Effect of Applied Weather Data Sets on the Computational Assessment of Hygrothermal Performance of Historical Masonry

2017 ◽  
Author(s):  
Jan Kocí ◽  
Robert Cerný
Keyword(s):  
Meteorological Data ◽  
Warming Trend ◽  
Weather Data ◽  
Data Sets ◽  
Climatic Data ◽  
Damage Functions ◽  
Historical Building ◽  
Time Period ◽  
Hygrothermal Performance ◽  
Historical Masonry

Several historical wall assemblies together with several weather data sets are investigated in order to study the effect of environmental load on hygrothermal performance of historical buildings. The effect of weather data is assessed using several damage functions with the emphasis placed on frost induced damage. The climatic data are represented by six different weather data sets, namely by the test reference year, positive and critical weather years, together with the meteorological data measured by the autors during the time period of 2013–2015. Special attention is paid to the recent weather data as there is an apparent trend of average temperature increase in the Central Europe in last few years. The results presented in the paper confirm the warming trend which is manifested by virtually no frost induced damage observed for weather years 2014 and 2015 in the analyzed historical building envelopes.

scholarly journals Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

2020 ◽  
Vol 12 (17) ◽  
pp. 6788 ◽  
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Vicente Gutiérrez González ◽  
Antonis Peppas ◽  
Carlos Fernández Bandera
Keyword(s):  
Energy Demand ◽  
Meteorological Data ◽  
Building Energy ◽  
Third Party ◽  
Weather Data ◽  
Data Sets ◽  
Weather Station ◽  
Energy Models ◽  
The Impact ◽  
Energy Strategies

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

scholarly journals Analysis of projected hydrological behavior of catchments based on signature indices

2011 ◽  
Vol 8 (2) ◽  
pp. 3571-3597
Author(s):  
M. C. Casper ◽  
G. Grigoryan ◽  
O. Gronz ◽  
O. Gutjahr ◽  
G. Heinemann ◽  
...  
Keyword(s):  
Water Balance ◽  
Bias Correction ◽  
Water Distribution ◽  
Meteorological Data ◽  
Temporal Distribution ◽  
Temperature Fields ◽  
Data Sets ◽  
Climatic Data ◽  
Runoff Generation ◽  
Meteorological Input

Abstract. To precisely map the changes in hydrologic response of catchments (e.g., water balance, reactivity or extremes) we need sensitive and interpretable indicators. In this study we defined nine hydrologically meaningful signature indices: five indices were sampled on the flow duration curve, four indices were closely linked to the distribution of event runoff coefficients. We applied these signature indices to the output from three hydrologic catchment models located in the Nahe basin (Western Germany) to detect differences in runoff behavior resulting from different meteorological input data. The models were driven by measured and simulated (COSMO-CLM) meteorological data. It could be shown that application of signature indices is a very sensitive tool to assess differences in simulated runoff behavior resulting from climatic data sets of different sources. The hydrological model acts as a filter for the meteorological input and is therefore very sensitive to biases in mean and spatio-temporal distribution of precipitation and temperature. The selected signature indices allow assessing changes in water balance, vertical water distribution, reactivity, seasonality and runoff generation. Bias correction of temperature fields and adjustment of bias correction of precipitation fields seemed to be indispensable. For this reason, future work will focus on improving bias correction for CCLM data sets. Signature indices may then act as indirect "efficiency measures" or "similarity measures" for the reference period of the simulation.

Updates to Hourly Climate Data for Use in AASHTOWare Pavement Mechanistic–Empirical Design

2017 ◽  
Vol 2640 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Wouter Brink ◽  
Harold Von Quintus ◽  
Leon F. Osborne
Keyword(s):  
Weather Data ◽  
Data Sets ◽  
Climatic Data ◽  
Systematic Bias ◽  
Climate Data ◽  
The North ◽  
Hourly Temperature ◽  
Regional Reanalysis ◽  
Pavement Damage ◽  
Empirical Design

The AASHTOWare Pavement Mechanistic–Empirical Design software requires hourly temperature, wind speed, percentage sunshine, precipitation, and relative humidity to properly calculate pavement damage and distresses. Actual or measured values, which vary hourly throughout a day for a given site, are required to properly capture the damage caused by environmental loadings. Currently the mechanistic–empirical design hourly climatic data contain approximately 1,200 U.S. and 300 Canadian stations. The U.S. stations typically contain data from 1995 through 2005, and data from the Canadian stations vary in length from 10 to 50 years, with the exception of some weather stations. Some agencies expanded their historical weather data to include longer periods of time. This paper documents the process and data sources that were used to update the current set of climate stations with climate data dating back to 1979 using the North American Regional Reanalysis (NARR) database. The results of the comparison between new climate files and the existing older climate data files for use in pavement design are presented. Overall, the NARR-generated climate data showed a very good comparison. The paper details the background of the NARR and its limitations and compares the performance predictions made by using the old and new climate data. The results indicate there is no systematic bias between the two climate data sets.

Our climate conditions are already changing – Should we care?

2021 ◽  
pp. 014362442110042
Author(s):  
Drury B Crawley ◽  
Linda K Lawrie
Keyword(s):  
Energy Simulation ◽  
Weather Data ◽  
Building Performance ◽  
Temperature Record ◽  
Data Sets ◽  
Climatic Data ◽  
Climate Conditions ◽  
The Past ◽  
Changing Climate ◽  
The World

The IPCC and many others predict significant changes to our climates over the rest of this century, including average temperature increases for 2–5°C. However, we can see possible indications of change already – increasing frequency of severe storms and other weather events. However, many of the major weather data sets used around the world for building energy simulation are more than 15 years old. Does it matter? This paper compares several of the major data sets used in building performance simulation against newer data derived from the past 15 years. Ten of the past 15 years are the hottest on record and this rapidly changing climate already is evident in the temperature record. We use energy simulation to demonstrate how the various data sets impact energy use. In addition, the design conditions for heating and cooling calculations are already seeing slight changes over the past 20 years. Data for 12 locations around the world is used to demonstrate the changing climate that we already see. Practical application: This paper encourages building designers to use the most up-to-date climatic data in their design and evaluation of building performance.

Offshore Wind Shear Estimations for Wind Power Assessment

2008 ◽  
Author(s):  
Susan W. Stewart
Keyword(s):  
Wind Power ◽  
Wind Shear ◽  
Meteorological Data ◽  
Open Water ◽  
Offshore Wind ◽  
Wind Data ◽  
South Atlantic Bight ◽  
Data Sets ◽  
Time Period ◽  
Bodies Of Water

Appropriate wind shear estimates are extremely important when assessing any regions’ wind power resource. Wind shear is used not only to estimate wind velocity at wind turbine hub heights other than the data collection height, but also as a siting tool to compare the wind resources in different locations when wind data are not available at a consistent height. Models for wind shear over land, as well as simple models for wind shear over open water have been found to correlate poorly with offshore wind data. This is thought to be partially due to the effect of changing wave conditions on wind shear as well as differences in thermal effects over bodies of water. In this study, offshore wind data from the South Atlantic Bight region is used to estimate the offshore wind shear conditions in this area. Data sets include collocated 10 m and 50 m meteorological data as well as wave data, all taken over a three and a half year time period. Offshore wind shear assessments from other studies are analyzed and compared to the current study as well.

scholarly journals To what extent does the detection of climate change in Hungary depend on the choice of statistical methods?

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Beatrix Izsák ◽  
Tamás Szentimrey
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Linear Trend ◽  
Meteorological Data ◽  
Warming Trend ◽  
Data Series ◽  
Data Sets ◽  
Raw Data ◽  
Temperature Trends ◽  
Trend Data

AbstractThe trend analysis of meteorological time series has gained prominence in recent decades, the most common method being the so-called ‘linear analytical trend analysis’. Until the mid-1990s, trend analysis was commonly performed on non-homogenized data sets, which frequently led to erroneous conclusions. Nowadays, only homogenized data sets are examined, so it really is possible to detect climate change in long meteorological data sets. In this paper, the methodology of linear trend analysis is summarized, the way in which the model can be validated is demonstrated, and there is a discussion of the results obtained if unjustified discontinuities caused by changing measurement conditions, such as the relocation of stations, changes in measurement time, or instrument change occur. On the basis of an examination of records for the preceding 118 years, it is possible to state that both annual and seasonal mean temperature trends display a significant warming trend. In the case of homogenized data series, the change is significant over the entire territory of Hungary; in the case of raw data series, however, the change is not significant everywhere. The validity of the linear model is tested using the F-test, a task as yet carried out on the entire Hungarian data series, series comprising records for over 100 years. Furthermore, neither has a comparison been made of the trend data for raw data series and the homogenized data series with the help of information on station history to explore the causes of inhomogeneity.

Sizing of Photovoltaic-Wind-Battery Hybrid System for a Mediterranean Island Community Based on Estimated and Measured Meteorological Data

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
S. M. Sajed Sadati ◽  
Elham Jahani ◽  
Onur Taylan ◽  
Derek K. Baker
Keyword(s):  
Hybrid System ◽  
Meteorological Data ◽  
Unit Cost ◽  
Weather Data ◽  
Data Sets ◽  
Small Community ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity ◽  
Mediterranean Island ◽  
Storage Units

Deploying renewable energy systems (RES) to supply electricity faces many challenges related to cost and the variability of the renewable resources. One possible solution to these challenges is to hybridize RES with conventional power systems and include energy storage units. In this study, the feasibility analysis of a grid-connected photovoltaic (PV)-wind-battery hybrid system is presented as a microgrid for a university campus-scale community on a Mediterranean island. Models for PV and wind turbine systems are presented to estimate energy production, and net present cost (NPC) and levelized cost of electricity (LCOE) are used as economic metrics. A parametric study is performed with hourly time-steps to determine the sizes of energy generation and storage units to minimize the NPC for a small community as the case study. Two alternate configurations with and without storage are proposed. In both cases, the resulting LCOE is 0.15 USD/kWh while the current electricity tariff for the analyzed location was 0.175 USD/kWh in 2015. This lower unit cost of electricity leads to a lower NPC considering a 25-year lifetime. Different estimated and measured solar irradiance and wind speed data sets are used to evaluate the performance of the designed microgrid. Sensitivity analysis on different available weather data sets shows that the uncertainty in wind resource estimations is much higher than the uncertainty in solar resource estimations. Moreover, the results show that solar and wind resources could be utilized synergistically for the studied location.

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