Coupled simulations of the Indian monsoon intraseasonal oscillation using a fine-resolution mixed-layer ocean model

The intraseasonal variability (ISV) of the Indian summer monsoon is dominated by a 30–50 day oscillation between “active” and “break” events of enhanced and reduced rainfall over the subcontinent, respectively. These organized convective events form in the equatorial Indian Ocean and propagate north to India. Atmosphere–ocean coupled processes are thought to play a key role the intensity and propagation of these events. A high-resolution, coupled atmosphere–mixed-layer-oceanmodel is assembled: HadKPP. HadKPP comprises the Hadley Centre Atmospheric Model (HadAM3) and the K Profile Parameterization (KPP) mixed-layer ocean model. Following studies that upper-ocean vertical resolution and sub-diurnal coupling frequencies improve the simulation of ISV in SSTs, KPP is run at 1 m vertical resolution near the surface; the atmosphere and ocean are coupled every three hours. HadKPP accurately simulates the 30–50 day ISV in rainfall and SSTs over India and the Bay of Bengal, respectively, but suffers from low ISV on the equator. This is due to the HadAM3 convection scheme producing limited ISV in surface fluxes. HadKPP demonstrates little of the observed northward propagation of intraseasonal events, producing instead a standing oscillation. The lack of equatorial ISV in convection in HadAM3 constrains the ability of KPP to produce equatorial SST anomalies, which further weakens the ISV of convection. It is concluded that while atmosphere–ocean interactions are undoubtedly essential to an accurate simulation of ISV, they are not a panacea for model deficiencies. In regions where the atmospheric forcing is adequate, such as the Bay of Bengal, KPP produces SST anomalies that are comparable to the Tropical Rainfall Measuring Mission Microwave Imager (TMI) SST analyses in both their magnitude and their timing with respect to rainfall anomalies over India. HadKPP also displays a much-improved phase relationship between rainfall and SSTs over a HadAM3 ensemble forced by observed SSTs, when both are compared to observations. Coupling to mixed-layer models such as KPP has the potential to improve operational predictions of ISV, particularly when the persistence time of SST anomalies is shorter than the forecast lead time.

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.

Using aircraft measurements to determine the refractive index of Saharan dust during the DODO Experiments

Much uncertainty in the value of the imaginary part of the refractive index of mineral dust contributes to uncertainty in the radiative effect of mineral dust in the atmosphere. A synthesis of optical, chemical and physical in-situ aircraft measurements from the DODO experiments during February and August 2006 are used to calculate the refractive index mineral dust encountered over West Africa. Radiative transfer modeling and measurements of broadband shortwave irradiance at a range of altitudes are used to test and validate these calculations for a specific dust event on 23 August 2006 over Mauritania. Two techniques are used to determine the refractive index: firstly a method combining measurements of scattering, absorption, size distributions and Mie code simulations, and secondly a method using composition measured on filter samples to apportion the content of internally mixed quartz, calcite and iron oxide-clay aggregates, where the iron oxide is represented by either hematite or goethite and clay by either illite or kaolinite. The imaginary part of the refractive index at 550 nm (ni550) is found to range between 0.0001 i to 0.0046 i, and where filter samples are available, agreement between methods is found depending on mineral combination assumed. The refractive indices are also found to agree well with AERONET data where comparisons are possible. ni550 is found to vary with dust source, which is investigated with the NAME model for each case. The relationship between both size distribution and ni550 on the accumulation mode single scattering albedo at 550 nm (ω0550) are examined and size distribution is found to have no correlation to ω0550, while ni550 shows a strong linear relationship with ω0550. Radiative transfer modeling was performed with different models (Mie-derived refractive indices, but also filter sampling composition assuming both internal and external mixing). Our calculations indicate that Mie-derived values of ni550 and the externally mixed dust where the iron oxide-clay aggregate corresponds to the goethite-kaolinite combination result in the best agreement with irradiance measurements. The radiative effect of the dust is found to be very sensitive to the mineral combination (and hence refractive index) assumed, and to whether the dust is assumed to be internally or externally mixed.

Revisiting youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

Percentile growth charts for biomedical studies using a porcine model

Increasing rates of obesity and heart disease are compromising quality of life for a growing number of people. There is much research linking adult disease with the growth and development both in utero and during the first year of life. The pig is an ideal model for studying the origins of developmental programming. The objective of this paper was to construct percentile growth curves for the pig for use in biomedical studies. The body weight (BIN) of pigs was recorded from birth to 150 days of age and their crown-to-rump length was measured over the neonatal period to enable the ponderal index (Pl; kg/m(3)) to be calculated. Data were normalised and percentile curves were constructed using Cole's lambda-mu-sigma (LMS) method for BW and PI. The construction of these percentile charts for use in biomedical research will allow a more detailed and precise tracking of growth and development of individual pigs under experimental conditions.

Unravelling the rationale of 'overgrazing' and stocking rates in the beef production systems of Central Brazil using a bi-criteria compromise programming model

In Central Brazil, the long-term sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, ‘asset value of cattle (representing cattle ownership)' and ‘present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics, and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple ‘no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil.

Unravelling the rationale of 'overgrazing' and stocking rates in the beef production systems of Central Brazil using a bi-criteria compromise programming model

In Central Brazil, the long-term, sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from. degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, 'asset value of cattle (representing cattle ownership and 'present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring caring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics,and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple 'no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil. (C) 2004 Elsevier Ltd. All rights reserved.

Revisiting Youden's index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous Score for classification of study participants into healthy, or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between Studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might he confounded by a potentially unknown variation of the cut-off Value. To cope with this phenomena it is suggested to use, instead an overall estimate of the misclassification error previously suggested and used as Youden's index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel-Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden's index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

EnvironalPlanning: an analytical network process model for environmentally conscious construction planning

Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.

Successful manipulation of the quality and quantity of fat and carbohydrate consumed by free-living individuals using a food exchange model

Our objective in this study was to develop and implement an effective intervention strategy to manipulate the amount and composition of dietary fat and carbohydrate (CHO) in free-living individuals in the RISCK study. The study was a randomized, controlled dietary intervention study that was conducted in 720 participants identified as higher risk for or with metabolic syndrome. All followed a 4-wk run-in reference diet [high saturated fatty acids (SF)/high glycemic index (GI)]. Volunteers were randomized to continue this diet for a further 24 wk or to I of 4 isoenergetic prescriptions [high monounsaturated fatty acids (MUFA)/high GI; high MUFA/low GI; low fat (LF)/high GI; and LF/low GI]. We developed a food exchange model to implement each diet. Dietary records and plasma phospholipid fatty acids were used to assess the effectiveness of the intervention strategy. Reported fat intake from the LF diets was significantly reduced to 28% of energy (%E) compared with 38% E from the HM and LF diets. SF intake was successfully decreased in the HM and LF diets was similar to 10% E compared with 17% E in the reference diet (P = 0.001). Dietary MUFA in the HIM diets was similar to 17% E, significantly higher than in the reference (12% E) and LF diets (10% E) (P = 0.001). Changes in plasma phospholipid fatty acids provided further evidence for the successful manipulation of fat intake. The GI of the HGI and LGI arms differed by similar to 9 points (P = 0.001). The food exchange model provided an effective dietary strategy for the design and implementation across multiple sites of 5 experimental diets with specific targets for the proportion of fat and CHO. J. Nutr. 139: 1534-1540, 2009.

Effect of fecal water on an in vitro model of colonic mucosal barrier function

Fecal water (FW) has been shown to exert, in cultured cells, cytotoxic and genotoxic effects that have implications for colorectal cancer (CRC) risk. We have investigated a further biological activity of FW, namely, the ability to affect gap junctions in CACO2 cell monolayers as an index of mucosal barrier function, which is known to be disrupted in cancer. FW samples fi-om healthy, free-living, European subjects that were divided into two broad age groups, adult (40 +/- 9.7 yr; n = 53) and elderly (76 +/- 7.5 yr; n = 55) were tested for effects on gap junction using the transepithelial resistance (TER) assay. Overall, treatment of CACO2 cells with FW samples fi-om adults increased TER (+ 4 %), whereas FW from elderly subjects decreased TER (-5%); the difference between the two groups was significant (P < 0.05). We also measured several components of FW potentially associated with modulation of TER, namely, short-chain fatty acid (SCFA) and ammonia. SCFAs (propionic, acetic, and n-butyric) were significantly lower in the elderly population (-30%, -35%, and -21%, respectively, all P pound 0.01). We consider that FW modulation of in vitro epithelial barrier function is a potentially useful noninvasive biomarker, but it requires further validation to establish its relationship to CRC risk.

Revised QUICKI provides a strong surrogate estimate of insulin sensitivity when compared with the minimal model

OBJECTIVE: To compare insulin sensitivity (Si) from a frequently sampled intravenous glucose tolerance test (FSIGT) and subsequent minimal model analyses with surrogate measures of insulin sensitivity and resistance and to compare features of the metabolic syndrome between Caucasians and Indian Asians living in the UK. SUBJECTS: In all, 27 healthy male volunteers (14 UK Caucasians and 13 UK Indian Asians), with a mean age of 51.2 +/- 1.5 y, BMI of 25.8 +/- 0.6 kg/m(2) and Si of 2.85 +/- 0.37. MEASUREMENTS: Si was determined from an FSIGT with subsequent minimal model analysis. The concentrations of insulin, glucose and nonesterified fatty acids (NEFA) were analysed in fasting plasma and used to calculate surrogate measure of insulin sensitivity (quantitative insulin sensitivity check index (QUICKI), revised QUICKI) and resistance (homeostasis for insulin resistance (HOMA IR), fasting insulin resistance index (FIRI), Bennetts index, fasting insulin, insulin-to-glucose ratio). Plasma concentrations of triacylglycerol (TAG), total cholesterol, high density cholesterol, (HDL-C) and low density cholesterol, (LDL-C) were also measured in the fasted state. Anthropometric measurements were conducted to determine body-fat distribution. RESULTS: Correlation analysis identified the strongest relationship between Si and the revised QUICKI (r = 0.67; P = 0.000). Significant associations were also observed between Si and QUICKI (r = 0.51; P = 0.007), HOMA IR (r = -0.50; P = 0.009), FIRI and fasting insulin. The Indian Asian group had lower HDL-C (P = 0.001), a higher waist-hip ratio (P = 0.01) and were significantly less insulin sensitive (Si) than the Caucasian group (P = 0.02). CONCLUSION: The revised QUICKI demonstrated a statistically strong relationship with the minimal model. However, it was unable to differentiate between insulin-sensitive and -resistant groups in this study. Future larger studies in population groups with varying degrees of insulin sensitivity are recommended to investigate the general applicability of the revised QUICKI surrogate technique.

Rifaximin modulates the colonic microbiota of patients with Crohn's disease: an in vitro approach using a continuous culture colonic model system.

Rifaximin, a rifamycin derivative, has been reported to induce clinical remission of active Crohn's disease (CD), a chronic inflammatory bowel disorder. In order to understand how rifaximin affects the colonic microbiota and its metabolism, an in vitro human colonic model system was used in this study. We investigated the impact of the administration of 1800 mg/day of rifaximin on the faecal microbiota of four patients affected by colonic active CD [Crohn's disease activity index (CDAI > 200)] using a continuous culture colonic model system. We studied the effect of rifaximin on the human gut microbiota using fluorescence in situ hybridization, quantitative PCR and PCR–denaturing gradient gel electrophoresis. Furthermore, we investigated the effect of the antibiotic on microbial metabolic profiles, using 1H-NMR and solid phase microextraction coupled with gas chromatography/mass spectrometry, and its potential genotoxicity and cytotoxicity, using Comet and growth curve assays. Rifaximin did not affect the overall composition of the gut microbiota, whereas it caused an increase in concentration of Bifidobacterium, Atopobium and Faecalibacterium prausnitzii. A shift in microbial metabolism was observed, as shown by increases in short-chain fatty acids, propanol, decanol, nonanone and aromatic organic compounds, and decreases in ethanol, methanol and glutamate. No genotoxicity or cytotoxicity was attributed to rifaximin, and conversely rifaximin was shown to have a chemopreventive role by protecting against hydrogen peroxide-induced DNA damage. We demonstrated that rifaximin, while not altering the overall structure of the human colonic microbiota, increased bifidobacteria and led to variation of metabolic profiles associated with potential beneficial effects on the host.

Simulating the impacts of global warming on wheat in China using a large area crop model

Temperature is one of the most prominent environmental factors that determine plant growth, devel- opment, and yield. Cool and moist conditions are most favorable for wheat. Wheat is likely to be highly vulnerable to further warming because currently the temperature is already close to or above optimum. In this study, the impacts of warming and extreme high temperature stress on wheat yield over China were investigated by using the general large area model (GLAM) for annual crops. The results showed that each 1±C rise in daily mean temperature would reduce the average wheat yield in China by about 4.6%{5.7% mainly due to the shorter growth duration, except for a small increase in yield at some grid cells. When the maximum temperature exceeded 30.5±C, the simulated grain-set fraction declined from 1 at 30.5±C to close to 0 at about 36±C. When the total grain-set was lower than the critical fractional grain-set (0.575{0.6), harvest index and potential grain yield were reduced. In order to reduce the negative impacts of warming, it is crucial to take serious actions to adapt to the climate change, for example, by shifting sowing date, adjusting crop distribution and structure, breeding heat-resistant varieties, and improving the monitoring, forecasting, and early warning of extreme climate events.