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Natural Hazards - Integrated disaster risk management in a changing climate is a key concern for disaster reduction and global sustainable development now and in the future. This study conducted... 相似文献
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Influence of SST biases on future climate change projections 总被引：1，自引：0，他引：1
We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection. 相似文献
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Farhat Abbas Ashfaq Ahmad Mohammad Safeeq Shafaqat Ali Farhan Saleem Hafiz Mohkum Hammad Wajid Farhad 《Theoretical and Applied Climatology》2014,116(3-4):671-680
Asymmetrical monsoons during the recent past have resulted into spatially variable and devastating floods in South Asia. Analysis of historic precipitation extremes record may help in formulating mitigation strategies at local level. Eleven indices of precipitation extremes were evaluated using RClimDex and daily time series data for analysis period of 1981–2010 from five representative cities across Punjab province of Pakistan. The indices include consecutive dry days, consecutive wet days, number of days above daily average precipitation, number of days with precipitation ≥10 mm, number of days with precipitation ≥20 mm, very wet days, extremely wet days, simple daily intensity index, maximum 1-day precipitation quantity, maximum 5 consecutive day precipitation quantity, and annual total wet-day precipitation. Mann-Kendall test and Sen’s slope extremes were used to detect trends in indices. Droughts and excessive precipitation were dictated by elevation from mean sea level with prolonged dry spells in southern Punjab and vice versa confirming spatial trends for precipitation extremes. However, no temporal trend was observed for any of the indices. Summer in the region is the wettest season depicting contribution of monsoons during June through August toward devastating floods in the region. 相似文献
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Kafeel Ahmad Zafar Iqbal Khan Asma Ashfaq Muhammad Ashraf Nudrat Aisha Akram Muhammad Sher Hazoor Ahmad Shad Vincenzo Tufarelli Antonio Lonigro Mariano Fracchiolla Eugenio Cazzato 《Environmental Earth Sciences》2017,76(8):322
Bio-concentration of elements such as Mo, As, Se, Fe, Cu, Zn, Ni and Pb was analyzed in spring onion (Allium fistulosum L.) in three different locations of central Punjab, Pakistan. At location GW, relatively low level of hazardous elements was found in spring onion, suggesting that groundwater is a safe source of water for irrigating food crops. The pH of soil at wastewater irrigation was found less acidic (pH 7.4) than the other sites. The range of concentration in the different samples of spring onion was as follows: 6.15–8.16 mg kg?1 for Mo, 2.77–4.28 mg kg?1 for As, 0.395–0.705 mg kg?1 for Se, 36.73–48.17 mg kg?1 for Fe, 10.58–16.26 mg kg?1 for Cu, 28.87–39.79 mg kg?1 for Zn, 6.66–8.75 mg kg?1 for Ni and 4.33–6.09 mg kg?1 for Pb, respectively. High bio-concentration of Zn (15.37) from soil to spring onion was found at canal water irrigated location. The estimated daily intake of metal for spring onion was less, but the health risk index was higher than 1 for Mo, As, Cu, Pb and Ni, respectively. This was due to higher proportion of spring onion in diet, which consequently increased the health risk index for metals. Therefore, it is recommended to avoid growing vegetables in untreated urban and rural wastewater containing elevated amounts of metals. 相似文献
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The geochemical baselines and distribution of 31 elements (Al, Fe, K, Na, Mg, Ca, Mn, Ba, Cr, Zr, Ni, Sr, Zn, Y, Li, Cu, Mo, Nb, Th, Co, Ga, W, Ta, Be, Ti, Ge, Se, Bi, Te, Sc and Re) and physico-chemical parameters of the tropical surface sediments of the Terengganu River basin, Malaysia, are reported. Sediments are sandy loam to sand in texture consisting of mostly quartz, low organic matter content (average-2.68%), low CEC (average-2.02 cmol(+)/kg) and mildly acidic pH1:5 (average-5.91). Concentrations of Mn, Fe, Ba, Cr, Ni, Cu, Mo and Se were measured to be above the environmental sediment quality criteria at various locations. Lake sediments registered significantly higher Al, Fe, Ti, Mg, Ca, Mn, Te and Sc concentrations as compared to the river sediments. Most of the elements investigated showed an association with silt size fraction (2-63 μm). Among the investigated metals, Mo and Fe concentrations showed an increasing (5-fold) and decreasing (3-fold) trend, respectively, along the river path from the upstream to the downstream depending on the stream pH-redox conditions. The enrichment factor values (EF 5) of Cr, Ni, Mo and Se indicated enrichment from anthropogenic activities. Alkali and alkali earth metals registered a significant depletion (EF values 0.7) as compared to the Earth's crust. Principal component analysis of the two main components (PC1, 87.4% and PC2, 8.7%) revealed a well-defined group of estuary sediments. Lake and river sediment sampling locations did not form defined groups revealing heterogeneity in the origin of geologic material and the in-stream geochemical processes. However, Cr, Ni, Mo and Se formed a separate group with elevated concentrations (e.g. Cr1,000 mg/kg) indicating contamination of sediments. This work presents the geochemical baselines of the tropical sediments as industrial development and urbanization along the north east coast of Peninsular Malaysia are advancing rapidly. 相似文献
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This study presents an investigation of the time to peak of unit response functions for design flood studies. It is based on an empirical analysis of observed rainfall–runoff data for 49 basins in the UK and explores the relationship between unit response time to peak (tp) and flood peak magnitude (Qp). The results show that tp varies significantly between events but suggest a systematic relationship between tp and Qp. The relationships which have been developed suggest that tp decreases with flood magnitude and approaches to an asymptotic value for very large values of Qp. These findings confirm numerous physical and field investigations and also support the reduction in response time for probable maximum flood (PMF) recommended in the Soil Conservation Services method, the Flood Studies Report method and the Flood Estimation Handbook. The findings also suggest that tp should be modified in unit hydrograph methods of design flood analysis for return periods that differ from those used in deriving unit hydrographs. A simple correction curve has been developed for adjusting tp according to the design flood return period. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
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This study is aimed at using the Empirical Line Method (ELM) to eliminate atmospheric effects with respect to visible and
near infrared bands of advanced spaceborne thermal emission and reflection radiometer (ASTER) and enhanced thematic mapper
plus (ETM+) data. Two targets (Amran limestone as light target and quartz-biotite-sericite-graphite schists as dark target),
which were widely exposed and easy to identify in the imagery were selected. The accuracy of the atmospheric correction method
was evaluated from three targets (vegetation cover, Amran limestone and Akbra shale) of the surface reflectance. Analytical
spectral devices (ASD) FieldSpec3 was used to measure the spectra of target samples. ETM+ data were less influenced by the
atmospheric effect when compared to ASTER data. Normalized differences vegetation indices (NDVI) displayed good results with
reflectance data when compared with digital number (DN) data because it is highly sensitive to ground truth reflectance (GTR).
Most of the differences observed before and after calibration of satellite images (ASTER and ETM+) were absorbed in the SWIR
region.
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Human activities have affected the urban environment resulting in a drastic change in the surface temperature. The impact of urban heat islands is noticeable in urban areas than in rural areas. The thermal band of Landsat 8 data is used to retrieve the spatial distribution of land surface temperature (LST) over Kohima Sadar for the years 2009, 2015 and 2020 with the Mono-window algorithm. Urban Thermal Field Variance Index (UTFVI) is used to assess the ecological condition in the area impacted by LST. Cartosat-1 Digital Elevation Model (Carto DEM) is used to understand the variations of LST and indices values with reference to the elevation profile located at different random points. The variations in the land cover are categorized as per the values of normalized difference vegetation index (NDVI) and built-up density index (BUI). This work estimates the influence of elevation over LST, vegetation, and the built-up area. Results implies a negative correlation between LST and NDVI whereas a positive correlation between LST and BUI. Likewise, NDVI and BUI show a strong negative correlation. It is observed that LST is independent of elevation profile but the variation of LST depends on the impact of change in topography urbanization, deforestation, and afforestation. There is no significant relationship of elevation with the variations in NDVI and BUI values. It is observed that the impact of emissivity influences the estimation of LST values. For the locations having the highest and lowest LST, NDVI, and BUI values, 50 random points are generated for the entire region, and validation is executed with the google earth historical image.
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