Title:	Impacts of Tropical-Extratropical Air-Sea Interactions
DNr:	NAISS 2025/22-19
Project Type:	NAISS Small Compute
Principal Investigator:	Koffi Worou <koffi.worou@geo.uu.se>
Affiliation:	Uppsala universitet
Duration:	2025-02-01 – 2026-02-01
Classification:	10501
Keywords:

Abstract

El Niño is the main climate mode of variability of the Earth system, operating on interannual timescales and characterized by anomalous warming and cooling of sea surface temperatures in the eastern tropical Pacific. Its phases have significant socio-economic impacts on a global scale, making it a critical climate variable to monitor, understand, and predict. However, interactions between the tropical Pacific and other oceanic basins can yield varied outcomes in terms of these impacts. While substantial progress has been made in understanding teleconnection dynamics, there is limited research quantifying their socio-economic consequences, such as fatalities, affected populations, and financial losses. This research aims to link the occurrence of climatic hazards, such as droughts and floods, to climate indices representing dominant oceanic and atmospheric modes of variability. We assess how different couplings between oceanic basins influence climate and weather patterns and their associated impacts. Specifically, the study focuses on three key objectives: 1. Investigating the non-linear relationship between the El Niño mode and the North Atlantic Oscillation, along with their associated impacts in Europe. 2. Examining interactions among the El Niño mode, the Atlantic Zonal Mode, and the Indian Ocean Dipole, and their resulting large-scale impacts. 3. The physics underlying new non-linear air-sea interactions will be highlighted. We utilize ERA5 climate reanalysis data to compute indices of intrinsic climate variability modes and the Emergency Disaster Database (EM-DAT) to quantify socio-economic impacts. This study aims to evaluate the contribution of climate variability modes to observed socio-economic impacts. By doing so, it seeks to improve predictions of the costs associated with high-impact weather and climate events and enhance preparedness strategies for future events.