10 research outputs found

    Exploring the differences in cloud properties observed by the Terra and Aqua MODIS Sensors

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    The aerosol-cloud interaction in different parts of the globe is examined here using multi-year statistics of remotely sensed data from two MODIS sensors aboard NASA's <i>Terra</i> (morning) and <i>Aqua</i> (afternoon) satellites. Simultaneous retrievals of aerosol loadings and cloud properties by the MODIS sensor allowed us to explore morning-to-afternoon variation of liquid cloud fraction (CF) and optical thickness (COT) for clean, moderately polluted and heavily polluted clouds in different seasons. Data analysis for seven-years of MODIS retrievals revealed strong temporal and spatial patterns in morning-to-afternoon variation of cloud fraction and optical thickness over different parts of the global oceans and the land. For the vast areas of stratocumulus cloud regions, the data shows that the days with elevated aerosol abundance were also associated with enhanced afternoon reduction of CF and COT pointing to the possible reduction of the indirect climate forcing. A positive correlation between aerosol optical depth and morning-to-afternoon variation of trade wind cumulus cloud cover was also found over the northern Indian Ocean, though no clear relationship between the concentration of Indo-Asian haze and morning-to-afternoon variation of COT was established. Over the Amazon region during wet conditions, aerosols are associated with an enhanced convective process in which morning shallow warm clouds are organized into afternoon deep convection with greater ice cloud coverage. Analysis presented here demonstrates that the new technique for exploring morning-to-afternoon variability in cloud properties by using the differences in data products from the two daily MODIS overpasses is capable of capturing some of the major features of diurnal variations in cloud properties and can be used for better understanding of aerosol radiative effects

    Representation of Tropical Cyclones by the Modern-Era Retrospective Analysis for Research and Applications Version 2

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    This study examines the veracity of the tropical cyclone (TC) statistics estimated from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) global atmospheric reanalysis, focusing on the climatological-mean genesis regions, tracks and their lifetime maximum intensity, as well as the interannual and intraseasonal variations in TC activity. The results are validated against the International Best Track Archive for Climate Stewardship (IBTrACS) data for 1980-2016. MERRA-2 represents the spatial distribution of the TC genesis location and the tracks realistically over all main development regions (MDRs), but the simulated TCs are initiated at lower latitudes closer to the equator compared with the observations. Over the western North Pacific and the North Atlantic, MERRA-2 underestimates recurving TCs steered by background westerlies in the mid-latitudes and thereby exaggerates northwestward moving TCs, resulting in an overestimate of the landfall probability in East Asia and North America. Excessive development of TCs over the Bay of Bengal also tends to exaggerate the landfall probability in India. In spite of the discrepancies in the annual TC number, the seasonal variation of TC genesis is realistic in MERRA-2. MERRA-2 also captures the TC intensity relationship between the minimum pressure and the maximum surface wind speed at the mature stage, although the maximum intensity is weaker than in the observations. While MERRA-2 tends to reproduce the interannual variations of the observed TC number and the power dissipation index (PDI), the level of accuracy varies by each ocean basin. MERRA-2 describes the changes in the TC genesis region and tracks realistically according to the different phases of El Nino and the Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), although it is less realistic over the North Indian Ocean

    Recent advance in understanding the dynamics of the Madden-Julian oscillation

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