An optical study of multiple NEIAL events driven by low energy electron precipitation

Optical data are compared with EISCAT radar observations of multiple Naturally Enhanced Ion-Acoustic Line (NEIAL) events in the dayside cusp. This study uses narrow field of view cameras to observe small-scale, short-lived auroral features. Using multiple-wavelength optical observations, a direct link between NEIAL occurrences and low energy (about 100 eV) optical emissions is shown. This is consistent with the Langmuir wave decay interpretation of NEIALs being driven by streams of low-energy electrons. Modelling work connected with this study shows that, for the measured ionospheric conditions and precipitation characteristics, growth of unstable Langmuir (electron plasma) waves can occur, which decay into ion-acoustic wave modes. The link with low energy optical emissions shown here, will enable future studies of the shape, extent, lifetime, grouping and motions of NEIALs.

Factors controlling the distribution of ozone in the West African lower troposphere during the AMMA (African Monsoon Multidisciplinary Analysis) wet season campaign

Ozone and its precursors were measured on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 Atmospheric Research Aircraft during the monsoon season 2006 as part of the African Monsoon Multidisciplinary Analysis (AMMA) campaign. One of the main features observed in the west African boundary layer is the increase of the ozone mixing ratios from 25 ppbv over the forested area (south of 12° N) up to 40 ppbv over the Sahelian area. We employ a two-dimensional (latitudinal versus vertical) meteorological model coupled with an O3-NOx-VOC chemistry scheme to simulate the distribution of trace gases over West Africa during the monsoon season and to analyse the processes involved in the establishment of such a gradient. Including an additional source of NO over the Sahelian region to account for NO emitted by soils we simulate a mean NOx concentration of 0.7 ppbv at 16° N versus 0.3 ppbv over the vegetated region further south in reasonable agreement with the observations. As a consequence, ozone is photochemically produced with a rate of 0.25 ppbv h−1 over the vegetated region whilst it reaches up to 0.75 ppbv h−1 at 16° N. We find that the modelled gradient is due to a combination of enhanced deposition to vegetation, which decreases the ozone levels by up to 11 pbbv, and the aforementioned enhanced photochemical production north of 12° N. The peroxy radicals required for this enhanced production in the north come from the oxidation of background CO and CH4 as well as from VOCs. Sensitivity studies reveal that both the background CH4 and partially oxidised VOCs, produced from the oxidation of isoprene emitted from the vegetation in the south, contribute around 5–6 ppbv to the ozone gradient. These results suggest that the northward transport of trace gases by the monsoon flux, especially during nighttime, can have a significant, though secondary, role in determining the ozone gradient in the boundary layer. Convection, anthropogenic emissions and NO produced from lightning do not contribute to the establishment of the discussed ozone gradient.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Changing precipitation patterns alter plant community dynamics and succession in an ex-arable grassland

1. Changes in the frequency of extreme events, such as droughts, may be one of the most significant impacts of climate change for ecosystems. Models predict more frequent summer droughts in much of England: this paper investigates the impact on different types of plants in an ex-arable grassland community. 2. A long-term experiment simulated increased and decreased summer precipitation. Substantial interannual variation allowed the effects of summer drought to be tested in combination with wet and dry weather in other seasons. This is important, as climate models predict increased winter precipitation. 3. Total cover abundance in early summer increased with increasing water supply in the previous summer; there was no effect of winter precipitation. Productivity is therefore likely to decrease with more frequent summer droughts, with no mitigating effect of wetter winters. 4. The percentage cover of perennial grasses declined during a natural drought in 1995-97; this was exacerbated by the experimental drought treatment and reduced by supplemented rainfall. Simultaneously, short-lived ruderal species increased; this was greatest in drought treatments and least with supplemented rainfall. 4. These trends were subsequently reversed during several years of unusually wet weather, with perennial grasses increasing and short-lived forbs decreasing. This occurred even in experimentally droughted plots, and we propose that it resulted from rapid coverage of gaps during wet autumns and winters. 6. Deep-rooted species generally proved to be more drought resistant, but there were exceptions. 7. We conclude that increased frequency of summer droughts could have serious implications for the establishment and successional development of ex-arable grasslands. Increased winter precipitation would moderate the impact on species composition, but not on productivity.

Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa

We describe the nature of recent (50 year) rainfall variability in the summer rainfall zone, South Africa, and how variability is recognised and responded to on the ground by farmers. Using daily rainfall data and self-organising mapping (SOM) we identify 12 internally homogeneous rainfall regions displaying differing parameters of precipitation change. Three regions, characterised by changing onset and timing of rains, rainfall frequencies and intensities, in Limpopo, North West and KwaZulu Natal provinces, were selected to investigate farmer perceptions of, and responses to, rainfall parameter changes. Village and household level analyses demonstrate that the trends and variabilities in precipitation parameters differentiated by the SOM analysis were clearly recognised by people living in the areas in which they occurred. A range of specific coping and adaptation strategies are employed by farmers to respond to climate shifts, some generic across regions and some facilitated by specific local factors. The study has begun to understand the complexity of coping and adaptation, and the factors that influence the decisions that are taken.

Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

Factors controlling the distribution of ozone in the West African lower troposphere during the AMMA (African Monsoon Multidisciplinary Analysis) wet season campaign

Ozone and its precursors were measured on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 Atmospheric Research Aircraft during the monsoon season 2006 as part of the African Monsoon Multidisciplinary Analysis (AMMA) campaign. One of the main features observed in the west African boundary layer is the increase of the ozone mixing ratios from 25 ppbv over the forested area (south of 12 degrees N) up to 40 ppbv over the Sahelian area. We employ a two-dimensional ( latitudinal versus vertical) meteorological model coupled with an O-3-NOx-VOC chemistry scheme to simulate the distribution of trace gases over West Africa during the monsoon season and to analyse the processes involved in the establishment of such a gradient. Including an additional source of NO over the Sahelian region to account for NO emitted by soils we simulate a mean NOx concentration of 0.7 ppbv at 16 degrees N versus 0.3 ppbv over the vegetated region further south in reasonable agreement with the observations. As a consequence, ozone is photochemically produced with a rate of 0.25 ppbv h(-1) over the vegetated region whilst it reaches up to 0.75 ppbv h(-1) at 16 degrees N. We find that the modelled gradient is due to a combination of enhanced deposition to vegetation, which decreases the ozone levels by up to 11 pbbv, and the aforementioned enhanced photochemical production north of 12 degrees N. The peroxy radicals required for this enhanced production in the north come from the oxidation of background CO and CH4 as well as from VOCs. Sensitivity studies reveal that both the background CH4 and partially oxidised VOCs, produced from the oxidation of isoprene emitted from the vegetation in the south, contribute around 5-6 ppbv to the ozone gradient. These results suggest that the northward transport of trace gases by the monsoon flux, especially during nighttime, can have a significant, though secondary, role in determining the ozone gradient in the boundary layer. Convection, anthropogenic emissions and NO produced from lightning do not contribute to the establishment of the discussed ozone gradient.

Formation of crystalline macrocyclic phases during electrophilic precipitation-polycondensation syntheses of poly(arylene ether ketone)s

Elongated crystalline particles formed as by-products during poly(arylene ether ketone) synthesis by electrophilic precipitation-polycondensation of 4,4'-diphenoxybenzophenone with terephthaloyl chloride or isophthaloyl chloride, thought previously to be polymer-whiskers, have now been identified as macrocyclic phases. Single crystal X-ray analysis of the needle-like particles formed in the reaction with terephthaloyl chloride, using the microdiffraction technique with synchrotron radiation, revealed that they consist of a macrocylic compound containing ten phenylene units, i.e. the [2 + 2] cyclic dimer. An analogous structure has also been demonstrated for the corresponding macrocycle derived from the reaction of 4,4-diphenoxybenzophenone with isophthaloyl chloride. Chloroform extraction of the products of the two polycondensations dissolved the macrocyclic material (but not the linear polymer), and analysis of the extracts by MALDI-TOF mass spectrometry demonstrated the presence in both cases of homologous families of macrocyclic products. Higher yields of macrocycles were obtained under pseudo-high dilution conditions, enabling the [2 + 2] cyclodimers from reactions of 4,4'-diphenoxybenzophenone with both terephthaloyl and isophthaloyl chloride to be isolated as pure compounds and fully characterised. (C) 2003 Published by Elsevier Ltd.

Are definitions of adiposity appropriate for identification of cardiovascular disease risk in South Asian populations?

South Asian populations living in the UK have a high prevalence of the metabolic syndrome, cardiovascular disease (CVD) and type 2 diabetes which impacts greatly on the morbidity and mortality of this ethnic group. The identification of ‘at risk’ individuals is essential to initiate reventative treatment. However, this is considerably hindered by the lack of appropriate cut-off values for anthropometric measures. CVD risk is significantly higher at a lower body mass index (BMI) in many Asian groups compared with Caucasians and adiposity (particularly central deposition) is higher at similar BMI levels. The definition of adiposity in Asians needs to be firmly established and appropriate lower BMI and waist circumference cut-offs implemented in ethnic subpopulations to facilitate appropriate treatment strategies.

Precipitation and latent heating distributions from satellite passive microwave radiometry. Part I: improved method and uncertainties

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

Case studies in interannual to decadal climate predictability

The predictability of ocean and climate variables is investigated, using a perfect model-based case study approach that recognises that predictability is dependent on the initial climate state. In line with previous studies, large scale ocean variables, show predictability for several years or more; by contrast, the predictability of climate variables is generally limited to, 2 years at most. That predictability shows high sensitivity to the initial state is demonstrated by predictable climate signals, arising in different regions, variables and seasons for different initial conditions. The predictability of climate variables, in the second year is of particular interest, because this is beyond the timescale that is usually considered to be the limit, of seasonal predictability. For different initial conditions, second year predictability is found in: temperatures in southeastern, North America (winter) and western Europe (winter and summer), and precipitation in India (summer monsoon) and in the tropical, South Atlantic. Second year predictability arises either from persistence of large-scale sea surface temperature (SST) and, related ocean heat content anomalies, particularly in regions such as the North Atlantic and Southern Ocean, or from mechanisms, that involve El Nino Southern Oscillation (ENSO) dynamics.