Latest additions to the knowledge base

By using reanalysis data and climate model output together with a deep learning model, the study explores the relationship between positive-phase North Atlantic Tripole (NAT) sea-surface temperature anomalies and Southeastern Siberia wildfire increases.

With the help of an AI algorithm, researchers grouped forest regions into distinct zones with similar fire patterns and underlying causes, uncovering the worrying extent to which climate change is fuelling the expansion of forest fires in high latitudes.

The results, published in the journal Earth’s Future, suggest significant and widespread effects on air quality, climate, health, and economics under the most extreme wildfire scenarios.

This seismic risk profile of Russia, produced by the Global Earthquake Model (GEM) Foundation summarizes key metrics of seismic risk, allowing stakeholders in risk management to get an overview of the risk in the country.

The Voluntary National Report of the Russian Federation for the Midterm Review of the Implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030 (MTR SF).

The Russian Federation's first Nationally Determined Contribution outlines the country's aims in relation to the the implementation of the United Nations Framework Convention on Climate Change.

A research team led by Professor Jonghun Kam at POSTECH reveals the reason behind hot and wet winters in northwest Russia from 2019/20 winter.

Scientists are worried that wildfires might burn out of control in Siberia while the Russian military units that normally keep them in check are dispatched to Ukraine.