• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用地面测量和全球再分析产品对索马里兰的太阳辐照度进行评估和校正。

Evaluation and correction of solar irradiance in Somaliland using ground measurements and global reanalysis products.

作者信息

Khan Muhammad Umair, Jama Mohamed Abdi

机构信息

Department of Electrical, Computer and Biomedical Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates.

出版信息

Heliyon. 2024 Aug 6;10(16):e35256. doi: 10.1016/j.heliyon.2024.e35256. eCollection 2024 Aug 30.

DOI:10.1016/j.heliyon.2024.e35256
PMID:39687859
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11647872/
Abstract

Properly understanding solar irradiance can help accurately quantify the solar energy resource and guide sustainable development projects, particularly where measured solar data are scarce or suffer from detrimental data quality issues. This study aims to assess and improve solar global horizontal irradiance (GHI) data from a diverse range of global reanalysis datasets by utilizing measured data from two ground weather stations located in Somaliland. A comprehensive evaluation framework is employed, combining various statistical and regression error metrics, whereas bias correction methods are implemented. The comparative study covers several analytical facets such as the hourly, daily and monthly data analysis before and after correction along with analyzing the seasonal variations, clear-sky and all-sky conditions. The analysis revealed pattern of an overall underestimation of GHI with varying degrees of accuracy in the estimated GHI datasets before and after correction. The annual ranges for rMBE, rMAE, rRMSE and R extend from 3-31%, 12-33%, 19-53% and 0.797-0.979, respectively, across all datasets for six-hourly data in the two observed stations. Following bias correction, the ranges for rMBE, rMAE, rRMSE reduce to is 0%, 8-31%, 11-34% and R increase to 0.897-0.984 respectively. While certain datasets such as MERRA-2 and SARAH-2 demonstrate close alignment with ground data before correction, other especially ERA5-Land exhibit exceptional improvement after the bias correction.

摘要

正确理解太阳辐照度有助于准确量化太阳能资源,并指导可持续发展项目,特别是在实测太阳数据稀缺或存在有害数据质量问题的地区。本研究旨在利用位于索马里兰的两个地面气象站的实测数据,评估和改进来自各种全球再分析数据集的全球水平总辐照度(GHI)数据。采用了一个综合评估框架,结合了各种统计和回归误差指标,并实施了偏差校正方法。比较研究涵盖了几个分析方面,如校正前后的每小时、每日和每月数据分析,以及分析季节变化、晴空和全天条件。分析揭示了在估计的GHI数据集中,校正前后GHI总体上存在不同程度的低估模式。在两个观测站,所有数据集的六小时数据的rMBE、rMAE、rRMSE和R的年范围分别为3 - 31%、12 - 33%、19 - 53%和0.797 - 0.979。经过偏差校正后,rMBE、rMAE、rRMSE的范围分别降至0%、8 - 31%、11 - 34%,R增加到0.897 - 0.984。虽然某些数据集,如MERRA - 2和SARAH - 2在校正前与地面数据显示出密切的一致性,但其他数据集,特别是ERA5 - Land在偏差校正后表现出显著的改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/bc970f61cffa/gr022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/212f2e9f570e/gr001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/21c017baa951/gr002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6eaef52bbd9a/gr003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/b7a627f3ba7a/gr004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/236e9fa6de98/gr005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/ad2102fac322/gr006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/2565de073012/gr007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/ccd1fdbed698/gr008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/b7ab74f37227/gr009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6ede9ddfc079/gr010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/2f70b082bde0/gr011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/bbdeca031809/gr012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/8e69f1736520/gr013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/50b6a7965d0e/gr014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/5b5c4b552479/gr015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6e0a55cc4819/gr016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/64743ddbbeb0/gr017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/4956f06ee598/gr018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/934227b8d237/gr019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/39eed2addf10/gr020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/17cd40eeae1c/gr021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/bc970f61cffa/gr022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/212f2e9f570e/gr001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/21c017baa951/gr002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6eaef52bbd9a/gr003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/b7a627f3ba7a/gr004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/236e9fa6de98/gr005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/ad2102fac322/gr006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/2565de073012/gr007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/ccd1fdbed698/gr008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/b7ab74f37227/gr009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6ede9ddfc079/gr010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/2f70b082bde0/gr011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/bbdeca031809/gr012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/8e69f1736520/gr013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/50b6a7965d0e/gr014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/5b5c4b552479/gr015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/6e0a55cc4819/gr016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/64743ddbbeb0/gr017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/4956f06ee598/gr018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/934227b8d237/gr019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/39eed2addf10/gr020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/17cd40eeae1c/gr021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8676/11647872/bc970f61cffa/gr022.jpg

相似文献

1
Evaluation and correction of solar irradiance in Somaliland using ground measurements and global reanalysis products.利用地面测量和全球再分析产品对索马里兰的太阳辐照度进行评估和校正。
Heliyon. 2024 Aug 6;10(16):e35256. doi: 10.1016/j.heliyon.2024.e35256. eCollection 2024 Aug 30.
2
Hourly global horizontal irradiance data of three stations in Punjab, Pakistan.巴基斯坦旁遮普省三个站点的每小时全球水平辐照度数据。
Data Brief. 2021 Sep 17;38:107371. doi: 10.1016/j.dib.2021.107371. eCollection 2021 Oct.
3
Reference evapotranspiration estimation using reanalysis and WaPOR products in dryland Croplands.利用再分析数据和WaPOR产品估算旱地农田的参考作物蒸散量
Heliyon. 2024 Feb 19;10(4):e26531. doi: 10.1016/j.heliyon.2024.e26531. eCollection 2024 Feb 29.
4
Evaluation of air temperature estimated by ERA5-Land reanalysis using surface data in Pernambuco, Brazil.利用巴西伯南布哥州地面数据评估 ERA5-Land 再分析估算的气温。
Environ Monit Assess. 2022 Apr 20;194(5):381. doi: 10.1007/s10661-022-10047-2.
5
A solar radiation database for Chile.智利的一个太阳辐射数据库。
Sci Rep. 2017 Nov 1;7(1):14823. doi: 10.1038/s41598-017-13761-x.
6
Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China.ERA5-Land 再分析资料在中国东南部沿海城市群的气温表现。
Sci Total Environ. 2022 Jul 1;828:154459. doi: 10.1016/j.scitotenv.2022.154459. Epub 2022 Mar 9.
7
Long-Term Variations of Global Solar Radiation and Its Potential Effects at Dome C (Antarctica).南极 Dome C 地区全球太阳辐射长期变化及其潜在影响。
Int J Environ Res Public Health. 2022 Mar 6;19(5):3084. doi: 10.3390/ijerph19053084.
8
Global Corrections to Reference Irradiance Spectra for Non-Clear-Sky Conditions.全球非晴天空条件下参考辐照度光谱的校正。
Environ Sci Technol. 2023 Feb 14;57(6):2682-2690. doi: 10.1021/acs.est.2c07359. Epub 2023 Feb 3.
9
Compilation and spatio-temporal analysis of publicly available total solar and UV irradiance data in the contiguous United States.编译和分析美国本土的公开全日太阳和紫外线辐射数据的时空分布。
Environ Pollut. 2019 Oct;253:130-140. doi: 10.1016/j.envpol.2019.06.074. Epub 2019 Jun 26.
10
Mapping of 10-km daily diffuse solar radiation across China from reanalysis data and a Machine-Learning method.利用再分析数据和机器学习方法绘制中国每日10公里分辨率的漫射太阳辐射图。
Sci Data. 2024 Jul 11;11(1):756. doi: 10.1038/s41597-024-03609-1.

本文引用的文献

1
Solar irradiance measurement instrumentation and power solar generation forecasting based on Artificial Neural Networks (ANN): A review of five years research trend.基于人工神经网络(ANN)的太阳辐照度测量仪器和太阳能发电预测:五年研究趋势综述。
Sci Total Environ. 2020 May 1;715:136848. doi: 10.1016/j.scitotenv.2020.136848. Epub 2020 Jan 22.
2
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).现代时代研究与应用回顾分析第2版(MERRA-2)
J Clim. 2017 Jun 20;Volume 30(Iss 13):5419-5454. doi: 10.1175/JCLI-D-16-0758.1.