M. M. Ali

Detection of Bay of Bengal eddies from TOPEX and in situ observations

Oceanic eddies have warm or cold temperatures and high or low sea surface height (SSH) at the center depending upon the direction of rotation. However, since the Bay of Bengal waters are highly stratified, sea surface temperature (SST) gradients may not be detectable even though the subsurface temperature sections and the SSH show prominent eddy signatures. In this investigation, SSH observations from TOPEX altimeter data and the expendable bathy thermograph (XBT) temperature sections along the Madras‐Andamans track have been analyzed to study the Bay of Bengal eddies. Several cyclonic and anticyclonic eddies are identified from the TOPEX altimeter observations. These eddies located along the ship’s tracks have significant variations in amplitudes and show good qualitative agreement with the subsurface isotherm features (troughs and ridges) of the in situ temperature profiles. However, this agreement does not extend to the surface and hence SST patterns are not good indicators of eddy positions in the Bay of Bengal where the waters are highly stratified. Therefore, a better approach to the study of eddies in regions like the Bay of Bengal is to use SSH observations. Due to the extensive spatial coverage of remote sensing observations, the exact position and shape of the eddies can be characterized from altimeter-derived SSH observations which is not possible using the limited in situ profiles. Interannual variations in both the positions and intensities of eddies are observed during the study period.

Identification of large-scale atmospheric and oceanic features from IRS-P4 multifrequency scanning microwave radiometer: Preliminary results

Abstract Large-scale features of sea surface temperature, wind speed, water vapor, and cloud liquid water, derived from multifrequency scanning microwave radiometer (MSMR) on board Indian oceanographic satellite IRS-P4 could be identified during 15 June–23 August 1999. This is the period during which extensive validation was carried out. MSMR is the only sensor in orbit operating at 6.6 GHz. Average distribution of these parameters brings out large-scale atmospheric and oceanographic features. Zonal averages of these parameters were also studied to examine the consistency of MSMR data over larger spatial scales. Linear correlations between all parameters were also computed to check for the interconsistency of these parameters. The present analysis shows the potential use of MSMR products in studying the oceanographic and atmospheric phenomena.

Estimation of mixed layer depth in the equatorial Indian Ocean using Geosat altimeter data

Mixed layer depth (MLD) is an important parameter in the study of air‐sea interaction, acoustic propagation, and fisheries. With the onset of the southwest monsoon, a jetlike surface water flow develops from west to east along the equatorial Indian Ocean (EIO) creating an upward west to east sea surface slope. This in turn creates a slope in MLD in the opposing direction. In this paper, emphasis is placed on obtaining monthly coefficients between MLD and sea level for three regions across the EIO. Using these coefficients, MLD has been estimated from Geosat altimeter data. MLD in this region has been computed with an RMS error of 16 m, from altimeter data, as verified by TOGA in situ profiles.

Validation of satellite-derived tropical cyclone heat potential with in situ observations in the North Indian Ocean

Tropical cyclone heat potential (TCHP) is an important ocean parameter influencing cyclones and hurricanes. The best approach for computing TCHP is to use in situ measurements. However, since in situ data have both spatial and temporal limitations, there is a need for satellite-based estimations. One potential solution is to use sea surface height anomalies (SSHAs) from altimeter observations. However, any estimation derived from satellite measurements requires extensive regional validation. In this letter, we compare satellite-derived TCHP values with those estimated using in situ measurements of the North Indian Ocean collected during 1993–2009. All the available measurements collected from the conductivity temperature and depth (CTD) profiler, expendable CTD profiler (XCTD), bathythermograph (BT), expendable BT (XBT) and Argo floats were used to estimate in situ derived TCHP values. TCHP estimations from satellite observations and in situ measurements are well correlated, with coefficient of determination R 2 of 0.65 (0.76) and a scatter index (SI) of 0.33 (0.25) on a daily (monthly) basis for the North Indian Ocean.

Use of Sea Surface Temperature for Cyclone Intensity Prediction Needs a Relook

If a cyclones track and intensity can be predicted precisely, the losses due to cyclones can be minimized. While efforts are under way to improve the understanding of the physics of the problem of track and intensity prediction, it is worthwhile to look again at the efficiency of the input parameters presently used in models and to look for new approaches.

Atmospheric CO₂ Variations in Two Contrasting Environmental Sites Over India

We analyzed the influence of environmental parameters on the temporal variation of atmospheric carbon dioxide (CO2) mixing ratios in two environmentally contrasting Indian sites, Dehradun (30.1°N, 77.4°E, humid subtropical station) and Gadanki (13.5°N, 79.18°E, dry tropical station), from October 2010 to September 2011. The annual range of mixing ratios is low in Gadanki as compared to those of Dehradun because of relatively less monthly variation in temperature and relative humidity (RH) at Gadanki. At both the stations, the minimum mixing ratios are present during the high ecosystem productivity seasons in the afternoon hours. The maximum values are in the early morning hours. However, low wind speed conditions control the unexpected afternoon high mixing ratios in Gadanki during the pre-monsoon season. The early morning maximum is high during monsoon and post-monsoon seasons in Dehradun and Gadanki, respectively, whereas morning inflexion occurred earlier in Gadanki compared with Dehradun. The effect of cloudiness on the CO2 uptake depends on the canopy cover.

Interannual Variation of Eddy Kinetic Energy from TOPEX Altimeter Observations

Monthly mesoscale eddy kinetic energy (EKE) per unit mass has been computed for four years, 1993-1996, from TOPEX altimeter data in the Indian Ocean. It ranges from 50 cm2/s2 to 2,700 cm2/s2 (about 4,000 cm2/s2 near the Somali region in a few months). In the Arabian Sea and the Bay of Bengal, regions of high energies associated with various current systems under the influence of monsoonal winds have been delineated. Monthly variation of EKE near the Somali region has been studied. In this region the maximum EKE per unit mass has been observed during August every year, with variations in magnitude from year to year. The mesoscale eddy kinetic energy computed from TOPEX altimeter-derived SSH during 1993-1996 is highest near the Somali region during the SW monsoon, due to formation of mesoscale eddies and also because of upwelling. In the Bay of Bengal, high eddy kinetic energy is seen toward the western side during nonmonsoonal months due to the western boundary current. In the South Indian Ocean, it is hig...

Temporal Variations of Atmospheric CO2 in Dehradun, India during 2009

The present study reports the temporal variations of CO2 mixing ratio measured using Vaisala GMP-343 sensor (at 15 m height) in Dehradun (30.1 °N, 77.4 °E) during 2009. Being a valley station, the mixing ratios are controlled by biospheric processes but not by large scale transport phenomenon or local pollution. A distinct diurnal cycle varies from 317.9 ppm in the afternoon to 377.2 ppm in the morning (before sunrise). The minimum early morning (0700-1000 IST) drop and minimum afternoon (1300-1700 IST) trough observed during monsoon months are related to the enhanced vegetation activity due to rain at the site. The maximum night time (2200 IST to next day 0700 IST) build up of CO2 observed during monsoon season is associated with the increase in heterotrophic respiration due to high moisture content in the soil. This is also confirmed by the positive coherence between night time CO2 mixing ratio with soil respiration simulated from Carnagie-Ames-Standford Approach (CASA) model. The strong negative coherence with net ecosystem productivity (simulated from the same model) shows that observations captured the regional changes in emission and uptake of CO2 in atmosphere.

Obtaining sea surface height signals from ERS‐1 altimeter data

Abstract Satellite‐borne radar altimeter gave ample opportunity for observing dynamical oceanographic features repeatedly over a larger scale. Before getting sea surface height signals altimeter data have to be corrected for a number of effects. Besides applying corrections given in the geophysical data records (GDR), the altimeter profiles must be processed and further corrections must be applied. This paper describes the various corrections, such as editing for rain cell effects, removal of orbit error and local geoid effects, etc., to be applied to the sea surface height observations. These corrections have to be applied in addition to those given in ERS‐1 altimeter operational products to get dynamic sea surface topographic signals. The signals in the sea surface heights obtained in this analysis are of the expected order.

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.