Causes of irregularities in trends of global mean surface temperature since the late 19th century

The time series of monthly global mean surface temperature (GST) since 1891 is successfully reconstructed from known natural and anthropogenic forcing factors, including internal climate variability, using a multiple regression technique. Comparisons are made with the performance of 40 CMIP5 models in predicting GST. The relative contributions of the various forcing factors to GST changes vary in time, but most of the warming since 1891 is found to be attributable to the net influence of increasing greenhouse gases and anthropogenic aerosols. Separate statistically independent analyses are also carried out for three periods of GST slowdown (1896–1910, 1941–1975, and 1998–2013 and subperiods); two periods of strong warming (1911–1940 and 1976–1997) are also analyzed. A reduction in total incident solar radiation forcing played a significant cooling role over 2001–2010. The only serious disagreements between the reconstructions and observations occur during the Second World War, especially in the period 1944–1945, when observed near-worldwide sea surface temperatures (SSTs) may be significantly warm-biased. In contrast, reconstructions of near-worldwide SSTs were rather warmer than those observed between about 1907 and 1910. However, the generally high reconstruction accuracy shows that known external and internal forcing factors explain all the main variations in GST between 1891 and 2015, allowing for our current understanding of their uncertainties. Accordingly, no important additional factors are needed to explain the two main warming and three main slowdown periods during this epoch

Decadal to multidecadal variability and the climate change background

Three prominent quasi-global patterns of variability and change are observed using the Met Office's sea surface temperature (SST) analysis and almost independent night marine air temperature analysis. The first is a global warming signal that is very highly correlated with global mean SST. The second is a decadal to multidecadal fluctuation with some geographical similarity to the El Niño–Southern Oscillation (ENSO). It is associated with the Pacific Decadal Oscillation (PDO), and its Pacific-wide manifestation has been termed the Interdecadal Pacific Oscillation (IPO). We present model investigations of the relationship between the IPO and ENSO. The third mode is an interhemispheric variation on multidecadal timescales which, in view of climate model experiments, is likely to be at least partly due to natural variations in the thermohaline circulation. Observed climatic impacts of this mode also appear in model simulations. Smaller-scale, regional atmospheric phenomena also affect climate on decadal to interdecadal timescales. We concentrate on one such mode, the winter North Atlantic Oscillation (NAO). This shows strong decadal to interdecadal variability and a correspondingly strong influence on surface climate variability which is largely additional to the effects of recent regional anthropogenic climate change. The winter NAO is likely influenced by both SST forcing and stratospheric variability. A full understanding of decadal changes in the NAO and European winter climate may require a detailed representation of the stratosphere that is hitherto missing in the major climate models used to study climate change

Rainfall variability at decadal and longer time scales: signal or noise?

Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Nino-Southern Oscillation (ENSO) frequency domain (2.5-8.0 yr), followed by a slightly weaker but highly significant decadal signal (9-13 yr), with some evidence of lesser but significant rainfall variability at interclecadal time scales (15-18 yr). Most of the rainfall variability significantly linked to frequencies tower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models

Global meteorological influences on the record UK rainfall of winter 2013-14

The UK experienced record average rainfall in winter 2013–14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean–atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013–14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013–14

The effect of temperature, gradient and load carriage on oxygen consumption, posture and gait characteristics

Purpose The purpose of this experiment was to evaluate the effect of load carriage in a range of temperatures to establish the interaction between cold exposure, the magnitude of change from unloaded to loaded walking and gradient. Methods Eleven participants (19-27 years) provided written informed consent before performing six randomly ordered walking trials in six temperatures (20°C, 10°C, 5°C, 0°C, -5°C and -10°C). Trials involved two unloaded walking bouts before and after loaded walking (18.2 kg) at 4 km.hr⁻¹, on 0% and 10% gradients in 4 minute bouts. Results The change in absolute oxygen consumption (V̇O₂) from the first unloaded bout to loaded walking was similar across all six temperatures. When repeating the second unloaded bout, V̇O₂ at both -5°C and-10°C was greater compared to the first. At -10°C, V̇O₂ was increased from 1.60 ± 0.30 L.min⁻¹ to 1.89 ± 0.51 L.min⁻¹. Regardless of temperature, gradient had a greater effect on V̇O₂ and heart rate (HR) than backpack load. HR was unaffected by temperature. Stride length (SL) decreased with decreasing temperature but trunk forward lean was greater during cold exposure. Conclusion Decreased ambient temperature did not influence the magnitude of change in V̇O₂ from unloaded to loaded walking. However, in cold temperatures, V̇O₂ was significantly higher than in warm conditions. The increased V̇O₂ in colder temperatures at the same exercise intensity is predicted to ultimately lead to earlier onset of fatigue and cessation of exercise. These results highlight the need to consider both appropriate clothing and fitness during cold exposure

Summer North Atlantic Oscillation (SNAO) variability on decadal to palaeoclimate time scales

The influence of the North Atlantic Oscillation (NAO) on climate in the North Atlantic region has been highlighted over the past few decades. Although most prominent during winter, the NAO is one of the few modes of variability that persist throughout the year, although there are systematic differences in its configuration through the seasons (Barnston and Livezey, 1987). This is related to seasonal variations of the North Atlantic jet stream which on average moves northwards in summer relative to winter. Consequently, the positive and negative nodes of the dipole NAO pattern have more northerly positions during summer. Until recently, most studies of the link between the NAO and climate have focused on winter, but after a thorough study of the summer NAO (SNAO) by Folland et al. (2009, henceforth F09), attention has also been directed to summer

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

High Values of the Arctic Amplification in the Early Decades of the 21st Century: Causes of Discrepancy by CMIP6 Models Between Observation and Simulation

Arctic Amplification (AA) in the first decade of the 21st century has reached values between 4 and 5, with a subsequent decrease to current values of about 3.6, while the value was from 2 to 3 during the twentieth century. The ensemble mean of the CMIP6 models has difficulty in reproducing the recently observed high values of the AA. In this report, we identify the main reason for this difficulty to be the CMIP6 models overestimate of the mean global temperature trend since about 1990. The largest values of the AA are observed in winter and spring. A sharp AA peak in 1987 spring was caused by a peak in the Arctic temperature trend occurring at the same time as a dip in the trend of mean global temperature. The winter AA has increased almost monotonically since 1990. Dividing the AA between the Arctic land and ocean areas shows that the ocean area makes a larger contribution to the AA. Our future projection of the AA suggests an increasing AA for about the next decade, followed by a slow decrease to about 3.5 in the 2050s

Annual Mean Arctic Amplification 1970–2020: Observed and Simulated by CMIP6 Climate Models

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the “best” CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step-like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time

Will 2024 be the first year that global temperature exceeds 1.5°C?

Global mean near surface temperature change is the key metric by which our warming climate is monitored and for which international climate policy is set. At the end of each year the Met Office issues a global mean temperature forecast for the coming year. Following on from the new record in 2023, we predict that 2024 will likely (76% chance) be a new record year with a 1-in-3 chance of exceeding 1.5°C above pre-industrial. Whilst a one-year temporary exceedance of 1.5°C would not constitute a breach of the Paris Agreement target, our forecast highlights how close we are now to this. Our 2024 forecast is primarily driven by the strong warming trend of +0.2°C/decade (1981–2023) and secondly by the lagged warming effect of a strong tropical Pacific El Niño event. We highlight that 2023 itself was significantly warmer than the Met Office DePreSys3 forecast, with much of this additional observed warming coming from the southern hemisphere, the cause of which requires further understanding. © 2024 Crown copyright. Atmospheric Science Letters published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. This article is published with the permission of the Controller of HMSO and the King's Printer for Scotland