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 Processes01:12

Precipitation Processes

428
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...
428
What is Weather?01:07

What is Weather?

18.2K
Overview
18.2K
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

1.7K
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...
1.7K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.4K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.4K
Random Error01:04

Random Error

840
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
840
Random Variables01:09

Random Variables

11.4K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
11.4K

You might also read

Related Articles

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

Sort by
Same author

Machine learning modeling of vegetation and limited two dimensional urban morphology effects on land surface temperature in Osaka using open data.

Scientific reports·2026
Same author

Passive cooling garments for outdoor thermal adaptation: a field experiment.

International journal of biometeorology·2026
Same author

High-resolution urban-scale impact of retro-reflective façade materials on building thermal load.

Scientific reports·2025
Same author

Future climate impacts on urban office Buildings: Energy, comfort, and passive solutions in Osaka, Japan.

Journal of thermal biology·2025
Same author

Acquired ROS1 fusion and iruplinalkib response in advanced NSCLC after multiple lines of systematic therapy: a case report.

Frontiers in oncology·2025
Same author

Influence of kindergarten dormitory bed layout on the proximity propagation characteristics of exhaled pollutants.

Journal of occupational and environmental hygiene·2025

Related Experiment Video

Updated: Jun 9, 2025

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device
14:48

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device

Published on: April 17, 2021

4.0K

Multivariate stochastic generation of meteorological data for building simulation through interdependent

Zhichao Jiao1, Jihui Yuan2, Craig Farnham3

  • 1Department of Housing and Environmental Design, Graduate School of Human Life and Ecology, Osaka Metropolitan University, Osaka, 558-8585, Japan. jiaozhichao1995@gmail.com.

Scientific Reports
|October 22, 2024
PubMed
Summary

This study introduces a new method for generating realistic weather data, crucial for assessing building energy use under climate change. The generated data captures original characteristics while better reflecting weather uncertainties.

Keywords:
Building energy simulationMultivariate time seriesS-vine copulaStatistical downscalingStochastic weather generator

More Related Videos

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

10.7K
Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

8.7K

Related Experiment Videos

Last Updated: Jun 9, 2025

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device
14:48

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device

Published on: April 17, 2021

4.0K
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

10.7K
Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

8.7K

Area of Science:

  • Building energy assessment
  • Climate change impact studies
  • Meteorological data generation

Background:

  • Increasing attention on weather uncertainty and climate change impacts on building energy assessment.
  • Existing stochastic meteorological data generation methods face challenges with non-continuous variables like solar radiation.
  • Need for methods that fully account for simultaneity among multiple meteorological elements.

Purpose of the Study:

  • To propose a novel framework for generating stochastic meteorological data that addresses challenges with non-continuous variables.
  • To improve the accuracy and representativeness of weather data for building energy simulations.
  • To provide a method that captures both original data characteristics and inherent weather uncertainties.

Main Methods:

  • Multivariate time series modeling using S-vine copula for daily 12:00 air temperature, solar radiation, and absolute humidity.
  • Simulation of 365-day series data at 12:00 for a typical year.
  • Expansion of 12:00 data to 24-hour series based on historical probability of change for yearly stochastic data generation.

Main Results:

  • Generated data closely matches original air temperature and solar radiation distribution characteristics over 30 years.
  • Minor deviation observed in the kurtosis of absolute humidity compared to original data.
  • Thermal load distributions for office buildings using generated data encompass the original data curve, indicating captured uncertainty.

Conclusions:

  • The proposed framework successfully generates yearly stochastic weather data that retains original characteristics while incorporating greater uncertainty.
  • The method is suitable for building energy assessment, providing a more robust dataset for climate change impact studies.
  • Further refinement may be needed to fully match the kurtosis of absolute humidity in generated datasets.