مدل‌های جهانی برای بررسی شکوفایی گیاد‌روایانی (فیتوپلانکتونی) در دریای عمان و شمال‌غربی دریای عرب

نوع مقاله : مقاله پژوهشی‌

نویسندگان

1 دانشگاه آزاد اسلامی، واحد علوم و تحقیقات

2 دانشگاه جانزهاپکینز

3 موسسه ژئوفیزیک دانشگاه تهران، تهران

4 پژوهشکده اکولوژی خلیج فارس و دریای عمان

چکیده

در سال‌های اخیر، افزایشی در شکوفایی کشند قرمز در شمال غربی دریای عرب و دریای عمان مشاهده شده است که این سؤال را در ذهن به وجود می‌آورد: آیا تغییرات اقلیمی باعث افزایش این روند شده است یا خیر؟ با هدف پاسخ به این سوال، در این پژوهش از مدل‌های مختلف سامانه زمین و داده‌های ماهواره‌ای استفاده شده ‌است. داده‌های ماهواره‌ای دو شکوفایی را در این منطقه نشان می‌دهند، شکوفایی زمستانی که بیشینه آن در ماه فوریه و شکوفایی تابستانی که بیشینه آن در ماه سپتامبر است. تغییرات درون‌سالانه‌ای نیز در شکوفایی زمستانی حاصل از اثر پیچک‌های چرخندی که توزیع مکانی متفاوتی از یک سال به سال دیگر دارند، مشخص شده است. دو مدل با تفکیک کم (°1) با بخش زیست‌زمین‌شیمیایی تقریباً پیچیده (مدل TOPAZ) چرخه سالانه را نشان می‌دهند ولی قادر به نمایش پیچک‌ها و تغییرات درون‌سالانه نیستند. مدل‌های با تفکیک بیشتر (GFDL CM2.6) که توانایی مدل‌سازی پیچک‌ها را دارند همراه با بخش زیست‌زمین‌شیمیایی ساده‌تر (مدل miniBLING) تغییرات درون‌سالانه بزرگ‌تری را نشان می‌دهند، اما مقدار شکوفایی زمستانی را بیش از اندازه پیش‌بینی می‌کنند. این مدل اگرچه رابطه‌ بین شکوفایی و پیچک را در بخش جنوبی به‌خوبی نشان می‌دهد، اما در بخش شمالی منطقه موفق نیست. این امر به‌دلیل نداشتن توانایی در مدل‌سازی دماشیب (ترموکلاین) و غذاشیب (نوتری‌کلاین) قوی و درست در آن مناطق می‌باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Global models for investigation of phytoplankton blooms in the Gulf of Oman and the northwest of Arabian Sea

نویسندگان [English]

  • Seyedeh Safoora Seddigh Marvasti 1
  • Anand Gnanadesikan 2
  • AbbasAli AliAkbari Bidokhti 3
  • Sarmad Ghader 3
  • Mohammad Seddigh Mortezavi 4
1 Science and Research Branch, Islamic Azad University
2 Johns Hopkins University
3 Institute of Geophysics, University of Tehran
4 Institute of Persian Gulf and Oman Sea Ecology
چکیده [English]

This study evaluates the performance of Earth system models for accurately simulating the phytoplankton productivity and bloom dynamics in the Oman Sea and the northwest of Arabian Sea. Satellite data (SeaWIFS ocean color) show two climatological blooms in this region, a wintertime bloom peaking in February and a summertime bloom peaking in September. On a regional scale, interannual variability of the wintertime bloom is dominated by cyclonic eddies which vary in location from year to year. During the wintertime, while both cooling in the winter and eddies control the blooms, variability in bloom location will arise from variability in the location of eddies, and so may not be predictable. In contrast, during the Southwest Monsoon, the dominant upwelling associated with the intense environmental forcing supersedes the effects of eddies, and the activity of the cold eddies is not pronounced. We consider numerical results from five different 3-D global Earth system models, which are denoted by CORE-TOPAZ, Coupled-TOPAZ, Coupled-BLING, Coupled-miniBLING, and the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model version 2.6 (CM2.6 miniBLING). Two coarse (1° grid resolution) models with a relatively complex biogeochemistry (TOPAZ: Tracers of Ocean Productivity with Allometric Zooplankton) capture the annual cycle but fail to capture both the eddies and the interannual variability. The results showed that the models differ from the observational data in terms of interannual variability. The low-resolution models (CORE- and coupled-TOPAZ) provide an almost uniform seasonal coefficient of variation, while both the data and eddy resolving CM2.6 models show higher interannual variability and seasonal changes. The coefficients of variabilities are particularly higher during the winter and summer blooms in the observations, while the low-resolution models do not see these signals. In other words, the low-resolution models fail to attain enough variability, while the high-resolution models (i.e. CM2.6) produce too much interannual variability. Accordingly, eddies are necessary to explain the variability in the data as opposed to the low-resolution models, but that the high-resolution model does not properly capture this variability. An eddy-resolving model (GFDL CM2.6) with a simpler biogeochemistry (miniBLING) displays larger interannual variability, but overestimates the wintertime bloom and captures eddy-bloom coupling in the south but not in the north. The models fail to capture both the magnitude of the wintertime bloom and its modulation by the eddies in part because of their failure to capture the observed sharp thermocline/nutricline in this region. In the wintertime, this leads to the excessive convective supply of nutrients and too strong of a bloom. However, for a few cases, eddies with blooms at the center are tracked in the southern part of the domain. For the model to simulate the observed wintertime blooms within cyclones, it will be necessary to represent this relatively unusual nutrient structure as well as the cyclonic or cold eddies. Both the temperature and mixed layer biases in the northern part of the Arabian Sea may result from having too much water from the Persian Gulf in this region. This is a challenge in the northern Arabian Sea as it requires capturing the details of the outflow from the Persian Gulf, something that is poorly done in global models.
 

کلیدواژه‌ها [English]

  • red tide
  • bloom
  • Numerical modeling
  • eddy
  • Earth system models
  • biogeochemistry
Abbott, M. R., and Zion, P., 1985, Satellite observations of phytoplankton variability during an upwelling event: Continental Shelf Research, 4, 661–680.
Al-Azri, A. R., Piontkovski, S., Al-Hashmi, K., Goes, J., and Gomes, H., 2010, Chlorophyll a as a measure of seasonal coupling between phytoplankton and the monsoon periods in the Gulf of Oman: Aquatic Ecology, 44, 449–461.
Dunne, J. P., Gnanadesikan, A., Jorge, Sarmiento, L., and Richard, D. S., 2010, Technical description of the prototype version (v0) of Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) ocean biogeochemical model as used in the Princeton IFMIP model: Biogeosciences Supplement, 7, 3593.
Ezam, M., Bidokhti, A. A., and Javid. A. H., 2010, Numerical simulations of spreading of the Persian Gulf outflow into the Oman Sea: Ocean Science, 6, 887–900.
Galbraith, E. D., Gnanadesikan, A., Dunne, J. P., and Hiscock, M. R., 2010, Regional impacts of iron-light colimitation in a global biogeochemical model: Biogeosciences, 7, 1043–1064.
Galbraith, E. D., John P. D., Gnanadesikan, A., Slater, R. D., Sarmiento, J. L., Dufour, C. O., de Souza, G. F.,  Bianchi, D., Claret, M., Rodgers, K. B., Sedigh Marvasti, S., 2015, Complex functionality with minimal computation: Promise and pitfalls of reduced-tracer ocean biogeochemistry models: J. Advances in Modeling Earth Systems, 4, 2012–2028.
Gnanadesikan, A., Keith W., Dixon, S. M., Griffies, V., Balaji, M., Barreiro, J. A., Beesley, W. F., Cooke, Delworth, T. L., Gerdes, R., Harrison, M. J., Held, I. M., Hurlin, W. J., Lee, H-C., Liang, Z., Nong, G., Pacanowski, R. C., Rosati, A., Russell, J., Samuels, B. L., Song, Q., Spelman, M. J., Stouffer, R. J., Sweeney, C. O., Vecchi, G., Winton, M., Wittenberg, A. T., Zeng, F., Zhang, R., and Dunne, J. P., 2006, GFDL’s CM2 global coupled climate models. Part II: The baseline ocean simulation: J. Climate, 19, 675–697.
Kawamiya, M., and Oschlies, A., 2003, An eddy-permitting, coupled ecosystem-circulation model of the Arabian Sea: Comparison with observations: J. Marine Systems, 38, 221–257.
Kumar, S. P., Ramaiah, N., Gauns, M., Sarma, V. S., Muraleedharan, P. M., Raghukumar, S., Kumar, M. D., and Madhupratap, M., 2001, Physical forcing of biological productivity in the Northern Arabian Sea during the Northeast Monsoon: Deep Sea Research II, 48, 1115–11126.
Levy, M., Shankar, D., Andre, J., Shenoi, S. S. C., Durand, F., and De Boyer Montegut, C., 2007, Basin-wide seasonal evolution of the Indian Ocean’s phytoplankton blooms: J. Geophys. Res., 112, C12014, 1–14.
Murtugudde, R., Seager, R., and Thoppil, P., 2007, Arabian Sea response to monsoon variations: Paleoceanography, 22, 1–17.
Piontkovski, S. A., Nezlin, N. P., Al-Azri, A., and Al-Hashmi, K., 2012, Mesoscale eddies and variability of chlorophyll-a in the Sea of Oman: Int. J. Remote Sensing, 33, 5341–5346. 
Wang, D., and Zhao, H., 2008, Estimation of phytoplankton responses to Hurricane Gonu over the Arabian Sea based on ocean color data: Sensors, 8, 4878–4893, DOI: 10.3390/s8084878.
Wiggert, J. D., Murtugudde, R. G., and Mcclain, C. R., 2002, Processes controlling interannual variations in wintertime (Northeast Monsoon) primary productivity in the central Arabian Sea: Deep Sea Research II, 49, 2319–2343.