Resource assessment uncertainty reduction via bias correction: On the temporal and spatial sensitivity analysis

The present study addresses the necessity of a wide and reliable knowledge of metocean conditions for the design and operation of Offshore Renewable Energy (ORE) installations. Statistical bias correction techniques, including a directionally-sensitive technique, are implemented and tested in several locations around the Spanish coast, using information coming from in-situ measurements, with the objective to reduce the uncertainty on wave statistics of re-analysis datasets. In addition, the most effective techniques ( i.e. EGQM and DAGQM) are taken as a reference to carry out a temporal and spatial sensitivity analysis, aimed at extending the validity of the aforementioned calibration techniques both in time and space. Encouraging results are obtained concerning temporal sensitivity, showing that a period between 4 and 5 years is the ideal for effectively calibrating several years of re-analysis data, and that a window of just 3 months could be enough to achieve a good bias correction. On the other hand, spatial sensitivity analysis does not highlight a trend as clear as the previous one. Uncertainty reduction after bias correction is limited to the buoys surroundings, and no critical radius could be obtained. Due to the multitude of relevant local geographical factors, such as bathymetry and coast morphology, it can be concluded that correction factors obtained in a specific site cannot always be effectively used to calibrate datasets beyond the observation point.

Authors

Institutions

Publication Details

Journal
Applied Ocean Research
Published
2025-10-22
DOI
https://doi.org/10.1016/j.apor.2025.104818
Citations
1
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Resource assessment uncertainty reduction via bias correction: On the temporal and spatial sensitivity analysis

Ander Martinez-Perurena, Gregório Iglesias, Markel Peñalba, Giuseppe Giorgi et al.
1 citations
Applied Ocean Research
Atmospheric and Environmental Gas Dynamics
1.11
article

Resource assessment uncertainty reduction via bias correction: On the temporal and spatial sensitivity analysis

Ander Martinez-Perurena, Gregório Iglesias, Markel Peñalba, Giuseppe Giorgi, Francesco Callea
article en
1 citations

Abstract

The present study addresses the necessity of a wide and reliable knowledge of metocean conditions for the design and operation of Offshore Renewable Energy (ORE) installations. Statistical bias correction techniques, including a directionally-sensitive technique, are implemented and tested in several locations around the Spanish coast, using information coming from in-situ measurements, with the objective to reduce the uncertainty on wave statistics of re-analysis datasets. In addition, the most effective techniques ( i.e. EGQM and DAGQM) are taken as a reference to carry out a temporal and spatial sensitivity analysis, aimed at extending the validity of the aforementioned calibration techniques both in time and space. Encouraging results are obtained concerning temporal sensitivity, showing that a period between 4 and 5 years is the ideal for effectively calibrating several years of re-analysis data, and that a window of just 3 months could be enough to achieve a good bias correction. On the other hand, spatial sensitivity analysis does not highlight a trend as clear as the previous one. Uncertainty reduction after bias correction is limited to the buoys surroundings, and no critical radius could be obtained. Due to the multitude of relevant local geographical factors, such as bathymetry and coast morphology, it can be concluded that correction factors obtained in a specific site cannot always be effectively used to calibrate datasets beyond the observation point.

Applied Ocean ResearchVol. 165
Ikerbasque (ES), Mondragon Unibertsitatea (ES), Politecnico di Torino (IT), University College Cork (IE), University of Plymouth (GB)
Openalex Percentile: Top 18%
Atmospheric and Environmental Gas Dynamics
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Resource assessment uncertainty reduction via bias correction: On the temporal and spatial sensitivity analysis — Ander Martinez-Perurena, Gregório Iglesias, et al. · Applied Ocean Research (2025) | TGRS Research Map | TGRS