# Stochastic climate theory and modeling

@article{Franzke2014StochasticCT, title={Stochastic climate theory and modeling}, author={Christian L. E. Franzke and Terence J. O'Kane and Judith Berner and Paul D. Williams and Valerio Lucarini}, journal={Wiley Interdisciplinary Reviews: Climate Change}, year={2014}, volume={6} }

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid‐scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all…

## 152 Citations

### Advances and challenges in climate modeling

- Environmental ScienceClimatic Change
- 2022

In spite of the chaotic nature of the atmosphere and involvement of complex nonlinear dynamics, forecasting climate fluctuations over different timescales is feasible due to the interaction between…

### Stochastic weather and climate models

- Environmental ScienceNature Reviews Physics
- 2019

The ways in which introducing stochasticity into the parameterized representations of subgrid processes in comprehensive weather and climate models has improved the skill of forecasts and has reduced systematic model error are surveyed.

### Stochastic Parameterization: Towards a new view of Weather and Climate Models

- Environmental Science
- 2015

AbstractThe last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic…

### Stochastic Climate Theory

- Computer Science
- 2016

This chapter provides a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism and expresses standard model reduction methods such as averaging and homogenization which eliminate the memory term.

### Global Climate Models Exploring the Reliability, Consistency, Limitations, Deficiencies, Uncertainties, and Methods of Global Climate Models in a Nonlinear and Chaotic Climate System

- Environmental Science
- 2018

The current climate change dialogue revolves around many different climate elements and their processes but central to the anthropogenic warming hypothesis (some call it a theory but I’m not going to…

### Predicting Climate Change Using Response Theory: Global Averages and Spatial Patterns

- Environmental Science
- 2015

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source…

### UvA-DARE (Digital Academic Repository) Stochastic climate theory

- Computer Science
- 2016

This chapter provides a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism and expresses standard model reduction methods such as averaging and homogenization which eliminate the memory term.

### Spatial Covariance Modeling for Stochastic Subgrid‐Scale Parameterizations Using Dynamic Mode Decomposition

- Environmental Science, PhysicsJournal of Advances in Modeling Earth Systems
- 2020

This paper presents a meta-modelling procedure that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of modeling subgrid scale processes through stochastic parameterizations.

### Data Assimilation in a Multi-Scale Model

- Environmental Science
- 2017

This work examines the role of unresolved scales and model error in data assimilation using the Ensemble Kalman filter with the two-level Lorenz-96 model as a conceptual prototype model of the multi-scale climate system and uses stochastic parameterization schemes to mitigate the model errors from the unresolved scales.

### Using regional scaling for temperature forecasts with the Stochastic Seasonal to Interannual Prediction System (StocSIPS)

- Environmental ScienceClimate Dynamics
- 2021

Over time scales between 10 days and 10–20 years—the macroweather regime—atmospheric fields, including the temperature, respect statistical scale symmetries, such as power-law correlations, that…

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