A multimodel assessment of the influence of regional anthropogenic emission reductions on aerosol direct radiative forcing and the role of intercontinental transport

In this study, we assess changes of aerosol optical depth (AOD) and direct radiative forcing (DRF) in response to the reduction of anthropogenic emissions in four major pollution regions in the Northern Hemisphere by using results from nine global models in the framework of the Hemispheric Transport of Air Pollution (HTAP). DRF at top of atmosphere (TOA) and surface is estimated based on AOD results from the HTAP models and AOD-normalized DRF (NDRF) from a chemical transport model. The multimodel results show that, on average, a 20% reduction of anthropogenic emissions in North America, Europe, East Asia, and South Asia lowers the global mean AOD (all-sky TOA DRF) by 9.2% (9.0%), 3.5% (3.0%), and 9.4% (10.0%) for sulfate, particulate organic matter (POM), and black carbon (BC), respectively. Global annual average TOA all-sky forcing efficiency relative to particle or gaseous precursor emissions from the four regions (expressed as multimodel mean ± one standard deviation) is  ±3.5 ±0.8,  ±4.0 ±1.7, and 29.5 ±18.1mWm ±2 per Tg for sulfate (relative to SO2), POM, and BC, respectively. The impacts of the regional emission reductions on AOD and DRF extend well beyond the source regions because of intercontinental transport (ICT). On an annual basis, ICT accounts for 11 ±5% to 31 ±9% of AOD and DRF in a receptor region at continental or subcontinental scale, with domestic emissions accounting for the remainder, depending on regions and species. For sulfate AOD, the largest ICT contribution of 31 ±9% occurs in South Asia, which is dominated by the emissions from Europe. For BC AOD, the largest ICT contribution of 28 ±18% occurs in North America, which is dominated by the emissions from East Asia. The large spreads among models highlight the need to improve aerosol processes in models, and evaluate and constrain models with observations.

Absence of association between the INSIG2 gene polymorphism (rs7566605) and obesity in the European Youth Heart Study (EYHS)

The first genome-wide association study for BMI identified a polymorphism, rs7566605, 10 kb upstream of the insulin-induced gene 2 (INSIG2) transcription start site, as the most significantly associated variant in children and adults. Subsequent studies, however, showed inconsistent association of this polymorphism with obesity traits. This polymorphism has been hypothesized to alter INSIG2 expression leading to inhibition of fatty acid and cholesterol synthesis. Hence, we investigated the association of the INSIG2 rs7566605 polymorphism with obesity- and lipid-related traits in Danish and Estonian children (930 boys and 1,073 girls) from the European Youth Heart Study (EYHS), a school-based, cross-sectional study of pre- and early pubertal children. The association between the polymorphism and obesity traits was tested using additive and recessive models adjusted for age, age-group, gender, maturity and country. Interactions were tested by including the interaction terms in the model. Despite having sufficient power (98%) to detect the previously reported effect size for association with BMI, we did not find significant effects of rs7566605 on BMI (additive, P = 0.68; recessive, P = 0.24). Accordingly, the polymorphism was not associated with overweight (P = 0.87) or obesity (P = 0.34). We also did not find association with waist circumference (WC), sum of four skinfolds, or with total cholesterol, triglycerides, low-density lipoprotein, or high-density lipoprotein. There were no gender-specific (P = 0.55), age-group-specific (P = 0.63) or country-specific (P = 0.56) effects. There was also no evidence of interaction between genotype and physical activity (P = 0.95). Despite an adequately powered study, our findings suggest that rs7566605 is not associated with obesity-related traits and lipids in the EYHS.

Updated radiative forcing estimates of 65 halocarbons and nonmethane hydrocarbons

The direct radiative forcing of 65 chlorofluorocarbons, hydrochlorofluorocarbons, hydrofluorocarbons, hydrofluoroethers, halons, iodoalkanes, chloroalkanes, bromoalkanes, perfluorocarbons and nonmethane hydrocarbons has been evaluated using a consistent set of infrared absorption cross sections. For the radiative transfer models, both line-by-line and random band model approaches were employed for each gas. The line-by-line model was first validated against measurements taken by the Airborne Research Interferometer Evaluation System (ARIES) of the U.K. Meteorological Office; the computed spectrally integrated radiance of agreed to within 2% with experimental measurements. Three model atmospheres, derived from a three-dimensional climatology, were used in the radiative forcing calculations to more accurately represent hemispheric differences in water vapor, ozone concentrations, and cloud cover. Instantaneous, clear-sky radiative forcing values calculated by the line-by-line and band models were in close agreement. The band model values were subsequently modified to ensure exact agreement with the line-by-line model values. Calibrated band model radiative forcing values, for atmospheric profiles with clouds and using stratospheric adjustment, are reported and compared with previous literature values. Fourteen of the 65 molecules have forcings that differ by more than 15% from those in the World Meteorological Organization [1999] compilation. Eleven of the molecules have not been reported previously. The 65-molecule data set reported here is the most comprehensive and consistent database yet available to evaluate the relative impact of halocarbons and hydrocarbons on climate change.

Modelling methodology and forecast failure

We analyse by simulation the impact of model-selection strategies (sometimes called pre-testing) on forecast performance in both constant-and non-constant-parameter processes. Restricted, unrestricted and selected models are compared when either of the first two might generate the data. We find little evidence that strategies such as general-to-specific induce significant over-fitting, or thereby cause forecast-failure rejection rates to greatly exceed nominal sizes. Parameter non-constancies put a premium on correct specification, but in general, model-selection effects appear to be relatively small, and progressive research is able to detect the mis-specifications.

Tropical palaeoclimates at the Last Glacial Maximum: comparison of Palaeoclimate Modeling Intercomparison Project (PMIP)simulations and paleodata.

Seventeen simulations of the Last Glacial Maximum (LGM) climate have been performed using atmospheric general circulation models (AGCM) in the framework of the Paleoclimate Modeling Intercomparison Project (PMIP). These simulations use the boundary conditions for CO2, insolation and ice-sheets; surface temperatures (SSTs) are either (a) prescribed using CLIMAP data set (eight models) or (b) computed by coupling the AGCM with a slab ocean (nine models). The present-day (PD) tropical climate is correctly depicted by all the models, except the coarser resolution models, and the simulated geographical distribution of annual mean temperature is in good agreement with climatology. Tropical cooling at the LGM is less than at middle and high latitudes, but greatly exceeds the PD temperature variability. The LGM simulations with prescribed SSTs underestimate the observed temperature changes except over equatorial Africa where the models produce a temperature decrease consistent with the data. Our results confirm previous analyses showing that CLIMAP (1981) SSTs only produce a weak terrestrial cooling. When SSTs are computed, the models depict a cooling over the Pacific and Indian oceans in contrast with CLIMAP and most models produce cooler temperatures over land. Moreover four of the nine simulations, produce a cooling in good agreement with terrestrial data. Two of these model results over ocean are consistent with new SST reconstructions whereas two models simulate a homogeneous cooling. Finally, the LGM aridity inferred for most of the tropics from the data, is globally reproduced by the models with a strong underestimation for models using computed SSTs.

Understanding and representing atmospheric convection across scales: recommendations from the meeting held at Dartington Hall, Devon, UK, 28–30 January 2013

As weather and climate models move toward higher resolution, there is growing excitement about potential future improvements in the understanding and prediction of atmospheric convection and its interaction with larger-scale phenomena. A meeting in January 2013 in Dartington, Devon was convened to address the best way to maximise these improvements, specifically in a UK context but with international relevance. Specific recommendations included increased convective-scale observations, high-resolution virtual laboratories, and a system of parameterization test beds with a range of complexities. The main recommendation was to facilitate the development of physically based convective parameterizations that are scale-aware, non-local, non-equilibrium, and stochastic.

What does “retrofit” mean, and how can we scale up action in the UK sector?

Purpose – Progress in retrofitting the UK's commercial properties continues to be slow and fragmented. New research from the UK and USA suggests that radical changes are needed to drive large-scale retrofitting, and that new and innovative models of financing can create new opportunities. The purpose of this paper is to offer insights into the terminology of retrofit and the changes in UK policy and practice that are needed to scale up activity in the sector. Design/methodology/approach – The paper reviews and synthesises key published research into commercial property retrofitting in the UK and USA and also draws on policy and practice from the EU and Australia. Findings – The paper provides a definition of “retrofit”, and compares and contrasts this with “refurbishment” and “renovation” in an international context. The paper summarises key findings from recent research and suggests that there are a number of policy and practice measures which need to be implemented in the UK for commercial retrofitting to succeed at scale. These include improved funding vehicles for retrofit; better transparency in actual energy performance; and consistency in measurement, verification and assessment standards. Practical implications – Policy and practice in the UK needs to change if large-scale commercial property retrofit is to be rolled out successfully. This requires mandatory legislation underpinned by incentives and penalties for non-compliance. Originality/value – This paper synthesises recent research to provide a set of policy and practice recommendations which draw on international experience, and can assist on implementation in the UK.

From Hippocrates to commodities: three models of NHS governance

A series of inquiries and reports suggest considerable failings in the care provided to some patients in the NHS. Although the Bristol Inquiry report of 2001 led to the creation of many new regulatory bodies to supervise the NHS, they have never enjoyed consistent support from government and the Mid Staffordshire Inquiry in 2013 suggests they made little difference. Why do some parts of the NHS disregard patients’ interests and how we should we respond to the challenge? The following discusses the evolution of approaches to NHS governance through the Hippocratic, Managerial and Commercial models, and assesses their risks and benefits. Apart from the ethical imperative, the need for effective governance is driven both by the growth in information available to the public and the resources wasted by ineffective systems of care. Appropriate solutions depend on an understanding of the perverse incentives inherent in each model and the need for greater sensitivity to the voices of patients and the public.

Urban integrated meteorological observations: practice and experience in Shanghai, China

Observations of atmospheric conditions and processes in citiesare fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality and climate models, and providing key information for city end-users (e.g. decision-makers, stakeholders, public). In this paper, Shanghai's urban integrated meteorological observation network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being: multi- purpose (e.g. forecast, research, service), multi-function (high impact weather, city climate, special end-users), multi-scale (e.g. macro/meso-, urban-, neighborhood, street canyon), multi-variable (e.g. thermal, dynamic, chemical, bio-meteorological, ecological), and multi- platform (e.g. radar, wind profiler, ground-based, satellite based, in-situ observation/ sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments; to identify data gaps based on science and user driven requirements; and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

Optical properties of Saharan dust aerosol and contribution from the coarse mode as measured during the Fennec 2011 aircraft campaign

New in-situ aircraft measurements of Saharan dust originating from Mali, Mauritania and Algeria taken during the Fennec 2011 aircraft campaign over a remote part of the Sahara Desert are presented. Size distributions extending to 300 μm are shown, representing measurements extending further into the coarse mode than previously published for airborne Saharan dust. A significant coarse mode was present in the size distribution measurements with effective diameter (deff) from 2.3 to 19.4 μm and coarse mode volume median diameter (dvc) from 5.8 to 45.3 μm. The mean size distribution had a larger relative proportion of coarse mode particles than previous aircraft measurements. The largest particles (with deff >12 μm, or dvc >25 μm) were only encountered within 1 km of the ground. Number concentration, mass loading and extinction coefficient showed inverse relationships to dust age since uplift. Dust particle size showed a weak exponential relationship to dust age. Two cases of freshly uplifted dust showed quite different characteristics of size distribution and number concentration. Single Scattering Albed (SSA) values at 550 nm calculated from the measured size distributions revealed high absorption ranging from 0.70 to 0.97 depending on the refractive index. SSA was found to be strongly related to deff. New instrumentation revealed that direct measurements, behind Rosemount inlets, overestimate SSA by up to 0.11 when deff is greater than 2 μm. This is caused by aircraft inlet inefficiencies and sampling losses. Previous measurements of SSA from aircraft measurements may also have been overestimates for this reason. Radiative transfer calculations indicate that the range of SSAs during Fennec 2011 can lead to underestimates in shortwave atmospheric heating rates by 2.0 to 3.0 times if the coarse mode is neglected. This will have an impact on Saharan atmospheric dynamics and circulation,which should be taken into account by numerical weather prediction and climate models.

Centennial changes in solar activity and the response of galactic cosmic rays

There is a growing consensus that the eleven year modulation of galactic cosmic rays (GCRs) resulting from solar activity is related to interplanetary propagating diffusive barriers (PDBs). The source of these PDBs is not well understood and numerical models describing GCR modulation simulate their effect by scaling the diffusion tensor to the interplanetary magnetic field strength (IMF). The implications of a century-scale change in solar wind speed and open solar flux, for numerical modelling of GCR modulation and the reconstruction of GCR variations over the last hundred years are discussed. The dominant role of the solar non-axisymmetric magnetic field in both forcing longitudinal solar wind speed fluctuations at solar maximum and in increasing the IMF is discussed in the context of a long-term rise in the open solar magnetic flux.

Sources, sinks, and transatlantic transport of North African dust aerosol: a multimodel analysis and comparison with remote sensing data

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models.

K-Surfer: a KNIME extension for the management and analysis of Human brain MRI FreeSurfer/FSL data

Human brain imaging techniques, such as Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI), have been established as scientific and diagnostic tools and their adoption is growing in popularity. Statistical methods, machine learning and data mining algorithms have successfully been adopted to extract predictive and descriptive models from neuroimage data. However, the knowledge discovery process typically requires also the adoption of pre-processing, post-processing and visualisation techniques in complex data workflows. Currently, a main problem for the integrated preprocessing and mining of MRI data is the lack of comprehensive platforms able to avoid the manual invocation of preprocessing and mining tools, that yields to an error-prone and inefficient process. In this work we present K-Surfer, a novel plug-in of the Konstanz Information Miner (KNIME) workbench, that automatizes the preprocessing of brain images and leverages the mining capabilities of KNIME in an integrated way. K-Surfer supports the importing, filtering, merging and pre-processing of neuroimage data from FreeSurfer, a tool for human brain MRI feature extraction and interpretation. K-Surfer automatizes the steps for importing FreeSurfer data, reducing time costs, eliminating human errors and enabling the design of complex analytics workflow for neuroimage data by leveraging the rich functionalities available in the KNIME workbench.

Vertical structure and physical processes of the Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic heating and moistening

Many theories for the Madden-Julian oscillation (MJO) focus on diabatic processes, particularly the evolution of vertical heating and moistening. Poor MJO performance in weather and climate models is often blamed on biases in these processes and their interactions with the large-scale circulation. We introduce one of three components of a model-evaluation project, which aims to connect MJO fidelity in models to their representations of several physical processes, focusing on diabatic heating and moistening. This component consists of 20-day hindcasts, initialised daily during two MJO events in winter 2009-10. The 13 models exhibit a range of skill: several have accurate forecasts to 20 days' lead, while others perform similarly to statistical models (8-11 days). Models that maintain the observed MJO amplitude accurately predict propagation, but not vice versa. We find no link between hindcast fidelity and the precipitation-moisture relationship, in contrast to other recent studies. There is also no relationship between models' performance and the evolution of their diabatic-heating profiles with rain rate. A more robust association emerges between models' fidelity and net moistening: the highest-skill models show a clear transition from low-level moistening for light rainfall to mid-level moistening at moderate rainfall and upper-level moistening for heavy rainfall. The mid-level moistening, arising from both dynamics and physics, may be most important. Accurately representing many processes may be necessary, but not sufficient for capturing the MJO, which suggests that models fail to predict the MJO for a broad range of reasons and limits the possibility of finding a panacea.