Climate dynamics

Abstract:

The World Climate Research Programme (WCRP) envisions a world “that uses sound, relevant, and timely climate science to ensure a more resilient present and sustainable future for humankind.” This bold vision requires the climate science community to provide actionable scientific information that meets the evolving needs of societies all over the world. To realize its vision, WCRP has created five Lighthouse Activities to generate international commitment and support to tackle some of the most pressing challenges in climate science today. The overarching goal of the Lighthouse Activity on Explaining and Predicting Earth System Change is to develop an integrated capability to understand, attribute, and predict annual to decadal changes in the Earth system, including capabilities for early warning of potential high impact changes and events. This article provides an overview of both the scientific challenges that must be addressed, and the research and other activities required to achieve this goal. The work is organized in three thematic areas: (i) monitoring and modeling Earth system change; (ii) integrated attribution, prediction, and projection; and (iii) assessment of current and future hazards. Also discussed are the benefits that the new capability will deliver. These include improved capabilities for early warning of impactful changes in the Earth system, more reliable assessments of meteorological hazard risks, and quantitative attribution statements to support the Global Annual to Decadal Climate Update and State of the Climate reports issued by the World Meteorological Organization.

Abstract:

Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.

Abstract:

<jats:title>Abstract</jats:title> <jats:p>Since the 1980s, external forcing from increasing greenhouse gases and declining aerosols has had a large e ect on European summer temperatures. The forcing may therefore provide an important source of forecast skill, even for timescales as short as a season ahead. However, the relative importance of such forcing for seasonal forecasts has thus far not been quanti ed, particularly on a regional scale. In this study, we investigate forcing-induced skill by comparing the temperature skill of a multi-model ensemble of operational seasonal predictions from the Copernicus Climate Change Service (C3S) archive to that of an uninitialised ensemble of CMIP6 projections for European summers spanning the years 1993-2016. We show that in some regions, such as northern Europe, summer 2m temperature skill is relatively limited and the forced trend provides the primary source of skill in current seasonal forecast models at 2-4 month lead-times. Over large parts of northern Europe, summer temperature skill is actually higher in uninitialised predictions and in runs with long lead-times than at short lead-times suggesting that there may be problems with the initialisation. Conversely, 2m temperature in southern Europe is generally well predicted by seasonal forecast models out to 3-5 months due to a combination of dynamical skill and a strong forced trend. These results indicate that even uninitialised predictions can provide useful information for seasonal forecasts of European summer temperatures and secondly that the ability of models to capture dynamical signals for northern European summers requires further research.</jats:p>