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As most permanent observations in Antarctica started in the 1950s, understanding Antarctic climate variations throughout the twentieth century remains a challenge. To address this issue, the non-summer multi-decadal variability in pressure reconstructions poleward of 60°S is evaluated and assessed in conjunction with climate model simulations throughout the twentieth and early twenty-first centuries to understand historical atmospheric circulation variability over Antarctica. Austral autumn and winter seasons show broadly similar patterns, with negative anomalies in the early twentieth century (1905–1934), positive pressure anomalies in the middle twentieth century (1950–1980), and negative pressure anomalies in the most recent period (1984–2013), consistent with concurrent trends in the SAM index. In autumn, the anomalies are significant in the context of estimates of interannual variability and reconstruction uncertainty across most of the Antarctic continent, and the reconstructed patterns agree best with model-generated patterns when the simulation includes the forced response to tropical sea surface temperatures and external radiative forcing. In winter and spring, the reconstructed anomalies are less significant and are consistent with internal atmospheric variability alone. The specific role of tropical SST variability on pressure trends in these seasons is difficult to assess due to low reconstruction skill in the region of strongest tropical teleconnections, the large internal atmospheric variability, and uncertainty in the SST patterns themselves. Indirect estimates of pressure variability, whether through sea ice reconstructions, proxy records, or improved models and data assimilation schemes, will help to further constrain the magnitude of internal variability relative to the forced responses expected from SST trends and external radiative forcing. [ABSTRACT FROM AUTHOR]

A systematic comparison of El Niño Southern Oscillation reconstructions during the early to mid-nineteenth century is presented using a range of proxy and documentary sources. Reconstructions of the boreal winter Southern Oscillation Index (SOI) using data from ships’ logbooks presented in a companion paper are evaluated and compared to previous ENSO reconstructions. Comparisons between ENSO reconstructions and the instrumental SOI during a period of overlap (1876-1977) are made. These same proxy and documentary reconstructions are then compared to the logbook-based reconstructions, over 1815-1854. The logbook-based reconstructions compare best with a recent multi-proxy reconstruction that used signals taken from different teleconnection regions, and they have an improved agreement with multi-proxy records compared to a previous attempt to reconstruct the SOI from ships’ logbook data. The logbook-based and the multi-proxy reconstructions are found to capture El Niño events better than La Niña events, and East Pacific El Niño events better than Central Pacific El Niño events, thus suggesting a degree of bias in the historical reconstructions. These findings have important implications for future ENSO reconstructions, with a need for an increased understanding of the effects of different ENSO flavours for future reconstructions. [ABSTRACT FROM AUTHOR]

The meteorological information found within ships’ logbooks is a unique and fascinating source of data for historical climatology. This study uses wind observations from logbooks covering the period 1815 to 1854 to reconstruct an index of El Niño Southern Oscillation (ENSO) for boreal winter (DJF). Statistically-based reconstructions of the Southern Oscillation Index (SOI) are obtained using two methods: principal component regression (PCR) and composite-plus-scale (CPS). Calibration and validation are carried out over the modern period 1979–2014, assessing the relationship between re-gridded seasonal ERA-Interim reanalysis wind data and the instrumental SOI. The reconstruction skill of both the PCR and CPS methods is found to be high with reduction of error skill scores of 0.80 and 0.75, respectively. The relationships derived during the fitting period are then applied to the logbook wind data to reconstruct the historical SOI. We develop a new method to assess the sensitivity of the reconstructions to using a limited number of observations per season and find that the CPS method performs better than PCR with a limited number of observations. A difference in the distribution of wind force terms used by British and Dutch ships is found, and its impact on the reconstruction assessed. The logbook reconstructions agree well with a previous SOI reconstructed from Jakarta rain day counts, 1830–1850, adding robustness to our reconstructions. Comparisons to additional documentary and proxy data sources are provided in a companion paper. [ABSTRACT FROM AUTHOR]

ABSTRACT Polar front jet stream variability is responsible for instances of extreme weather and is crucial for regional climate change. The North Atlantic Polar Front jet stream is of particular significance to the heavily populated areas of western Europe and eastern North America as storm track variability, atmospheric modes of variability such as the North Atlantic Oscillation (NAO), temperature and rainfall are all intimately linked with jet stream changes. Although seasonal and interannual variability are often attributed to internal variability, there are several possible drivers of polar front jet stream changes that are reviewed in this study. Cryospheric effects from sea-ice extent and snow cover, oceanic effects from North Atlantic sea-surface temperatures and tropical influences such as the El-Niño Southern Oscillation, and stratospheric effects due to stratospheric circulation variability, solar variability, volcanic eruptions and the Quasi-Biennial Oscillation are all identified in the literature as factors that impact on the Atlantic Polar Front jet stream. These drivers of jet stream variability can oppose or reinforce one another, and there are some indications of possible nonlinear interactions between them. We also review the modelling of jet stream variability. While a consensus has now been reached that some observed drivers can be reproduced in climate models, we conclude that improved understanding of more recently identified drivers of the Atlantic extratropical jet stream is crucial for making progress in regional climate predictions on all timescales from months to decades ahead. [ABSTRACT FROM AUTHOR]

Atmospheric circulation in the oceans surrounding southern Africa plays an important role in determining its precipitation. This study uses wind information recorded in ships’ logbooks in order to statistically reconstruct summer and winter season precipitation at four southern African weather stations from 1796 to 1854. The reconstruction was obtained by first relating gridded 8° × 8° NCEP-DOE reanalysis seasonal mean wind vectors in the adjacent oceans to station precipitation. Over a 30-year calibration period (1979–2008), significant correlations between wind and precipitation at Cape Town, Mthatha and Royal National Park showed particular correspondence with those areas with the greatest concentration of logbook observations. Principal component regression was used to assess the potential of the dominant patterns of variability in the wind vectors as predictors to reconstruct precipitation. Cross-validation in the calibration period gave confidence that precipitation could be reconstructed at several stations across South Africa, meaning the regression relationships derived in the calibration period could be applied to the gridded seasonal mean logbook data to produce reconstructions of precipitation from 1796 to 1854. The reconstructions show a degree of correspondence with other regional data sets. For instance, the decade beginning in 1810 was the wettest of the period at Mthatha and Royal National Park, while the 1820s were the driest. At Cape Town, the 1820s were the wettest decade, with drier conditions observed in the 1830s. An index of west–east circulation in the summer season revealed correspondence with two documentary reconstructions of El Niño events and increased westerliness, although this did not always result in drier conditions. Attention is also drawn to the remaining 3000 yet to be digitised English East India Company logbooks which would provide a high-resolution picture of atmospheric circulation back to 1700 in the region under consideration. [ABSTRACT FROM PUBLISHER]

Correlation analysis of Greenland coastal weather station temperatures against the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO) indices for the summer season (when Ice Sheet melt and runoff occur) reveals significant temporal variations over the last 100 years, with periods of strongest correlations in the early twentieth century and during recent decades. During the mid-twentieth century, temperature changes at the stations are not significantly correlated with these circulation indices. Greenland coastal summer temperatures and Greenland Ice Sheet (GrIS) runoff since the 1970s are more strongly correlated with the Greenland Blocking Index (GBI) than with the NAO Index (NAOI), making the GBI a potentially useful predictor of ice-sheet mass balance changes. Our results show that the changing strength of NAOI-temperature relationships found in boreal winter also extends to summer over Greenland. Greenland temperatures and GrIS runoff over the last 30-40 years are significantly correlated with AMO variations, although they are more strongly correlated with GBI changes. GrIS melt extent is less significantly correlated with atmospheric and oceanic index changes than runoff, which we attribute to the latter being a more quantitative index of Ice Sheet response to climate change. Moreover, the four recent warm summers of 2007-2010 are characterised by unprecedented high pressure (since at least 1948-the start of the NCEP/NCAR reanalysis record) in the tropospheric column. Our results suggest complex and changing atmospheric forcing conditions that are not well captured using the NAO alone, and support theories of an oceanic influence on the recent increases in Greenland temperatures and GrIS runoff. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

• 0.11° and 0.44° RCMs are compared in four catchments using climate and flow indices. • The 0.11° simulations had superior skill in one catchment with complex topography. • The RCM flow simulation range is large for all catchments at both resolutions. • Bias correction improves the monthly but not the daily temporal variability. • Double Gamma quantile mapping outperforms the single Gamma quantile mapping. Regional Climate Models (RCMs) are an essential tool for analysing regional climate change impacts, such as hydrological change, as they provide simulations with more small-scale details and expected smaller errors than global climate models. There has been much effort to increase the spatial resolution and simulation skill of RCMs (i.e. through bias correction), yet the extent to which this improves the projection of hydrological change is unclear. Here, we evaluate the skill of five reanalysis-driven Euro-CORDEX RCMs in simulating precipitation and temperature, and as drivers of a hydrological model to simulate river flow on four UK catchments covering different physical, climatic and hydrological characteristics. We use a comprehensive range of evaluation indices for aspects of the distribution such as means and extremes, as well as for the structure of time series. We test whether high-resolution RCMs provide added value, through analysis of two RCM resolutions, 0.44° (50 km) and 0.11° (12.5 km), which are also bias-corrected employing the parametric quantile-mapping (QM) method, using the normal distribution for temperature, and the Gamma (GQM) and Double Gamma (DGQM) distributions for precipitation. The performance of these is considered for a range of meteorological variables and for the skill in simulating hydrological impacts at the catchment scale. In a small catchment with complex topography, the 0.11° RCMs clearly outperform their 0.44° version for precipitation and temperature, but when used in combination with the hydrological model, fail to capture the observed river flow distribution. In the other (larger) catchments, only one high-resolution RCM consistently outperforms its low-resolution version, implying that in general there is no added value from using the high-resolution RCMs in those catchments. Both resolutions produce river flow simulations that cover the observed flow duration curve, but the ensemble spread is large and therefore the simulations are difficult to use in practice. GQM decreases most of the simulation biases, except for extreme precipitation and high flows, which are further decreased by DGQM, which also reduces the multi-model simulation spread. Bias correction does not improve the representation of daily temporal variability measured by the Nash-Sutcliffe Efficiency Index, but it does for monthly variability, in particular when applying DGQM, which reduces most of the simulation biases. Overall, an increase in RCM resolution does not imply a better simulation of hydrology and bias-correction represents an alternative to ease decision-making. [ABSTRACT FROM AUTHOR]

Quantitative estimates of future Antarctic climate change are derived from numerical global climate models. Evaluation of the reliability of climate model projections involves many lines of evidence on past performance combined with knowledge of the processes that need to be represented. Routine model evaluation is mainly based on the modern observational period, which started with the establishment of a network of Antarctic weather stations in 1957/58. This period is too short to evaluate many fundamental aspects of the Antarctic and Southern Ocean climate system, such as decadal-to-century time-scale climate variability and trends. To help address this gap, we present a new evaluation of potential ways in which long-term observational and paleo-proxy reconstructions may be used, with a particular focus on improving projections. A wide range of data sources and time periods is included, ranging from ship observations of the early 20th century to ice core records spanning hundreds to hundreds of thousands of years to sediment records dating back 34 million years. We conclude that paleo-proxy records and long-term observational datasets are an underused resource in terms of strategies for improving Antarctic climate projections for the 21st century and beyond. We identify priorities and suggest next steps to addressing this. [ABSTRACT FROM AUTHOR]