Refine your search
Collections
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Dutt, C. B. S.
- Spatio-Temporal Dynamics of Surface Melting over Antarctica Using OSCAT and QuikSCAT Scatterometer Data (2001-2014)
Abstract Views :251 |
PDF Views:103
Authors
Affiliations
1 National Remote Sensing Centre (ISRO), Hyderabad 500 037, IN
1 National Remote Sensing Centre (ISRO), Hyderabad 500 037, IN
Source
Current Science, Vol 109, No 4 (2015), Pagination: 733-744Abstract
In this article, spatio-temporal dynamics of snowmelt in Antarctica from 2001 to 2014 using OSCAT and QuikSCAT scatterometer data is presented. Melting over Antarctic ice sheet can influence shelf dynamics and stability. Here, we have utilized the sensitivity of scatterometer data to detect the presence of liquid water in the snow caused due to melt conditions. After analysing decadal data, a spatial and temporal variation in the average backscatter coefficient was observed over the shelf areas. An adaptive thresholdbased classification using austral winter mean and standard deviation of HH polarization is used which takes into account the spatial and temporal variability in backscatter from snow/ice. Significant spatiotemporal variability in melt area, duration and melt index was observed. Around 9.5% of the continent experienced melt over the study period. Larsen C and George VI shelves had maximum melt duration. The high correlation between melt duration obtained from satellite data and the positive degree day validates the efficacy of the melt algorithm used in the analysis and sensitivity of OSCAT data in detecting presence of water due to melt. There is seasonal and spatial variation in melt onset. Based on MI, 2004-05 was the warmest summer over the continent with 2011-12 being the coldest summer. Consistent and intensive melting was observed over Amery, Larsen C, George VI, Lazarev and Fimbul shelves. Melting of sporadic nature was observed over Ronne-Filchner, Ross and Riiser-Larsen shelves. The East Antarctic shelves experienced large melt during the study period. This article presents the suitability of OSCAT in melt identification and status of melt over the continent.Keywords
Ice Shelves, Scatterometer Data, Spatiotemporal Dynamics, Snowmelt.Full Text
- Mesoscale Model Compatible IRS-P6 AWiFS-Derived Land use/Land Cover of Indian Region
Abstract Views :243 |
PDF Views:79
Authors
Affiliations
1 Atmospheric Chemistry and Processes Studies Division, Earth and Climate Science Area, Hyderabad 500 037, IN
2 Remote Sensing Area, National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, IN
3 Karnataka State Rural Development and Panchyat Raj University, Gadag 582 101, IN
1 Atmospheric Chemistry and Processes Studies Division, Earth and Climate Science Area, Hyderabad 500 037, IN
2 Remote Sensing Area, National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, IN
3 Karnataka State Rural Development and Panchyat Raj University, Gadag 582 101, IN
Source
Current Science, Vol 115, No 12 (2018), Pagination: 2301-2306Abstract
Mesoscale models, in general, are run using the US Geological Survey (USGS) 25-category land use/ land cover (LU/LC) data available at different spatial resolutions. The USGS data over the Indian region suffers from two types of errors, viz. misclassification of LU/LC data and non-availability of up-to-date satellite-based LU/LC data. To improve the accuracy and capture interannual changes better, the LU/LC data generated by the National Remote Sensing Centre (NRSC) using IRS-P6 AWiFS with 56 m basic resolution have been scaled to 5, 2 min and 30 sec resolution which is available at yearly intervals. In the next step, the Indian region of USGS data was replaced with IRS-P6 AWiFS-derived data and made compatible to MM5 and WRF mesoscale models. Thus the resultant product is a global USGS LU/LC data with the Indian region replaced by the information originally derived from AWiFS 56 m resolution imagery, for the years 2004–05 to 2012–13 (nine cycles). This communication describes the required LU/LC data format for MM5 and WRF models and the methodology adopted for compatible product generation. In addition, accuracy of AWiFS-derived LU/LC data converted to 30 sec resolution has also been determined. The present effort will provide the necessary reference for the atmospheric modelling community to address the Indian satellite based model compatible LU/LC data product. These data products are currently available on Bhuvan, the NRSC/ISRO geospatial portal.Keywords
Land Use/land Cover Data, Land-surface Processes, Mesoscale Model, Spatial Resolution.Full Text
References
- Nataly, P. and Pinhas, A., Effect of land use modification on potential increase of convection: a numerical mesoscale study over south Israel. J. Geophys. Res., 2001, 106(D19), 621–634.
- Narisma, G. T. and Pitman, A. J., The impact of 200-years land cover change on the Australian near-surface climate. J. Hydrometeorol., 2003, 4, 424–436.
- Pitman, A. J., Narisma, G. T., Pielke Sr, R. A. and Holbrook, N. J., Impact of land cover change on the climate of southwest Western Australia. J. Geophys. Res., 2004, 109, D18109; doi:10.1029/ 2003JD004347 1-12.
- Quattrochi, D. A., Lapenta, W. M., Crosson, W. L., Estes, M. G., Limaye, A. and Khan, M., The application of satellite-derived, high-resolution land use/land cover data to improve urban air quality model forecasts, NASA/TP-2006-214710, November 2006.
- Byun, D. W., Kim, S. T., Czader, B. and Cheng, B., Modeling effects of land use and land cover modifications on the urban heat island phenomena and air quality in Houston. Project H17 Final Report prepared for Houston Advanced Research Center, Houston, TX, USA, 2004.
- Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L. and Merchant, J. W., Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int. J. Remote Sensing, 2000, 21(6&7), 1303–1330.
- Ran, L., Pleim, J. and Gilliam, R., Impact of high resolution landuse data in meteorology and air quality modeling system. In Air Pollution Modelling and its Application (eds Steyn, D. G. and Rao, S. T.), Springer Science+Business Media BV, 2010, XX; doi:10.1007/978-90-48-3812-8.
- Sertel, E., Robock, A. and Ormecci, C., Impacts of land cover data quality on regional climate simulations. Int. J. Clim., 2009; doi:10.1002/JOC.2036.
- Dutta, K. S., Das, S., Kar, S. C., Mohanty, U. C. and Joshi, P. C., Impact of vegetation on the simulation of seasonal monsoon rainfall over the Indian subcontinent using a regional model. J. Earth Syst. Sci., 2009, 118(5), 413–440.
- Unnikrishnan, C. K., Gharai, B., Mohandas, S., Mamgain, A., Rajagopal, E. N., Gopal, R. I. and Rao, P. V. N., Recent change on land use/land cover over Indian region and its impact on the weather prediction using Unified model. Atmosp. Sci. Lett., 2016, doi:10.1002/asl.658.