Meteorological Applications最新文献_第6页

A multi-model likelihood analysis of unprecedented extreme rainfall along the east coast of Australia 澳大利亚东海岸前所未有的极端降雨的多模型可能性分析

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-06-01 DOI: 10.1002/met.2217

Damien B. Irving, James S. Risbey, Dougal T. Squire, Richard Matear, Carly Tozer, Didier P. Monselesan, Nandini Ramesh, P. Jyoteeshkumar Reddy, Mandy Freund

{"title":"A multi-model likelihood analysis of unprecedented extreme rainfall along the east coast of Australia","authors":"Damien B. Irving, James S. Risbey, Dougal T. Squire, Richard Matear, Carly Tozer, Didier P. Monselesan, Nandini Ramesh, P. Jyoteeshkumar Reddy, Mandy Freund","doi":"10.1002/met.2217","DOIUrl":"https://doi.org/10.1002/met.2217","url":null,"abstract":"A large stretch of the east coast of Australia experienced unprecedented rainfall and flooding over a two-week period in early 2022. It is difficult to reliably estimate the likelihood of such a rare event from the relatively short observational record, so an alternative is to use data from an ensemble prediction system (e.g., a seasonal or decadal forecast system) to obtain a much larger sample of simulated weather events. This so-called ‘UNSEEN’ method has been successfully applied in several scientific studies, but those studies typically rely on a single prediction system. In this study, we use data from the Decadal Climate Prediction Project to explore the model uncertainty associated with the UNSEEN method by assessing 10 different hindcast ensembles. Using the 15-day rainfall total averaged over the river catchments impacted by the 2022 east coast event, we find that the models produce a wide range of likelihood estimates. Even after excluding a number of models that fail basic fidelity tests, estimates of the event return period ranged from 320 to 1814 years. The vast majority of models suggested the event is rarer than a standard extreme value assessment of the observational record (297 years). Such large model uncertainty suggests that multi-model analysis should become part of the standard UNSEEN procedure.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying renewable energy potential and realized capacity in India: Opportunities and challenges 量化印度的可再生能源潜力和实现能力：机遇与挑战

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-29 DOI: 10.1002/met.2196

Kieran M. R. Hunt, Hannah C. Bloomfield

{"title":"Quantifying renewable energy potential and realized capacity in India: Opportunities and challenges","authors":"Kieran M. R. Hunt, Hannah C. Bloomfield","doi":"10.1002/met.2196","DOIUrl":"https://doi.org/10.1002/met.2196","url":null,"abstract":"As both the population and economic output of India continue to grow, so does its demand for electricity. Coupled with an increasing determination to transition to net zero, India has responded to this rising demand by rapidly expanding its installed renewable capacity: an increase of 60% in the last 5 years has been driven largely by a quintupling of installed solar capacity. In this study, we use broad variety of data sources to quantify potential and realized capacity over India from 1979 to 2022. For potential capacity, we identify spatiotemporal patterns in solar, wind, hydro and wave power. We show that solar capacity factor is relatively homogeneous across India, except over the western Himalaya, and is highest during the pre-monsoon. Wind capacity factor is highest during the summer monsoon, and has high values off the southern coast, along the Western Ghats, and in Gujarat. We argue that wave power could be a useful source of renewable energy for the Andaman and Nicobar Islands, which are not connected to the main Indian power grid. Using gridded estimates of existing installed capacity combined with our historical capacity factor dataset, we create a simple but effective renewable production model. We use this model to identify weaknesses in the existing grid—particularly a lack of complementarity between wind and solar production in north India, and vulnerability to high-deficit generation in the winter. We discuss potential avenues for future renewable investment to counter existing seasonality problems, principally offshore wind and high-altitude solar.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2196","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141182173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of aerosol–meteorology interactions on visibility during a wintertime heavily polluted episode in Central-East, China 气溶胶-气象相互作用对中国中东部冬季重污染天气能见度的影响

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-28 DOI: 10.1002/met.2207

Xin Zhang, Yue Wang, Zibo Zhuang, Chengduo Yuan

{"title":"Influence of aerosol–meteorology interactions on visibility during a wintertime heavily polluted episode in Central-East, China","authors":"Xin Zhang, Yue Wang, Zibo Zhuang, Chengduo Yuan","doi":"10.1002/met.2207","DOIUrl":"https://doi.org/10.1002/met.2207","url":null,"abstract":"Atmospheric visibility profoundly impacts daily life, and accurate prediction is crucial, particularly in conditions of low visibility characterized by high aerosol loading and humidity. This study employed the WRF-Chem model to simulate a severe wintertime haze pollution episode that transpired from January 17 to 19, 2010, in Central-East China (112–122° E, 34–42° N). The results reveal that excluding aerosol–meteorology interactions led to underestimated PM2.5 concentrations and relative humidity in comparison with ground-based measurement data, accompanied by a significant overestimation of visibility. Aerosols can engage with meteorological elements, particularly humidity, resulting in positive feedback. Upon considering these feedback interactions, the simulation results showed an increase of 5.17% and 1.99% in PM2.5 concentration and relative humidity, respectively, compared with the original simulation. This adjustment narrowed the bias between simulated and measured data. The overestimation of simulated visibility was reduced by 16% and 25% for the entire study period and the severe haze pollution period, respectively. These findings underscore the vital role of incorporating aerosol–meteorology interactions in visibility simulations using the WRF-Chem model. Notably, the inclusion of aerosol–meteorological feedback significantly enhances the accuracy of visibility predictions, particularly during heavily polluted periods.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2207","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141164815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning bias correction and downscaling of urban heatwave temperature predictions from kilometre to hectometre scale 城市热浪温度预测的机器学习纠偏和降尺度（从千米尺度到公顷尺度

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-17 DOI: 10.1002/met.2200

Lewis P. Blunn, Flynn Ames, Hannah L. Croad, Adam Gainford, Ieuan Higgs, Mathew Lipson, Chun Hay Brian Lo

{"title":"Machine learning bias correction and downscaling of urban heatwave temperature predictions from kilometre to hectometre scale","authors":"Lewis P. Blunn, Flynn Ames, Hannah L. Croad, Adam Gainford, Ieuan Higgs, Mathew Lipson, Chun Hay Brian Lo","doi":"10.1002/met.2200","DOIUrl":"https://doi.org/10.1002/met.2200","url":null,"abstract":"The urban heat island (UHI) effect exacerbates near-surface air temperature (T) extremes in cities, with negative impacts for human health, building energy consumption and infrastructure. Using conventional weather models, it is both difficult and computationally expensive to simulate the complex processes controlling neighbourhood-scale variation of T. We use machine learning (ML) to bias correct and downscale T predictions made by the Met Office operational regional forecast model (UKV) to 100 m horizontal grid length over London, UK. A set of ML models (random forest, XGBoost, multiplayer perceptron) are trained using citizen weather station observations and UKV variables from eight heatwaves, along with high-resolution land cover data. The ML models improve the T mean absolute error (MAE) by up to 0.12°C (11%) relative to the UKV. They also improve the UHI diurnal and spatial representation, reducing the UHI profile MAE from 0.64°C (UKV) to 0.15°C. A multiple linear regression performs almost as well as the ML models in terms of T MAE, but cannot match the UHI bias correction performance of the ML models, only reducing the UHI profile MAE to 0.49°C. UKV latent heat flux is found to be the most important predictor of T bias. It is demonstrated that including more heatwaves and observation sites in training would reduce overfitting and improve ML model performance.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2200","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140953081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Defining model complexity: An ecological perspective 定义模型的复杂性：生态学视角

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-17 DOI: 10.1002/met.2202

Charlotte A. Malmborg, Alyssa M. Willson, L. M. Bradley, Meghan A. Beatty, David H. Klinges, Gerbrand Koren, Abigail S. L. Lewis, Kayode Oshinubi, Whitney M. Woelmer

{"title":"Defining model complexity: An ecological perspective","authors":"Charlotte A. Malmborg, Alyssa M. Willson, L. M. Bradley, Meghan A. Beatty, David H. Klinges, Gerbrand Koren, Abigail S. L. Lewis, Kayode Oshinubi, Whitney M. Woelmer","doi":"10.1002/met.2202","DOIUrl":"https://doi.org/10.1002/met.2202","url":null,"abstract":"Models have become a key component of scientific hypothesis testing and climate and sustainability planning, as enabled by increased data availability and computing power. As a result, understanding how the perceived ‘complexity’ of a model corresponds to its accuracy and predictive power has become a prevalent research topic. However, a wide variety of definitions of model complexity have been proposed and used, leading to an imprecise understanding of what model complexity is and its consequences across research studies, study systems, and disciplines. Here, we propose a more explicit definition of model complexity, incorporating four facets—model class, model inputs, model parameters, and computational complexity—which are modulated by the complexity of the real-world process being modelled. We illustrate these facets with several examples drawn from ecological literature. Overall, we argue that precise terminology and metrics of model complexity (e.g., number of parameters, number of inputs) may be necessary to characterize the emergent outcomes of complexity, including model comparison, model performance, model transferability and decision support.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2202","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140953080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps 我的应用程序可不是这么说的：对天气应用程序准确性、一致性和信任度的看法

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-09 DOI: 10.1002/met.2205

Cole Vaughn, Kathleen Sherman-Morris, Michael Brown, Barrett Gutter

{"title":"That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps","authors":"Cole Vaughn, Kathleen Sherman-Morris, Michael Brown, Barrett Gutter","doi":"10.1002/met.2205","DOIUrl":"https://doi.org/10.1002/met.2205","url":null,"abstract":"The usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140902655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the impact of bias correction approaches on climate extremes and the climate change signal 评估偏差修正方法对极端气候和气候变化信号的影响

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-08 DOI: 10.1002/met.2204

Hong Zhang, Sarah Chapman, Ralph Trancoso, Nathan Toombs, Jozef Syktus

{"title":"Assessing the impact of bias correction approaches on climate extremes and the climate change signal","authors":"Hong Zhang, Sarah Chapman, Ralph Trancoso, Nathan Toombs, Jozef Syktus","doi":"10.1002/met.2204","DOIUrl":"https://doi.org/10.1002/met.2204","url":null,"abstract":"We assess the impact of three bias correction approaches on present day means and extremes, and climate change signal, for six climate variables (precipitation, minimum and maximum temperature, radiation, vapour pressure and mean sea level pressure) from dynamically downscaled climate simulations over Queensland, Australia. Results show that all bias-correction methods are effective at removing systematic model biases, however the results are variable and season-dependent. Importantly, our results are based on fully independent cross-validation, an advantage over similar studies. Linear scaling preserves the climate change signals for temperature, while quantile mapping and the distribution-based transfer function modify the climate change signal and patterns of change. The Perkins score for all the values above the 95th percentile and below the 5th percentile was used to evaluate how well the climate model matches the observational data. Bias correction improved Perkins score for extremes for some variables and seasons. We rank the bias-correction methods based on the Kling–Gupta efficiency (KGE) score calculated during the validation period. We find that linear scaling and empirical quantile mapping are the best approaches for Queensland for mean climatology. On average, bias correction led to an improvement in the KGE score of 23% annually. However, in terms of extreme values, quantile mapping and statistical distribution-based transfer function approaches perform best, and linear scaling tends to perform worst. Our results show that, except linear scaling, all approaches impact the climate change signal.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140895170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang 二氧化碳排放峰值目标下的中国区域二氧化碳排放预测方法：浙江案例研究

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-08 DOI: 10.1002/met.2203

Shuaixi Xu, Zeyan Lv, Jiezhen Wu, Lijun Chen, Junhong Wu, Yi Gao, Chengmiao Lin, Yan Wang, Die Song, Jiecan Cui

{"title":"Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang","authors":"Shuaixi Xu, Zeyan Lv, Jiezhen Wu, Lijun Chen, Junhong Wu, Yi Gao, Chengmiao Lin, Yan Wang, Die Song, Jiecan Cui","doi":"10.1002/met.2203","DOIUrl":"https://doi.org/10.1002/met.2203","url":null,"abstract":"All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom-up energy consumption prediction and top-down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom-up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy-consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140895171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How well can global ensemble forecasts predict tropical cyclones in the southwest Indian Ocean? 全球集合预报对西南印度洋热带气旋的预测效果如何？

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-06 DOI: 10.1002/met.2195

R. Emerton, K. I. Hodges, E. Stephens, V. Amelie, M. Mustafa, Z. Rakotomavo, E. Coughlan de Perez, L. Magnusson, P.-L. Vidale

{"title":"How well can global ensemble forecasts predict tropical cyclones in the southwest Indian Ocean?","authors":"R. Emerton, K. I. Hodges, E. Stephens, V. Amelie, M. Mustafa, Z. Rakotomavo, E. Coughlan de Perez, L. Magnusson, P.-L. Vidale","doi":"10.1002/met.2195","DOIUrl":"https://doi.org/10.1002/met.2195","url":null,"abstract":"The southwest Indian Ocean (SWIO) recently experienced its most active, costliest and deadliest cyclone season on record (2018–2019). The anticipation and forecasting of natural hazards, such as tropical cyclones, are crucial to preparing for their impacts, but it is important to understand how well forecasting systems can predict them. Despite the vulnerability of the SWIO to tropical cyclones, comparatively little research has focused on this region, including understanding the ability of numerical weather prediction systems to predict cyclones and their impacts in southeast Africa. In this study, we evaluate ensemble probabilistic and high-resolution deterministic forecasts of tropical cyclones in the SWIO from 2010 to 2020, using two state-of-the-art global forecasting systems: one from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the other from the U.K. Met Office. We evaluate predictions of the track, assessing the location of the centre of each storm and its speed of movement, as well as its intensity, looking at maximum wind speeds and minimum central pressure, and discuss how the forecasts have evolved over the 10-year period. Overall, ECMWF typically provides more accurate forecasts, but both systems tend to underestimate translation speed and intensity. We also investigate the impact of the Madden-Julian Oscillation (MJO) on tropical cyclones and their forecasts. The MJO impacts where and when tropical cyclones form, their tracks and intensities, which in turn impacts forecast skill. These results are intended to provide an increased understanding of the ability of global forecasting systems to predict tropical cyclones in the SWIO, for the purpose of decision making and anticipatory action.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2195","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140844851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting clear-sky periods from photovoltaic power measurements 从光伏功率测量中检测晴空时段

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-05-05 DOI: 10.1002/met.2201

William Wandji Nyamsi, Anders Lindfors

{"title":"Detecting clear-sky periods from photovoltaic power measurements","authors":"William Wandji Nyamsi, Anders Lindfors","doi":"10.1002/met.2201","DOIUrl":"https://doi.org/10.1002/met.2201","url":null,"abstract":"A method for detecting clear-sky periods from photovoltaic (PV) power measurements is presented and validated. It uses five tests dealing with parameters characterizing the connections between the measured PV power and the corresponding clear-sky power. To estimate clear-sky PV power, a PV model has been designed using as inputs downwelling shortwave irradiance and its direct and diffuse components received at ground level under clear-sky conditions as well as reflectivity of the Earth's surface and extraterrestrial irradiance, altogether provided by the McClear service. In addition to McClear products, the PV model requires wind speed and temperature as inputs taken from ECMWF twentieth century reanalysis ERA5 products. The performance of the proposed method has been assessed and validated by visual inspection and compared to two well-known algorithms identifying clear-sky periods with broadband global and diffuse irradiance measurements on a horizontal surface. The assessment was carried out at two stations located in Finland offering collocated 1-min PV power and broadband irradiance measurements. Overall, total agreement ranges between 84% and 97% (depending on the season) in discriminating clear-sky and cloudy periods with respect to the two well-known algorithms serving as reference. The disagreement fluctuating between 6% and 15%, depending on the season, primarily occurs while the PV module temperature is adequately high and/or when the sun is close to the horizon with many more interactions between the radiation, the atmosphere and the ground surface.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2201","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140826207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0