The Generation of Typical Meteorological Year and Climatic Database of Turkey for the Energy Analysis of Buildings

For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given region are the most important consideration for the proper design of space AC （Air Conditioning） systems. In this study, the typical meteorological year and climatic database of Turkey for the energy analysis of buildings were generated by SQL （Structured Query Language） database programmimg language. The Finkelstein-Schafer statistical method was applied to analyze the hourly measured weather data of a 23-year period （1989-2012） and select representative TMMs （Typical Meteorological Months）. The selection criteria were based on 13 meteorological parameters. These parameters are the daily mean, maximum and minimum values and ranges of temperature, dew-point and wind velocity and the daily values of global solar radiation. According to results of TMY （Typical Meteorological Year）, climatic database of Turkey including daily or hourly climate variables was created in SQL data tables.

The Response of Anomalous Vertically Integrated Moisture Flux Patterns Related to Drought and Flood in Southern China to Sea Surface Temperature Anomaly

With the extreme drought(flood)event in southern China from July to August in 2022(1999)as the research object,based on the comprehensive diagnosis and composite analysis on the anomalous drought and flood years from July to August in 1961-2022,it is found that there are significant differences in the characteristics of the vertically integrated moisture flux(VIMF)anomaly circulation pattern and the VIMF convergence(VIMFC)anomaly in southern China in drought and flood years,and the VIMFC,a physical quantity,can be regarded as an indicative physical factor for the"strong signal"of drought and flood in southern China.Specifically,in drought years,the VIMF anomaly in southern China is an anticyclonic circulation pattern and the divergence characteristics of the VIMFC are prominent,while those are opposite in flood years.Based on the SST anomaly in the typical draught year of 2022 in southern China and the SST deviation distribution characteristics of abnormal draught and flood years from 1961 to 2022,five SST high impact areas(i.e.,the North Pacific Ocean,Northwest Pacific Ocean,Southwest Pacific Ocean,Indian Ocean,and East Pacific Ocean)are selected via the correlation analysis of VIMFC and the global SST in the preceding months(May and June)and in the study period(July and August)in 1961-2022,and their contributions to drought and flood in southern China are quantified.Our study reveals not only the persistent anomalous variation of SST in the Pacific and the Indian Ocean but also its impact on the pattern of moisture transport.Furthermore,it can be discovered from the positive and negative phase fitting of SST that the SST composite flow field in high impact areas can exhibit two types of anomalous moisture transport structures that are opposite to each other,namely an anticyclonic(cyclonic)circulation pattern anomaly in southern China and the coastal areas of east China.These two types of opposite anomalous moisture transport structures can not only drive the formation of drought(flood)in southern China but also exert its influence on the persistent development of the extreme weather.

A method of determining typical meteorological year for evaluating overheating performance of passive buildings

In the simulation of building overheating risks,the use of typical meteorological years(TMY)can greatly reduce the simulation workload and accurately reflect the distribution of simulation results according to the weather conditions over a given period.However,all meteorological parameters in most current TMY methods use a uniform weighting factor which may make the simulation results against the actual simulation results of the period and negatively affect the accuracy of the evaluation results.In addition to differences in climate characteristics between climate zones,the sensitivity of different simulation results to external parameters will also be different.Therefore,a TMY method based on the Finkelstein-Schafer statistical method is proposed,which considers the climatic characteristics of different regions and the correlation with the output parameters of indoor simulation to select the typical month.The proposed method is demonstrated in the three future scenarios for the three cities in different climate zones in China.The results show that the traditional TMY method has an overestimated weight of solar radiation and wind speed and an undervalued weight of dry bulb temperature when indoor temperature-related indicators are the output target.Compared with the traditional TMY method,the TMY generated by the improved method is closer to the distribution characteristics of the long-term outdoor weather data.Furthermore,when using the improved TMY data to evaluate the overheating performance of the passive residential buildings,the difference of the results of the unmet degree hours,indoor overheating degree,and the overheating escalation factor between the long-term projected data and the TMY data can be reduced by 63%–67%compared with the traditional TMY data.

A global typical meteorological year(TMY)database on ERA5 dataset

The outdoor climate condition is one of the deterministic factors influencing building energy consumption.Building performance simulation(BPS)tools usually adopt typical meteorological year(TMY)as the outdoor climate input.Despite that many scholars and institutes have developed TMY datasets,these datasets are usually based on distinct data sources and methods.Considering the increase of international cooperation construction projects,compatible TMY dataset for different countries is in urgent need.This paper presents a global typical meteorological year(TMY)database covering 38,947 stations worldwide based on the fifth-generation atmospheric reanalysis product released by the European Center(ERA5).The data is created with Chinese Standard Weather Database(CSWD)method to reflect the average level of historical weather.The dataset is saved in a 55 GB database of compressed CSV files and a website is established where users can download their required TMY data for certain cities according to the longitude and latitude information.A systematic validation is conducted to confirm the feasibility of ERA5 as data source and validity of generated TMY data.This TMY-ERA5 dataset is fundamental and essential in building system designs of international construction projects,building performance simulation,especially for some countries lacking ground meteorological stations or missing meteorological year data in the building sector.It can be used as references for other meteorological climate studies.

Effect of typical meteorological year selection on integrated daylight modeling and building energy simulation

The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently.Luminous environment parameters have not been taken into consideration in existing TMY generation methods.In this study,the feasibility of existing TMY generation process has been examined.A generic office model implementing sided window daylighting is established.Historical meteorological data of Hong Kong region from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month(TMM)selection procedures.Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation.The result demonstrates that,on annual basis,the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value.The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%.However,further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level.The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%.As the energy performance daylight utilization is subject to weather change,analysis on daily and monthly energy level is important,especially during design stage.The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.

Asymmetric relationships between El Nino/La Nina and floods/droughts in the following summer over Chongqing,China

This study presents a detailed analysis of the asymmetric relationships between the warm/cold phase of the El Ni?o–Southern Oscillation and the typical flood/drought years in summer over Chongqing.Furthermore,its underpinning mechanisms are also explored.The results show that:(1)El Ni?o and La Ni?a have an asymmetric influence on summer precipitation in the following year over Chongqing.Generally,the composite atmospheric circulation anomalies for El Ni?o years are consistent with the composite results for typical flood years in summer over Chongqing,which indicates a tight link between typical flood years in summer over Chongqing and El Ni?o events.However,the relationship between typical drought years in summer over Chongqing and La Ni?a events is not significant.(2)From winter to the following summer,the extent of positive SST anomalies in the equatorial eastern Pacific associated with typical flood years in summer over Chongqing shrinks,whereas in the tropical Indian Ocean,the extent slightly expands.This trend indicates that the impact of El Ni?o on typical flood years in summer over Chongqing is maintained through the‘relay effect’of SSTs in the tropical Indian Ocean,which is the result of a lagged response of positive SST anomalies in the tropical Indian Ocean to El Ni?o events in winter.