Simulating rainfall time-series: how to account for statistical variability at multiple scales?

Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is the modified Markov model, belonging to the family of Markov-chain based techniques, which introduces non-stationarity in the chain parameters to preserve the long-term behavior of rainfall. The second technique is direct sampling, based on multiple-point statistics, which aims at simulating a complex statistical structure by reproducing the same data patterns found in a training data set. The two techniques are compared by first simulating a synthetic daily rainfall time-series showing a highly irregular alternation of two regimes and then a real rainfall data set. This comparison allows analyzing the efficiency of different elements characterizing the two techniques, such as the application of a variable time dependence, the adaptive kernel smoothing or the use of low-frequency rainfall covariates. The results suggest, under different data availability scenarios, which of these elements are more appropriate to represent the rainfall amount probability distribution at different scales, the annual seasonality, the dry-wet temporal pattern, and the persistence of the rainfall events.     

Upper layer circulation,hydrography, and biological response of the Andaman waters during winter monsoon based on in situ and satellite observations

Upper layer circulation, hydrography, and biological response of Andaman waters during winter monsoon are assessed based on the observations carried out onboard FORV Sagar Sampada during January 2009 and November–December 2011. Cool and dry air carried by the moderate winds (6 m/s) from north and northeast indicates the influence of northeast monsoon (NEM) in the area during the observation time. The characteristics of physical parameters and the water mass indicate that the southeastern side is dominated by the less saline water from South China Sea intruded through the Malacca Strait, whereas the northeast is influenced by the freshwater from Ayeyarwady-Salween river system. The western side of the Andaman and Nicobar Islands exhibits similar properties of Bay of Bengal (BoB) water as evidenced in the T-S relation. Circulation pattern is uniform for the upper 88 m and is found to be more geostrophic rather than wind driven. Magnitude of the current velocity varies between 100 and 900 mm/s in November–December 2011 with strong current (900 mm/s) near Katchal and Nancowry islands and 100 and 1000 mm/s in January 2009 recording strong current (1000 mm/s) near the Little Nicobar Island. The Andaman waters are observed as less productive during the season based on the satellite-derived surface chl-a (0.1–0.4 mg/m³) and column-integrated primary productivity (PP) (100–275 mgC/m²/d).     

Accuracy improvement of ASTER stereo satellite generated DEM using texture filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment i...     

Forecasting hourly particulate matter concentrations based on the advanced multivariate methods

In this study, several multivariate methods were used for forecasting hourly PM₁₀ concentrations at four locations based on SO₂ and meteorological data from the previous period. According to the results, boosted decision trees and multi-layer perceptrons yielded the best predictions. The forecasting performances were similar for all examined locations, despite the additional PM₁₀ spatio-temporal analysis showed that the sites were affected by different emission sources, topographic and microclimatic conditions. The best prediction of PM₁₀ concentrations was obtained for industrial sites, probably due to the simplicity and regularity of dominant pollutant emissions on a daily basis. Conversely, somewhat weaker forecast accuracy was achieved at urban canyon avenue, which can be attributed to the specific urban morphology and most diverse emission sources. In conclusion to this, the integration of advanced multivariate methods in air quality forecasting systems could enhance accuracy and provide the basis for efficient decision-making in environmental regulatory management.     

Extraction and analysis of geological lineaments of Kolli hills,Tamil Nadu: a study using remote sensing and GIS

The aim of the present study is to investigate the lineaments of Kolli hills of Tamil Nadu State for which CARTOSAT-1 satellite’s DEM output has been made use of. The extracted lineaments were analysed using ArcGIS and Rockworks software. The total number and length of lineaments are 523 and 943.81 km, respectively. Shorter lineaments constitute about 3/4th of the total number of lineaments. The density of the lineaments varies from 0 to 7.41 km/km², and areas of very high to high density are restricted to the south central, central and north eastern parts, and these areas reflect the high degree of rock fracturing and shearing which makes these areas unsuitable for the construction of dams and reservoirs. However, these areas could be targeted for groundwater exploitation as they possess higher groundwater potential. The lineaments are oriented in diverse directions. However, those orienting in ENEWSW, NE-SW and NW-SE are predominating followed by those oriented in sub E-W and sub N-S directions. These orientations corroborate with results of previous regional studies and with orientations of prominent geological structures and features of the study area. Distinct variation in the predominant orientations of lineaments of varied sizes is observed, while the shorter ones are oriented in either NW-SE or NNW-SSE directions, the longer ones are oriented in either NE-SW or ENE-WSW. A comparative analysis of lineament datasets of the eight azimuth angles and the final lineament map underlines the need to extract lineaments from various azimuth angles to get a reliable picture about the lineaments.     

Seismic vulnerability assessment in the new urban area of Diriyah Governorate,Riyadh, Saudi Arabia

Nine seismic refraction profiles were conducted and processed to study the near-surface sediments in the new urban area of Diriyah. The 2D geoseismic models illustrate two layers: a surface layer of soft sediments and weathered to hard limestone bedrock. Moreover, microtremor measurements were performed at 38 sites for 40 min using three-component seismographs and processed to assess the peak spectral amplitude and the corresponding fundamental resonance frequency. The seismic vulnerability index at each measurement site was estimated. These results correlate well with the geotechnical borehole data. The north-western zone is highly vulnerable due to the great thickness of the soft sediments.     

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

Determination of Ocean Wave Period from Altimeter Data Using Wave-Age Concept

This study makes use of the concept of wave age in estimating ocean wave period from space borne altimeter measurements of backscattering coefficient and significant wave height. Introduction of wave age allowed better accounting of the difference between swells and wind waves. Using two years (1998 and 1999) data of TOPEX/Poseidon altimeter and ocean data buoy observations in the Indian Ocean, coefficients were generated for wave period, which were subsequently tested against data for the years 2000 and 2001. The results showed the wave period accuracy to be of the order of 0.6 sec (against 1.3 sec obtained with the semiempirical approach, reported earlier).     

Numerical Simulation of North Indian Ocean State Prior to the Onset of SW Monsoon Using SSM/I Winds

The Sea Surface Temperatures (SST) and currents are simulated over the north Indian Ocean, during the onset phase of southwest monsoon for the three years 1994, 1995, and 1996, using daily Special Sensor Microwave/Imager (SSM/I) winds and National Center for Environmental Prediction (NCEP) heat fluxes as forcings in the 2½ layer thermodynamic numerical ocean model. The results are discussed for the 30-day period from 16 May to 13 June for all the three years, to determine the ocean state during the onset phase of SW monsoon. The maximum variability in the simulated SST is found along the Somali coast, Indian coasts, and equatorial regions. The maximum SST in the North Arabian Sea is found to be greater than 30°C and minimum SST in the west equatorial region is 25°C during the onset phase of all three years. Model SSTs are in agreement with Reynolds SST. SST gradients in the north-south as well as in the east-west directions, west of 80°E are found to change significantly prior to the onset. It can be inferred from the study that the SST gradient of 2.5°C/2000 km is seen due north and due west of the region 2° - 7°S, 60° - 65°E, about 8 to 10 days prior to the arrival of SW monsoon near Kerala coast. Upper and lower layer circulation fields do not show prominent interannual variability.     

Inter-Comparison of Numerical Model Generated Surface Winds with QuikSCAT Winds over the Indian Ocean

The accurate surface wind in the equatorial Indian Ocean is crucial for modeling ocean circulation over this region. In this study, the surface wind analysis generated at the European Center for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) are compared with NASA QuikSCAT satellite derived Level2B (swath level) and Level3 (gridded) surface winds for the year 2005. It is observed that the ECMWF winds exhibit speed bias of 1.5 m/s with respect to QuikSCAT Level3 in the southern equatorial Indian Ocean. The NCEP winds are found to exhibit speed bias (1.0–1.5 m/s) in the southern equatorial Indian Ocean specifically during January–February 2005. The biases are also observed in the analysis when compared with Level2B product as well; however, it is less in comparison to Level3 products. The amplitude of daily variations of both ECMWF and NCEP wind speed in Bay of Bengal and parts of the Arabian Sea is about 80% of that in QuikSCAT, while in the equatorial Indian Ocean it is about 60% of that of QuikSCAT.