Age of Saurashtra miliolites by U-Th decay series methods: possible implications to their origin

The miliolite deposits of Saurashtra have been dated by²³⁴U,²³⁰Th,²³¹Pa and¹⁴C methods. Concordant ages of 10⁵ years using the U decay series isotopes are obtained which agree with the ages of the coral reefs of Okha-Dwaraka coast suggesting a contemporaneous origin for both. The lower¹⁴C ages (≤40,000 years) may be due to a recent influx of seawater or ground water. Quartz and clay minerals together constitute only ≤10% by weight, as such the aeolian characteristics of quartz grains may not be relevant to the origin of the miliolites.     

Analysis and farmers’ perception of climate change in the Kashmir Valley,India

Theoretical and Applied Climatology - Analysis of climatic variables is important for the detection and attribution of climate change trends and has received considerable attention from researchers...     

On rising temperature trends of Karachi in Pakistan

Karachi is the largest city of Pakistan. The temperature change in Karachi is studied in this research by analyzing the time series data of mean maximum temperature (MMxT), mean minimum temperature (MMiT) and mean annual temperature (MAT) from 1947 to 2005 (59 years). Data is analyzed in three parts by running linear regression and by taking anomalies of all time periods: (a) whole period from 1947–2005; (b) phase one 1947–1975 and (c) phase two 1976–2005. During 1947 to 2005 MMxT has increased about 4.6°C, MMiT has no change and MAT has increased 2.25°C. During 1947–1975, MMxT increased 1.9°C, in this period there is − 1.3°C decrease in MMiT and MAT has raised upto 0.3°C. During 1976–2005, the MMxT, MMiT and MAT increased 2.7°C, 1.2°C and 1.95°C, respectively. The analysis shows significantly the role of extreme vulnerability of MMxT in rising the temperature of Karachi than the MMiT.     

Performance of CMORPH,TMPA, and PERSIANN rainfall datasets over plain,mountainous, and glacial regions of Pakistan

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.     

ANALYSIS OF SURFACE AIR TEMPERATURE RECORDED IN LAHORE AND MIANWALI OVER THE PAST THREE DECADES

Surface air temperatures recorded over the past three decades at the weather stations located in Lahore (anindustrialized and densely populated city) and Mianwali (a small and sparsely populated city) were analyzed in order tostudy their climatic trend.Lahore,where meteorological data are recorded at two weather stations (city station and air-port station) indicates a cooling trend,of about 0.5℃ per record period of 1953—1992,for the airport station (31°31′N,74°24′E) and a slight warming trend,of about 0.2℃,for the city station (31°33′N,74°20′E) for the record period of 1950—1992.The Mianwali weather station (32°33′N,71°31′E) also shows a slight cooling trend,of about 0.4℃ per recordperiod of 1959—1992.The climatic variability at these stations was studied by computing seasonal and annual tempera-ture anomalies.The results are explained in terms of the local environmental conditions.     

Multi-factor impact analysis of agricultural production in Bangladesh with climate change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040–2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21 Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins’ hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.     

Validation of Chlorophyll-a Algorithms in the Coastal Waters of Bay of Bengal Initial Validation Results from OCM-2

In this paper we report chlorophyll measurements made during an ocean colour validation cruise in April 2011 of the research vessel, Sagar Paschimi in the coastal waters of Northern Bay of Bengal. The chlorophyll-a concentration in these waters range from 0.2 to 4.0 mg/m³. Chlorophyll-a concentration from OCM-2 was estimated using the global ocean colour algorithms namely, OC2, OC3, OC4 and Chl-a algorithms respectively. OCM data was processed using the global SeaWiFS Data Analysis System (SeaDAS) in which all the above mentioned algorithms are embedded for estimating the chlorophyll-a concentration. A comparative study was made between and in-situ and satellite derived chlorophyll-a concentration. Although the matchups between in-situ and satellite data from OCM-2 were sparse, it indicates that direct application of the standard SeaWiFS algorithm-the OC4-V4 algorithm—in the coastal waters of the Bay of Bengal will underestimate chlorophyll-a by up to 30%. The results show a good correlation with an R value of 0.61 using OC2 algorithm. However, all the other global algorithms over estimate the chlorophyll-a concentration even in low chlorophyll concentration range. The comparison between in-situ and all the existing chlorophyll algorithms shows the efficiency of these algorithms for quantification of chlorophyll in coastal waters and hence the need to develop regional algorithms and fluorescence based algorithms for better quantification.     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

An international comparison of governmental disclosure of hydrocarbon spills from offshore oil and gas installations

The cumulative effect of accidental spills from oil and gas extraction in the marine environment can have significant impacts on marine wildlife. Oil and gas operators are typically required to report spill data as part of a regulatory process. We conducted a survey of the public disclosure of hydrocarbon spill data for four countries, Australia, Canada, United Kingdom and United States. There was significant variation in the spill data statistics that were publicly reported by the regulators. No country provided full disclosure of spill data or follow-up actions taken by the regulator on their website. The lack of disclosure of spill data is of concern because the scale of environmental effects is more difficult to assess, insufficient information is available to assess the accuracy of predictions made in the environmental assessment process, and without consistency of spill reporting there is no method to compare regional differences of spill rates.     

Lead in Port Phillip Bay mussels

Lead levels in the indicator mussel Mytilus edulis, exceeds the WHO food standards in 19 of the 22 locations sampled in Port Phillip Bay, Melbourne. While this seriously reflects contamination of the food chain, LD₅₀ experiments on Mytilus indicate that the lethal effect of lead on this organism is much less severe than excessive doses of mercury, cadmium, copper or zinc. Little is known about the long term effects of lead on Mytilus.