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Andreas Groth

Research interests

The interdisciplinary character of my research activity plays an important role in my effort to advance and disseminate knowledge at the interface of climate, environment, economics and data analysis. In the broader context of climate impact research, my field of expertise is that of trying to better understand the complex coupled behavior of the socio-economic systems and the climate systems, each of which is highly complex and nonlinear.

My work has led to significant mathematical improvements and a better understanding of the advanced spectral method of Singular Spectrum Analysis (SSA).  In the data analysis of complex coupled systems, the improved SSA methodology greatly helps the identification and interpretation of the underlying mechanisms generating an observed time series.

My climate research covers data analysis of global climatic teleconnections and advances in a better understanding of interannual variability, specifically of shared atmosphere-ocean mechanisms and their changes over time. Furthermore, my research delves into a better understanding of intraseasonal timescales, more recently called sub-seasonal to seasonal (S2S), and which range from the deterministic limit of atmospheric predictability (about 10 days) up to a season (say, 100 days). These timescales are of particular importance to sub-seasonal prediction.

In my socio-economic research, the improved SSA methodology has provided strikingly new insights in the study of business cycles and has helped us better understand synchronization of world economic activity. A complex-valued extension of SSA helps us explore the cluster configuration of synchronization, as well as identify several major economic events that have markedly influenced world economic activity in the postwar era. Moreover, my work has led to a better understanding of the influence of interannual climate variability on the agricultural sector in the Sahel region.

Research topics


  • Advanced spectral methods -- Singular Spectrum Analysis
  • Monte Carlo hypothesis testing
  • Data analysis of complex coupled systems -- Synchronization
  • Data-driven low-order modeling and empirical model reduction


  • Global climate teleconnections
  • Interannual variability of shared atmosphere-ocean mechanisms and their changes over time
  • Intraseasonal variability and sub-seasonal prediction


  • Synchronization of world economic activity, cross-country relationships and international business cycles
  • Deterministic causes of macroeconomic fluctuations
  • Vulnerability of an economy to exogenous shocks, such as climatic extreme events
  • Influence of interannual climate variability on the agricultural sector in the Sahel region


  • Influence of interannual climate forcing on ecosystem dynamics
  • Effects of temperature variation on fish population structure

Article dans une revue12 documents

  • Keroboto B.Z. Ogutu, Fabio d'Andrea, Andreas Groth, Michael Ghil. Coupled Climate-Economy-Ecology (CoCEB) Modeling: A Dynamic Approach. SSRN Electronic Journal, In press, ⟨10.2139/ssrn.3697299⟩. ⟨hal-03006628⟩
  • Vivien Sainte Fare Garnot, Andreas Groth, Michael Ghil. Coupled Climate-Economic Modes in the Sahel's Interannual Variability. Ecological Economics, Elsevier, 2018, 153, pp.111-123. ⟨10.1016/j.ecolecon.2018.07.006⟩. ⟨hal-01855370⟩
  • Andreas Groth, Michael Ghil. Synchronization of world economic activity. Chaos: An Interdisciplinary Journal of Nonlinear Science, American Institute of Physics, 2017, 27 (12), ⟨10.1063/1.5001820⟩. ⟨hal-01701086⟩
  • Andreas Groth, yizhak Feliks, Dmitri D Kondrashov, Michael Ghil. Interannual Variability in the North Atlantic Ocean’s Temperature Field and Its Association with the Wind Stress Forcing. Journal of Climate, American Meteorological Society, 2017, 30 (7), pp.2655-2678. ⟨10.1175/jcli-d-16-0370.1⟩. ⟨hal-01701108⟩
  • Eric Edeline, Andreas Groth, Bernard Cazelles, David Claessen, Ian J. Winfield, et al.. Pathogens trigger top-down climate forcing on ecosystem dynamics. Oecologia, Springer Verlag, 2016, 181 (2), pp.519-532. ⟨10.1007/s00442-016-3575-8⟩. ⟨hal-01288260⟩
  • Lisa Sella, Gianna Vivaldo, Andreas Groth, Michael Ghil. Economic Cycles and Their Synchronization: A Comparison of Cyclic Modes in Three European Countries. Journal of Business Cycle Research, Springer, 2016, 12 (1), pp.25 - 48. ⟨10.1007/s41549-016-0003-4⟩. ⟨hal-01701122⟩
  • Andreas Groth, M. Ghil, Stéphane Hallegatte, Patrice Dumas. The role of oscillatory modes in US business cycles. OECD Journal: Journal of Business Cycle Measurement and Analysis, 2015, 2015 (1), pp.63-81. ⟨10.1787/jbcma-2015-5jrs0lv715wl⟩. ⟨hal-01239779⟩
  • Andreas Groth, Michael Ghil. Monte Carlo Singular Spectrum Analysis (SSA) Revisited: Detecting Oscillator Clusters in Multivariate Datasets. Journal of Climate, American Meteorological Society, 2015, 28 (19), pp.7873-7893. ⟨10.1175/JCLI-D-15-0100.1⟩. ⟨hal-01701132⟩
  • yizhak Feliks, Andreas Groth, Michael Ghil, Andrew W. Robertson. Oscillatory Climate Modes in the Indian Monsoon, North Atlantic, and Tropical Pacific. Journal of Climate, American Meteorological Society, 2013, 26 (23), pp.9528-9544. ⟨10.1175/JCLI-D-13-00105.1⟩. ⟨hal-01099078⟩
  • Andreas Groth, Michael Ghil. Multivariate singular spectrum analysis and the road to phase synchronization. Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, American Physical Society, 2011, 84 (3), pp.9528-9544. ⟨10.1103/PhysRevE.84.036206⟩. ⟨hal-01701146⟩
  • Norbert Marwan, Andreas Groth, Jürgen Kurths. Quantification of Order Patterns Recurrence Plots of Event Related Potentials. Chaos and Complexity Letters, Nova Science Publishers, 2007, 2, pp.301-314. ⟨hal-01712785⟩
  • Andreas Groth. Visualization of coupling in time series by order recurrence plots. Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, American Physical Society, 2005, 72 (4), ⟨10.1103/PhysRevE.72.046220⟩. ⟨hal-01701163⟩

Chapitre d'ouvrage3 documents

  • Michael Ghil, Andreas Groth, Dmitri D Kondrashov, Andrew W Robertson. Extratropical Sub-seasonal to Seasonal Oscillations and Multiple Regimes: The Dynamical Systems View. Andrew W. Robertson; Frédéric Vitart. Sub-Seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting, Elsevier, pp.119 - 142, 2018, 978-0-12-811714-9. ⟨10.1016/b978-0-12-811714-9.00006-1⟩. ⟨hal-01910214⟩
  • Andreas Groth, Patrice Dumas, Michael Ghil, Stéphane Hallegatte. Impacts of Natural Disasters on a Dynamic Economy. Mario Chavez, Michael Ghil, Jaime Urrutia-Fucugauchi. Extreme Events: Observations, Modeling, and Economics, Wiley, pp.343-360, 2015, Geophysical Monograph Series, 978-1-119-15701-4. ⟨10.1002/9781119157052.ch19⟩. ⟨hal-01678074⟩
  • Christoph Bandt, Andreas Groth, Norbert Marwan, M. Carmen Carmen Romano, Marco Thiel, et al.. Analysis of bivariate coupling by means of recurrence. Rainer Dahlhaus; Jürgen Kurths; Peter Maass; Jens Timmer. Mathematical Methods in Signal Processing and Digital Image Analysis, Springer Berlin Heidelberg, pp.153-182, 2008, Understanding Complex Systems 978-3-540-75631-6. ⟨10.1007/978-3-540-75632-3_5⟩. ⟨hal-01701452⟩

Thèse1 document

  • Andreas Groth. Analyse der Wiederkehr in dynamischen Systemen auf einer Ordinalskala. Dynamical Systems [math.DS]. Ernst-Moritz-Arndt Universität Greifswald, 2006. German. ⟨tel-01718849⟩