.2K
Survival Tree01:19

Survival Tree

153
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
153

You might also read

Related Articles

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

Sort by
Same author

Regulatory mechanisms of two epiphytic cultivation modes of Cunninghamia lanceolata on growth, disease resistance and root-stem characteristics of Dendrobium devonianum.

BMC plant biology·2026
Same author

Effect of temperature on the quality and microbial community during Daocai fermentation.

Food chemistry: X·2024
Same author

Solute carrier family 16 member 1 as a potential prognostic factor for pancreatic ductal adenocarcinoma and its influence on tumor immunity.

Journal of gastrointestinal oncology·2024
Same author

Research on the facile regeneration of degraded cathode materials from spent LiNi<sub>0.5</sub>Co<sub>0.2</sub>Mn<sub>0.3</sub>O<sub>2</sub> lithium-ion batteries.

Frontiers in chemistry·2024
Same author

VGLL2 and TEAD1 fusion proteins drive YAP/TAZ-independent tumorigenesis by engaging p300.

bioRxiv : the preprint server for biology·2024
Same author

Picein alleviates oxidative stress and promotes bone regeneration in osteoporotic bone defect by inhibiting ferroptosis via Nrf2/HO-1/GPX4 pathway.

Environmental toxicology·2024
Same journal

Validation of the ECTemp™ algorithm in construction workers: a comparison of photoplethysmography smartwatch and chest strap heart rate monitors.

Environmental research communications·2026
Same journal

Tropical cyclone exposure and risk of adverse birth outcomes in urban and rural areas of Georgia.

Environmental research communications·2026
Same journal

Black carbon emissions in Jordan: national inventory, climate and health implications (2022-2050).

Environmental research communications·2026
Same journal

The effect of wildfire air pollution on local hospital admissions in New York.

Environmental research communications·2026
Same journal

Exceptional use: examining methyl bromide applications in California 2016-2022.

Environmental research communications·2026
Same journal

The Accra school health and environment study (ASHES): a study of the urban environment and child health and development in Accra.

Environmental research communications·2026
See all related articles

Related Experiment Video

Updated: Sep 5, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

Statistical and Machine Learning Methods Applied to the Prediction of Different Tropical Rainfall Types.

Jiayi Wang1, Raymond K W Wong1, Mikyoung Jun2

  • 1Department of Statistics, Texas A&M University.

Environmental Research Communications
|July 11, 2022
PubMed
Summary
This summary is machine-generated.

Predicting tropical rainfall using machine learning and statistical methods showed limitations. Current approaches struggle with accuracy and capturing extreme rain events, indicating a need for new climate modeling strategies.

Keywords:
Convective stormsGeneralized linear modelNeural networkPrecipitation occurrenceRain rate extremesRandom forest

More Related Videos

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.1K

Related Experiment Videos

Last Updated: Sep 5, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.1K

Area of Science:

  • Atmospheric Science and Meteorology
  • Climate Modeling
  • Machine Learning Applications in Earth Science

Background:

  • Predicting rainfall from large-scale environmental variables is a significant challenge for climate models.
  • The efficacy of numerical methods in capturing true rainfall characteristics without storm-scale information remains uncertain.
  • Rainfall exhibits diverse types (deep convective, stratiform, shallow convective) with distinct structures influencing predictability.

Purpose of the Study:

  • To evaluate the predictive capabilities of three statistical and machine learning methods for rainfall occurrence and intensity.
  • To assess these methods using Global Precipitation Measurement (GPM) satellite radar data and MERRA-2 reanalysis environmental profiles.
  • To investigate if machine learning methods outperform traditional statistical models in predicting different rain types.

Main Methods:

  • Employed three prediction methods: a generalized linear model (statistical), a neural network, and a random forest (machine learning).
  • Utilized 3-hourly rain observations from the GPM satellite radar over the tropical Pacific.
  • Incorporated large-scale environmental profiles (temperature, moisture) from the MERRA-2 reanalysis dataset.

Main Results:

  • No single method significantly outperformed the others in predicting rain occurrence and intensity.
  • All tested methods exhibited common climate model issues: over-predicting rain frequency and failing to capture extreme rain rates.
  • The performance differences between statistical and machine learning approaches were not pronounced for this rainfall prediction task.

Conclusions:

  • Machine learning tools require careful validation and are not universally superior for all big data challenges.
  • Traditional climate modeling approaches are insufficient for accurately predicting extreme rainfall events.
  • Further research into alternative methods is necessary to improve the prediction of extreme weather phenomena.