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Abstract

Assessing the statistics and trends of atmospheric variables is the very basic step for the climate change risk management. The numerical weather prediction models have displayed an increasing credibility for achieving sound simulations of the interactions between the atmosphere and the earth surface. Those models have been used together with the assimilation procedure which combines the model forecasts with all available observations including conventional and satellite information to generate gridded reanalysis datasets. Atmospheric reanalysis datasets are commonly used and are reliable sources for analyzing the long-term variations of atmospheric variables because of their uniform global coverage and long-term availabilities. This study is also developed by using one of those widely referred atmospheric reanalysis datasets, i.e. European Center for Medium- Range Weather Forecast ERA-interim. Era-Interim data has 0.75掳 horizontal grid spacing, 28 vertical levels, consisting of 1 surface level and 27 pressure levels from 1000 hPa to 100 hPa and available with 6 hours interval (00 UTC, 06 UTC, 12 UTC, 18 UTC). Parameters such as 2-meter temperature, maximum temperature, minimum temperature, sea surface temperature, total column water vapor and total precipitation are analyzed for the 38-year period of 1979-2017.

Biography

Seyda Tilev is currently working as an Assistant Professor at Abu Dhabi Polytechnic, Meteorology Department. She has completed her MSc in Satellite Communication and Remote Sensing (2009) and PhD degree in Atmospheric Sciences (2016) from Istanbul Technical University, Turkey. She received the scholarship from University of Manchester, School of Earth and Environmental Sciences. She has published many papers in reputed journals. Her research interests include renewable energies, climate change, air pollution, severe convective storms, atmospheric modeling and NWP and data assimilation. She is also a Member of American Meteorological Society.

E-mail: seyda.tanriover@adpoly.ac.ae