284 resultados para Oceanic mythology.


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In this study, the fine-scale structure of the diurnal variability of ground-based lightning is systematically compared with satellite-based rain. At the outset, it is shown that tropical variability of lightning exhibits a prominent diurnal mode, much like rain. A comparison of the geographical distribution of the timing of the diurnal maximum shows that there is very good agreement between the two observables over continental and coastal regions throughout the tropics. Following this global tropical comparison, we focus on two regions, Borneo and equatorial South America, both of which show the interplay between oceanward and landward propagations of the phase of the diurnal maximum. Over Borneo, both rain and lightning clearly show a climatological cycle of ``breathing in'' (afternoon to early morning) and ``breathing out'' (morning to early afternoon). Over the equatorial east coast of South America, landward propagation is noticed in rain and lightning from early afternoon to early morning. Along the Pacific coast of South America, both rain and lightning show oceanward propagation. Though qualitatively consistent, over both regions the propagation is seen to extend further in rainfall. Additionally, given that lightning highlights vigorous convection, the timing of its diurnal maximum often precedes that of rainfall in the convective life cycle. (C) 2015 Elsevier B.V. All rights reserved.

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Interannual variation of Indian summer monsoon rainfall (ISMR) is linked to El Nino-Southern oscillation (ENSO) as well as the Equatorial Indian Ocean oscillation (EQUINOO) with the link with the seasonal value of the ENSO index being stronger than that with the EQUINOO index. We show that the variation of a composite index determined through bivariate analysis, explains 54% of ISMR variance, suggesting a strong dependence of the skill of monsoon prediction on the skill of prediction of ENSO and EQUINOO. We explored the possibility of prediction of the Indian rainfall during the summer monsoon season on the basis of prior values of the indices. We find that such predictions are possible for July-September rainfall on the basis of June indices and for August-September rainfall based on the July indices. This will be a useful input for second and later stage forecasts made after the commencement of the monsoon season.

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Multi-year observations from the network of ground-based observatories (ARFINET), established under the project `Aerosol Radiative Forcing over India' (ARFI) of Indian Space Research Organization and space-borne lidar `Cloud Aerosol Lidar with Orthogonal Polarization' (CALIOP) along with simulations from the chemical transport model `Goddard Chemistry Aerosol Radiation and Transport' (GOCART), are used to characterize the vertical distribution of atmospheric aerosols over the Indian landmass and its spatial structure. While the vertical distribution of aerosol extinction showed higher values close to the surface followed by a gradual decrease at increasing altitudes, a strong meridional increase is observed in the vertical spread of aerosols across the Indian region in all seasons. It emerges that the strong thermal convections cause deepening of the atmospheric boundary layer, which although reduces the aerosol concentration at lower altitudes, enhances the concentration at higher elevations by pumping up more aerosols from below and also helping the lofted particles to reach higher levels in the atmosphere. Aerosol depolarization ratios derived from CALIPSO as well as the GOCART simulations indicate the dominance of mineral dust aerosols during spring and summer and anthropogenic aerosols in winter. During summer monsoon, though heavy rainfall associated with the Indian monsoon removes large amounts of aerosols, the prevailing southwesterly winds advect more marine aerosols over to landmass (from the adjoining oceans) leading to increase in aerosol loading at lower altitudes than in spring. During spring and summer months, aerosol loading is found to be significant, even at altitudes as high as 4 km, and this is proposed to have significant impacts on the regional climate systems such as Indian monsoon. (C) 2015 Elsevier Ltd. All rights reserved.

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Long-term (2009-2012) data from ground-based measurements of aerosol black carbon (BC) from a semi-urban site, Pantnagar (29.0 degrees N, 79.5 degrees E, 231 m amsl), in the Indo-Gangetic Plain (IGP) near the Himalayan foothills are analyzed to study the regional characterization. Large variations are seen in BC at both diurnal and seasonal scales, associated with the mesoscale and synoptic meteorological processes, and local/regional anthropogenic activities. BC diurnal variations show two peaks (morning and evening) arising from the combined effects of the atmospheric boundary layer (ABL) dynamics and local emissions. The diurnal amplitudes as well as the rates of diurnal evolution are the highest in winter season, followed by autumn, and the lowest in summer-monsoon. BC exhibits nearly an inverse relation with mixing layer depth in all seasons; being strongest in winter (R-2 = 0.89) and weakest (R-2 = 0.33) in monsoon (July-August). Unlike BC, co-located aerosol optical depths (AOD) and aerosol absorption are highest in spring over IGP, probably due to the presence of higher abundances of aerosols (including dust) above the ABL (in the free troposphere). AOD (500 nm) showed annual peak (>0.6) in May-June, dominated by coarse mode, while fine mode aerosols dominated in late autumn and early winter. Aerosols profiles from CALIPSO show highest values close to the surface in winter/autumn, similar to the feature seen in surface BC, whereas at altitudes > 2 km, the extinction is maximum in spring/summer. WRF-Chem model is used to simulate BC temporal variations and then compared with observed BC. The model captures most of the important features of the diurnal and seasonal variations but significantly underestimated the observed BC levels, suggesting improvements in diurnal and seasonal varying BC emissions apart from the boundary layer processes. (C) 2015 Elsevier Ltd. All rights reserved.

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Aerosol loading over the South Asian region has the potential to affect the monsoon rainfall, Himalayan glaciers and regional air-quality, with implications for the billions in this region. While field campaigns and network observations provide primary data, they tend to be location/season specific. Numerical models are useful to regionalize such location-specific data. Studies have shown that numerical models underestimate the aerosol scenario over the Indian region, mainly due to shortcomings related to meteorology and the emission inventories used. In this context, we have evaluated the performance of two such chemistry-transport models: WRF-Chem and SPRINTARS over an India-centric domain. The models differ in many aspects including physical domain, horizontal resolution, meteorological forcing and so on etc. Despite these differences, both the models simulated similar spatial patterns of Black Carbon (BC) mass concentration, (with a spatial correlation of 0.9 with each other), and a reasonable estimates of its concentration, though both of them under-estimated vis-a-vis the observations. While the emissions are lower (higher) in SPRINTARS (WRF-Chem), overestimation of wind parameters in WRF-Chem caused the concentration to be similar in both models. Additionally, we quantified the under-estimations of anthropogenic BC emissions in the inventories used these two models and three other widely used emission inventories. Our analysis indicates that all these emission inventories underestimate the emissions of BC over India by a factor that ranges from 1.5 to 2.9. We have also studied the model simulations of aerosol optical depth over the Indian region. The models differ significantly in simulations of AOD, with WRF-Chem having a better agreement with satellite observations of AOD as far as the spatial pattern is concerned. It is important to note that in addition to BC, dust can also contribute significantly to AOD. The models differ in simulations of the spatial pattern of mineral dust over the Indian region. We find that both meteorological forcing and emission formulation contribute to these differences. Since AOD is column integrated parameter, description of vertical profiles in both models, especially since elevated aerosol layers are often observed over Indian region, could be also a contributing factor. Additionally, differences in the prescription of the optical properties of BC between the models appear to affect the AOD simulations. We also compared simulation of sea-salt concentration in the two models and found that WRF-Chem underestimated its concentration vis-a-vis SPRINTARS. The differences in near-surface oceanic wind speeds appear to be the main source of this difference. In-spite of these differences, we note that there are similarities in their simulation of spatial patterns of various aerosol species (with each other and with observations) and hence models could be valuable tools for aerosol-related studies over the Indian region. Better estimation of emission inventories could improve aerosol-related simulations. (C) 2015 Elsevier Ltd. All rights reserved.

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Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

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The derivation of a quasi-geostrophic system from the rotating shallow-water equations on a midlatitude -plane coupled with moisture is presented. Condensation is prescribed to occur whenever the moisture at a point exceeds a prescribed saturation value. It is seen that a slow condensation time-scale is required to obtain a consistent set of equations at leading order. Further, since the advecting wind fields are geostrophic, changes in moisture (and hence precipitation) occur only via non-divergent mechanisms. Following observations, a saturation profile with gradients in the zonal and meridional directions is prescribed. A purely meridional gradient has the effect of slowing down the dry Rossby waves, through a reduction in the equivalent gradient' of the background potential vorticity. A large-scale unstable moist mode results on the inclusion of a zonal gradient by itself, or in conjunction with a meridional moisture gradient. For gradients that are are representative of the atmosphere, the most unstable moist mode propagates zonally in the direction of increasing moisture, matures over an intraseasonal time-scale and has small phase speed.

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Anthropogenic aerosols play a crucial role in our environment, climate, and health. Assessment of spatial and temporal variation in anthropogenic aerosols is essential to determine their impact. Aerosols are of natural and anthropogenic origin and together constitute a composite aerosol system. Information about either component needs elimination of the other from the composite aerosol system. In the present work we estimated the anthropogenic aerosol fraction (AF) over the Indian region following two different approaches and inter-compared the estimates. We espouse multi-satellite data analysis and model simulations (using the CHIMERE Chemical transport model) to derive natural aerosol distribution, which was subsequently used to estimate AF over the Indian subcontinent. These two approaches are significantly different from each other. Natural aerosol satellite-derived information was extracted in terms of optical depth while model simulations yielded mass concentration. Anthropogenic aerosol fraction distribution was studied over two periods in 2008: premonsoon (March-May) and winter (November-February) in regard to the known distinct seasonality in aerosol loading and type over the Indian region. Although both techniques have derived the same property, considerable differences were noted in temporal and spatial distribution. Satellite retrieval of AF showed maximum values during the pre-monsoon and summer months while lowest values were observed in winter. On the other hand, model simulations showed the highest concentration of AF in winter and the lowest during pre-monsoon and summer months. Both techniques provided an annual average AF of comparable magnitude (similar to 0.43 +/- 0.06 from the satellite and similar to 0.48 +/- 0.19 from the model). For winter months the model-estimated AF was similar to 0.62 +/- 0.09, significantly higher than that (0.39 +/- 0.05) estimated from the satellite, while during pre-monsoon months satellite-estimated AF was similar to 0.46 +/- 0.06 and the model simulation estimation similar to 0.53 +/- 0.14. Preliminary results from this work indicate that model-simulated results are nearer to the actual variation as compared to satellite estimation in view of general seasonal variation in aerosol concentrations.

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The Southern Granulite Terrain in India is a collage of crustal blocks ranging in age from Archean to Neoproterozoic. This study investigate the tectonic evolution of one of the northernmost block- the Biligiri Block (BRB) through a multidisciplinary approach involving field investigation, petrographic studies, LA-ICPMS zircon U-Pb geochronology, Hf isotopic analyses, metamorphic P-T phase diagram computations, and crustal thickness modeling. The garnet bearing quartzofeldspathic gneiss from the central BRB preserve Mesoarchean magmatic zircons with ages between 3207 and 2806 Ma and positive epsilon Hf value (+2.7) which possibly indicates vestiges of a Mesoarchean primitive continental crust. The occurrence of quartzite-iron formation intercalation as well as ultramafic lenses along the western boundary of the BRB is interpreted to indicate that the Kollegal structural lineament is a possible paleo-suture. Phase diagram computation of a metagabbro from the southwestern periphery of the Kollegal suture zone reveals high-pressure (similar to 18.5 kbar) and medium-temperature (similar to 840 degrees C) metamorphism, likely during eastward subduction of the Western Dharwar oceanic crust beneath the Mesoarchean BRB. In the model presented here, slab subduction, melting and underplating processes generated arc magmatism and subsequent charnockitization within the BRB between ca. 2650 Ma and ca. 2498 Ma. These results thus reveal Meso- to Neoarchean tectonic evolution of the BRB. The spatial variation of crustal thickness, derived from flexure inversion technique, provides additional constraints on the tectonic linkage of the BRB with its surrounding terrains. In conjunction with published data, the Moyar and the Kollegal suture zones are considered to mark the trace of ocean closure along which the Nilgiri and Biligiri Rangan Blocks accreted on to the Western Dharwar Craton. (C) 2016 Elsevier B.V. All rights reserved.

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We have addressed the question of whether the massive deficit of 42% in rainfall over the Indian region in June 2014 can be attributed primarily to the El Nino. We have shown that the variation of convection over the Northern part of the Tropical West Pacific (NWTP: 120-150E, 20-30N) plays a major role in determining the all-India rainfall in June with deficit (excess) in rainfall associated with enhancement (suppression) of convection over NWTP. In June 2014, the outgoing long wave radiation (OLR) anomaly over this region was unfavourable, whereas in June 2015, the OLR anomaly over NWTP was favourable and the all-India rainfall was 16% higher than the long-term average. We find that during El Nino, when the convection over the equatorial central Pacific intensifies, there is a high propensity for intensification of convection over NWTP. Thus, El Nino appears to have an impact on the rainfall over the Indian region via its impact on the convection over the West Pacific, particularly over NWTP. This occurred in June 2014, which suggests that the large deficit in June 2014, could be primarily attributed to the El Nino acting via intensification of convection over NWTP.

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Vulnerability of communities and natural ecosystems, to potential impacts of climate change in developing countries like India, and the need for adaptation are rapidly emerging as central issues in the debate around policy responses to climate change. The present study presents an approach to identify and prioritize the most vulnerable districts, villages and households in Karnataka State, through a multi-scale assessment of inherent vulnerability to current climate variability. It also identifies the drivers of inherent vulnerability, thereby providing a tool for developing and mainstreaming adaptation strategies, in ongoing developmental or dedicated adaptation programmes. The multi-scale assessment was made for all 30 districts at the state level in Karnataka, about 1220 villages in Chikballapur district, and at the household level for two villages - Gundlapalli and Saddapalli - in Bagepalli taluk of Chikballapur district. At the district, village and household levels, low levels of education and skills are the dominant factors contributing to vulnerability. At the village and household level, the lack of income diversification and livelihood support institutions are key drivers of vulnerability. The approach of multi-scale vulnerability assessment facilitates identification and prioritization of the drivers of vulnerability at different scales, to focus adaptation interventions to address these drivers.

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Oceanic intraplate earthquakes are known to occur either on active ridge-transform structures or by reactivation of their inactive counterparts, generally referred to as fossil ridges or transforms. The Indian Ocean, one of the most active oceanic intraplate regions, has generated large earthquakes associated with both these types of structures. The moderate earthquake that occurred on 21 May 2014 (M-w 6.1) in the northern Bay of Bengal followed an alternate mechanism, as it showed no clear association either with active or extinct ridge-transform structures. Its focal depth of >50 km is uncommon but not improbable, given the similar to 90 Ma age of the ocean floor with 12-km-thick overlying sediments. No tectonic features have been mapped in the near vicinity of its epicenter, the closest being the 85 degrees E ridge, located similar to 100 km to its west, hitherto regarded as seismically inactive. The few earthquakes that have occurred here in the past are clustered around its southern or northern limits, and a few are located midway, at around 10 degrees N. The 2014 earthquake, sourced close to the northern cluster, seems to be associated with a northwest-southeast-oriented fracture, located on the eastern flanks of the 85 degrees E ridge. If this causal association is possible, we believe that reactivation of fossil hotspot trails could be considered as another mechanism for oceanic intraplate seismicity.