Tim Woollings

Abstract:

Climate model hindcasts are analyzed to reveal the impacts of the North Atlantic Oscillation (NAO) on the North Atlantic subpolar ocean, which exhibits variability on seasonal to decadal timescales. The ocean response to a single winter NAO event is separated into fast and slow responses. The fast response persists over winter–spring seasons, during which wind stress and heat flux anomalies associated with the NAO rapidly modify ocean temperatures via changes in Ekman transport and ocean-atmosphere heat exchanges. The slow response persists for 3–4 years, during which overturning and gyre circulations redistribute opposing-signed surface temperature anomalies created by the NAO. This redistribution modifies east-west temperature contrasts altering the meridional heat transport associated with gyres and changing the strength of the overturning circulation. Hence, the fast and slow responses lead to opposing-signed subpolar temperature anomalies in time from the competing effects of local forcing and horizontal heat convergence.

Abstract:

The physical understanding and timely prediction of extreme weather events are of enormous importance to society due to their associated impacts. In this article, we highlight several types of weather extremes occurring in Europe in connection with a particular atmospheric flow pattern, known as atmospheric blocking. This flow pattern effectively blocks the prevailing westerly large-scale atmospheric flow, resulting in changing flow anomalies in the vicinity of the blocking system and persistent conditions in the immediate region of its occurrence. Blocking systems are long-lasting, quasi-stationary and self-sustaining systems that occur frequently over certain regions. Their presence and characteristics have an impact on the predictability of weather extremes and can thus be used as potential indicators. The phasing between the surface and the upper-level blocking anomalies is of major importance for the development of the extreme event. In summer, heat waves and droughts form below the blocking anticyclone primarily via large-scale subsidence that leads to cloud-free skies and, thus, persistent shortwave radiative warming of the ground. In winter, cold waves that occur during atmospheric blocking are normally observed downstream or south of these systems. Here, meridional advection of cold air masses from higher latitudes plays a decisive role. Depending on their location, blocking systems also may lead to a shift in the storm track, which influences the occurrence of wind and precipitation anomalies. Due to these multifaceted linkages, compound events are often observed in conjunction with blocking conditions. In addition to the aforementioned relations, the predictability of extreme events associated with blocking and links to climate change are assessed. Finally, current knowledge gaps and pertinent research perspectives for the future are discussed.

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:

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.