The distribution of the ring current: Cluster observations

Extending previous studies, a full-circle investigation of the ring current has been made using Cluster 4-spacecraft observations near perigee, at times when the Cluster array had relatively small separations and nearly regular tetrahedral configurations, and when the Dst index was greater than −30 nT (non-storm conditions). These observations result in direct estimations of the near equatorial current density at all magnetic local times (MLT) for the first time and with sufficient accuracy, for the following observations. The results confirm that the ring current flows westward and show that the in situ average measured current density (sampled in the radial range accessed by Cluster 4–4.5RE) is asymmetric in MLT, ranging from 9 to 27 nAm−2. The direction of current is shown to be very well ordered for the whole range of MLT. Both of these results are in line with previous studies on partial ring extent. The magnitude of the current density, however, reveals a distinct asymmetry: growing from 10 to 27 nAm−2 as azimuth reduces from about 12:00MLT to 03:00 and falling from 20 to 10 nAm−2 less steadily as azimuth reduces from 24:00 to 12:00MLT. This result has not been reported before and we suggest it could reflect a number of effects. Firstly, we argue it is consistent with the operation of region-2 field aligned-currents (FACs), which are expected to flow upward into the ring current around 09:00MLT and downward out of the ring current around 14:00MLT. Secondly, we note that it is also consistent with a possible asymmetry in the radial distribution profile of current density (resulting in higher peak at 4– 4.5RE). We note that part of the enhanced current could reflect an increase in the mean AE activity (during the periods in which Cluster samples those MLT).

A spatial–temporal analysis of the impact of access restrictions on forest landscapes and household welfare in Tanzania

This paper explores the impact of the re-introduction of access restrictions to forests in Tanzania, through participatory forest management (PFM), that have excluded villagers from forests to which they have traditionally, albeit illegally, had access to collect non-timber forest products (NTFPs). Motivated by our fieldwork, and using a spatial–temporal model, we focus on the paths of forest degradation and regeneration and villagers' utility before and after an access restriction is introduced. Our paper illustrates a number of key points for policy makers. First, the benefits of forest conservation tend to be greatest in the first few periods after an access restriction is introduced, after which the overall forest quality often declines. Second, villagers may displace their NTFP collection into more distant forests that may have been completely protected by distance alone before access to a closer forest was restricted. Third, permitting villagers to collect limited amounts of NTFPs for a fee, or alternatively fining villagers caught collecting illegally from the protected forest, and returning the fee or fine revenue to the villagers, can improve both forest quality and villagers' livelihoods.

Impact of the quantity and flavonoid content of fruits and vegetables on markers of intake in adults with an increased risk of cardiovascular disease: the FLAVURS Trial

Purpose Limited robust randomised controlled trials investigating fruit and vegetable (F&V) intake in people at risk of cardiovascular disease (CVD) exist. We aimed to design and validate a dietary strategy of increasing flavonoid-rich versus flavonoid-poor F&V consumption on nutrient biomarker profile. Methods A parallel, randomised, controlled, dose–response dietary intervention study. Participants with a CVD relative risk of 1.5 assessed by risk scores were randomly assigned to one of the 3 groups: habitual (control, CT), high-flavonoid (HF) or low-flavonoid (LF) diets. While the CT group (n = 57) consumed their habitual diet throughout, the HF (n = 58) and LF (n = 59) groups sequentially increased their daily F&V intake by an additional 2, 4 and 6 portions for 6-week periods during the 18-week study. Results Compliance to target numbers and types of F&V was broadly met and verified by dietary records, and plasma and urinary biomarkers. Mean (±SEM) number of F&V portions/day consumed by the HF and LF groups at baseline (3.8 ± 0.3 and 3.4 ± 0.3), 6 weeks (6.3 ± 0.4 and 5.8 ± 0.3), 12 weeks (7.0 ± 0.3 and 6.8 ± 0.3) and 18 weeks (7.6 ± 0.4 and 8.1 ± 0.4), respectively, was similar at baseline yet higher than the CT group (3.9 ± 0.3, 4.3 ± 0.3, 4.6 ± 0.4, 4.5 ± 0.3) (P = 0.015). There was a dose-dependent increase in dietary and urinary flavonoids in the HF group, with no change in other groups (P = 0.0001). Significantly higher dietary intakes of folate (P = 0.035), non-starch polysaccharides (P = 0.001), vitamin C (P = 0.0001) and carotenoids (P = 0.0001) were observed in both intervention groups compared with CT, which were broadly supported by nutrient biomarker analysis. Conclusions The success of improving nutrient profile by active encouragement of F&V intake in an intervention study implies the need for a more hands-on public health approach.

Asymmetric response of demand-supply mismatch to investor's sentiment

We look through both the demand and supply side information to understand dynamics of price determination in the real estate market and examine how accurately investors’ attitudes predict the market returns and thereby flagging off extent of any demand-supply mismatch. Our hypothesis is based on the possibility that investors’ call for action in terms of their buy/sell decision and adjustment in reservation/offer prices may indicate impending demand-supply imbalances in the market. In the process, we study several real estate sectors to inform our analysis. The timeframe of our analysis (1995-2010) allows us to observe market dynamics over several economic cycles and in various stages of those cycles. Additionally, we also seek to understand how investors’ attitude or the sentiment affects the market activity over the cycles through asymmetric responses. We test our hypothesis variously using a number of measures of market activity and attitude indicators within several model specifications. The empirical models are estimated using Vector Error Correction framework. Our analysis suggests that investors’ attitude exert strong and statistically significant feedback effects in price determination. Moreover, these effects do reveal heterogeneous responses across the real estate sectors. Interestingly, our results indicate the asymmetric responses during boom, normal and recessionary periods. These results are consistent with the theoretical underpinnings.

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25×25 km grid, which is then reprojected onto a 1×1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25×25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean1. These links are extensive, influencing a range of climate processes such as hurricane activity2 and African Sahel3, 4, 5 and Amazonian5 droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations6, 7, 8, 9, 10. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures11, 12, but climate models have so far failed to reproduce these interactions6, 9 and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860–2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910–1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol–cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol–cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

An investigation of QBO signals in the east Asian and Indian monsoon in GCM experiments

Observations have shown that the monsoon is a highly variable phenomenon of the tropical troposphere, which exhibits significant variance in the temporal range of two to three years. The reason for this specific interannual variability has not yet been identified unequivocally. Observational analyses have also shown that EI Niño indices or western Pacific SSTs exhibit some power in the two to three year period range and therefore it was suggested that an ocean-atmosphere interaction could excite and support such a cycle. Similar mechanisms include land-surface-atmosphere interaction as a possible driving mechanism. A rather different explanation could be provided by a forcing mechanism based on the quasi-biennial oscillation of the zonal wind in the lower equatorial stratosphere (QBO). The QBO is a phenomenon driven by equatorial waves with periods of some days which are excited in the troposphere. Provided that the monsoon circulation reacts to the modulation of tropopause conditions as forced by the QBO, this could explain monsoon variability in the quasi-biennial window. The possibility of a QBO-driven monsoon variability is investigated in this study in a number of general circulation model experiments where the QBO is assimilated to externally controlled phase states. These experiments show that the boreal summer monsoon is significantly influenced by the QBO. A QBO westerly phase implies less precipitation in the western Pacific, but more in India, in agreement with observations. The austral summer monsoon is exposed to similar but weaker mechanisms and the precipitation does not change significantly.

Simulating the interannual variability of major dust storms on Mars using variable lifting thresholds

The redistribution of a finite amount of martian surface dust during global dust storms and in the intervening periods has been modelled in a dust lifting version of the UK Mars General Circulation Model. When using a constant, uniform threshold in the model’s wind stress lifting parameterisation and assuming an unlimited supply of surface dust, multiannual simulations displayed some variability in dust lifting activity from year to year, arising from internal variability manifested in surface wind stress, but dust storms were limited in size and formed within a relatively short seasonal window. Lifting thresholds were then allowed to vary at each model gridpoint, dependent on the rates of emission or deposition of dust. This enhanced interannual variability in dust storm magnitude and timing, such that model storms covered most of the observed ranges in size and initiation date within a single multiannual simulation. Peak storm magnitude in a given year was primarily determined by the availability of surface dust at a number of key sites in the southern hemisphere. The observed global dust storm (GDS) frequency of roughly one in every 3 years was approximately reproduced, but the model failed to generate these GDSs spontaneously in the southern hemisphere, where they have typically been observed to initiate. After several years of simulation, the surface threshold field—a proxy for net change in surface dust density—showed good qualitative agreement with the observed pattern of martian surface dust cover. The model produced a net northward cross-equatorial dust mass flux, which necessitated the addition of an artificial threshold decrease rate in order to allow the continued generation of dust storms over the course of a multiannual simulation. At standard model resolution, for the southward mass flux due to cross-equatorial flushing storms to offset the northward flux due to GDSs on a timescale of ∼3 years would require an increase in the former by a factor of 3–4. Results at higher model resolution and uncertainties in dust vertical profiles mean that quasi-periodic redistribution of dust on such a timescale nevertheless appears to be a plausible explanation for the observed GDS frequency.

Late Quaternary fire regimes of Australasia

We have compiled 223 sedimentary charcoal records from Australasia in order to examine the temporal and spatial variability of fire regimes during the Late Quaternary. While some of these records cover more than a full glacial cycle, here we focus on the last 70,000 years when the number of individual records in the compilation allows more robust conclusions. On orbital time scales, fire in Australasia predominantly reflects climate, with colder periods characterized by less and warmer intervals by more biomass burning. The composite record for the region also shows considerable millennial-scale variability during the last glacial interval (73.5–14.7 ka). Within the limits of the dating uncertainties of individual records, the variability shown by the composite charcoal record is more similar to the form, number and timing of Dansgaard–Oeschger cycles as observed in Greenland ice cores than to the variability expressed in the Antarctic ice-core record. The composite charcoal record suggests increased biomass burning in the Australasian region during Greenland Interstadials and reduced burning during Greenland Stadials. Millennial-scale variability is characteristic of the composite record of the sub-tropical high pressure belt during the past 21 ka, but the tropics show a somewhat simpler pattern of variability with major peaks in biomass burning around 15 ka and 8 ka. There is no distinct change in fire regime corresponding to the arrival of humans in Australia at 50 ± 10 ka and no correlation between archaeological evidence of increased human activity during the past 40 ka and the history of biomass burning. However, changes in biomass burning in the last 200 years may have been exacerbated or influenced by humans.

Analysis of the seasonal cycle within the first international urban land-surface model comparison

A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.