Assessment of nonlinear trends and seasonal variations in global sea level using singular spectrum analysis and wavelet multiresolution analysis

The main purpose of this paper is to apply the singular spectrum analysis (SSA), based on the phase space, and the wavelet multiresolution analysis (WMA), based on the frequency space, to the weekly time series of global sea level anomaly (GSLA) derived from satellite altimetry data over 1993–2013, in order to assess its nonlinear trends and its seasonal signals. The SSA results show that the GSLA time series is mainly dominated by a nonlinear trend explaining 89.89 % of the total GSLA variability, followed by annual and semi-annual signals with an explained variance of 9.15 and 0.32 %, respectively. For the annual signal, both methods give similar results. Its amplitude is less than 14 mm with an average of about 11 mm, and its minimum and maximum occur in April and October, respectively. The calculation of sea level trend, by both methods, is direct without removing the seasonal signals from the original GSLA time series as the most commonly used in the literature. The global sea level trend obtained from the WMA is about 2.52 ± 0.01 mm/year which is in good agreement with 2.94 ± 0.05 mm/year estimated from the SSA. Furthermore, the SSA method is most suitable for seasonal adjustment, and the WMA method is more useful for providing the different rates of sea level rise. Indeed, the WMA reveals that the global sea level has risen with the rate of 3.43 ± 0.01 mm/year from January/1993 to January/1998, 0.66 ± 0.01 mm/year from February/1998 to May/2000, 5.71 ± 0.03 mm/year from June/2000 to October/2003, and 1.57 ± 0.01 mm/year since January/2004.     

First record of Australian bonito,Sarda Australis,from New Zealand

The range of the Australian bonito, Sarda australis (Macleay, 1880), previously known only from eastern Australia and Norfolk Island, is now extended to include New Zealand. Data on two specimens examined from northern New Zealand are presented.     

Effects of vegetation cover on summer climate in China during 1982–2001

In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001 and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to 1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation) in most zones of China; these suggest that, when the vegetation cover increases, the summer precipitation will increase, and the lagged correlations show a significant difference between zones. The stronger correlations between NDVI in previous season and summer climate occur in three zones (Mid-temperate zone, Warm-temperate zone and Plateau climate zone), and this implies that vegetation changes have more sensitive feedback effects on climate in the three zones in China.     

Extraction and accuracy assessment of high-resolution DEM and derived orthoimages from ALOS-PRISM data over Sahel-Doukkala (Morocco)

In Sahel-Doukkala, which is characterized by lands of a relatively low relief, global DEMs and DEMs generated from digitizing topographic maps, have been the primary source of several multidisciplinary researches. Although these products present a great value of the conducted research, the level of the given accuracy is not sufficient enough for detailed geospatial analysis. These requirements led us to generate a high-resolution DEM as an alternative of available global DEMs or/and DEMs generated from digitizing topographic maps. In this study, we present a workflow to extract high-resolution DEM at 5 m resolution and derived orthoimages from ALOS-PRISM data over Sahel-Doukkala, through photogrammetric techniques, using a variation of GCPs obtained from topographic maps at scale 1:25,000. The accuracy of the generated products is reported according to NSSDA standards. Using ten GCPs, a PRISM-DEM with 3.88 m vertical accuracy and 11.60 m horizontal accuracy, both at 95% confidence level is obtained. This DEM will serve as base dataset for further detailed geospatial analysis and mapping applications in order to identify the relationship between surface parameters and groundwater, and also to assess and understand all factors influencing the development of karst landscapes and consequently subsurface stability in the investigated area.     

Chelonodontops bengalensis (Tetraodontiformes: Tetraodontidae): A New Species of Puffer Fish from the Northern Bay of Bengal Based on Morphology and DNA Barcode

Ocean Science Journal - The new puffer fish species Chelonodontops bengalensis (Pisces: Tetraodontidae) is described from two specimens collected on the southwest coast of the Bay of Bengal,...