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Author

Nikolay Koldunov

5 papers indexed here

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#machine learning Preprint Oct 2026

ClimateBench v2.0: Probabilistic Climate Model Benchmarking

We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in projecting mid-century regional temperature and precipitation changes. The protocol is designed to evaluate any physics-based, data-driven, or hybrid climate model on equal foot...

Duncan Watson-Parris, Willa Tobin, Aytaç Paçal et al. · 0 citations
#large language models Open access Sep 2026

Climate Knowledge in Large Language Models

This evaluation framework provides a reproducible benchmark for quantifying parametric climate knowledge in LLMs, and shows that LLMs reproduce broad geographic regularities in climatological temperature fields, capturing latitudinal and topographic patterns.

Ivan S. Kuznetsov, Jacopo Grassi, Dmitrii Pantiukhin et al. · 0 citations
#machine learning Preprint Sep 2026

HClimRep-Ocean: A Global Ocean Emulator on an Unstructured Mesh

HlimRep-Ocean is presented, an ocean emulator that operates directly on the native unstructured mesh of FESOM2, and achieves the lowest RMSE against GLORYS reanalysis among all assessed systems, confirming the competitiveness of the native-mesh approach.

K. Nowak, A. Koldunov, Nikolay Koldunov et al. · 0 citations
Open access Aug 2026

AQUA v1.0.0: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin – the core engine

Abstract. The increasing availability of kilometer-scale climate simulations presents major challenges for data access, processing, and analysis due to the unprecedented volume and heterogeneity of the outputs. Different data formats, structures, and metadata conventions, require dedicated solutions to ensure interoper...

Matteo Nurisso, Jost von Hardenberg, Marco Cadau et al. · 0 citations

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