CL Campfire - If you can’t measure it, then reconstruct or model it to better understand past, present and future climates
Speakers, their presentation title and short abstract:
Dr. Mukund Rao
Topic: “Seven centuries of reconstructed Brahmaputra River discharge demonstrate underestimated high discharge and flood hazard frequency”)
Abstract: The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309–2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956–1986 C.E.) ranks amongst the driest of the past seven centuries (13th percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24–38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.
Prof. Stephanie Fiedler
Topic: “How can we better understand aerosol effects on climate?“
Abstract: Aerosols influence climate by affecting atmospheric radiation transfer and cloud properties. Anthropogenic aerosols cool the Earth, but the magnitude of their effects remains uncertain in the understanding of climate change. We will examine current estimates of anthropogenic aerosol radiative forcing for the present in the Coupled Model Intercomparison Project phase six (CMIP6), which contributed to the latest IPCC climate change assessment report. These estimates are based on model experiments conducted for the Radiative Forcing Model Intercomparison Project (RFMIP). Some of the model experiments employed a simplified aerosol representation to better understand how differences in model components other than the ones for aerosols contribute to uncertainty in forcing. The intercomparison of model results for the radiative forcing of anthropogenic aerosols at the process level allowed us to pinpoint opportunities to better constrain aerosol forcing in climate models.
Dr. Leonard Borchert
Topic: Using oceanic information for near-term prediction of European summer climate and extremes
Abstract: Long-term climate projections until the end of the 21st century primarily rely on representation of the greenhouse gas emission trajectories, while more short-term climate prediction for the next years needs to also capture internal climate variability. The climatic memory that enables near-term climate prediction commonly resides in the ocean. As atmospheric models struggle to transport oceanic information over land, the skill at predicting impactful variables is often limited. Here, we explore the direct use of ocean predictions for improving European summer temperature (EUST) predictions for up to 10 years ahead. Prediction skill for EUST can be improved using spring North Atlantic SST. In decadal prediction simulations from the CMIP6 archive, a link between predictable spring eastern North Atlantic SST variations and EUST enables coupling a statistical model to dynamical decadal spring SST predictions to produce skillful predictions of southern EUST 2-9 years ahead. We also show that this technique enables prediction of extremely warm EUST. These studies do not only shed light on the practical issue of predicting EUST, but also indicate teleconnection mechanisms that couple ocean and land temperature variability during summer.
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