88 resultados para Tyendinaga Indian Reserve


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Uncertainties in changes to the spatial distribution and magnitude of the heaviest extremes of daily monsoon rainfall over India are assessed in the doubled CO2 climate change scenarios in the IPCC Fourth Assessment Report. Results show diverse changes to the spatial pattern of the 95th and 99th subseasonal percentiles, which are strongly tied to the mean precipitation change during boreal summer. In some models, the projected increase in heaviest rainfall over India at CO2 doubling is entirely predictable based upon the surface warming and the Clausius–Clapeyron relation, a result which may depend upon the choice of convection scheme. Copyright © 2009 Royal Meteorological Society and Crown Copyright

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Changes to the behaviour of subseasonal precipitation extremes and active-break cycles of the Indian summer monsoon are assessed in this study using pre-industrial and 2 × CO2 integrations of the Hadley Centre coupled model HadCM3, which is able to simulate the monsoon seasonal cycle reasonably. At 2 × CO2, mean summer rainfall increases slightly, especially over central and northern India. The mean intensity of daily precipitation during the monsoon is found to increase, consistent with fewer wet days, and there are increases to heavy rain events beyond changes in the mean alone. The chance of reaching particular thresholds of heavy rainfall is found to approximately double over northern India, increasing the likelihood of damaging floods on a seasonal basis. The local distribution of such projections is uncertain, however, given the large spread in mean monsoon rainfall change and associated extremes amongst even the most recent coupled climate models. The measured increase of the heaviest precipitation events over India is found to be broadly in line with the degree of atmospheric warming and associated increases in specific humidity, lending a degree of predictability to changes in rainfall extremes. Active-break cycles of the Indian summer monsoon, important particularly due to their effect on agricultural output, are shown to be reasonably represented in HadCM3, in particular with some degree of northward propagation. We note an intensification of both active and break events, particularly when measured against the annual cycle, although there is no suggestion of any change to the duration or likelihood of monsoon breaks. Copyright © 2009 Royal Meteorological Society

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Whereas the predominance of El Niño Southern Oscillation (ENSO) mode in the tropical Pacific sea surface temperature (SST) variability is well established, no such consensus seems to have been reached by climate scientists regarding the Indian Ocean. While a number of researchers think that the Indian Ocean SST variability is dominated by an active dipolar-type mode of variability, similar to ENSO, others suggest that the variability is mostly passive and behaves like an autocorrelated noise. For example, it is suggested recently that the Indian Ocean SST variability is consistent with the null hypothesis of a homogeneous diffusion process. However, the existence of the basin-wide warming trend represents a deviation from a homogeneous diffusion process, which needs to be considered. An efficient way of detrending, based on differencing, is introduced and applied to the Hadley Centre ice and SST. The filtered SST anomalies over the basin (23.5N-29.5S, 30.5E-119.5E) are then analysed and found to be inconsistent with the null hypothesis on intraseasonal and interannual timescales. The same differencing method is then applied to the smaller tropical Indian Ocean domain. This smaller domain is also inconsistent with the null hypothesis on intraseasonal and interannual timescales. In particular, it is found that the leading mode of variability yields the Indian Ocean dipole, and departs significantly from the null hypothesis only in the autumn season.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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The Youngest Toba Tuff (YTT) eruption, which occurred in Indonesia 74,000 years ago, is one of Earth's largest known volcanic events. The effect of the YTT eruption on existing populations of humans, and accordingly on the course of human evolution, is debated. Here we associate the YTT with archaeological assemblages at Jwalapuram, in the Jurreru River valley of southern India. Broad continuity of Middle Paleolithic technology across the YTT event suggests that hominins persisted regionally across this major eruptive event.

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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.

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Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.

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The question of whether and how tropical Indian Ocean dipole or zonal mode (IOZM) interannual variability is independent of El Nino-Southern Oscillation (ENSO) variability in the Pacific is addressed in a comparison of twin 200-yr runs of a coupled climate model. The first is a reference simulation, and the second has ENSO-scale variability suppressed with a constraint on the tropical Pacific wind stress. The IOZM can exist in the model without ENSO, and the composite evolution of the main anomalies in the Indian Ocean in the two simulations is virtually identical. Its growth depends on a positive feedback between anomalous equatorial easterly winds, upwelling equatorial and coastal Kelvin waves reducing the thermocline depth and sea surface temperature off the coast of Sumatra, and the atmospheric dynamical response to the subsequently reduced convection. Two IOZM triggers in the boreal spring are found. The first is an anomalous Hadley circulation over the eastern tropical Indian Ocean and Maritime Continent, with an early northward penetration of the Southern Hemisphere southeasterly trades. This situation grows out of cooler sea surface temperatures in the southeastern tropical Indian Ocean left behind by a reinforcement of the late austral summer winds. The second trigger is a consequence of a zonal shift in the center of convection associated with a developing El Nino, a Walker cell anomaly. The first trigger is the only one present in the constrained simulation and is similar to the evolution of anomalies in 1994, when the IOZM occurred in the absence of a Pacific El Nino state. The presence of these two triggers-the first independent of ENSO and the second phase locking the IOZM to El Nino-allows an understanding of both the existence of IOZM events when Pacific conditions are neutral and the significant correlation between the IOZM and El Nino.

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In 2002 India experienced a severe drought, one among the five worst droughts since records began in 1871, notable for its countrywide influence. The drought was primarily due to an unprecedented break in the monsoon during July, which persisted for almost the whole month and affected most of the sub-continent. The failure of the monsoon in 2002 was not predicted and India was not prepared for the devastating impacts on, for example, agriculture. This paper documents the evolution of the 2002 Indian summer monsoon and considers the possible factors that contributed to the drought and the failure of the forecasts. The development of the 2002/2003 El Nino and the unusually high levels of Madden-Julian Oscillation (MJO) activity during the monsoon season are identified as the central players. The 2002/2003 El Nino was characterised by very high sea-surface temperatures (SSTs) in the central Pacific that developed rapidly during the monsoon season. It is suggested that the unusual character of the developing El Nino was associated with the MJO and was a consequence of the eastward extension of the West Pacific Warm Pool, brought about primarily by a series of westerly wind events (WWEs) as part of the eastward movement of the active phase of the MJO. During the boreal summer, the MJO is usually characterised by northward movement, but in 2002 the northward component of the MJO was weak and the MJO was dominated by a strong eastward component, probably driven by the abnormally high SSTs in the central Pacific. It is suggested that a positive feedback existed between the developing El Nino and the eastward component of the MJO, which weakened the active phases of the monsoon. In particular, the unprecedented monsoon break in July could be associated with the juxtaposition of strong MJO activity with a developing El Nino, both of which interfered constructively with each other to produce major perturbations to the distribution of tropical heating. Subsequently, the main impact of the developing El Nino was a modulation of the Walker circulation that led to the overall suppression of the Indian monsoon during thess latter part of the season. It is argued that the unique combination of a rapidly developing El Nino and strong MJO activity, which was timed within the seasonal cycle to have maximum impact on the Indian summer monsoon, meant that prediction of the prolonged break in July and the seasonally deficient rainfall was a challenge for both the empirical and dynamical forecasting systems. Copyright (C) 2006 Royal Meteorological Society.