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Abstract:

Significant challenges in modelling clouds render observational data an important resource for quantifying cloud feedbacks. Here, we use data from satellite and reanalysis products to estimate tropical cloud feedbacks over a wide range of circulation regimes. We use two distinct methods, month-to-month variability and linear multi-decadal trends, to gain insight as to whether short-term feedbacks are representative of feedbacks associated with CO₂-induced warming. We also investigate the extent to which cloud feedbacks are circulation-driven by decomposing the relative contributions of circulation versus thermodynamic changes to the feedbacks in each regime. The influence of thermodynamic processes on cloud feedbacks has been shown to be dominant at large spatial scales in global climate models (Byrne and Schneider, 2018), but it is unclear whether observed feedbacks are consistent with model behaviour. A particular focus of our analysis is the effect of circulation on the tropical anvil cloud area feedback in ascending regions, as this feedback constitutes the largest source of uncertainty in the overall cloud feedback yet is relatively understudied (Sherwood et al. 2020).   

References:

• Byrne, M. P., & Schneider, T. (2018). Atmospheric dynamics feedback: Concept, simulations, and climate implications. Journal of Climate, 31(8), 3249-3264.
• Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., ... & Zelinka, M. D. (2020). An assessment of Earth's climate sensitivity using multiple lines of evidence. Reviews of Geophysics, 58(4), e2019RG000678.

Abstract:

We employ multi-ensemble Met Office Decadal Prediction System hindcasts to analyse the impact of atmospheric winds and North Atlantic Oscillation (NAO) phases on the overturning circulation in the North Atlantic Ocean. A positive NAO phase is generally associated with an anomalously strong and/or northward shifted jet stream in the North Atlantic, and the vice-versa is true for a negative NAO phase. As a consequence of relatively strong winds, oceans tend to lose more heat to the atmosphere in winter in many parts of the subpolar North Atlantic Ocean. This process is expected to create negative anomalies in sea surface temperature and generate more dense water on the ocean surface at high latitudes resulting in a strengthening in the overturning circulation. Here, we examine the sensitivity of the overturning circulation to NAO phases in multi-ensemble decadal hindcasts to understand how the interior ocean responds to different NAO phases. For this purpose, we analyse the changes in east-west density contrasts, upper ocean heat content, mixed-layer depth, meridional heat and salt transport in different oceanic regions, i.e. Labrador Sea, Irminger Sea and Nordic Seas. In particular, we perform a linear regression analysis for the above-mentioned diagnostics and NAO indices to assess how sensitive the upper ocean is to changes in the atmospheric state. We further compare our results against reanalysis data and in-situ observations.

Abstract:

The leading mode of wintertime atmospheric variability over the North Atlantic-North Eurasia sector is dominated by the North Atlantic Oscillation (NAO) and accounts for more than one third of the total variability. This study explores the influences of the leading mode on decadal climate variability of Northern Eurasia. We focus on the little-explored decadal covariations of surface air temperature (SAT), snowfall, snow water equivalent (SWE) and snow cover over the region, using extensive model output from the Coupled Model Intercomparison Project sixth phase. Recent decadal trends (−0.92σ per decade) in the leading mode identified, are found to be largely a manifestation of internal climate variability (at least two thirds from the most conservative estimate). These internally-generated decadal trends strongly contributed to recent trends in SAT, snowfall, SWE and snow cover over Eurasia. External forcings should have played a minor role over Eurasia as they usually suggest opposite decadal trends to those observed. An exception is found for snowfall and SWE in east Eurasia, for which external forcings may have driven a large part of the recent upward trends, equally as important as the NAO-dominated mode. This points to a complex interplay between internally-generated and externally-forced climate variability over Northern Eurasia. Model discrepancies are identified in reproducing the linkages between the leading mode and the Eurasian surface climate variability. The internally-generated variability of this leading mode thus represents a large source of uncertainty in future decadal climate projections over Eurasia and, due to the memory effects of snow, also in modelling springtime climate variability.

Abstract:

What: Approximately 40 participants – with expertise spanning energy, computer science, weather and climate research -– joined a week-long Energy-Climate data “hackathon” in June 2021. It was hosted by the Universities of 91̽�� and Reading in partnership with the UK Met Office as part of a series of themed hackathons 91̽��ed by the Met Office and held in the run-up to the UN COP26 conference. Six projects were initiated and developed by teams over the course of the week, 91̽��ed by access to state-of-the-art computational resources on the UK’s CEDA-JASMIN service, and stimulated by keynote speakers from industry and academia. The hackathon concluded with teams presenting their outputs to a panel of invited experts. Several teams plan to build on their hackathon success in publications, ongoing collaborations and research funding proposals. When: 18th May (half-day “scoping” event) & 21st-25th June 2021 (main hackathon) Where: Online via Zoom and Gather.Town, 91̽��ed by Slack communication channels Affiliations: Initiated by: 91̽�� Dr Sarah Sparrow, Professor David Wallom, Professor Tim Woollings, & University of Reading Professor David Brayshaw, Dr Hannah Bloomfield, In partnership with the Met Office, the UK’s national meteorological service, and with 91̽�� from the UK’s CEDA-JASMIN service and Gurobi optimization software.