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Development of typical meteorological years based on quality control of datasets in Indonesia

Author

Listed:
  • Putra, I Dewa Gede Arya
  • Nimiya, Hideyo
  • Sopaheluwakan, Ardhasena
  • Kubota, Tetsu
  • Lee, Han Soo
  • Pradana, Radyan Putra
  • Alfata, Muhammad Nur Fajri
  • Perdana, Reza Bayu
  • Permana, Donaldi Sukma
  • Riama, Nelly Florida
  • Karnawati, Dwikorita

Abstract

This study aims to demonstrate the comprehensive development of typical meteorological years (TMYs) under relatively limited observational data. The distribution of missing hourly observational data of the 2011–2020 period at all sites was examined. This paper proposes a quality control method for filling the gaps in the missing hourly observational data using bias-corrected ERA5 reanalysis data in the process of developing TMYs. Initially, the temperature bias distribution from −4.5 °C to 2.7 °C was reduced to a range of −0.014 °C to 0.005 °C. The relative humidity bias distribution was −6 % to 10 %, and was reduced to −0.32 % to 0.07 %. The bias distribution of wind speeds ranging from −4 m/s to 2 m/s was reduced to −0.02 m/s to 0.35 m/s. The Sandia method with a modified weighting of Finkelstein-Shaffer (FS) statistics was applied to eight climate elements, namely, global horizontal irradiance, direct normal irradiance, diffuse horizontal irradiance, temperature, precipitation, wind speed, relative humidity, and dew point temperature to generate TMYs at 106 sites across eight climate zones in Indonesia. The verification results showed that the average correlation and RMSE between TMYs and their long-term averages were 0.96 and 75 w/m2 for global horizontal radiation, respectively, while those for temperature were 0.86 and 1.3 °C, respectively.

Suggested Citation

  • Putra, I Dewa Gede Arya & Nimiya, Hideyo & Sopaheluwakan, Ardhasena & Kubota, Tetsu & Lee, Han Soo & Pradana, Radyan Putra & Alfata, Muhammad Nur Fajri & Perdana, Reza Bayu & Permana, Donaldi Sukma & , 2024. "Development of typical meteorological years based on quality control of datasets in Indonesia," Renewable Energy, Elsevier, vol. 221(C).
  • Handle: RePEc:eee:renene:v:221:y:2024:i:c:s0960148123016142
    DOI: 10.1016/j.renene.2023.119699
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