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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Dataset for "Convective Environments Over the Arabian Peninsula in Current and Future Climates: A Machine Learning Approach"

Authors: Homoudi, Ahmed;

Dataset for "Convective Environments Over the Arabian Peninsula in Current and Future Climates: A Machine Learning Approach"

Abstract

This dataset provides convection indices or predictors derived from ERA5 over the Arabian Peninsula, covering the period 2001 - 2024 at 1 degree x 1 degree and a 6-hour interval. Additionally, the 6-hourly accumulated precipitation from IMERG V07 is included. The dataset includes raw (not bias-corrected) convective indices estimated from the historical and SSP5-8.5 experiments from CMIP6. However, only the years corresponding to the current regional warming level (+1.22°C above the preindustrial level) and to two future levels (+2.22°C and +4.22°C) are provided. The indices were computed using the R package MeteoMate and are provided in HDF5 format. Bias correction was applied to the CMIP6 indices using the MBCn algorithm from the R package MBC prior to estimating convection probabilities. The repository includes trained random forest (RF), extreme gradient boosting (XGB), and deep learning (DL) models for detecting or estimating the probability of convective environments. Additional information can be found in the README file. The dataset is intended to foster research on convective environments, extreme precipitation, convection-permitting modelling and climate change impacts over the region.

AcknowledgementsThe author gratefully acknowledges the computing time provided on the high-performance computer at the NHR Centre of TU Dresden. This centre is jointly supported by the Federal Ministry of Research, Technology and Space of Germany and the state governments participating in the NHR (www.nhr-verein.de/unsere-partner).

Related Organizations
Keywords

Convective environments, Machine learning, Convective indices, Arabian Peninsula, Climate change

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Impulse provided by BIP!
0
Average
Average
Average