Bayesian Conditional Cointegration

Cointegration is an important topic for time-series, and describes a relationship between two series in which a linear combination is stationary. Classically, the test for cointegration is based on a two stage process in which first the linear relation between the series is estimated by Ordinary Least Squares. Subsequently a unit root test is performed on the residuals. A well-known deficiency of this classical approach is that it can lead to erroneous conclusions about the presence of cointegration. As an alternative, we present a framework for estimating whether cointegration exists using Bayesian inference which is empirically superior to the classical approach. Finally, we apply our technique to model segmented cointegration in which cointegration may exist only for limited time. In contrast to previous approaches our model makes no restriction on the number of possible cointegration segments.Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012

An Antarctic assessment of IPCC AR4 coupled models

We assess 19 coupled models from the IPCC fourth assessment report archive from the simulation of the 20th century, based on the calculation of " skill scores.'' The models show a wide range of scores when assessed against Antarctic or global measures of large- scale circulation indices. Except for continental mass balance, the model average proves a more reliable estimate than that for any one model. Individual models show a very wide scatter in simulated Antarctic temperature trends over the past century; the large trend over the Antarctic peninsula in winter is not well represented, which makes it clear that whatever has been driving these trends is not well captured by many GCMs. Trends in temperature are clearly linked to the sea ice simulation, another variable that most models do not simulate well

Assessment of sea ice-atmosphere links in CMIP5 models

© 2016, Springer-Verlag Berlin Heidelberg. The Arctic is currently undergoing drastic changes in climate, largely thought to be due to so-called ‘Arctic amplification’, whereby local feedbacks enhance global warming. Recently, a number of observational and modelling studies have questioned what the implications of this change in Arctic sea ice extent might be for weather in Northern Hemisphere midlatitudes, and in particular whether recent extremely cold winters such as 2009/10 might be consistent with an influence from observed Arctic sea ice decline. However, the proposed mechanisms for these links have not been consistently demonstrated. In a uniquely comprehensive cross-season and cross-model study, we show that the CMIP5 models provide no support for a relationship between declining Arctic sea ice and a negative NAM, or between declining Barents–Kara sea ice and cold European temperatures. The lack of evidence for the proposed links is consistent with studies that report a low signal-to-noise ratio in these relationships. These results imply that, whilst links may exist between declining sea ice and extreme cold weather events in the Northern Hemisphere, the CMIP5 model experiments do not show this to be a leading order effect in the long-term. We argue that this is likely due to a combination of the limitations of the CMIP5 models and an indication of other important long-term influences on Northern Hemisphere climate

The importance of sea ice area biases in 21st century multimodel projections of Antarctic temperature and precipitation

This is the final version of the article. Available from the publisher via the DOI in this record.Climate models exhibit large biases in sea ice area (SIA) in their historical simulations. This study explores the impacts of these biases on multimodel uncertainty in Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble projections of 21st century change in Antarctic surface temperature, net precipitation, and SIA. The analysis is based on time slice climatologies in the Representative Concentration Pathway 8.5 future scenario (2070-2099) and historical (1970-1999) simulations across 37 different CMIP5 models. Projected changes in net precipitation, temperature, and SIA are found to be strongly associated with simulated historical mean SIA (e.g., cross-model correlations of r = 0.77, 0.71, and -0.85, respectively). Furthermore, historical SIA bias is found to have a large impact on the simulated ratio between net precipitation response and temperature response. This ratio is smaller in models with smaller-than-observed SIA. These strong emergent relationships on SIA bias could, if found to be physically robust, be exploited to give more precise climate projections for Antarctica.We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table S1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provided the coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The original CMIP5 data can be accessed through the ESGF data portals (see http://pcmdi-cmip.llnl.gov/cmip5/ availability.html). This study is part of the British Antarctic Survey Polar Science for Planet Earth Programme. It was funded by The UK Natural Environment Research Council (grant reference NE/K00445X/1). We would like to thank Paul Holland for his useful discussions and comments on an earlier version of this manuscript

Early‐to-late winter 20th century North Atlantic multidecadal atmospheric variability in observations, CMIP5 and CMIP6

The strong multi-decadal variability in North Atlantic (NA) winter atmospheric circulation is poorly understood and appears too weak in climate models. Recent research has shown peak atmospheric multi-decadal variability over the NA in late winter, particularly March, linked to Atlantic multi-decadal variability (AMV) of the ocean. Here a range of NA atmospheric circulation indices are assessed to provide a comprehensive picture of early-to-late winter low-frequency variability and its representation in the latest generation of climate models (Coupled Model Intercomparison Project Phase 6 (CMIP6)). As found for CMIP5, CMIP6 models exhibit too-weak multi-decadal NA atmospheric variability compared to reanalysis data over the period 1862-2005. Consistent with previous research, the eastern part of the NA westerly jet (U700NA) exhibits peak low-frequency variability in March. However, for NA-wide jet speed and the NAO, low-frequency variability and model-reanalysis discrepancies are strongest in January and February, associated with too-weak NA ocean-atmosphere linkages

A comparative study of wave forcing derived from the ERA-40 and ERA-interim reanalysis data sets

The Eliassen–Palm (E-P) flux divergences derived from ERA-40 and ERA-Interim show significant differences during northern winter. The discrepancies are marked by vertically alternating positive and negative anomalies at high latitudes and are manifested via a difference in the climatology. The magnitude of the discrepancies can be greater than the interannual variability in certain regions. These wave forcing discrepancies are only partially linked to differences in the residual circulation but they are evidently related to the static stability in the affected regions. Thus, the main cause of the discrepancies is most likely an imbalance of radiative heating. Two significant sudden changes are detected in the differences between the eddy heat fluxes derived from the two reanalyses. One of the changes may be linked to the bias corrections applied to the infrared radiances from the NOAA-12 High-Resolution Infrared Radiation Sounder in ERA-40, which is known to be contaminated by volcanic aerosol from the 1991 eruption of Mt. Pinatubo. The other change may be due in part to the use of uncorrected radiances from the NOAA-15 Advanced Microwave Sounding Units by ERA-Interim since 1998. These sudden changes have the potential to alter the wave forcing trends in the affected reanalysis, suggesting that extreme care is needed when one comes to extract trends from the highly derived wave forcing quantities

The establishment of histology in the curriculum of the London medical schools: 1826-1886

This thesis sets out the way in which histology became established in the curriculum of the London medical schools between 1826 and 1886. The text provides a very large number of references to original material, some of it previously unreported. Histology had its origins in continental Europe in the early years of the nineteenth century, in the work of Bichat. The introductory chapter examines how this was translated both as to language and as to practical experience into England. The role of the developing achromatic microscope is also briefly considered. The changes in medical education in London which fostered the teaching of 'general anatomy' (histology) are then described from primary sources in some detail, and with extensive necessary quotation. The establishment and development of medical departments and the appointment of key teachers was pivotal and is fully investigated, while the role of the medical press in infuencing change is also assessed. The teaching programme of each college is explored using evidence from surviving lecture notes, texts, diaries, calendars and correspondence. The changing requirements for qualification, and their influence on the examination system, which accompanied the growth of histological teaching, are discussed. In order to trace the incorporation of the cell theory, the growing understanding of the tissue concept, and the relationship between structure and function, into the teaching of histology, a case study of the histology of the liver has been pursued throughout the thesis. The development of knowledge of the histology of the liver has been traced through the large number of textbooks which were produced to support courses in histology. Throughout the period, steadily increasing specialisms from virtually all other aspects of the curriculum vied for inclusion, with more and more time being given over to new and diverse subjects. In this competition for time and resources histology eventually found a permanent place. The events leading to a formal requirement to teach practical histology are examined, and key people in these changes are identified. The effects of the legislation on texts, equipment, specialist accommodation, teaching skills, and time are assessed