Environmental impact of genetically modified cotton in South Africa

This paper presents the results of a large-scale study designed to monitor the impact arising from the introduction of insect-resistant Bt cotton in the Makhathini Flats, Republic of South Africa. Bt cotton provides a degree of resistance to cotton bollworm complex (Lepidoptera). Data were collected on the use of insecticides (type and quantity) as well as the farm-level economics of production from over 2200 farmers in three growing seasons (1998/1999, 1999/2000 and 2000/2001). and the results are discussed within the context of environmental impact brought about by insecticide. Over the three seasons of the study it was clear that Bt cotton provided benefits in terms of higher yield and gross margin relative to farmers growing conventional (non-Bt) cotton, and the benefits were particularly apparent for the smallest producers. Bt growers also used significantly less insecticide than growers of non-Bt cotton. Once quantities of insecticide applied to Bt and non-Bt cotton were converted into a Biocide Index and an Environmental Impact Quotient (EIQ) in order to allow for differences in terms of toxicity and persistence in the environment, it was apparent that the growing of Bt had a less negative impact on the environment. While this points to beneficial impacts on agricultural sustainability there are wider concerns regarding the vulnerability of resource-poor farmers in an area with limited (as yet) marketing options for their product and options for livelihood diversification both within and outside agriculture. Cotton producers in Makhathini are vulnerable as they rely on just One company for inputs (including, credit) and for their market. While Bt cotton provides benefits it does not in itself address some of the structural limitations that farmers face. (c) 2006 Elsevier B.V. All rights reserved.

Isolating the 'farmer' effect as a component of the advantage of growing genetically modified varieties in developing countries: a Bt cotton case study from Jalgaon, India

The present paper explores the 'farmer' effect in economic advantages often claimed for Bt cotton varieties (those with the endotoxin gene from Bacillus thuringiensis conferring resistance to some insect pests) compared to non-Bt varieties. Critics claim that much of the yield advantage of Bt cotton could be due to the fact that farmers adopting the technology are in a better position to provide inputs and management and so much of any claimed Bt advantage is an artefact rather than reflecting a real advantage of the variety per se. The present paper provides an in-depth analysis of 63 non-adopting and 94 adopting households of Bt cotton in Jalgaon, Maharashtra State, India, spanning the seasons 2002 and 2003. Results suggest that Bt adopters are indeed different from non-adopters in a number of ways. Adopters appear to specialize more on cotton (at least in terms of the land area they devote to the crop), spend more money on irrigation and grow well-performing non-Bt varieties of cotton (Bunny). Taking gross margin as the basis for comparison, Bt plots had 2.5 times the gross margin of non-Bt plots in both seasons. If only adopters are considered then the gross margin advantage of Bt plots reduces to 1.6 times that of non-Bt plots. This is still a significant advantage and could well explain the popularity of Bt in Maharashtra. However, it is clear that great care needs to be taken with such comparative studies.

Genetically modified insect resistance in cotton: some farm level economic impacts in India

The paper explores the impact of insect-resistant Bacillus thuringiensis (Bt) cotton on costs and returns over the first two seasons of its commercial release in three sub-regions of Maharashtra State, India. It is the first such research conducted in India based on farmers' own practices rather than trial plots. Data were collected for a total of 7793 cotton plots in 2002 and 1577 plots in 2003. Results suggest that while the cost of cotton seed was much higher for farmers growing Bt cotton relative to those growing non-Bt cotton, the costs of bollworm spray were much lower. While Bt plots had greater costs (seed plus insecticide) than non-Bt plots, the yields and revenue from Bt plots were much higher than those of non-Bt plots (some 39% and 63% higher in 2002 and 2003, respectively). Overall, the gross margins of Bt plots were some 43% (2002) and 73% (2003) higher than those of non-Bt plots, although there was some variation between the three sub-regions of the state. The results suggest that Bt cotton has provided substantial benefits for farmers in India over the 2 years, but there are questions as to whether these benefits are sustainable. (c) 2004 Elsevier Ltd. All rights reserved.

Past, present and future precipitation in the Middle East: insights from models and observations

Anthropogenic changes in precipitation pose a serious threat to society—particularly in regions such as the Middle East that already face serious water shortages. However, climate model projections of regional precipitation remain highly uncertain. Moreover, standard resolution climate models have particular difficulty representing precipitation in the Middle East, which is modulated by complex topography, inland water bodies and proximity to the Mediterranean Sea. Here we compare precipitation changes over the twenty-first century against both millennial variability during the Holocene and interannual variability in the present day. In order to assess the climate model and to make consistent comparisons, this study uses new regional climate model simulations of the past, present and future in conjunction with proxy and historical observations. We show that the pattern of precipitation change within Europe and the Middle East projected by the end of the twenty-first century has some similarities to that which occurred during the Holocene. In both cases, a poleward shift of the North Atlantic storm track and a weakening of the Mediterranean storm track appear to cause decreased winter rainfall in southern Europe and the Middle East and increased rainfall further north. In contrast, on an interannual time scale, anomalously dry seasons in the Middle East are associated with a strengthening and focusing of the storm track in the north Mediterranean and hence wet conditions throughout southern Europe.

Evidence for long-term regional changes in precipitation on the East Coast Mountains in Mauritius

Global climate change and its impacts are being increasingly studied and precipitation trends are one of the measures of quantifying climate change especially in the tropics. This study uses daily rainfall data to determine if there are changes in the long-term trends in rainfall variability in the East Coast Mountains of Mauritius during the last few decades, and to investigate the factors influencing the trends in the inter-annual to inter-decadal rainfall variability. Statistical modelling has been used to investigate the trends in total seasonal rainfall, the number of rain days and the mean amount of rain per rainy days and the local, regional and large-scale factors that affect them on inter-annual to inter-decadal time scales. The strongest inter-decadal trend was found in the number of rain days for both rainfall seasons, and the other variables were found to have weak or insignificant trends. Both local factors, such as the surrounding sea surface temperatures and large-scale phenomena such as Indian Monsoon and the El Niño Southern Oscillation were found to influence rainfall patterns.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Studies on particulate matter (PM10) and its precursors over urban environment of Reading, UK

The extent to which airborne particles penetrate into the human respiratory system is determined mainly by their size, with possible health effects. The research over the scientific evidence of the role of airborne particles in adverse health effects has been intensified in recent years. In the present study, seasonal variations of PM10 and its relation with anthropogenic activities have been studied by using the data from UK National Air Quality Archive over Reading, UK. The diurnal variation of PM10 shows a morning peak during 7:00-10:00 LT and an evening peak during 19:00-22:00 LT. 3 The variation between 12:00 and 17:00 LT remains more or less steady for PM10 with the minimum value of similar to 16 mu g m(-3). PM10 and black smoke (BS) concentrations during weekdays were found to be high compared to weekends. A reduction in the concentration of PM10 has been found during the Christmas holidays compared to normal days during December. Seasonal variations of PM10 showed high values during spring compared to other seasons. A linear relationship has been found between PM10 and NO, during March, July, November and December suggesting that most of the PM10 is due to local traffic exhaust emissions. PM10 and SO2 concentrations showed positive correlation with the correlation coefficient of R-2 = 0.65 over the study area. Seasonal variations of SO2 and NOx showed high concentrations during winter and low concentrations during spring. Fraction of BS in PM10 has been found to be 50% during 2004 over the study area. (C) 2005 Elsevier Ltd. All rights reserved.

Equatorial waves in the lower stratosphere. II: Annual and interannual variability

The annual and interannual variability of idealized, linear, equatorial waves in the lower stratosphere is investigated using the temperature and velocity fields from the ECMWF 15-year re-analysis dataset. Peak Kelvin wave activity occurs during solstice seasons at 100 hPa, during December-February at 70 hPa and in the easterly to westerly quasi-biennial oscillation (QBO) phase transition at 50 hPa. Peak Rossby-gravity wave activity occurs during equinox seasons at 100 hPa, during June-August/September-November at 70 hPa and in the westerly to easterly QBO phase transition at 50 hPa. Although neglect of wind shear means that the results for inertio-gravity waves are likely to be less accurate, they are still qualitatively reasonable and an annual cycle is observed in these waves at 100 hPa and 70 hPa. Inertio-gravity waves with n = 1 are correlated with the QBO at 50 hPa, but the eastward inertio-gravity n = 0 wave is not, due to its very fast vertical group velocity in all background winds. The relative importance of different wave types in driving the QBO at 50 hPa is also discussed. The strongest acceleration appears to be provided by the Kelvin wave while the acceleration provided by the Rossby-gravity wave is negligible. Of the higher-frequency waves, the westward inertio-gravity n = 1 wave appears able to contribute more to the acceleration of the 50 hPa mean zonal wind than the eastward inertio-gravity n = 1 wave.

The meteorology of the Western Indian Ocean, and the influence of the east African highlands

This paper reviews the meteorology of the Western Indian Ocean and uses a state–of–the–art atmospheric general circulation model to investigate the influence of the East African Highlands on the climate of the Indian Ocean and its surrounding regions. The new 44–year re–analysis produced by the European Centre for Medium range Weather Forecasts (ECMWF) has been used to construct a new climatology of the Western Indian Ocean. A brief overview of the seasonal cycle of the Western Indian Ocean is presented which emphasizes the importance of the geography of the Indian Ocean basin for controlling the meteorology of the Western Indian Ocean. The principal modes of inter–annual variability are described, associated with El Niño and the Indian Ocean Dipole or Zonal Mode, and the basic characteristics of the subseasonal weather over the Western Indian Ocean are presented, including new statistics on cyclone tracks derived from the ECMWF re–analyses. Sensitivity experiments, in which the orographic effects of East Africa are removed, have shown that the East African Highlands, although not very high, play a significant role in the climate of Africa, India and Southeast Asia, and in the heat, salinity and momentum forcing of the Western Indian Ocean. The hydrological cycle over Africa is systematically enhanced in all seasons by the presence of the East African Highlands, and during the Asian summer monsoon there is a major redistribution of the rainfall across India and Southeast Asia. The implied impact of the East African Highlands on the ocean is substantial. The East African Highlands systematically freshen the tropical Indian Ocean, and act to focus the monsoon winds along the coast, leading to greater upwelling and cooler sea–surface temperatures.

Global observed changes in daily climate extremes of temperature and precipitation

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

Characteristics and variability of storm tracks in the north Pacific, Bering Sea, and Alaska

The North Pacific and Bering Sea regions represent loci of cyclogenesis and storm track activity. In this paper climatological properties of extratropical storms in the North Pacific/Bering Sea are presented based upon aggregate statistics of individual storm tracks calculated by means of a feature-tracking algorithm run using NCEP–NCAR reanalysis data from 1948/49 to 2008, provided by the NOAA/Earth System Research Laboratory and the Cooperative Institute for Research in Environmental Sciences, Climate Diagnostics Center. Storm identification is based on the 850-hPa relative vorticity field (ζ) instead of the often-used mean sea level pressure; ζ is a prognostic field, a good indicator of synoptic-scale dynamics, and is directly related to the wind speed. Emphasis extends beyond winter to provide detailed consideration of all seasons. Results show that the interseasonal variability is not as large during the spring and autumn seasons. Most of the storm variables—genesis, intensity, track density—exhibited a maxima pattern that was oriented along a zonal axis. From season to season this axis underwent a north–south shift and, in some cases, a rotation to the northeast. This was determined to be a result of zonal heating variations and midtropospheric moisture patterns. Barotropic processes have an influence in shaping the downstream end of storm tracks and, together with the blocking influence of the coastal orography of northwest North America, result in high lysis concentrations, effectively making the Gulf of Alaska the “graveyard” of Pacific storms. Summer storms tended to be longest in duration. Temporal trends tended to be weak over the study area. SST did not emerge as a major cyclogenesis control in the Gulf of Alaska.

Overview of observations from the RADAGAST experiment in Niamey, Niger: 2. Radiative fluxes and divergences

Broadband shortwave and longwave radiative fluxes observed both at the surface and from space during the Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA Stations (RADAGAST) experiment in Niamey, Niger, in 2006 are presented. The surface fluxes were measured by the Atmospheric Radiation Measurement (ARM) Program Mobile Facility (AMF) at Niamey airport, while the fluxes at the top of the atmosphere (TOA) are from the Geostationary Earth Radiation Budget (GERB) instrument on the Meteosat-8 satellite. The data are analyzed as daily averages, in order to minimize sampling differences between the surface and top of atmosphere instruments, while retaining the synoptic and seasonal changes that are the main focus of this study. A cloud mask is used to identify days with cloud versus those with predominantly clear skies. The influence of temperature, water vapor, aerosols, and clouds is investigated. Aerosols are ubiquitous throughout the year and have a significant impact on both the shortwave and longwave fluxes. The large and systematic seasonal changes in temperature and column integrated water vapor (CWV) through the dry and wet seasons are found to exert strong influences on the longwave fluxes. These influences are often in opposition to each other, because the highest temperatures occur at the end of the dry season when the CWV is lowest, while in the wet season the lowest temperatures are associated with the highest values of CWV. Apart from aerosols, the shortwave fluxes are also affected by clouds and by the seasonal changes in CWV. The fluxes are combined to provide estimates of the divergence of radiation across the atmosphere throughout 2006. The longwave divergence shows a relatively small variation through the year, because of a partial compensation between the seasonal variations in the outgoing longwave radiation (OLR) and surface net longwave radiation. A simple model of the greenhouse effect is used to interpret this result in terms of the dependence of the normalized greenhouse effect at the TOA and of the effective emissivity of the atmosphere at the surface on the CWV. It is shown that, as the CWV increases, the atmosphere loses longwave energy to the surface with about the same increasing efficiency with which it traps the OLR. When combined with the changes in temperature, this maintains the atmospheric longwave divergence within the narrow range that is observed. The shortwave divergence is mainly determined by the CWV and aerosol loadings and the effect of clouds is much smaller than on the component fluxes.

Evaluation of forest snow processes models (SnowMIP2)

Thirty‐three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above‐freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal “best” model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

A comparison of three canopy interception models for a leafless mixed deciduous forest stand in the eastern United States

Canopy interception of incident precipitation is a critical component of the forest water balance during each of the four seasons. Models have been developed to predict precipitation interception from standard meteorological variables because of acknowledged difficulty in extrapolating direct measurements of interception loss from forest to forest. No known study has compared and validated canopy interception models for a leafless deciduous forest stand in the eastern United States. Interception measurements from an experimental plot in a leafless deciduous forest in northeastern Maryland (39°42'N, 75°5'W) for 11 rainstorms in winter and early spring 2004/05 were compared to predictions from three models. The Mulder model maintains a moist canopy between storms. The Gash model requires few input variables and is formulated for a sparse canopy. The WiMo model optimizes the canopy storage capacity for the maximum wind speed during each storm. All models showed marked underestimates and overestimates for individual storms when the measured ratio of interception to gross precipitation was far more or less, respectively, than the specified fraction of canopy cover. The models predicted the percentage of total gross precipitation (PG) intercepted to within the probable standard error (8.1%) of the measured value: the Mulder model overestimated the measured value by 0.1% of PG; the WiMo model underestimated by 0.6% of PG; and the Gash model underestimated by 1.1% of PG. The WiMo model’s advantage over the Gash model indicates that the canopy storage capacity increases logarithmically with the maximum wind speed. This study has demonstrated that dormant-season precipitation interception in a leafless deciduous forest may be satisfactorily predicted by existing canopy interception models.