Concurrent Use of OSCAT and AltiKa to Characterize Antarctic Ice Surface Features

Radar altimetry provides an important geophysical parameter, backscatter coefficient (σ₀), which is useful in studying target surface characteristics. Ku-band (Oceansat-2 scatterometer- OSCAT) and Ka-band (SARAL-AltiKa altimeter) data are concurrently used to characterize polar surface features over the Antarctic region. Maximum-likelihood classification has been employed to classify combined data set (AltiKa and OSCAT) for discrimination among sea ice, open water, and ice sheet (interior and exterior). The sea ice region obtained using the current approach has been compared with sea ice boundary derived from passive microwave data.     

Assessment of Indian summer monsoon simulation by Community Atmosphere Model (CAM3)

Seasonal prediction of Indian Summer Monsoon (ISM) has been attempted for the current year 2011 using Community Atmosphere Model (CAM) developed at the National Centre for Atmospheric Research (NCAR). First, 30?years of model climatology starting from 1981 to 2010 has been generated to capture the variability of ISM over the Indian region using 30 seasonal simulations. The simulated model climatology has been validated with different sets of observed climatology, and it was observed that the simulated climatological rainfall is affected by model bias. Subsequently, a bias correction procedure using the Tropical Rainfall Measuring Mission (TRMM) 3B43 rainfall has been proposed. The bias-corrected rainfall climatology shows both spatial and temporal variability of ISM satisfactorily. Further, four sets of 10-member ensemble simulations of ISM 2009 and 2010 have been performed in hindcast mode using observed sea surface temperature (SST) and persistence of April SST anomaly, and it has been found that the bias-corrected model rainfall captures the seasonal variability of ISM reasonably well with some discrepancies in these two contrasting monsoon years. With this positive background, the seasonal prediction of ISM 2011 has been carried out in forecast mode with the assumption of persistence of May SST anomaly from June through September 2011. The model assessment shows an 11% deficiency in All-India Rainfall (AIR) of ISM 2011. In particular, the monthly accumulated rains are predicted to be 101% (17.6?cm), 86% (24.3?cm), 83% (21.0?cm) and 95% (15.5?cm) of normal AIR for the months of June, July, August and September, respectively.     

Physical and biological response of the Arabian Sea to tropical cyclone Phyan and its implications

The response to the tropical cyclone Phyan, which developed in the eastern Arabian Sea during 9-11 November 2009, was rapid cooling of sea surface temperature (SST), enhancement of chlorophyll a and two-fold increase in net primary productivity (NPP). Cooling of SST was immediate in response to the strong wind-mixing, and the subsequent upward Ekman pumping sustained the cooling even after the dissipation of Phyan. The biological response mediated by the upward Ekman pumping driven vertical transport of subsurface nutrient showed a time lag of 3-4 days. The CO? flux to the atmosphere associated with Phyan was 0.123 Tg C, which accounted for ~85% of the total out-gassing from the eastern Arabian Sea during November. Thus, an increased occurrence of cyclones in a warming environment will lead to an enhanced biomass production and also increase in CO? out-gassing.     

Debris flow susceptibility zonation using statistical models in parts of Northwest Indian Himalayas—implementation,validation, and comparative evaluation

Natural Hazards - Debris flows are natural disasters with devastating consequences and frequent recurrence in changing climatic regime of the Indian Himalayas. Therefore, it is necessary to...     

Measurement and modeling of bed shear stress under solitary waves

Direct measurements of bed shear stresses (using a shear cell apparatus) generated by non-breaking solitary waves are presented. The measurements were carried out over a smooth bed in laminar and transitional flow regimes (~ 10⁴ < R_e < ~ 10⁵). Measurements were carried out where the wave height to water depth (h/d) ratio varied between 0.12 and 0.68; maximum near bed velocity varied between 0.16 m/s and 0.51 m/s and the maximum total shear stress (sum of skin shear stress and Froude–Krylov force) varied between 0.386 Pa and 2.06 Pa. The total stress is important in determining the stability of submarine sediment and in sheet flow regimes. Analytical modeling was carried out to predict total and skin shear stresses using convolution integration methods forced with the free stream velocity and incorporating a range of eddy viscosity models. Wave friction factors were estimated from skin shear stress at different instances over the wave (viz., time of maximum positive total shear stress, maximum skin shear stress and at the time of maximum velocity) using both the maximum velocity and the instantaneous velocity at that phase of the wave cycle. Similarly, force coefficients obtained from total stress were estimated at time of maximum positive and negative total stress and at maximum velocity. Maximum positive total shear stress was approximately 1.5 times larger than minimum negative total stress. Modeled and measured positive bed shear stresses are well correlated using the best convolution model, but the model underestimates the data by about 4%. Friction factors are dependent on the choice of normalizing using the maximum velocity, as is conventional, or the instantaneous velocity. These differ because the stress is not in phase with the velocity in general. Friction factors are consistent with previous data for monochromatic waves, and vary inversely with the square-root of the Reynolds number. The total shear stress leads the free stream fluid velocity by approximately 50°, whereas the skin friction shear stress leads by about 30°, which is similar to that reported by earlier researchers.     

On the application of similitude to installation operations of offshore steel jackets

The role of similitude in scaled simulation of major installation operations of offshore steel jackets, namely, loadout, launching and upending has been studied. The physical modelling can be looked upon both as an adjunct to numerical modelling using computers and also as an independent tool of investigation. The problems of design of models and of experiments are discussed and the prediction equations based on similitude are given.     

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.     

Directional spread parameter at intermediate water depth

The characteristics of directional spread parameters at intermediate water depth are investigated based on a cosine power ‘2s' directional spreading model. This is based on wave measurements carried out using a Datawell directional waverider buoy in 23 m water depth. An empirical equation for the frequency dependent directional spreading parameter is presented. Directional spreading function estimated based on the Maximum Entropy Method is compared with those obtained using a cosine power ‘2s' parameter model. A set of empirical equations relating the directional spreading parameter corresponding to the peak of wave spectrum to other wave parameters like significant wave height and period are obtained. It shows that the wave directional spreading at peak wave frequency can be related to the non-linearity parameter, which allows estimation of directional spreading without reference to wind information.     

Interpolation of wave heights

Remote sensing of waves often necessitates presentation of data in the form of wave height values grouped over large time intervals. This restricts their use to long-term applications only. This paper describes how such data can be made suitable for short-term usage in the field. Weekly mean significant wave heights were derived from their monthly mean observations with the help of different alternative techniques. These include model-free neural network schemes as well as model-based statistical and numerical methods. Superiority of neural networks was noted when the estimations were compared with corresponding observations. The network was trained using three different training algorithms, viz., error back propagation, conjugate gradient and cascade correlation. The technique of cascade correlation took minimum training time and showed better coefficient of correlation between observations and network output.