Aerosol optical depth is regularly derived from SeaWiFS and MODIS sensor and used by the scientific community in various climatic studies. In the present study an attempt has been made to retrieve the aerosol optical depth using the IRS-P4 OCM sensor data and a comparison has been carried out using few representative datasets. The results show that the IRS-P4 OCM retrieved aerosol optical depth is in good agreement with the aerosols retrieved from SeaWiFS as well as MODIS. The RMSE are found to be ± 0.0522 between OCM and SeaWIFS and ± 0.0638 between OCM and MODIS respectively. However, IRS-P4 OCM sensor retrieved aerosol optical depth is closer to SeaWiFS (correlation = 0.88, slope = 0.96 and intercept = −0.013) compared to MODIS (correlation = 0.75, slope = 0.91 and intercept = 0.0198). The mean percentage difference indicates that OCM retrieved AOD is +12% higher compared to SeaWiFS and +8% higher compared to MODIS. The mean absolute percentage between OCM derived AOD and SeaWiFS is found to be less (16%) compared to OCM and MODIS (20%).

The above canopy carbon dioxide and water vapour fluxes were measured by micrometeorological gradient technique at three distant stations, within the world’s largest mangrove ecosystem of Sundarban (Indian part), between April 2011 and March 2012. Quadrat analysis revealed that all the three study sites are characterized by a strong heterogeneity in the mangrove vegetation cover. At day time the forest was a sink for CO₂, but its magnitude varied significantly from −0.39 to −1.33 mg m⁻² s⁻¹. The station named Jharkhali showed maximum annual fluxes followed by Henry Island and Bonnie Camp. Day time fluxes were higher during March and October, while in August and January the magnitudes were comparatively lower. The seasonal variation followed the same trend in all the sites. The spatial variation of CO₂ flux above the canopy was mainly explained by the canopy density and photosynthetic efficiency of the mangrove species. The CO₂ sink strength of the mangrove cover in different stations varied in the same way with the CO₂ uptake potential of the species diversity in the respective sites. The relationship between the magnitude of day time CO₂ uptake by the canopy and photosynthetic photon flux was defined by a non-linear exponential curve ($R^2$ ranging from 0.51 to 0.60). Water vapour fluxes varied between 1.4 and 69.5 mg m⁻² s⁻¹. There were significant differences in magnitude between day and night time water vapour fluxes, but no spatial variation was observed.

We report the initial results of the methane flux measured using eddy covariance method during summer months from the world’s largest mangrove ecosystem, Sundarbans of India. Mangrove ecosystems are known sources for methane (CH₄) having very high global warming potential. In order to quantify the methane flux in mangroves, an eddy covariance flux tower was recently erected in the largest unpolluted and undisturbed mangrove ecosystem in Sundarbans (India). The tower is equipped with eddy covariance flux tower instruments to continuously measure methane fluxes besides the mass and energy fluxes. This paper presents the preliminary results of methane flux variations during summer months (i.e., April and May 2012) in Sundarbans mangrove ecosystem. The mean concentrations of CH₄ emission over the study period was 1682 ± 956 ppb. The measured CH₄ fluxes computed from eddy covariance technique showed that the study area acts as a net source for CH₄ with daily mean flux of 150.22 ± 248.87 mg m⁻² day⁻¹. The methane emission as well as its flux showed very high variability diurnally. Though the environmental conditions controlling methane emission is not yet fully understood, an attempt has been made in the present study to analyse the relationships of methane efflux with tidal activity. This present study is part of Indian Space Research Organisation–Geosphere Biosphere Program (ISRO–GBP) initiative under ‘National Carbon Project’.

A study of the snow cover melt and freeze using Ku band Oceansat scatterometer (OSCAT) HH polarised backscatter coefficient (𝜎⁰_HH) for 2011 and 2012 is reported for the Himalayas, which contain the world’s largest reserve of ice and snow outside polar regions. The analysis shows spatial and temporal inter-annual variations in the onset of melt/freeze across four regions (Upper Himalaya, Western Himalaya, Central Himalaya, and Eastern Himalaya), nine elevation bands and four aspect zones. A threshold based on temperature–𝜎⁰_HH relation and average 𝜎⁰_HH for the months January–March was used for melt/freeze detection. When the three consecutive images (6 days) satisfied the threshold, the day of first image was selected as melt onset/freeze day. The average melt onset dates were found to be March 11 ± 11 days for Eastern Himalaya, April 3 ± 18 days for Central Himalaya, April 16 ± 27 days for Western Himalaya, and May 12 ± 18 days for Upper Himalaya. Similarly average freeze onset dates were found to be August 23 ± 27 days for Eastern Himalaya, September 08 ± 24 days for Central Himalaya, August 27 ± 11 days for Western Himalaya, and September 13 ± 11 days for Upper Himalaya. All the zones experienced the melt onset earlier by around 20 days in 2011 at elevation above 5000 m. All the zones experienced freeze earlier in 2012, with onset being 18, 19, 11, and 21 days earlier in Eastern, Central, Western, and Upper Himalaya, respectively.

Western Ghats are considered as one of the global biodiversity hotspots. There is an information gap on conservation status of the biodiversity hotspots. This study has quantified estimates of deforestation in the Western Ghats over a period of past nine decades. The classified forest cover maps for 1920, 1975, 1985, 1995, 2005 and 2013 indicates 95,446 (73.1%), 63,123 (48.4%), 62,286 (47.7%), 61,551 (47.2%), 61,511 (47.1%) and 61,511 km² (47.1%) of the forest area, respectively. The rates of deforestation have been analyzed in different time phases, i.e., 1920–1975, 1975–1985, 1985–1995, 1995–2005 and 2005–2013. The grid cells of 1 km² have been generated for time series analysis and describing spatial changes in forests. The net rate of deforestation was found to be 0.75 during 1920–1975, 0.13 during 1975–1985, 0.12 during 1985–1995 and 0.01 during 1995–2005. Overall forest loss in Western Ghats was estimated as 33,579 km² (35.3% of the total forest) from 1920's to 2013. Land use change analysis indicates highest transformation of forest to plantations, followed by agriculture and degradation to scrub. The dominant forest type is tropical semi-evergreen which comprises 21,678 km² (35.2%) of the total forest area of Western Ghats, followed by wet evergreen forest (30.6%), moist deciduous forest (24.8%) and dry deciduous forest (8.1%) in 2013. Even though it has the highest population density among the hotspots, there is no quantifiable net rate of deforestation from 2005 to 2013 which indicates increased measures of conservation.