Jaya Bhatt Post-doctoral Fellow, Indian Institute of Science (IIS), Bengaluru, India

Title: The impact of global warming on probable maximum precipitation (PMP) estimates in India

Abstract: Design flood estimate derived from Probable Maximum Precipitation (PMP) is desired for design, planning and risk assessment of large/critical infrastructures such as dams and nuclear power plants, whose failure can cause catastrophic damage to the environment, ecology, life and property. PMP is deemed as the theoretical upper bound of the maximum precipitation that is physically possible over a given area for a specified duration. The validity of the stationarity assumption in PMP estimation is often debated as there is mounting evidence in recent literature indicating increase in the magnitude of extreme precipitation (even beyond stationary PMP estimates derived using conventional approaches) due to global warming. While the previous studies have focused on developing or modifying existing stationary approaches to yield non-stationary PMP estimates, there is a need to explore the consequences of relaxing the stationarity assumption in PMP estimation and detect the time when stationary PMP differs significantly from its non-stationary counterpart under climate change. This is investigated for Indian river basins by considering the conventional (stationarity) moisture maximization approach and its three non-stationarity variants. In this analysis, historical records of precipitation, surface temperature and relative humidity, and their future projections corresponding to four CMIP-6 SSPs were utilized. The results indicate that there is a considerable difference between non-stationary PMP estimates and their stationary counterparts. This difference is expected to become significant in the near-future for high-emission scenarios. The PMP estimates obtained from this analysis could be used to force a rainfall-runoff model to determine the increase in risk associated with the projected design flood at dams and other critical infrastructures in Indian river basins. The information is necessary to devise appropriate mitigation strategies at various hotspots in India.

Alvin Christopher Galang Varquez Associate Professor, Global Urban Climate Studies Lab, Institute of Science, Tokyo, Japan

Title: Development of IAM-informed 1-km global anthropogenic heat emission scenarios

Abstract: Anthropogenic heat emissions (AHE) represent an excess “unwanted” heat source in the near-surface energy balance attributed to humans’ overall energy consumption (e.g., electricity use, transportation, industrial activities, physical metabolism). Because it directly links cities and their atmospheric environment, AHE needs to be prescribed or modelled in climate models to represent urban areas adequately. While AHE datasets and models are becoming increasingly available, futuristic AHE projections remain limited. In this presentation, a workflow to construct futuristic AHE scenarios consistent with the CMIP6 scenarios is introduced. The workflow utilises an integrated assessment model (i.e., Global Change Analysis Model [GCAM]) and a “top-down” AHE model that builds on the AH4GUC approach, which utilises various satellite-derived and climate-modelled products of global coverage. GCAM, which is among the few IAMs used to quantify the Shared-Socioeconomic Pathways (SSP), was used to generate projections of regional-level energy consumption at 5-year intervals for each SSP. Spatial weights were calculated to obtain various components of AHE, such as transportation and industrial emissions. Spatial weights were calculated from 1-km population projections of Wang et al. (2022) adjusted with the VIIRS nighttime lights, VIIRS fire, daily temperature projections from NEX-GDDP-CMIP6, and road density data. Through this approach, CMIP6-consistent AHE projections may be obtained. Furthermore, GCAM may be used to introduce policies that will eventually lead to policy-driven AHE estimates. The current workflow will be released as an “open-source” toolbox for various scientific and practical applications.

Chris Brierley Professor, Department of Geography, University College London, United Kingdom

Title: The next phase of the Paleoclimate Modelling Intercomparison Project – PMIP7

Abstract: The Paleoclimate Modelling Intercomparison Project (PMIP) was launched in 1995 and has since closely followed the phases of the Coupled Model Intercomparison Project (CMIP) providing understanding of past climate states based on the latest Global Climate Models and evaluation of their capacity to represent climates very different from the recent one. The upcoming phase of it, PMIP7, is an established community MIP with a large selection of experiments focused at different climate states in the geologic past. In this talk, we will describe the rationale of including an idealised paleoclimate simulation, “abrupt-127k”, in the Fast Track set of experiments. This experiment starts from the Fast Track pre-industrial control experiment and then abruptly changes the astronomical parameters to those for 127,000 years ago (as well as some minor greenhouse gas changes). This will allow analyses of the sensitivity of the Arctic sea ice to conditions favouring its summer decrease or even collapse, and can be extended to become a last interglacial simulation (lig127k). Then we will also briefly describe the other experiments that will included in the community phase of PMIP7.