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The uncertainty in the climate projection arising from various climate models is very common, and averaging such results poses a risk of underestimation or sometimes overestimation of impact in magnitude and frequency. Further, the performance of various climate models in monsoon degrades drastically due to the skewed nature. Under these circumstances, the performance of the climate model in the monsoon and non-monsoon periods is critical for accurate assessment. A multimodal approach has been used in the present work to quantify the uncertainty involved in the climate model using reliability ensemble averaging (REA). Based on AR6 of IPCC, the ensemble of 26 global climate models (GCMs) was used to evaluate the model performance and possible change in seasonal precipitation in four cities with distinct climate conditions, namely, Coimbatore, Rajkot, Udaipur, and Siliguri. The results show that non-monsoon and monsoon rainfall are expected to increase in all the regions. Most of the models perform poorly in simulating monsoon climate, especially in the monsoon period and are highly inconsistent spatially. The study also finds that the model performance is largely linked to the ratio of natural variability and mean. HIGHLIGHTS The paper discusses multimodal performance in climate change assessment in a monsoon-fed climate where the precipitation pattern is skewed.; Model bias for each climate model was quantified on a seasonal scale using Reliability Ensemble Averaging.; The performance of the GCMs largely depends on the ratio of natural variability to mean at regional level.; A reliable estimate of the change in climate variables is made using REA in CMIP6 framework for four climate scenarios, namely, SSP126, SSP245, SSP370, and SSP585.;

The IPCC's scientific assessment of the timing of net‐zero emissions and 2030 emission reduction targets consistent with limiting warming to 1.5°C or 2°C rests on large scenario databases. Updates to this assessment, such as between the IPCC's Special Report on Global Warming of 1.5°C (SR1.5) of warming and the Sixth Assessment Report (AR6), are the result of intertwined, sometimes opaque, factors. Here we isolate one factor: the Earth System Model emulators used to estimate the global warming implications of scenarios. We show that warming projections using AR6‐calibrated emulators are consistent, to within around 0.1°C, with projections made by the emulators used in SR1.5. The consistency is due to two almost compensating changes: the increase in assessed historical warming between SR1.5 (based on AR5) and AR6, and a reduction in projected warming due to improved agreement between the emulators' response to emissions and the assessment to which it is calibrated. Plain Language Summary: The IPCC's latest physical science report, the Working Group 1 Contribution to the Sixth Assessment Report (AR6), was released in August 2021. That report includes an update to the tools used to project the climate outcome of emission scenarios. Here we apply these newly calibrated tools, called earth system model emulators, to the set of scenarios assessed in the IPCC's Special Report on warming of 1.5°C (SR1.5). We find that two compensating changes lead to a remarkable consistency (peak warming projections within 0.1°C) between the projections made by the emulators used in SR1.5 and their descendants used in AR6. First, updates to the historical warming assessment since the SR1.5 (which was based on the IPCC's 2013 physical science report (AR5)) increase future warming projections. However, improved consistency between the emulators and the assessment of the underlying physics, particularly the short‐term warming response to emissions, lowers warming projections by an approximately equivalent amount. Our work reinforces the key messages from the IPCC: limiting warming to around 1.5°C is a great and urgent challenge, and it is up to us to decide whether we pull out all the stops to hold temperatures around 1.5°C or whether we sail on by. Key Points: Emulators used in IPCC Special Report on warming of 1.5°C and Sixth Assessment Report are remarkably consistent, despite their entirely new calibrationsThe consistency is due to two compensating factors: change in assessed historical warming and improvements to emulator calibration methods [ABSTRACT FROM AUTHOR]

The delivery of effective climate adaptation on the ground requires that the (climate adaptation) practitioner community be better incorporated into the process of producing, gathering and synthesizing evidence on adaptation as part of the Intergovernmental Panel on Climate Change (IPCC) process. This is not a recent issue and the co-production of knowledge, that goes beyond the traditional realms of 'science speaks to power', can only fully inform adequate and robust adaptation if it incorporates more practitioners, end-users, and those working at the interface of science, policy and practice. Through a high-level analysis of authors of the IPCC's Working Group II reports and special reports of AR6, we explore the evolution of representation of practitioners in IPCC WGII author teams from AR5 to AR6 and we find that practitioner representation has increased in AR6, however this remains low. We discuss how this low representation can affect readership and the potential to inform climate adaptation practice. As the IPCC evolves and reflects on its own practices, we seek to inform this process by providing further reflection on how the IPCC outputs can continue to be policy-relevant and maintain neutrality while ensuring accesibility and usability by climate adaptation practitioners. • Practitioner representation in IPCC WGII author teams remains low. • Adaptation practitioners provide invaluable knowledge on adaptation best practice. • Increased practitioners participation can help incorporate different perspectives. • The IPCC must prioritise diversity in authorship teams to inform climate action. [ABSTRACT FROM AUTHOR]

In this study, temperature changes and its concentration distribution in the period of 1984–2015 and 2015–2100 were investigated under CanESM5 climate model and SSP126, SSP245 and SSP585 scenarios. By confirming the correlation (more than 0.96) and the efficiency coefficient of the model (more than 0.82), the trend of temperature values using modified Mann-Kendall test and temperature concentration index (TCI) values in the sub-basins of Zayanderood Dam, Iran was estimated. The results indicated a non-significant upward trend in the base period (1984–2015) and a significant increasing trend at the level of 5% in the future period (2015–2100) produced by the mentioned scenarios. According to the slope of the trend line, an increase of 1.45, 4 and 9.8 degrees Celsius is predicted during the period of 2015–2100 according to the SSP126, SSP245 and SSP585 scenarios, respectively. The evaluation of changes in TCI values in the studied area showed that in the future period, the distribution of rainfall patterns will be regular and the uniformity of temperature distribution in the SSP585 scenario is more than in the other two scenarios. The results of the temperature pattern distribution in the study area showed that according to the upcoming climate changes and under the studied scenarios, it is expected that while the study area is warming in the future, the uniformity of the temperature distribution will also appear in the months of the year. This shows the reduction of temperature fluctuations and the uniformity of the average temperature in the months of the year. The reduction of TCI values shows the equalization of average temperature changes in the seasons. The results of the investigations showed that the combination of climate change scenarios with the TCI can well show the concentration and distribution of the temperature in different periods. [Display omitted] • Examining the different scenarios of the 6th IPCC such as SSP126, SSP245 and SSP585 based on temperature concentration index. • Investigate the temperature distribution pattern in the study area, considering climate changes. • Evaluation the trend of temperature and its concentration in the base period (1984–2015) and the future period (2015-2100). [ABSTRACT FROM AUTHOR]