Fang Li Professor, Institute of Atmospheric Physics, Chinese Academy of Sciences

Title: Global fire simulations in CMIP Earth system models

Abstract: Fire is the primary form of terrestrial ecosystem disturbance on a global scale and a crucial Earth system process, regulated by climate, vegetation characteristics, and human activities, while influencing climate mainly by changing the structure and functioning of terrestrial ecosystems and by emitting aerosols and trace gases. Most Earth system models (ESMs) now include fire modelling, with 19 models submitting fire-related outputs to the CMIP6. Here, we provide the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based reconstructions. Most CMIP6 models simulate global burned area and fire carbon emissions within observed ranges, capturing spatial patterns, seasonal cycles, and ENSO influences. Regional biomass burning (BB) emissions align with charcoal-based reconstructions, although regional mismatches exist, such as in South America and North America. CMIP6 models address critical CMIP5 issues, including underestimated global burned area and weak seasonal variability, but still fail to reproduce declines in burned area in recent decades and spring fire peak in NH mid-latitudes mainly due to underestimated anthropogenic fire suppression and crop fires, respectively. Improvements are also needed in estimating fire sensitivity to wet-dry conditions. Based on these findings, we present specific guidance for fire scheme development and suggest the post-processing methodology for generating reliable future BB emissions forcing data. Finally, we will introduce FireMIP in CMIP7, outlining its targets and protocol.

C A Rama Rao Principal Scientist, Central Research Institute for Dryland Agriculture, Indian Council of Agricultural Research

Title: Climate change risk assessment for adaptation planning in Indian agriculture

Abstract: Considering the importance of identifying hotspots of climate change risk and vulnerability for adaptation planning, this paper conducted a district level climate change risk and vulnerability assessment for India as per the framework suggested by the IPCC’s FifthAssessment Report. Climate change risk was assessed in terms of an aggregated index of exposure, vulnerability and hazard that were constructed by aggregating relevant indicators. Climate change projections obtained using CMIP5 climate models for the scenario RCP 4.5 for the period 2020–49 were used to represent hazard. The study categorised 193 districts into ‘very high’ or ‘high’ vulnerability many of which are in the states of Arunachal Pradesh, Chhattisgarh, Jharkhand, Karnataka, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, etc. One hundred and nine districts categorised as ‘very high’ risk are in the states of Bihar, Kerala, Odisha, Rajasthan, Uttar Pradesh, Uttarakhand, etc. and those categorised as ‘high’ risk districts are in Chhattisgarh, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan, Uttar Pradesh, etc. Adaptation planning and implementation may prioritise these districts with relatively higher risk and vulnerability and identify adaptation strategies based on the drivers of risk and vulnerability identified.

Iana Strigunova Post-doctoral researcher, Department of Earth Sciences, Uppsala University

Title: Mean state and day-to-day variability of planetary-scale barotropic Rossby waves during Eurasian heat extremes in CMIP models

Abstract: Reanalysis data indicates a clear relationship between Eurasian heatwaves and distinct patterns in large-scale atmospheric Rossby waves, particularly in their day-to-day variations. Accurately simulating these relationships remains a challenge for climate models. This study investigates the ability of several climate models to reproduce the mean and variability of planetary-scale Rossby waves associated with present-day and future Eurasian heatwaves. The analysis reveals that while the models generally capture the average structure of Rossby waves and the occurrence of heatwaves in historical simulations, they struggle to adequately reproduce the observed day-to-day variations. Furthermore, for the future climate scenario, the models show considerable uncertainty and a lack of agreement regarding the mean state of Rossby waves and their daily variability during projected heatwaves.