Suchandra Aich Bhowmick

Relative Calibration Using Natural Terrestrial Targets: A Preparation Towards Oceansat-2 Scatterometer

Scatterometer instruments transmit a series of microwave pulses and measure the returned echo to determine the normalized radar cross section (σ⁰) over the target to derive the near-ocean-surface wind vector. Accuracy of the derived wind vector over the data sparse oceans therefore depends on the accuracy of σ⁰ measurement. For this purpose, accurate calibration of the scatterometer is required. As a preparation toward calibration of the Oceansat-2 mission, of the Indian Space Research Organisation, a relative calibration technique has been proposed in this study by selecting homogeneous areas over the globe with isotropic radar response and temporally stable signature of σ⁰. For this purpose, the daily averaged σ⁰ and Level-2A (L2A) σ⁰ measurements of the QuikSCAT scatterometer have been used. Analyzing the monthly mean and standard deviation in σ⁰ for the period of 2005-2006, several regions are chosen which have a quasi-isotropic radar response and minimal temporal variation in σ⁰. The analysis shows that the selected areas over Antarctica and Greenland with permanent ice covers have temporally stable signatures of σ⁰. The regions like the Amazon forests and parts of Australia also show high temporal stability of σ⁰ but greater standard deviation than the snow-covered areas. The QuikSCAT L2A data have also been used to study the day-night variation and azimuthal dependence of the σ⁰ over these targets. The present work demonstrated that quasi-uniform natural sites such as Sahara, Amazon forest, Kutch, Greenland region, and Antarctica region, covering wide dynamic range of σ⁰, can be used for the purpose of calibration.

Cross Calibration of the OceanSAT -2 Scatterometer With QuikSCAT Scatterometer Using Natural Terrestrial Targets

The accuracy of ocean surface wind vectors measured by satellite-borne scatterometers depends on measured backscattering coefficient (σ^°). Hence, an in-flight calibration of a satellite scatterometer is essential as this is not guaranteed by its prelaunch absolute calibration. The postlaunch calibration of σ^° is also required to monitor the time evolution of the accuracy of measured σ ^°. This is performed using relative calibration over land targets with minor spatiotemporal variation of σ^°. A few such targets are the Amazon rainforest, Greenland, Antarctica, etc. In this paper, relative calibration of σ^° from the OceanSAT-2 Scatterometer (OSCAT) has been carried out by comparing it with a similar quantity from the Quick Scatterometer (QuikSCAT) for November 2009. The differences between the average σ^° of QuikSCAT and that of OSCAT have been calculated globally to check the overall consistency. Over the calibration sites, the differences are within ±0.25 dB. Histograms of differences in ascending/descending passes and fore/aft looks of OSCAT have also been analyzed over the calibration sites. These indicate that look bias in OSCAT σ^° is within the range of ±0.5 dB. It is also evident that pass biases, i.e., differences between ascending and descending passes, exist over the Amazon rainforest for both QuikSCAT and OSCAT. This diurnal variation in σ^° may go up to 1.25 dB in OSCAT. Further, computations of daily average and standard deviation over the calibration site show that mean OSCAT σ^° is consistent with mean QuikSCAT σ^°, whereas the standard deviation in OSCAT is marginally higher. Further, time-series analysis of OSCAT σ^° shows its temporal stability.

Geophysical Model Function for Wind Speed Retrieval from SARAL/AltiKa

With the launch of SARAL/AltiKa altimeter, efforts have been made to develop wind speed retrieval algorithms. Here we present two algorithms for estimating and validating wind speed from AltiKa. The first method is based on a theoretical Geophysical Model Function (GMF) using forward model simulations for Ka band specifications. The second is the model function developed using the matched database of input and output vectors of Normalized Radar Cross Section (NRCS) from AltiKa and wind speed measurements from concurrent Jason-2 altimeters. Since the NRCS depends on both the surface roughness due to surface wind speed and on mean square slope of the surfaces, the significant wave height is used along with wind speed for model development as an proxy variable. Both the theoretical and empirical GMFs are evaluated for retrieval of wind speed from AltiKa and validated with NDBC buoys data. The empirical model provide wind speed retrieval accuracy of 1.4 m/s. The accuracy of wind retrievals from theoretical model is also in the similar range (1.6 m/s), indicating the sound physical basis applicable for the future altimeters with various incidence angles. The retrieved wind speed is applied for various case studies, bringing out all the regional and global features quite well.

Sensitivity Study of a Coastal Wave Model for Prediction of Ocean Waves over Indian Ocean Region

In this article, sensitivity of the SWAN coastal wave model towards wind inputs and physics options has been performed over the Indian Ocean by forcing the model with analyzed GDAS winds. Wind forcing simulations show that the model is sensitive to the wind errors. The simulations obtained using different physics options have been compared with altimeter and in situ data. The study indicates that the model with Janssen physics options simulates the significant wave height with a fairly high degree of accuracy. It has also been observed that the simulations are not too sensitive to the choice of propagation schemes.

The Benefits of the Ka-Band as Evidenced from the SARAL/AltiKa Altimetric Mission: Scientific Applications

The India–France SARAL/AltiKa mission is the first Ka-band altimetric mission dedicated primarily to oceanography. The mission objectives were firstly the observation of the oceanic mesoscales but also global and regional sea level monitoring, including the coastal zone, data assimilation, and operational oceanography. SARAL/AltiKa proved also to be a great opportunity for inland waters applications, for observing ice sheet or icebergs, as well as for geodetic investigations. The mission ended its nominal phase after three years in orbit and began a new phase (drifting orbit) in July 2016. The objective of this paper is to highlight some of the most remarkable achievements of the SARAL/AltiKa mission in terms of scientific applications. Compared to the standard Ku-band altimetry measurements, the Ka-band provides substantial improvements in terms of spatial resolution and data accuracy. We show here that this leads to remarkable advances in terms of observation of the mesoscale and coastal ocean, waves, river water levels, ice sheets, icebergs, fine scale bathymetry features as well as for the many related applications.

An Artificial Neural Network Model Function (AMF) for SARAL-Altika Winds

High-quality winds over the ocean surface, at an enhanced spatio-temporal resolution are required for a better understanding of the dynamics of the ocean and atmosphere. Altimetry helps in increasing the frequency of satellite observations. Traditional algorithms for wind speed retrievals from altimeter consider only the backscatter (sigma-0) and possibly the significant wave height (SWH). In this study, we propose an artificial neural network (ANN) model function for AltiKa on board Satellite for ARgos and ALtiKa (SARAL) to relate wind speed to sigma-0, SWH, the width of the waveform leading edge, the two brightness temperatures (TBK and TBKa), and the amplitude of the 1-Hz echo. These parameters influence either the backscatter from the ocean or the propagation of the altimeter radar signal. The wind estimates have significantly improved by incorporating these parameters.

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.

Retrieval of Wind Stress at the Ocean Surface From AltiKa Measurements

Wind stress is an important parameter in generating the ocean surface currents. Here, for the first time, we directly estimate this parameter at the ocean surface using all the observations from AltiKa and the accompanying radiometer that affect the wind stress estimates and radar signal propagation through the atmosphere. For this purpose, we used an artificial neural network approach using in situ estimates as the dependent parameter and satellite records as the independent parameters. In the absence of sufficient in situ measurements, wind stress is generally inferred from wind speed at 10-m height obtained from spaceborne scatterometers and altimeters which has been extrapolated to the surface to estimate stress, assuming certain atmospheric conditions that are rarely correct. Hence, we obtained this parameter directly at the ocean surface from satellite records. The estimates for the independent validation data set have a standard deviation of the difference between the in situ and satellite-derived values of 0.032 Nm-2 with Pearsons correlation coefficient of 0.96 significant at 99% confidence level.

Impact of scatterometer winds in the Indian coastal region using SWAN model

The lack of adequate observational information over the ocean, create a great difficulty in prediction of ocean state near the Indian coasts. Frequent satellite passes over this region provides valuable wind data resources that can be used to force regional models to evaluate ocean wave spectrum near coasts with a better accuracy. In this work both scatterometer wind from QuikSCAT as well as the ETA model wind from NCMRWF are used to force coastal wave model SWAN nested in open-ocean WAM model. The results indicate that the SWAN nested in WAM predicts the wind generated wave height with better accuracy when forced when forced with the QuikSCAT wind. But the swell height predominantly depends on the boundary conditions provided on the model.

Role of ocean heat content in boosting post-monsoon tropical storms over Bay of Bengal during La-Niña events

This study aims to analyze the role of ocean heat content in boosting the post-monsoon cyclonic activities over Bay of Bengal during La-Niña events. In strong La-Niña years, accumulated cyclone energy in Bay of Bengal is much more as compared to any other year. It is observed that during late June to October of moderate to strong La-Nina years, western Pacific is warmer. Sea surface temperature anomaly of western Pacific Ocean clearly indicates the presence of relatively warmer water mass in the channel connecting the Indian Ocean and Pacific Ocean, situated above Australia. Ocean currents transport the heat zonally from Pacific to South eastern Indian Ocean. Excess heat of the southern Indian Ocean is eventually transported to eastern equatorial Indian Ocean through strong geostrophic component of ocean current. By September the northward transport of this excess heat from eastern equatorial Indian Ocean to Bay of Bengal takes place during La-Nina years boosting the cyclonic activities thereafter.