Retrieval of effective ice crystal size in the infrared: sensitivity study and global measurements from TIROS-N Operational Vertical Sounder

The difference between cirrus emissivities at 8 and 11 μm is sensitive to the mean effective ice crystal size of the cirrus cloud, De. By using single scattering properties of ice crystals shaped as planar polycrystals, diameters of up to about 70 μm can be retrieved, instead of up to 45 μm assuming spheres or hexagonal columns. The method described in this article is used for a global determination of mean effective ice crystal sizes of cirrus clouds from TOVS satellite observations. A sensitivity study of the De retrieval to uncertainties in hypotheses on ice crystal shape, size distributions, and temperature profiles, as well as in vertical and horizontal cloud heterogeneities shows that uncertainties can be as large as 30%. However, the TOVS data set is one of few data sets which provides global and long-term coverage. Having analyzed the years 1987–1991, it was found that measured effective ice crystal diameters De are stable from year to year. For 1990 a global median De of 53.5 μm was determined. Averages distinguishing ocean/land, season, and latitude lie between 23 μm in winter over Northern Hemisphere midlatitude land and 64 μm in the tropics. In general, larger Des are found in regions with higher atmospheric water vapor and for cirrus with a smaller effective emissivity.

Ideational change in the WTO and its impacts on EU agricultural policy institutions and the CAP

This paper argues that the Uruguay Round Agreement on Agriculture (URAA) introduced the market liberal paradigm as the ideational underpinning of the new farm trade regime. Though the immediate consequences in terms of limitations on agricultural support and protection were very modest, the Agreement did impact on the way in which domestic farm policy evolves. It forced EU agricultural policy makers to consider the agricultural negotiations when reforming the Common Agricultural Policy (CAP). The new paradigm in global farm trade resulted in a process of institutional layering in which concerns raised in the World Trade Organization (WTO) were gradually incorporated in EU agricultural institutions. This has resulted in gradual reform of the CAP in which policy instruments have been changed in order to make the CAP more WTO compatible. The underlying paradigm, the state-assisted paradigm, has been sustained though it has been rephrased by introducing the concept of multifunctionality.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

A study of students' metacognitive beliefs about foreign language study and their impact on learning

This article reports on an investigation into the language learning beliefs of students of French in England, aged 16 to 18. It focuses on qualitative data from two groups of learners (10 in total). While both groups had broadly similar levels of achievement in French in terns of examination success, they dffered greatly in the self-image they had of themselves as language learners, with one group displaying low levels of self-eficacy beliefs regarding the possibility of future success. The implica tions of such beliefs for students' levels of motivation and persistence are discussed, together with their possible causes. The article concludes by suggesting changes in classroom practice that might help students develop a more positive image of them selves as language learners.

Safety evaluation of oligofructose: 13 Week rat study and in vitro mutagenicity

Oligofructose (OF), comprised of fructose oligomers with a terminal glucose unit, is a family Of oligosaccharides derived from the hydrolysis of inulin. Consumption of OF in animals and humans increases colonic bifidobacteria levels. The present study evaluates the safety of OF in both a 13 week rat feeding Study and Using in Vitro mutagenicity tests. Fecal bifidobacteria levels were also determined by in situ hybridization to assess a biological function of OF. Rats received either a control diet OF diets containing one of four doses of OF. Total, HDL, and LDL-cholesterol levels were significantly lower at several time points during the study in groups receiving OF compared to controls with the largest effects Occurring in the high dose male animals. Weight gain in the male high dose group was significantly lower at early time points compared to controls but]lot Significantly different at the end of study. As expected, cecal weights increased in a dose-related manner and fecal bifidobacteria levels also demonstrated a dose-related increase. There were no consistent differences in gross pathology or histopathology related to dietary OF. OF did not induce a positive response in the Ames test or chromosomal aberration test with CHO cells. These results demonstrate no adverse effects of OF. (C) 2008 Elsevier Ltd. All rights reserved.

Urban tracer dispersion experiment in London (DAPPLE) 2003: field study and comparison with empirical prediction

The DAPPLE (Dispersion of Air Pollutants and their Penetration into the Local Environment) project seeks to characterise near-field urban atmospheric dispersion using a multidisciplinary approach. In this paper we report on the first tracer dispersion experiment carried out in May 2003. Results of concurrent meteorological measurements are presented. Variations of receptor tracer concentration with time are presented. Meteorological observations suggest that in-street channelling and flow-switching at intersections take place. A comparison between roof top and surface measurements suggest that rapid vertical mixing occurs, and a comparison between a simple dispersion model and maximum concentrations observed are presented