Research

Work in progress

• Relevant large-scale predictors for sub-seasonal precipitation forecast identified via explainable neural networks

Peer-reviewed publications

Lagged Teleconnections of Climate Variables Identified via Complex Rotated Maximum Covariance Analysis

Niclas Rieger, Álvaro Corral, Estrella Olmedo, Antonio Turiel, "Lagged Teleconnections of Climate Variables Identified via Complex Rotated Maximum Covariance Analysis." Journal of Climate, 2021.

Talks, presentations etc.

Climate variability in the northern Arabian Sea during the Holocene

July 28, 2019

Poster at INQUA, Dublin, Ireland

Complex Maximum Covariance analysis: a method to detect lagged correlations between variables

November 18, 2020

Talk at EO4Water, Online

Complex rotated MCA: a method to correlate lagged geophysical variables

April 24, 2021

Talk at EGU21, Online

Identifying relevant large-scale predictors for sub-seasonal precipitation forecast using explainable neural networks

November 04, 2021

Poster at 3rd CAFE Workshop, Météo France, Toulouse, France