Tim Woollings

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 Oxford and Reading in partnership with the UK Met Office as part of a series of themed hackathons supported 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, supported 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, supported by Slack communication channels Affiliations: Initiated by: University of Oxford 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 support from the UK’s CEDA-JASMIN service and Gurobi optimization software.

Abstract:

The East Asian summer jet (EASJ) is an important component of the East Asian summer monsoon system and its variability is correlated with precipitation and surface temperature variations over this region. Whilst many studies have considered the interannual variability of the EASJ, less is known about variations on a decadal time-scale. This study investigates the relationship between decadal EASJ variability and sea surface temperatures (SSTs) and thus the potential predictability that SSTs may provide. Given the relatively short observational record, we make use of the long pre-industrial control simulations in the Coupled Model Intercomparison Project phase 6 (CMIP6) in addition to a large ensemble of atmosphere-only experiments, forced with random SST patterns. We then create an SST-based reconstruction of the dominant modes of EASJ variability in the CMIP6 models, finding a median EASJ–reconstruction correlation for the dominant mode of 0.43. Much of the skill in the reconstruction arises from variations in Pacific SSTs, however the tropical Atlantic also makes a significant contribution. These findings suggest the potential for multi-year predictions of the EASJ, provided that skilful SST forecasts are available.

Abstract:

Internal climate variability will play a major role in determining change on regional scales under global warming. In the extratropics, large-scale atmospheric circulation is responsible for much of observed regional climate variability, from seasonal to multidecadal timescales. However, the extratropical circulation variability on multidecadal timescales is systematically weaker in coupled climate models. Here we show that projections of future extratropical climate from coupled model simulations significantly underestimate the projected uncertainty range originating from large-scale atmospheric circulation variability. Using observational datasets and large ensembles of coupled climate models, we produce synthetic ensemble projections constrained to have variability consistent with the large-scale atmospheric circulation in observations. Compared to the raw model projections, the synthetic observationally-constrained projections exhibit an increased uncertainty in projected 21st century temperature and precipitation changes across much of the Northern extratropics. This increased uncertainty is also associated with an increase of the projected occurrence of future extreme seasons.