114 resultados para equatorial climate


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A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.

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The capacity of species to track shifting climates into the future will strongly influence outcomes for biodiversity under a rapidly changing climate. However, we know remarkably little about the dispersal abilities of most species and how these may be influenced by climate change. Here we show that climate change is projected to substantially reduce the seed dispersal services provided by frugivorous vertebrates in rainforests across the Australian Wet Tropics. Our model projections show reductions in both median and long-distance seed dispersal, which may markedly reduce the capacity of many rainforest plant species to track shifts in suitable habitat under climate change. However, our analyses suggest that active management to maintain the abundances of a small set of important frugivores under climate change could markedly reduce the projected loss of seed dispersal services and facilitate shifting distributions of rainforest plant species.

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In this study, the Tropical Rainfall Measurement Mission based Microwave Imager estimates (2A12) have been used to compare and contrast the characteristics of cloud liquid water and ice over the Indian land region and the ocean surrounding it, during the premonsoon (May) and monsoon (June-September) seasons. Based on the spatial homogeneity of rainfall, we have selected five regions for our study (three over ocean, two over land). Comparison across three ocean regions suggests that the cloud liquid water (CLW) over the orographically influenced Arabian Sea (close to the Indian west coast) behaves differently from the CLW over a trapped ocean (Bay of Bengal) or an open ocean (equatorial Indian Ocean). Specifically, the Arabian Sea region shows higher liquid water for a lower range of rainfall, whereas the Bay of Bengal and the equatorial Indian Ocean show higher liquid water for a higher range of rainfall. Apart from geographic differences, we also documented seasonal differences by comparing CLW profiles between monsoon and premonsoon periods, as well as between early and peak phases of the monsoon. We find that the CLW during the lean periods of rainfall (May or June) is higher than during the peak and late monsoon season (July-September) for raining clouds. As active and break phases are important signatures of the monsoon progression, we also analysed the differences in CLW during various phases of the monsoon, namely, active, break, active-to-break and break-to-active transition phases. We find that the cloud liquid water content during the break-to-active transition phase is significantly higher than during the active-to-break transition phase over central India. We speculate that this could be attributed to higher amount of aerosol loading over this region during the break phase. We lend credence to this aerosol-CLW/rain association by comparing the central Indian CLW with that over southeast Asia (where the aerosol loading is significantly smaller) and find that in the latter region, there are no significant differences in CLW during the different phases of the monsoon. While our hypothesis needs to be further investigated with numerical models, the results presented in this study can potentially serve as a good benchmark in evaluating the performance of cloud resolving models over the Indian region.

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Eleven GCMs (BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1) were evaluated for India (covering 73 grid points of 2.5 degrees x 2.5 degrees) for the climate variable `precipitation rate' using 5 performance indicators. Performance indicators used were the correlation coefficient, normalised root mean square error, absolute normalised mean bias error, average absolute relative error and skill score. We used a nested bias correction methodology to remove the systematic biases in GCM simulations. The Entropy method was employed to obtain weights of these 5 indicators. Ranks of the 11 GCMs were obtained through a multicriterion decision-making outranking method, PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation). An equal weight scenario (assigning 0.2 weight for each indicator) was also used to rank the GCMs. An effort was also made to rank GCMs for 4 river basins (Godavari, Krishna, Mahanadi and Cauvery) in peninsular India. The upper Malaprabha catchment in Karnataka, India, was chosen to demonstrate the Entropy and PROMETHEE-2 methods. The Spearman rank correlation coefficient was employed to assess the association between the ranking patterns. Our results suggest that the ensemble of GFDL2.0, MIROC3, BCCR-BCCM2.0, UKMO-HADCM3, MPIECHAM4 and UKMO-HADGEM1 is suitable for India. The methodology proposed can be extended to rank GCMs for any selected region.

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Sugganahalli, a rural vernacular community in a warm-humid region in South India, is under transition towards adopting modern construction practices. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete (RCC)/tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Vernacular architecture evolves adopting local resources in response to the local climate adopting passive solar designs. This paper investigates the effectiveness of passive solar elements on the indoor thermal comfort by adopting modern climate-responsive design strategies. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Age-old traditional design considerations were found to concur with modern understanding into bio-climatic response and climate-responsiveness. Modern transitions were found to increase the average indoor temperatures in excess of 7 degrees C. Such transformations tend to shift the indoor conditions to a psychrometric zone that is likely to require active air-conditioning. Also, the surveyed thermal sensation votes were found to lie outside the extended thermal comfort boundary for hot developing countries provided by Givoni in the bio-climatic chart.

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Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric Research to investigate the global hydrological implications of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2, global mean radiative forcing is larger when aerosol concentration is maximum at the poles leading to a warmer global mean climate and consequently an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature and 3% in precipitation changes by varying the distribution pattern in our simulations: this range is about 50% of the climate change from a doubling of CO2. Hence, our study demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is an idealized study and thus not all important realistic climate processes are modeled.

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Motivated by observations of the mean state of tropical precipitable water (PW), a moist, first baroclinic mode, shallow-water system on an equatorial beta-plane with a background saturation profile that depends on latitude and longitude is studied. In the presence of a latitudinal moisture gradient, linear analysis of the non-rotating problem reveals large-scale, symmetric, eastward and westward propagating unstable modes. The introduction of a zonal moisture gradient breaks the east-west symmetry of the unstable modes. The effects of rotation are then included by numerically solving the resulting eigenvalue problem on an equatorial beta-plane. With a purely meridional moisture gradient, the system supports large-scale, low-frequency, eastward and westward moving neutral modes. Some of the similarities, and some of the discrepancies of these modes with intraseasonal tropical waves are pointed out. Finally, a zonal moisture gradient in the presence of rotation renders some of the aforementioned neutral modes unstable. In particular, according to observations of large-scale, low-frequency tropical variability, it is seen that regions where the background saturation profile increases (decreases) to the east favour eastward (westward) moving moist modes.

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Developments in the statistical extreme value theory, which allow non-stationary modeling of changes in the frequency and severity of extremes, are explored to analyze changes in return levels of droughts for the Colorado River. The transient future return levels (conditional quantiles) derived from regional drought projections using appropriate extreme value models, are compared with those from observed naturalized streamflows. The time of detection is computed as the time at which significant differences exist between the observed and future extreme drought levels, accounting for the uncertainties in their estimates. Projections from multiple climate model-scenario combinations are considered; no uniform pattern of changes in drought quantiles is observed across all the projections. While some projections indicate shifting to another stationary regime, for many projections which are found to be non-stationary, detection of change in tail quantiles of droughts occurs within the 21st century with no unanimity in the time of detection. Earlier detection is observed in droughts levels of higher probability of exceedance. (C) 2014 Elsevier Ltd. All rights reserved.

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The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

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The nonlinear response of a spherical shallow water model to an imposed heat source in the presence of realistic zonal mean zonal winds is investigated numerically. The solutions exhibit elongated, meridionally tilted ridges and troughs indicative of a poleward dispersion of wave activity. As the speed of the jets is increased, the equatorial Kelvin wave is unaffected but the global Rossby wave train coalesces to form a compact, amplified quadrupole structure that bears a striking resemblance to the observed upper level structure of the Madden-Julian oscillation. In the presence of strong subtropical westerly jets, the advection of planetary vorticity by the meridional flow and relative vorticity by the zonally averaged background flow conspire to create the distinctive quadrupole configuration of flanking Rossby waves.

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Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.

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AimBiodiversity outcomes under global change will be influenced by a range of ecological processes, and these processes are increasingly being considered in models of biodiversity change. However, the level of model complexity required to adequately account for important ecological processes often remains unclear. Here we assess how considering realistically complex frugivore-mediated seed dispersal influences the projected climate change outcomes for plant diversity in the Australian Wet Tropics (all 4313 species). LocationThe Australian Wet Tropics, Queensland, Australia. MethodsWe applied a metacommunity model (M-SET) to project biodiversity outcomes using seed dispersal models that varied in complexity, combined with alternative climate change scenarios and habitat restoration scenarios. ResultsWe found that the complexity of the dispersal model had a larger effect on projected biodiversity outcomes than did dramatically different climate change scenarios. Applying a simple dispersal model that ignored spatial, temporal and taxonomic variation due to frugivore-mediated seed dispersal underestimated the reduction in the area of occurrence of plant species under climate change and overestimated the loss of diversity in fragmented tropical forest remnants. The complexity of the dispersal model also changed the habitat restoration approach identified as the best for promoting persistence of biodiversity under climate change. Main conclusionsThe consideration of complex processes such as frugivore-mediated seed dispersal can make an important difference in how we understand and respond to the influence of climate change on biodiversity.

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Rivers of the world discharge about 36000 km 3 of freshwater into the ocean every year. To investigate the impact of river discharge on climate, we have carried out two 100 year simulations using the Community Climate System Model (CCSM3), one including the river runoff into the ocean and the other excluding it. When the river discharge is shut off, global average sea surface temperature (SST) rises by about 0.5 degrees C and the Indian Summer Monsoon Rainfall (ISMR) increases by about 10% of the seasonal total with large increase in the eastern Bay of Bengal and along the west coast of India. In addition, the frequency of occurrence of La Nina-like cooling events in the equatorial Pacific increases and the correlation between ISMR and Pacific SST anomalies become stronger. The teleconnection between the SST anomalies in the Pacific and monsoon is effected via upper tropospheric meridional temperature gradient and the North African-Asian Jet axis.

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Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.