Improving climate models and projections using observations - Assimilation Workshop Summary

The workshop, organized 25 years after the inception of the Estimating the Circulation and Climate of the Ocean (ECCO), was an effort to lay out the roadmap for future development of DA in support of climate modeling and climate knowledge improvements, or “climate DA”. The following is a summary of the workshop outcomes and recommendations arising to move the field of DA forward in the context of climate modeling. 

Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales.

Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach  those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty.

Workshop recommendations and future plans 

Enhancing and further developing DA methodologies, including parameter estimation approaches, ML tools, and model structure inference, will be essential to further exploit the availability of new climate modelling tools and high-resolution observations and to provide a detailed analysis of the state of the Earth. The field must now target a comprehensive approach towards coupled Earth system reanalysis and better future projections by improving the description of changes of energy, water, carbon and biogeochemical cycles in the system, and by allowing for more consistent analyses of climate variability and change, taking into account feedbacks and interactions.

To realize the full capabilities of climate DA we need to advance science and technologies for analyzing and merging global observations and Earth system model data in the context of Earth system DA.

Specific recommendations for required actions and funding that emerged from the workshop’s discussions will be summarized below under the headings of

1. Exploitation of Earth Observations;
2. Development of AD and ML Infrastructure;
3. Advances in Ensemble and Variational DA and ML Methods;
4. Model Improvements through Parameter Estimation;
5. Performing Earth System Reanalysis;
6. Understanding, Prediction, and Projection of Earth System Evolution.