Search

Results for "Kӧppen-Geiger"

New climate maps predict major changes in vegetation by end of century

KAUST · Oct 24

A KAUST-led study published in Scientific Data provides updated global climate classification maps from 1901-2020 and projects future conditions up to 2099. Researchers used a refined selection of climate models, excluding those with unrealistic CO2-induced warming rates, to ensure accuracy. Projections indicate significant shifts in land surface climate, with large areas transitioning to warmer climate zones by the end of the century under moderate emission scenarios. Why it matters: The updated maps provide a crucial tool for understanding climate change impacts, ecological studies, and informing policy decisions in the face of global warming, especially for a region like the Middle East that is highly vulnerable to climate change.

Weather impact on daily cases of COVID-19 in Saudi Arabia using machine learning

arXiv · May 7

This paper examines the relationship between COVID-19 spread and weather patterns across 89 cities in Saudi Arabia using machine learning. The study uses daily COVID-19 case reports from the Saudi Ministry of Health and historical weather data. The results indicate that temperature and wind speed have the strongest correlation with the spread of COVID-19, with a random forest model achieving the best performance.

Climate-based Pre-screening of Self-sustaining Regreening Opportunities in Drylands: A Case Study for Saudi Arabia

arXiv · May 5

Researchers have developed a scalable pre-screening framework that integrates climate and remote sensing data to identify cost-efficient sites for sustainable dryland restoration, using Saudi Arabia as a case study. The framework employs machine learning models to derive a Climate Suitability Score (CSS), which captures climatic dependencies on vegetation persistence. National-scale prediction maps were generated using multi-year ERA5-Land data for Saudi Arabia, leading to the identification of thirteen priority locations with an estimated potential for a 2.5-fold increase in vegetation coverage. Why it matters: This approach significantly reduces the search space and costs associated with restoration efforts, supporting more resilient and sustainable ecosystem recovery planning in water-limited regions of the Middle East.