The Climatic Impact-Driver Framework for Assessment of Risk-Relevant Climate Information.

The climate science and applications communities need a broad and demand-driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the "climatic impact-driver" (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as "physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions." We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co-developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.

Increased risk of near term global warming due to a recent AMOC weakening.

Some of the new generation CMIP6 models are characterised by a strong temperature increase in response to increasing greenhouse gases concentration1. At first glance, these models seem less consistent with the temperature warming observed over the last decades. Here, we investigate this issue through the prism of low-frequency internal variability by comparing with observations an ensemble of 32 historical simulations performed with the IPSL-CM6A-LR model, characterized by a rather large climate sensitivity. We show that members with the smallest rates of global warming over the past 6-7 decades are also those with a large internally-driven weakening of the Atlantic Meridional Overturning Circulation (AMOC). This subset of members also matches several AMOC observational fingerprints, which are in line with such a weakening. This suggests that internal variability from the Atlantic Ocean may have dampened the magnitude of global warming over the historical era. Taking into account this AMOC weakening over the past decades means that it will be harder to avoid crossing the 2 °C warming threshold.

Multiyear predictability of tropical marine productivity.

With the emergence of decadal predictability simulations, research toward forecasting variations of the climate system now covers a large range of timescales. However, assessment of the capacity to predict natural variations of relevant biogeochemical variables like carbon fluxes, pH, or marine primary productivity remains unexplored. Among these, the net primary productivity (NPP) is of particular relevance in a forecasting perspective. Indeed, in regions like the tropical Pacific (30°N-30°S), NPP exhibits natural fluctuations at interannual to decadal timescales that have large impacts on marine ecosystems and fisheries. Here, we investigate predictions of NPP variations over the last decades (i.e., from 1997 to 2011) with an Earth system model within the tropical Pacific. Results suggest a predictive skill for NPP of 3 y, which is higher than that of sea surface temperature (1 y). We attribute the higher predictability of NPP to the poleward advection of nutrient anomalies (nitrate and iron), which sustain fluctuations in phytoplankton productivity over several years. These results open previously unidentified perspectives to the development of science-based management approaches to marine resources relying on integrated physical-biogeochemical forecasting systems.