To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on ...To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.展开更多
Boosted by a strong solar power market,the electricity grid is exposed to risk under an increasing share of fluctuant solar power.To increase the stability of the electricity grid,an accurate solar power forecast is n...Boosted by a strong solar power market,the electricity grid is exposed to risk under an increasing share of fluctuant solar power.To increase the stability of the electricity grid,an accurate solar power forecast is needed to evaluate such fluctuations.In terms of forecast,solar irradiance is the key factor of solar power generation,which is affected by atmospheric conditions,including surface meteorological variables and column integrated variables.These variables involve multiple numerical timeseries and images.However,few studies have focused on the processing method of multiple data types in an interhour direct normal irradiance(DNI)forecast.In this study,a framework for predicting the DNI for a 10-min time horizon was developed,which included the nondimensionalization of multiple data types and time-series,development of a forecast model,and transformation of the outputs.Several atmospheric variables were considered in the forecast framework,including the historical DNI,wind speed and direction,relative humidity time-series,and ground-based cloud images.Experiments were conducted to evaluate the performance of the forecast framework.The experimental results demonstrate that the proposed method performs well with a normalized mean bias error of 0.41%and a normalized root mean square error(n RMSE)of20.53%,and outperforms the persistent model with an improvement of 34%in the nRMSE.展开更多
The China Space Station Telescope(CSST,also known as Xuntian)is a serviceable two-meter-aperture wide-field telescope operating in the same orbit as the China Space Station.The CSST plans to survey a sky area of 17,50...The China Space Station Telescope(CSST,also known as Xuntian)is a serviceable two-meter-aperture wide-field telescope operating in the same orbit as the China Space Station.The CSST plans to survey a sky area of 17,500 deg^(2)of the medium-to-high Galactic latitude to a depth of 25-26 AB mag in at least 6 photometric bands over 255-1,000 nm.Within such a large sky area,slitless spectra will also be taken over the same wavelength range as the imaging survey.Even though the CSST survey is not dedicated to time-domain studies,it would still detect a large number of transients,such as supernovae(SNe).In this paper,we simulate photometric SN observations based on a strawman survey plan using the Sncosmo package.During its 10-year survey,the CSST is expected to observe about 5 million SNe of various types.With quality cuts,we obtain a“gold”sample that comprises roughly 7,400 SNe Ia,2,200 SNe Ibc,and 6,500 SNeⅡcandidates with correctly classified percentages reaching 91%,63%,and 93%(formally defined as classification precision),respectively.The same survey can also trigger alerts for the detection of about 15,500 SNe Ia(precision 61%)and 2,100 SNeⅡ(precision 49%)candidates at least two days before the light maxima.Moreover,the near-ultraviolet observations of the CSST will be able to catch hundreds of shock-cooling events serendipitously every year.These results demonstrate that the CSST can make a potentially significant contribution to SN studies.展开更多
基金supported by the Special Edu-cational Research Budget(Research Promotion)[FY2009]the Special Budget(Project)[FY2010 and later years]from the Ministry of Education,Culture,Sports,Science and Technology(MEXT),Japansupported by the GRENE Arctic Climate Change Research Project,Japan
文摘To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.
基金supported by the National Key Research and Development Program of China(No.2018YFB1500803)National Natural Science Foundation of China(No.61773118,No.61703100)Fundamental Research Funds for Central Universities.
文摘Boosted by a strong solar power market,the electricity grid is exposed to risk under an increasing share of fluctuant solar power.To increase the stability of the electricity grid,an accurate solar power forecast is needed to evaluate such fluctuations.In terms of forecast,solar irradiance is the key factor of solar power generation,which is affected by atmospheric conditions,including surface meteorological variables and column integrated variables.These variables involve multiple numerical timeseries and images.However,few studies have focused on the processing method of multiple data types in an interhour direct normal irradiance(DNI)forecast.In this study,a framework for predicting the DNI for a 10-min time horizon was developed,which included the nondimensionalization of multiple data types and time-series,development of a forecast model,and transformation of the outputs.Several atmospheric variables were considered in the forecast framework,including the historical DNI,wind speed and direction,relative humidity time-series,and ground-based cloud images.Experiments were conducted to evaluate the performance of the forecast framework.The experimental results demonstrate that the proposed method performs well with a normalized mean bias error of 0.41%and a normalized root mean square error(n RMSE)of20.53%,and outperforms the persistent model with an improvement of 34%in the nRMSE.
基金supported by the National Key R&D Program of China(Grant Nos.2022YFF0503400 and 2022YFF0503401)China Manned Space Program(Grant Nos.CMS-CSST-2021-B01,CMS-CSST-2021-B04,and CMS-CSST2021-A12)+2 种基金Science Program of Beijing Academy of Science and Technology(Grant No.24CD014)National Natural Science Foundation of China(Grant Nos.12288102 and 12033003)Tencent Xplorer Prize。
文摘The China Space Station Telescope(CSST,also known as Xuntian)is a serviceable two-meter-aperture wide-field telescope operating in the same orbit as the China Space Station.The CSST plans to survey a sky area of 17,500 deg^(2)of the medium-to-high Galactic latitude to a depth of 25-26 AB mag in at least 6 photometric bands over 255-1,000 nm.Within such a large sky area,slitless spectra will also be taken over the same wavelength range as the imaging survey.Even though the CSST survey is not dedicated to time-domain studies,it would still detect a large number of transients,such as supernovae(SNe).In this paper,we simulate photometric SN observations based on a strawman survey plan using the Sncosmo package.During its 10-year survey,the CSST is expected to observe about 5 million SNe of various types.With quality cuts,we obtain a“gold”sample that comprises roughly 7,400 SNe Ia,2,200 SNe Ibc,and 6,500 SNeⅡcandidates with correctly classified percentages reaching 91%,63%,and 93%(formally defined as classification precision),respectively.The same survey can also trigger alerts for the detection of about 15,500 SNe Ia(precision 61%)and 2,100 SNeⅡ(precision 49%)candidates at least two days before the light maxima.Moreover,the near-ultraviolet observations of the CSST will be able to catch hundreds of shock-cooling events serendipitously every year.These results demonstrate that the CSST can make a potentially significant contribution to SN studies.
