Typical Meteorological Days Research Articles

Analysis of geographical origin of solar terms based on the STTMD method

The 24 solar terms are a significant component of traditional Chinese culture. Amid global warming climate change, research on the Solar Terms has gained increasing prominence. Identifying the geographical origins of the Solar Terms not only provides evidence for studies on the origins of Chinese agricultural civilization but also serves as a critical foundation for the innovative utilization of traditional culture in the modern era. Previous research has primarily relied on historical records, literature review, and field investigation, often challenged by the vast and complex data, the difficulty distinguishing authenticity, the time-consuming nature of the work, and the need for direct scientific evidence. The STTMD (Solar Terms Typical Meteorological Day) method was used for typifying solar term meteorological data sequences, supplemented by isothermal estimation and clustering analysis. This approach was further validated using key crop germplasm sites, phenological indicators, and phenological observation contour maps. The results derived from statistical methods are cross-referenced with historical documents to infer the geographical origins of the 24 Solar Terms. The findings indicate that: (1)On a larger spatial scale, the Solar Terms originated in the middle and lower reaches of the Yellow River; (2)On a smaller spatial scale, the "Luoyang-Zhengzhou-Anyang" triangle is the most probable origin area; (3)The core area of origin is hypothesized to be in present-day Xingyang, Henan Province, or slightly further north. These results are consistent with historical literature and phenological records of crops, offering a novel analysis and transformative insights into the knowledge of Solar Terms. The study provides valuable evidence or methodological inspiration for historical agricultural research in China and offers references for agricultural production and the environmental impacts of global warming.

A typical meteorological day database of solar terms for simplified simulation of outdoor thermal environment on a long-term

The simulation of the outdoor thermal environment long-term, represented by the annual conditions, can describe outdoor thermal environment characteristics more completely. To simplify the simulation, Typical Meteorological Year (TMY) or Principal Component Analysis (PCA) methods are often used to generate a Typical Meteorological Day (TMD) as input conditions for a simplified simulation of the outdoor thermal environment in the long term. However, the results of these typical days are accidental, the time interval between the typical days is heterogeneous, and these typical days cannot be linked together to represent a data sequence used to describe meteorological features in the long term. By combining knowledge of Solar Terms in the traditional Chinese calendar with the CSWD (the Chinese standard year) method, a meteorological element data sequence of a typical weather day (Solar Terms Typical Meteorological Day, STTMD) can be generated. There are 24 typical days obtained by the STTMD method. In the traditional Chinese calendar, they have a definite time order, and the time interval between the typical days is about 15 days. Connecting these typical days can form a hypothetical meteorological year, which is used to simplify the description of the annual meteorological characteristics with the maximum probability of occurrence. Based on meteorological observation data from 1981 to 2010, the STTMD data series of 61 stations in China were generated. These data were used to form a simple national climate division, and then the meteorological representation of different divisions was analyzed. Meteorological representativeness analysis for these subtions indicated the good accuracy of STTMD data. The method can simplify the numerical simulation process for those studied on long-term and can be extended to applications such as outdoor comfort evaluation and urban building energy consumption.

Annual cyclical variations of urban green space cold island(GSCI) effect by combining remote sensing inversion and ENVI-met simulation

Combining multiple methods offers a practical approach to studying long-term variations in the urban green space cold island(GSCI) effect. This research integrates remote sensing inversion and numerical simulation to investigate the annual cycle of the GSCI in Huachong Park, Hefei City. Initially, 59 remote sensing images from various seasons between 2010 and 2020 were retrieved using Landsat series image data and atmospheric correction methods to invert Land Surface Temperatures(LST), which preliminary identified the GSCI's annual cycle variations. Subsequently, meteorological data for Hefei from 2010 to 2020 were extracted using the Solar Terms Typical Meteorological Day(STTMD) method to obtain representative annual meteorological data. These data were then input into the ENVI-met software for numerical simulations of the study area, capturing diurnal variations of the cold island effect at 24-time points and predicting annual changes in cold island intensity. The results indicate that: (1) The GSCI exhibits an annual cycle and seasonal variations characterized by “strong in summer and weak in winter, cooler in summer and warmer in winter”; (2) A progressive relationship exists between remote sensing inversion and ENVI-met numerical simulation in studying the temporal variation of the GSCI, with the integration of these methods yielding a more comprehensive spatiotemporal analysis of the GSCI over long-term scales;(3) The STTMD method effectively simplifies representative meteorological data, progressively combining remote sensing retrievals and numerical simulations to facilitate the acquisition of comprehensive spatiotemporal variations of the green space heat effect over extended periods. These findings advance understanding of the long-term dynamics of cold island effects within urban green spaces, providing valuable insights for urban planners and environmental researchers.

Characteristics Analysis of Volatile Organic Compounds Pollution in Residential Buildings in Northeast China Based on Field Measurement

A total of 8 mechanically ventilated residential buildings and 8 naturally ventilated residential buildings were selected to analyze the pollution characteristics of indoor VOCs under different ventilation modes in the severe cold area of northeast China. On typical meteorological days in each season, VOCs were detected on site, and ventilation modes were investigated by long-term online monitoring. The test results showed that the TVOC (total volatile organic compounds) concentrations varied greatly in different seasons or different functional rooms, and the TVOC concentration was the highest in winter, with a value of 0.994 mg/m3. The kitchen was the place with the most serious VOC pollution, and the TVOC concentration could reach 1.403 mg/m3. Benzene series and methylsiloxane had the highest detection rates, but the detected concentrations were low, and the average concentrations were 0.025 mg/m3 and 0.013 mg/m3 respectively. Among the VOC types with a detection rate greater than 50%, the average proportions of aldehydes, alkanes, and benzene series were 18.7%, 15.39%, and 14.38%, respectively. And their mass ratios were also high, which were 14.90%, 30.85%, and 15.70%, respectively. The annual daily average ventilation duration of mechanically ventilated residential buildings was 7.84 h longer than that of naturally ventilated residential buildings. The median TVOC concentrations of mechanically ventilated residential buildings and naturally ventilated residential buildings were 0.621 mg/m3 and 0.707 mg/m3, respectively. The fresh air system was applicable in the severe cold area of northeast China.

Investigation on the operating characteristics of a directly-attached light crystalline silicon PV roof

The building-integrated photovoltaic (PV) technology can alleviate electricity consumption during peak usage time. However, there are heavy and fragile problems in traditional silicon PV modules while low efficiency and poor stability in thin film modules. Hence, in the present study, a novel lightweight crystalline silicon PV module is first proposed. Then an electro-thermal coupling model for the novel lightweight PV roof is established and an experimental verification test platform based on four different substrates was built. Based on the data of typical meteorological days, the characteristics of operating, energy saving, and emission reduction of the novel lightweight PV roof in summer are analyzed. Finally, the influences of substrate thickness and wind speed on the characteristics of operating, energy-saving, and emission reduction of the novel lightweight PV roof are revealed. The results show that compared with the conventional roof, the lightweight PV roof slightly increases the building cooling load, but the electricity benefits guarantee the lightweight PV roof with a good building energy-saving effect in return. Among different substrates, the PV roof based on asphalt substrate achieves the best PV performance, building energy saving and emission reduction. The PV performance and the building energy saving of the lightweight PV roof based on TPO substrate are the most sensitive to thickness and wind speed while the asphalt is the least. In addition, thinning the substrate and increasing the wind speed could promote the net yield and CO2 emission reduction of the novel lightweight PV roof.

Ventilation and heat dissipation analysis of photovoltaic roof

In recent years, the development and utilization of new energy have attracted more and more attention. As a green and clean energy, the utilization and development of solar energy have attracted much attention. Moreover, solar photovoltaic (PV) technology has been vigorously promoted, with building-integrated photovoltaic (BIPV) technology widely used in the building sector. However, in BIPV, although PV modules can be used as building envelope materials and provide electricity for buildings, due to various conditions during installation and design, PV modules are prone to overheating problems and affect photovoltaic performance. Hence, in the present study, a novel type of PV roof structure with lightweight crystalline silicon PV modules installed on the building surface is proposed, and an air space is provided between the novel lightweight crystalline silicon PV modules and the building surface, the novel lightweight crystalline silicon PV module has the characteristics of thinness and flexibility. After that, an experimental test platform with air space is established, and the data of typical meteorological days are selected to analyze the electrothermal performance of the novel lightweight PV roof, to obtain the optimal structure with the best PV performance. The results show that, under the same conditions, when the spacing is 0 mm and 80 mm, the temperature of the backplane and the substrate of the PV module gradually decreases with the increase of the air space. In contrast, the PV power and electricity generation gradually increase with the growth of the spacing. At the same time, when the distance exceeds 40 mm, the changing trend of the backplane of the PV module temperature, the temperature of the roof substrate, and the electricity generation is not apparent. In the present study, the optimal spacing of the novel lightweight PV roof is 40 mm.

On the Summarization of Meteorological Data for Solar Thermal Power Generation Forecast

The establishment of the typical weather conditions of a given locality is of fundamental importance to determine the optimal configurations for solar thermal power plants and to calculate feasibility indicators in the power plant design phase. Therefore, this work proposes a summarization method to statistically represent historical weather data using typical meteorological days (TMDs) based on the cumulative distribution function (CDF) and hourly normalized root mean square difference (nRMSD). The proposed approach is compared with regular Sandia selection in forecasting the electricity produced by a solar thermal power plant in ten different Brazilian cities. Considering the determination of the annual generation of electricity, the results obtained show that when considering an overall average of weather characteristics, commonly used for analyzing solar thermal power plant designs, the normalized mean average error (nMAE) is 20.8 ± 4.8% relative to the use of historical data of 20 years established at hourly intervals. On the other hand, a typical meteorological year (TMY) is the most accurate approach (nMAE = 1.0 ± 1.1%), but the costliest in computational time (CT = 381.6 ± 56.3 s). Some TMD cases, in turn, present a reasonable trade-off between computational time and accuracy. The case using 4 TMD, for example, increased the error by about 11 percentual points while the computational time was reduced by about 81 times, which is quite significant for the simulation and optimization of complex heliothermic systems.

Effect of existing residential renovation strategies on heating and cooling load in Shanghai

To provide a reference for the renovation of Shanghai’s existing residential districts, this study quantifies and compares the relationships between common renovation strategies, microclimate, heating and cooling loads. These common strategies include improving the greening rate (G), improving the reflectivity of pavement (P), improving the reflectivity of wall materials (W), and improving the reflectivity of roof materials or applying green roof (R). These strategies are applied to a typical model extracted from existing residential areas in Shanghai, China. ENVI-met and EnergyPlus are combined to simulate the microclimate represented by the average meteorological parameters in front of building surfaces and the building heating and cooling load on a typical meteorological day in winter and summer. The results show that applying microclimate data around target building contributes to a significant difference in air conditioning load in both summer and winter. For summer, G, W, and R reduced their total cooling load, whereas P increased this parameter. R contributed the most significant decrease in the total cooling load, followed by W, and G contributed the least. G3P1W3R3 and G1P3W1R1 were the scenarios with the lowest and highest cooling load. The total cooling load under G3P1W3R3 was 136 kWh (12.7%) less than that under G1P3W1R1. For winter, P and applying green roof (R4) reduced the heating load of the target building, whereas G, W and improving roof reflectivity (R2, R3) increased it. G1P3W1R4 and G3P1W3R3 were the scenarios with the lowest and highest heating load. The heating load under G1P3W1R4 was 145 kWh (14.5%) less than that under G3P1W3R3.

Effect of existing residential renovation strategies on building cooling load: Cases in three Chinese cities

To provide a reference for the renovation of existing residential districts, this study quantifies and compares the relationships between common renovation strategies, microclimate, and cooling loads. These common strategies include improving the greening rate, improving the reflectivity of pavement, improving the reflectivity of wall materials, and improving the reflectivity of roof materials or applying green roof. These strategies are applied to a typical model extracted from existing residential areas in Beijing, Shanghai, and Guangzhou. ENVI-met and DesignBuilder are combined to simulate the microclimate represented by the average meteorological parameters in front of building surfaces and the building cooling load on a typical meteorological day in summer. The results show that increasing the vegetation has the most significant effect on the microclimate, and improving the roof reflectivity can yield the most reduction in the cooling load. Generally, all the strategies tend to be more effective under a climate zone with a stronger solar radiation. The sensible cooling load is underestimated and the latent cooling load is overestimated if neglecting microclimate effect. Furthermore, the difference in the total cooling load, between considering microclimate results and not, was affected by the proportion of sensible and latent cooling loads. To sum up, high-reflectivity roofs should be given priority, and building energy consumption should be simulated with microclimate results, especially relative humidity and wind speed.

A Method for Selecting the Typical Days with Full Urban Heat Island Development in Hot and Humid Area, Case Study in Guangzhou, China

The urban heat island (UHI) poses a significant threat to urban ecosystems, human health, and urban energy systems. Hence, days with a relatively higher UHI intensity should be selected for UHI observation and analysis. However, there is still a lack in the method and criteria for selecting the typical meteorological days for UHI survey and simulation. In this study, field measurements were conducted based on Local Climate Zone (LCZ) schemes over a one-year period to assess the UHI behavior in Guangzhou, China. The relationship between the diurnal temperature range (DTR) and UHI intensity was evaluated and analyzed quantitatively under different meteorological conditions classified by precipitation. The average daily maximum UHI intensity (UHIImax) during precipitation days was approximately 1.8 °C lower than that during non-precipitation days, confirming that precipitation has a negative effect on UHI development. The monthly DTR distribution was similar to the daily UHIImax distribution, which was higher in autumn and winter, but lower in spring and summer. DTR has a significant linear correlation with the daily UHIImax, with a Pearson’s correlation coefficient of >0.7 and statistical significance of <0.001. Based on a quantitative evaluation of our results, we determined that 10 °C could be regarded as the appropriate DTR threshold to identify the meteorological conditions conducive to UHI development; the meteorological conditions exhibited a high daily UHIImax in Guangzhou. This study provides a simple method to select typical meteorological days for UHI measurement and simulation, and a method to early-warning of intense UHI events based on weather forecasts.

A feedforward-feedback hybrid control strategy towards ordered utilization of concentrating solar energy

In this work, a feedforward-feedback hybrid control strategy was proposed for concentrating solar thermal technology. Inside, the feedforward unit was designed to counteract the measured disturbance (mainly originated from the changeable weather), and the feedback unit employing proportional-integral controller to counteract some unmeasured and non-linear disturbances, e.g. local cloud cover, local defocus and mirror damage. For disturbance-rejecting and setpoint-tracking regulating issues, the hybrid strategy is superior to the single control mode in improving responsiveness, reducing steady-state error, as well as weakening overshoot. A feedforward-relaxed hybrid scheme allows enough tolerance for feedforward implementation and simultaneously helps determine the optimal regulation. For a closed power plant, the regulated operation contributes to additional 0.5%–1% daily efficiency in four typical meteorological days. Above all, the high-performance control strategy in energy-supply side lays the foundation for scheduling and dispatching the available energy and leaves enough room for the global energy management and market balance. It is suggested to incorporate feedforward information to enhance regulation performance, meet multi-grade energy demands, as well as turn the feedback-dominated regulation tide.

Bus ultra-short-term load forecasting considering the impact of distributed photovoltaic power supply

Bus load base is small and volatile, so it is difficult to predict ultra-short-term load. Distributed photovoltaic power supply connected to bus power supply area further increases the uncertainty of bus load and directly affects the prediction accuracy. Aiming at the ultra-short-term load forecasting problem of bus with photovoltaic power supply under complex weather conditions, a method of bus ultra-short-term load forecasting based on feature selection and XGBoost is proposed. Firstly, a high-dimensional feature set is constructed with various influencing factors, and the XGBoost predictor is trained with the original feature set in the typical meteorological day historical data such as rainy and sunny days, and the degree of response between the bus load and the multi-factor is determined during the training process. Then, the MAPE value is used as the evaluation index. Forward search is used to select features to determine the optimal feature subsets of different typical weather day predictors. Finally, according to the selected optimal feature subsets, the optimal XGBoost prediction model for different weather days are established to predict the bus output of different weather days. Experiments on bus data with distributed photovoltaic in a certain area show that the new prediction model has higher prediction accuracy.

Integration of Microclimate into the Multi-Agent System Simulation in Urban Public Space

Urban public space is the main place for human outdoor activities. Simulating human behavior through the Multi-Agent System (MAS) is one of the most important methods for studying public space. However, most of the research on this topic is concerned with the way people behave and the connection to spatial layouts. It ignores the fact that in outdoor spaces, microclimate factors tend to have a more important impact on human behavior. In this study, microclimate factors were narrowed down into two main factors: outdoor thermal perception and sunshine perception. Both of these factors are integrated into the traditional MAS, together with visual perception as the influence factors of agent action. The new MAS was developed in Processing language and can dynamically and visually show agents activities in the space. Taking Gulou Square in Nanjing, China, as a case, the simulations were carried out with three typical meteorological days of spring equinox, summer solstice, and winter solstice. Through comparing the simulation results at different times, we found that the new MAS exhibits a significant impact of microclimate on human behavior. The new MAS can be used reasonably and effectively for the design and evaluation of urban public space.

Quantitative evaluation method for the complementarity of wind–solar–hydro power and optimization of wind–solar ratio

Complementarity between wind power, photovoltaic, and hydropower is of great importance for the optimal planning and operation of a combined power system. However, less attention has been paid to quantify the level of complementarity of wind power, photovoltaic and hydropower. Therefore, this paper proposes a complementarity evaluation method for wind power, photovoltaic and hydropower by thoroughly examining the fluctuation of the independent and combined power generation. To begin with, a series of evaluation indices are presented from two perspectives: random fluctuation between adjacent time slots and ramp within continuous time windows. Secondly, a method for screening the typical meteorological day is proposed by combining t-distributed stochastic neighbor embedding with K-means clustering algorithm to improve the evaluation of daily complementarity. This method can deal with the feature extraction of high-dimension and correlated data sequences. A case study is conducted for the validation of the proposed method, and the evaluation result of the proposed method was compared with that of the Kendall’ rank correlation coefficient based on the Gaussian copula function. It is found that the proposed method has higher accuracy because it describes the complementarity from two aspects including fluctuation and ramp. It is also found from the study case that the optimum complementarity level for a certain case can be achieved by changing the ratio of photovoltaic and wind power. This work will provide reference for the optimization of power grid dispatch and power supply planning of combined power stations.

Direct solar photocatalytic hydrogen generation with CPC photoreactors: System development

A new compound parabolic concentrator (CPC) for solar photocatalytic hydrogen production has been designed and estimated in the present study. Parameters of the CPC, i.e., the orientation, the acceptance angle and the absorber tube diameter are designed according to the local meteorological conditions. A north-south orientated, adjustable, single axis tracking truncated CPC with the concentration ratio of 4.22 is designed as one unit. An experimental system including 76 units with the total light area of 103.7m2 is developed and installed. The units have four different angles with inclination being 25°, 35°, 45° and 55°, respectively. The system is operated under the natural circulation condition for most of the time, with high pressure gas perturbing the sedimentary photocatalysts from time to time. NiS-CdxZn1−xS is used as the photocatalyst. Preliminary results show that the mean hydrogen productivity and cumulative hydrogen generation are 7.14NL/h and 42.84NL/day of the horizontal angle 25° row on a typical meteorological day. The average energy conversion efficiency is 0.087%. The daily hydrogen generation of the whole system is accumulated to be 160.34NL.

Effects of PCM on power consumption and temperature control performance of a thermal control system subject to periodic ambient conditions

Thermal control systems operating under periodic outdoor ambient conditions have numerous important applications in industrial fields. Reducing system energy consumption and enhancing temperature control effects are crucial to improving the performance of these systems. To this end, the application of phase change material (PCM) in the envelope of a thermal control system was investigated through experiment and simulation. A simulation model of an active ventilated thermal control system was constructed and verified with experimental results, and the influences of PCM incorporated in the envelope on the power consumption and temperature control effects were discussed in two time scales. The results for typical meteorological days indicate that excellent thermal control effects can be achieved when the phase change range of PCM brackets the temperature control setpoint and is consistent with the fluctuation range of the ambient temperature. The results for a typical meteorological year (TMY) demonstrate that an optimal phase change range can be determined according to TMY data to realize the optimal thermal control effects of PCM. When the required temperature control setpoint is not within the optimal phase change range, the phase change range bracketing the temperature control setpoint is recommended.

Research on the Planning Methods of Mitigating Summer Urban Heat Island Effects among Basin Cities——A Case Study at Xi’an, China

Along with the process of urbanization, urban heat island effects (UHI) has become an important issue which affecting the quality of human settlements especially for clam wind basin cities. In this paper, take basin city-Xi’an as the research object, based on the actual investigation of summer environmental climate parameters in central areas of Xi’an, combined with the average air temperature distribution map of summer typical meteorological day of Xi’an. Analyze the spatial distribution of the UHI and “cool source”, the urban ventilation channel is planned initially and the mitigation suggestions of UHI is proposed.

Evaluation of the seasonal effect of increasing albedo on urban climate and energy consumption of buildings in Montreal

In this paper, effect of increasing the urban albedo in Montreal (Canada), a cold climate region, on 2-m air temperature and energy consumption of HVAC systems is investigated. An algorithm is developed to select “monthly typical meteorological days” that represent the weather of each month in 2005. The Weather Research and Forecasting (WRF) model is coupled with a multi-layer urban canopy model and a building energy model to accurately simulate the urban climate. The albedo of roof, walls, and road is increased from 0.2 to 0.65, 0.6, and 0.45, respectively. The simulated 2-m air temperature is decreased in all months and the maximum decrease in daily-averaged air temperature is occurred in April (∼0.4°C). Air temperature decrease is mainly observed during the morning. The annual average decrease of the 2-m air temperature in the urban area is about 0.2°C (0.2°C in summer and 0.1°C in winter). Increasing the albedo in Montreal decreased the air temperature during summertime by as high as 4°C. Increasing urban albedo showed a small effect on net annual cooling and heating energy expenditure. With the simplified building energy model used in WRF, the annual energy expenditure savings is about 1$/100m2.

Comparison of Angular Reflectance Losses Between PV Modules With Planar and Textured Glass Under Singapore Outdoor Conditions

Photovoltaic (PV) modules are rated under standard test conditions with normally incident light, whereas under outdoor conditions photons arrive on a PV module surface at all angles. In this study, the angular losses of PV modules with a planar and textured front glass are investigated for the tropical conditions of Singapore. Angular reflectance for both modules is first measured using a goniophotometer. From the measurements, the angular loss factors due to the different radiation components are calculated. Then, the angular losses under Singapore outdoor conditions are determined using three transposition models: Liu and Jordan, Hay and Davies, and Perez et al. Two 60-cell PV modules with a planar and textured glass are fabricated and measured outdoors for validation of the modeling results. Outdoor measurement results show that the PV module with textured glass captures 1.4% extra light compared with the PV module with planar glass for the 6-mo period studied. Next, the annual angular loss, monthly angular loss, and typical meteorological day angular loss for both module structures are studied. For all cases studied, the PV module with textured glass has consistently lower angular losses compared with the PV module with a planar glass.

Outdoor PV Module Performance under Fluctuating Irradiance Conditions in Tropical Climates

Tropical climates (such as in Singapore) are characterised by fast-changing irradiance conditions due to high variations in cloud coverage. Different photovoltaic (PV) technologies possibly react differently to these variations of irradiance conditions, which in turn will also influence the module performance. In this study, a novel method is introduced to systematically investigate the fluctuating irradiance and its influence on module performance. Taking the Adnot clear-sky irradiance model as reference, the fluctuating irradiance is separated into high and low irradiance levels using the Typical Meteorological Day (TMD) irradiance values of 2011. These two irradiance groups are then analysed individually for the impact of the fluctuation frequency (defined via the number of minutes of constant irradiance) on the following module parameters: short-circuit current, module temperature and efficiency. The distribution of fluctuating irradiance over a whole year in Singapore and its impact on 5 different module technologies (monocrystalline Si, hetero-junction Si wafer, a-Si single junction, a-Si double junction and micromorph Si) are presented. The results show that the efficiency of wafer-based Si modules is not much influenced by the fast irradiance changes and dominated by the temperature effect at high irradiance. In contrast, Si-based thin-film technologies are stronger impacted by the fluctuations. Amorphous Si technologies show higher efficiencies at low irradiances, while micromorph Si modules react similar to monocrystalline Si at high irradiances, however with a slight drop in efficiency at low irradiances. This study gives valuable insights into the PV module response to varying irradiance.