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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Input data for: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution

Authors: Muis, Sanne; Dangendorf, Sönke; Irazoqui Apecechea, Maialen; Dullaart, Job; de Lima Rego, Joao; Madsen, Kristine Skovgaard; Su, Jian; +9 Authors

Input data for: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution

Abstract

This Zenodo archive contains essential input datasets utilized in our research study titled "Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution". This archive contains only input data. The Hourly Coastal water levels with Counterfactual (HCC) dataset is published in the ISIMIP repository. Datasets Included: CoDEC (Coastal Dataset for the Evaluation of Climate Impact): This dataset is described in Muis et al. (2020) cf_esl folder: Contains data representing total CoDEC water levels. Individual NetCDF files store data for each grid point. cf_tides folder: This folder holds data related to tidal elevation. coor_coastal.nc: A NetCDF file featuring the spatial grid utilized in CoDEC. This dataset comprises only coastal grid points. HR (Hybrid Reconstructions): HybridRec_Upd0422.mat: This file contains data from the Hybrid Reconstructions dataset (Dangendorf et al 2019), aligned to the CoDEC grid, and includes satellite altimetry integral to producing the Hybrid Reconstructions dataset. Each row corresponds to one grid point on the CoDEC grid. For ease of use in our applications, we offer a preprocessing script in our source code named split_hr_dataset_to_stations.py. We here provide the specific versions of HR and CoDEC that are used in our study to ensure accurate replication.

This research has received funding from the German Federal Ministry Ministry of Education and Research (BMBF) under the research projects QUIDIC (01LP1907A) and ISIAccess (16QK05), the European Union's Horizon 2020 research and innovation programme under agreement No 820712grant, and is based upon work from COST Action CA19139 PROCLIAS (PROcess-based models for CLimate Impact Attribution across Sectors), supported by COST (European Cooperation in Science and Technology; https://www.cost.eu). S.D. acknowledges support by NASA's Sea Level Change Team (award number 80NSSC20K1241) and David and Jane Flowerree for their endowment

Keywords

Hybrid Reconstructions, Sea Level Rise, Impact Attribution, Coastal Water Levels, CoDEC, Counterfactuals

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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