Enhancement of oceanic parameters associated with dust storms using satellite data

被引:75
|
作者
Singh, Ramesh P. [1 ,3 ]
Prasad, Anup K. [1 ,3 ]
Kayetha, Vinay K. [2 ,3 ]
Kafatos, Menas [1 ]
机构
[1] George Mason Univ, Coll Sci, Ctr Earth Observing & Space Res, Fairfax, VA 22030 USA
[2] Jawaharlal Nehru Technol Univ, Inst Sci & Technol, Ctr Spatial Informat Technol, Hyderabad 500085, Andhra Pradesh, India
[3] Indian Inst Technol, Dept Civil Engn, Kanpur 208016, Uttar Pradesh, India
关键词
D O I
10.1029/2008JC004815
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Atmospheric aerosols play a vital role on the dynamics of climate processes through direct and indirect effects. Dust storms originating over the world's arid regions contribute a large fraction of aerosols in the atmosphere. Using remote sensing data, an anomalous enhancement in the biological productivity of sea was observed in the Gulf of Oman which was attributed only to cold sea surface temperature ( SST) eddies ( during November to early December months of 1996-1999), whereas recent study has shown that during dust storms (June-July-August and October-November-December months of 1997-2004), major nutrient supply is from atmospheric dust deposition. We have carried out a study of individual cases of major dust storms over the Arabian Sea during the entire year ( December 2003-December 2006) to quantify role of dust storms and changes in ocean surface due to chlorophyll bloom. Using Moderate Resolution Imaging Spectroradiometer ( MODIS) Aqua, we have found that the deposition of dust along the passage of major dust storms ( aerosol optical depth (AOD) similar to 0.25-0.41) occuring over the Arabian Sea causes chlorophyll blooming ( usually 10-22.43 mg/m(3)) within a period of 1-2 to up to 3-4 days. However, we have also found significant anomalous cooling of the ocean surface ( SST) and relatively higher ocean wind speeds (QuikSCAT) during dust storms that may lead to favorable conditions for blooming. Exact nature and cause of chlorophyll bloom in the semienclosed northern Arabian Sea, surrounded by one of the world's major sources of dust storms ( Africa, Middle East, Iran, and Afghanistan), are very important in understanding the productivity and the biogeochemical cycles of the marine ecosystem. The results have been validated using the Indian Remote Sensing Polar-4 Ocean Color Monitor (IRS P4 OCM) data.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Paracas dust storms: Sources, trajectories and associated meteorological conditions
    Briceno-Zuluaga, F.
    Castagna, A.
    Rutllant, J. A.
    Flores-Aqueveque, V.
    Caquineau, S.
    Sifeddine, A.
    Velazco, F.
    Gutierrez, D.
    Cardich, J.
    ATMOSPHERIC ENVIRONMENT, 2017, 165 : 99 - 110
  • [32] Dust storms detection over the Indo-Gangetic basin using multi sensor data
    El-Askary, H.
    Gautam, R.
    Singh, R. P.
    Kafatos, M.
    NATURAL HAZARDS AND OCEANOGRAPHIC PROCESSES FROM SATELLITE DATA, 2006, 37 (04): : 728 - 733
  • [33] Dust Storms Are Associated with an Increase in Outpatient Visits for Rheumatoid Arthritis
    Chen, Conmin
    Chen, Chin-Shyan
    Liu, Tsai-Ching
    ATMOSPHERE, 2024, 15 (09)
  • [34] Dust storms evolution in Taklimakan Desert and its correlation with climatic parameters
    Xiao Fengjin
    Zhou Caiping
    Liao Yaoming
    JOURNAL OF GEOGRAPHICAL SCIENCES, 2008, 18 (04) : 415 - 424
  • [35] Investigation of dust storms entering Western Iran using remotely sensed data and synoptic analysis
    Ali D Boloorani
    Seyed O Nabavi
    Hosain A Bahrami
    Fardin Mirzapour
    Musa Kavosi
    Esmail Abasi
    Rasoul Azizi
    Journal of Environmental Health Science and Engineering, 12
  • [36] Investigation of dust storms entering Western Iran using remotely sensed data and synoptic analysis
    Boloorani, Ali D.
    Nabavi, Seyed O.
    Bahrami, Hosain A.
    Mirzapour, Fardin
    Kavosi, Musa
    Abasi, Esmail
    Azizi, Rasoul
    JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE AND ENGINEERING, 2014, 12
  • [37] Neural network multi-parameter algorithms to retrieve atmospheric and oceanic parameters from satellite data
    Krasnopolsky, V
    Gemmill, W
    SECOND CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2000, : 73 - 77
  • [38] Predicting Dust Storms Using Hybrid Intelligence System
    Al Murayziq, Tariq Saad
    Kapetanakis, Stelios
    Petridis, Miltos
    ARTIFICIAL INTELLIGENCE XXXIV, AI 2017, 2017, 10630 : 338 - 351
  • [39] AN EXAMINATION OF THE DIURNAL CYCLE IN OCEANIC TROPICAL RAINFALL USING SATELLITE AND IN-SITU DATA
    JANOWIAK, JE
    ARKIN, PA
    MORRISSEY, M
    MONTHLY WEATHER REVIEW, 1994, 122 (10) : 2296 - 2311
  • [40] On Accurate Detection of Oceanic Features from Satellite IR Data Using ICSED Method
    李俊
    周风仙
    Advances in Atmospheric Sciences, 1992, (03) : 373 - 382