scholarly journals Satellite-observed relationships between aerosol and trade-wind cumulus cloud properties over the Indian Ocean

2011 ◽  
Vol 38 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
Sagnik Dey ◽  
Larry Di Girolamo ◽  
Guangyu Zhao ◽  
Alexandra L. Jones ◽  
Greg M. McFarquhar
2004 ◽  
Vol 22 (8) ◽  
pp. 2679-2691 ◽  
Author(s):  
M. V. Ramana ◽  
P. Krishnan ◽  
S. Muraleedharan Nair ◽  
P. K. Kunhikrishnan

Abstract. Spatial and temporal variability of the Marine Atmospheric Boundary Layer (MABL) height for the Indian Ocean Experiment (INDOEX) study period are examined using the data collected through Cross-chained LORAN (Long-Range Aid to Navigation) Atmospheric Sounding System (CLASS) launchings during the Northern Hemispheric winter monsoon period. This paper reports the results of the analyses of the data collected during the pre-INDOEX (1997) and the INDOEX-First Field Phase (FFP; 1998) in the latitude range 14°N to 20°S over the Arabian Sea and the Indian Ocean. Mixed layer heights are derived from thermodynamic profiles and they indicated the variability of heights ranging from 400m to 1100m during daytime depending upon the location. Mixed layer heights over the Indian Ocean are slightly higher during the INDOEX-FFP than the pre-INDOEX due to anomalous conditions prevailing during the INDOEX-FFP. The trade wind inversion height varied from 2.3km to 4.5km during the pre-INDOEX and from 0.4km to 2.5km during the INDOEX-FFP. Elevated plumes of polluted air (lofted aerosol plumes) above the marine boundary layer are observed from thermodynamic profiles of the lower troposphere during the INDOEX-FFP. These elevated plumes are examined using 5-day back trajectory analysis and show that one group of air mass travelled a long way from Saudi Arabia and Iran/Iraq through India before reaching the location of measurement, while the other air mass originates from India and the Bay of Bengal.


2007 ◽  
Vol 20 (13) ◽  
pp. 2937-2960 ◽  
Author(s):  
Bohua Huang ◽  
J. Shukla

Abstract To understand the mechanisms of the interannual variability in the tropical Indian Ocean, two long-term simulations are conducted using a coupled ocean–atmosphere GCM—one with active air–sea coupling over the global ocean and the other with regional coupling restricted within the Indian Ocean to the north of 30°S while the climatological monthly sea surface temperatures (SSTs) are prescribed in the uncoupled oceans to drive the atmospheric circulation. The major spatial patterns of the observed upper-ocean heat content and SST anomalies can be reproduced realistically by both simulations, suggesting that they are determined by intrinsic coupled processes within the Indian Ocean. In both simulations, the interannual variability in the Indian Ocean is dominated by a tropical mode and a subtropical mode. The tropical mode is characterized by a coupled feedback among thermocline depth, zonal SST gradient, and wind anomalies over the equatorial and southern tropical Indian Ocean, which is strongest in boreal fall and winter. The tropical mode simulated by the global coupled model reproduces the main observational features, including a seasonal connection to the model El Niño–Southern Oscillation (ENSO). The ENSO influence, however, is weaker than that in a set of ensemble simulations described in Part I of this study, where the observed SST anomalies for 1950–98 are prescribed outside the Indian Ocean. Combining with the results from Part I of this study, it is concluded that ENSO can modulate the temporal variability of the tropical mode through atmospheric teleconnection. Its influence depends on the ENSO strength and duration. The stronger and more persistent El Niño events in the observations extend the life span of the anomalous events in the tropical Indian Ocean significantly. In the regional coupled simulation, the tropical mode is still active, but its dominant period is shifted away from that of ENSO. In the absence of ENSO forcing, the tropical mode is mainly stimulated by an anomalous atmospheric direct thermal cell forced by the fluctuations of the northwestern Pacific monsoon. The subtropical mode is characterized by an east–west dipole pattern of the SST anomalies in the southern subtropical Indian Ocean, which is strongest in austral fall. The SST anomalies are initially forced by surface heat flux anomalies caused by the anomalous southeast trade wind in the subtropical ocean during austral summer. The trade wind anomalies are in turn associated with extratropical variations from the southern annular mode. A thermodynamic air–sea feedback strengthens these subtropical anomalies quickly in austral fall and extends their remnants into the tropical ocean in austral winter. In the simulations, this subtropical variability is independent of ENSO.


2014 ◽  
Vol 14 (13) ◽  
pp. 6729-6738 ◽  
Author(s):  
M. K. Witte ◽  
P. Y. Chuang ◽  
G. Feingold

Abstract. Cumulus clouds exhibit a life cycle that consists of (a) the growth phase (increasing size, most notably in the vertical direction); (b) the mature phase (growth ceases; any precipitation that develops is strongest during this period); and (c) the dissipation phase (cloud dissipates because of precipitation and/or entrainment; no more dynamical support). Although radar can track clouds over time and give some sense of the age of a cloud, most aircraft in situ measurements lack temporal context. We use large eddy simulations of trade wind cumulus cloud fields from cases during the Barbados Oceanographic and Meteorological Experiment (BOMEX) and Rain In Cumulus over the Ocean (RICO) campaigns to demonstrate a potential cumulus cloud "clock." We find that the volume-averaged total water mixing ratio rt is a useful cloud clock for the 12 clouds studied. A cloud's initial rt is set by the subcloud mixed-layer mean rt and decreases monotonically from the initial value due primarily to entrainment. The clock is insensitive to aerosol loading, environmental sounding and extrinsic cloud properties such as lifetime and volume. In some cases (more commonly for larger clouds), multiple pulses of buoyancy occur, which complicate the cumulus clock by replenishing rt. The clock is most effectively used to classify clouds by life phase.


2005 ◽  
Author(s):  
Iliana Genkova ◽  
Guangyu Zhao ◽  
Gabriela Seiz ◽  
Eric Snodgrass ◽  
Marile Colon ◽  
...  

2013 ◽  
Vol 13 (9) ◽  
pp. 23461-23490
Author(s):  
M. K. Witte ◽  
P. Y. Chuang ◽  
G. Feingold

Abstract. Cumulus clouds exhibit a life cycle that consists of: (a) the growth phase (increasing size, most notably in the vertical direction); (b) the mature phase (growth ceases; any precipitation that develops is strongest during this period); and (c) the dissipation phase (cloud dissipates because of precipitation and/or entrainment; no more dynamical support). Although radar can track clouds over time and give some sense of the age of a cloud, most aircraft in situ measurements lack temporal context. We use large eddy simulations of trade wind cumulus cloud fields from cases during the Barbados Oceanographic and Meteorological Experiment (BOMEX) and Rain In Cumulus over the Ocean (RICO) campaigns to demonstrate a potential cumulus cloud "clock". We find that the volume-averaged total water mixing ratio rt is a useful cloud clock for the 12 clouds studied. A cloud's initial rt is set by the subcloud mixed-layer mean rt and decreases monotonically from the initial value due primarily to entrainment. The clock is insensitive to aerosol loading, environmental sounding and extrinsic cloud properties such as lifetime and volume. In some cases (more commonly for larger clouds), multiple pulses of buoyancy occur, which complicate the cumulus clock by replenishing rt. The clock is most effectively used to classify clouds by life phase.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinqiang Xu ◽  
Lei Wang ◽  
Weidong Yu

AbstractThe interannual variability of the sea surface temperature (SST) in the Indian Ocean is complex and characterized by various air-sea coupled modes, which occur around El Niño/La Niña's peak phase (i.e. December–January–February, DJF). Indian Ocean Dipole Mode (IODM) develops over the tropical Indian Ocean and peaks in September–October–November (SON), while Ningaloo Niño, Subtropical Indian Ocean Dipole (SIOD) and Indian Ocean Basin Mode (IOBM) occur respectively over northwest off Australia, subtropical and tropical Indian Ocean, during boreal winter to spring. The apparent contrast between their divergent regionality and convergent seasonality around DJF triggers the present study to examine the interaction between the local mean monsoonal cycle and the anomalous forcing from El Niño/La Niña. The diagnosis confirms that the Indian Ocean’s unique complexity, including the monsoonal circulation over the tropics and the trade wind over the subtropical southern Indian Ocean, plays the fundamental role in anchoring the various regional air-sea coupled modes across the basin. The SST anomalies can be readily explained by the wind-evaporation-SST (WES) mechanism, which works together with other more regional-dependent dynamic and thermodynamic mechanisms. This implies that El Niño/La Niña brings much predictability for the Indian Ocean variations.


2004 ◽  
Vol 31 (21) ◽  
pp. n/a-n/a ◽  
Author(s):  
Greg M. McFarquhar ◽  
Steven Platnick ◽  
Larry Di Girolamo ◽  
Hailong Wang ◽  
Gala Wind ◽  
...  

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