The signatures of large-scale patterns of atmospheric variability in Antarctic surface temperatures

We investigate the impact that the four principal large-scale patterns of Southern Hemisphere (SH) atmospheric circulation variability have on Antarctic surface air temperature (SAT): (1) the southern baroclinic annular mode (BAM), which is associated with variations in extratropical storm amplitude; (2) the Southern Annular Mode (SAM), associated with latitudinal shifts in the midlatitude jet; and (3) the two Pacific-South American patterns (PSA1 and PSA2), which are characterized by wave trains originating in the tropical Pacific that extend across the SH extratropics. A key aspect is the use of 35 years of daily observations and reanalysis data, which affords a sufficiently large sample size to assess the signatures of the circulation patterns in both the mean and variability of daily mean SAT anomalies. The BAM exerts the weakest influence on Antarctic SAT, albeit it is still important over select regions. Consistent with previous studies, the SAM is shown to influence SAT across most of the continent throughout the year. The PSA1 also affects SAT across almost all of Antarctica. Regionally, both PSA patterns can exert a greater impact on SAT than the SAM but also have a significantly weaker influence during summer, reflecting the seasonality of the SH response to El Niño–Southern Oscillation. The SAM and PSA patterns have distinct signatures in daily SAT variance that are physically consistent with their signatures in extratropical dynamic variability. The broad-scale climate linkages identified here provide benchmarks for interpreting the Antarctic climate response to future changes in tropical sea surface temperatures, ozone recovery, and greenhouse gas increases

Evaluating the performance of key ERA‐Interim, ERA5 and ERA5‐Land climate variables across Siberia

Reanalysis datasets provide a continuous picture of the past climate for every point on Earth. They are especially useful in areas with few direct observations, such as Siberia. However, to ensure these datasets are sufficiently accurate they need to be validated against readings from meteorological stations. Here, we analyse how values of six climate variables—the minimum, mean and maximum 2‐metre air temperature, snow depth (SD), total precipitation and wind speed (WSP)—from three reanalysis datasets—ERA‐Interim, ERA5 and ERA5‐Land—compare against observations from 29 meteorological stations across Siberia and the Russian Far East on a daily timescale from 1979 to 2019. All three reanalyses produce values of the mean and maximum daily 2‐metre air temperature that are close to those observed, with the average absolute bias not exceeding 1.54°C. However, care should be taken for the minimum 2‐metre air temperature during the summer months—there are nine stations where correlation values are <0.60 due to inadequate night‐time cooling. The reanalysis values of SD are generally close to those observed after 1992, especially ERA5, when data from some of the meteorological stations began to be assimilated, but the reanalysis SD should be used with caution (if at all) before 1992 as the lack of assimilation leads to large overestimations. For low daily precipitation values the reanalyses provide good approximations, however they struggle to attain the extreme high values. Similarly, for the 10‐metre WSP; the reanalyses perform well with speeds up to 2.5 ms−1 but struggle with those above 5.0 ms−1. For these variables, we recommend using ERA5 over ERA‐Interim and ERA5‐Land in future research. ERA5 shows minor improvements over ERA‐Interim, and, despite an increased spatial resolution, there is no advantage to using ERA5‐Land

A2_1 The fast inverse square root in scientific computing

Scientific computing often requires the calculation of square roots - a process which is very expensive in terms of processing time compared to most other floating point operations. In this paper we examine the use of a faster but less accurate square root algorithm in scientific computing using N-body simulations as an example. The results show that the the speed increase afforded by the faster algorithm is not offset by the reduction in accuracy, and hence an alternate approach is suggested

A2_9 Trajectory of a falling Batman

p, li { white-space: pre-wrap; } The film Batman Begins shows the character of Batman gliding using a rigid form of his cape. This paper assesses the feasibility of such a glide and finds that while a reasonable distance could be travelled if gliding from a tall building, the speed at which Batman would be travelling would be too dangerous to stop without some method of slowing down

A2_5 Rolling Violet

In the film Charlie and the Chocolate Factory, the character Violet Beauregarde swells up and becomes a very oversized blueberry after chewing a non-perfected strip of chewing gum. She is then rolled out of the room by three Oompa-Loompas and through the door with the assistance of her mother. This paper investigates what force would be required to start Violet rolling and finds that it is likely to require four times the amount of Oompa-Loompas shown in the film

Decadal variability in the impact of atmospheric circulation patterns on the winter climate of northern Russia

The Arctic continues to warm at a much faster rate than the global average. One process contributing to ‘Arctic amplification’ involves changes in low-frequency macro-scale atmospheric circulation patterns and their consequent influence on regional climate. Here, using ERA5 reanalysis data, we examine decadal changes in the impact of seven such patterns on winter near-surface temperature (SAT) and precipitation (PPN) in northern Russia and calculate the temporal consistency of any statistically significant relationships. We demonstrate that the 40-year climatology hides considerable decadal variability in the spatial extent of such circulation pattern-climate relationships across the region, with few areas where their temporal consistency exceeds 60%. This is primarily a response to the pronounced decadal expansion/contraction and/or mobility of the circulation patterns’ centers of action. The North Atlantic Oscillation (NAO) is the dominant pattern (having the highest temporal consistency) affecting SAT west of the Urals. Further east, the Scandinavian (SCA), Polar/Eurasia (POL) and West Pacific patterns are successively the dominant pattern influencing SAT across the West Siberian Plains, Central Siberian Plateau and mountains of Far East Siberia, respectively. From west to east, the SCA, POL and Pacific North American patterns exert the most consistent decadal influence on PPN. The only temporally invariant significant decadal relationships occur between the NAO and SAT and the SCA and PPN in small areas of the North European Plain