Climatic Systems Modeling Laboratory (243)
The laboratory is established in 2014. It provides development of new methods for complex data analysis and their application to different branches including the Earth climate system. Particular research directions and goals are:
- New methods for data-driven construction of evolution operators in different complex systems.
- New methods for data-driven decomposition of high-dimensional complex system data (climate data) into empirical modes.
- Methods for empirical model optimization.
- Creation of data-driven prognostic models of global Earth climate and different climate sub-systems.
- Methods for stability analysis of complex systems based on the observed data.
- Prediction of climate events (including extreme events).
ENSO prediction model "IAP-NN"
In our laboratory a data-driven model for real-time ENSO forecast was elaborated based on the analysis of sea surface temperature from NOAA_ERSST dataset (provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/). The model is based on the data dimensionality reduction by means of linear dynamical mode (LDM) decomposition and empirical construction of stochastic evolution operator for the LDMs in the form of artificial neural network. For the details of the method please see the paper [Gavrilov, A., Seleznev, A., Mukhin, D., Loskutov, E., Feigin, A., & Kurths, J. (2019). Linear dynamical modes as new variables for data-driven ENSO forecast. // Climate Dynamics, 52(3–4), 2199–2216. DOI: 10.1007/s00382-018-4255-7.]
From the July 2019 the model predictions of the Nino 3.4 index are included into the monthly updated ENSO forecast plume collecting the Nino 3.4 index predictions of leading ENSO models throughout the world and conducted by the International Research Institute for Climate and Society. The model is labeled "IAP-NN". Our latest prediction of the 3-month-mean Nino 3.4 values is below.
Monthly October 2020 Nino 3.4 forecast (values from OND-2020 to JJA-2021) : -0.854, -0.862, -0.820, -0.716, -0.564, -0.403, -0.243, -0.105, -0.013
Updated: 5 October 2020