A Review of Current and Future Weather Data for Building Simulation

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1. What contributions have the authors mentioned in the paper "A review of current and future weather data for building simulation" ?

2. What future works have the authors mentioned in the paper "A review of current and future weather data for building simulation" ?

3. What are some examples of methods to further investigate on the creation of super-synthetic?

4. What is the inverse probability associated with Bayes’ theorem?

Accepted Answer

This article provides the first comprehensive assessment of methods for the creation of weather variables for use in building simulation.. The authors undertake a critical analysis of the fundamental issues and limitations of each methodology and discusses new challenges, such as how to deal with uncertainty, the urban heat island, climate change and extreme events.. This article provides the first comprehensive assessment of their technical requirements to ensure buildings perform well in both current and future climates.. It is found that there are various issues with all current and suggested approaches, but the two areas most requiring attention are the production of weather files for the urban landscape and files specifically designed to test buildings against the criteria of morbidity, mortality and building services system failure.

Accepted Answer

The morphing methodology also has the inherent assumption that the weather patterns will not change in the future.. The future weather file will contain identical weather patterns to the base weather file albeit with magnitudes of weather variables shifted and stretched by the morphing algorithms.. This means that the future weather years will be comparable to the baseline years.. In general, RCMs with hourly temporal resolution can be used to successfully produce future weather data sets even for the case of extreme conditions [ 130 ] through the corresponding climate change projections.

Accepted Answer

Methods such as wavelets or Fourier time series decomposition, are basic examples of approaches to further investigate on the creation of super-synthetic weather files.

Accepted Answer

The ‘inverse probability’ associated with Bayes’ theorem allows us to infer unknown quantities, adapt their models, make predictions and learn from data, by combining prior distributions and likelihood into a posterior distributions of parameters.

Accepted Answer

Files for typical weather conditions include hourly data on temperature, dew point, global horizontal radiation, diffuse solar radiation, wind speed and wind direction.

Accepted Answer

According to the bi-annual publications of the International Building Performance Simulation Association (IBPSA), the most commonly used building simulator is EnergyPlus.

Accepted Answer

The nonparametric weather generators often use resampling and simulation methods that do not need to meet any inherent data assumption.

Accepted Answer

The most common semi-parametric weather generator model is described as follows: LARS-WG [86] is a semi-parametric version of WGEN, which uses a mathematical representation used for a daily weather simulation of the process where the model parameters are directly estimated from the sample data.

Accepted Answer

WeaGETS has the advantage of incorporating the computational schemes of other well-known weather generators, as well as offering unique options, such as correction of the underestimation of inter-annual variability and the ability to use Markov chains of varying orders.

Accepted Answer

Dynamic building energy simulations were developed as early as the 1950s [12], but it was not until the energy crisis of the 1970s that the scientific community started using them to help improve theenergy performance of buildings [13].

Accepted Answer

The most common non-parametric weather generator models is described as follows: KnnCAD version 4 [87] is a non-parametric weather generator algorithm for precipitation and temperature based on spatial rainfall simulations created through associated K-nearest neighbours’ weighting.

Accepted Answer

The alternative to using climate projections to prime a weather generator is to adjust (morph) current weather files [16] or even raw time series data taken at weather stations [107].

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Such weather data is generally used to show compliance with policy and regulations, or to examine design alternatives, however there is a growing need to investigate the resilience of building designs, and buildings, to extreme weather events or to climate change.

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The operative temperature is defined as the uniform temperature of a radiantly black enclosure in which an occupant would exchange the same amount of heat by radiation and convection as in the actual non-uniform environment.

Accepted Answer

the COPSE project, which had a wider remit than PROMETHEUS, also produced a methodology for the creation of future weather files [52].

Accepted Answer

Super-synthetic weather files are mathematical approximations of meteorological data sets which can be adapted to have several levels of representativeness of the local weather.

A Review of Current and Future Weather Data for Building Simulation

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Most frequently asked questions

1. What contributions have the authors mentioned in the paper "A review of current and future weather data for building simulation" ?

2. What future works have the authors mentioned in the paper "A review of current and future weather data for building simulation" ?

3. What are some examples of methods to further investigate on the creation of super-synthetic?

4. What is the inverse probability associated with Bayes’ theorem?

5. What are the common weather files?

6. What is the common building simulator?

7. What are the common types of weather generators?

8. What is the common semi-parametric weather generator?

9. What is the advantage of using a Matlab-based weather generator?

10. When did the scientific community start using dynamic building energy simulations?

11. What is the common non-parametric weather generator?

12. What is the alternative to using climate projections to prime a weather generator?

13. What is the need to investigate the resilience of buildings to extreme weather events?

14. What is the operative temperature of a radiantly black enclosure?

15. What was the methodology for the creation of future weather files?

16. What are the main objectives of super-synthetic weather files?

Figures

Citations

Climate change 2014 - Synthesis Report

Quantifying the impacts of climate change and extreme climate events on energy systems

Impacts of future weather data typology on building energy performance – Investigating long-term patterns of climate change and extreme weather conditions

Assessing the impact of climate change on building heating and cooling energy demand in Canada

Urban building energy modeling : State of the art and future prospects

References

An Overview of CMIP5 and the Experiment Design

Thermal Environmental Conditions for Human Occupancy

The next generation of scenarios for climate change research and assessment

Climate Change 2014 : Synthesis Report

Climate Extremes: Observations, Modeling, and Impacts

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