Research on the Caspian Clouds

Document Type : Full length article

Authors

1 PhD student of Climatology, Tabriz University, Tabriz, Iran

2 Professor, Department of Climatology, Tabriz University, Tabriz, Iran

3 PhD in Climatology, Tabriz University, Tabriz, Iran

Abstract

Extended Abstract
Introduction
What is known as a cloud is actually the accumulation of water vapor particles in the atmosphere around the nuclei of their density and cooling (Ghasemi, 2012). In this study, we will study and identify the clouds that are formed in terms of spatial distribution between the southern coast of the Caspian Sea to the Alborz Mountains and in terms of temporal distribution in all seasons, especially in summer. It seems that these clouds were different in terms of atmospheric formation mechanism and are formed under special environmental conditions of the Caspian coast. Therefore, the main purpose of this study will be to identify and study these clouds. For this purpose, 279 cloud days were selected for study.
 
Materials and methods
This study uses type, amount and height of low, medium clouds, including hourly data (00, 03, 06, 09, 12, 15, 18 and 21 UTC) and daily precipitation of 13 meteorological stations in the study area, for selected samples, were received from the Iran Meteorological Organization (IMO). The characteristics of the physical parameters of the cloud Included CTT, CTH, CER, COT and CWP were obtained from level 2 MODIS (MOD06 TERRA and MYD06 Aqua) with a resolution of 1 km. Upper atmosphere data were obtained from ERA5 at a resolution of 0.25° × 0.25 °. Which includes geopotential height, u- wind, v- wind, specific humidity and omega levels of 1000 to 500 hPa isobaric. Ground surface data (SLP, U-wind and V-wind 10m) were obtained from the NCEP/NCAR database and its circulation patterns were drawn in GRADS. HYSPLIT model and the backward method was used to identify the source of moisture. In this study, Global Data AssimilationSystem (GDAS 1°) meteorological data provided by NOAA HYSPLIT model were used to calculate the backward paths for altitudes of 50, 500 and 1000 m above the ground. First, the frequency percentage of the type and height of different layers of clouds were calculated. The average seasonal and monthly occurrence of Caspian clouds were calculated. The average seasonal and annual rainfall of Caspian clouds were calculated. The relationship between precipitation and cloud parameters was investigated by multivariate regression
Result and discussion
 During the 10-year statistical period (2020-2010), 279 cases (days) of the occurrence of Caspian clouds were identified. The research findings showed that the highest average monthly frequency of Caspian clouds occurs in August until its lowest occurrence in November to April. The maximum seasonal frequency of days with Caspian clouds occurs in summer with 16.1 days. These clouds are mainly in the form of low- and middle-level clouds in the region with their most common types being Stratus and Altocumulus. The analysis of rainfall rainfall from Caspian clouds indicates the annual rainfall of Caspian clouds in the region and in most stations more than 80 mm, and its highest amount occurs in summer and autumn chapters, respectively. Spatial distribution the average rainfall derived from Caspian clouds showed that its maximum is on the annual scale and summer and autumn seasons in the southwest and west of the region; but in the spring, it is placed in limited parts of the south. By applying the multivariate regression model, it was found that cloud parameters may predict 57% of the rainfall changes in Caspian clouds. Examination of the synoptic patterns shows that high-pressure settlement in the north of the Caspian Sea provides favorable conditions for wind flow and moisture transfer of the Caspian Sea to its southern coast. So that with the encounter of the humid air mass to the Alborz mountain range, it leads to orographic lift and formation of clouds and rain in the region. The HYSPLIT model indicates that the source of moisture for the formation of Caspian clouds is largely from the Caspian Sea.
 
Conclusion
The average frequency of the occurrence of Caspian clouds in August to stamp is more than spring and winter months. The average number of summer and autumn, as well as the average rainfall of Caspian clouds in the summer and autumn, is more than other seasons. These clouds are mainly in the form of low- and middle-level clouds in the region with their most common types being Stratus and Altocumulus. By applying the multivariate regression model, it was found that cloud parameters may predict 57% of the rainfall changes in Caspian clouds. Examination of the synoptic patterns shows that high-pressure settlement in the north of the Caspian Sea provides favorable conditions for wind flow and moisture transfer of the Caspian Sea to its southern coast. So that with the encounter of the humid air mass to the Alborz mountain range, it leads to orographic lift and formation of clouds and rain in the region. The HYSPLIT model confirmed the moisture transfer from the Caspian Sea to the study area.

Keywords

Main Subjects


  1. Ahmadi, M., Ahmadi, H., & Dadashiroudbari, A.A. (2018). Assessment of trends and spatial pattern seasonal and annual cloudiness in Iran. Journal of Natural Environment Hazards, 7(1), 239-256. [in Persian].
  2. Ahmadi, M.; Dadashi Rodbari, A.A. Nassiri Khuzani, B. Akbari Azirani, T. (2020).Seasonal changes of liquid clouds in Iran based on data received from MODIS sensor of TERRA satellite. Scientific Research Quarterly of Geographical Data, 29(13), 7-19. [in Persian].
  3. Alijani, b. (2008). Iran Climate, Eighth Edition, Tehran: Payame Noor University Publications. [in Persian].
  4. Batlles, F. J., Alonso, J., & López, G. (2014). Cloud cover forecasting from METEOSAT data Energy Procedia, 1317 – 1326.
  5. Bannayan, M., Mohamadian, A., & Alizadeh, A. (2010). On Climate Variability in North-East of Iran. Journal of Water and Soil, 24(1), 118-131. [in Persian].
  6. Chernokulsky, A., & Esau, I. (2019). Cloud cover and cloud types in the Eurasian Arctic in 1936–2012. International Journal of Climatology, 39(15), 1-20.
  7. Farhoudi, R.l. (2006). Predictive Techniques in Urban and Regional Planning, Textbooks, Faculty of Geography, University of Tehran. [in Persian].
  8. Free, M., & Sun, B. (2013). Time-Varying Biases in U.S. Total Cloud Cover Data, JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 1, 2838-2849.
  9. Ghasemi, A. R. (2012). Modeling of spatial and temporal variations of cloud cover with emphasis on precipitation in Iran, Supervisor Dr. Ali Akbar Rasouli, University of Tabriz. [in Persian].
  10. Ghasemifar, E., Farajzadeh Asl, M., Ghavidel Rahimi, Y., & Aliakbari Bidokhti, A. A. (2019).Validating MODIS Cloud Mask Based on a Regional Cloud Mask of AVHRR. Physical Geography Research Quarterly, 51(3), 447-468. [in Persian].
  11. Ioannidis, E., Lolis, C.J., Papadimas, C.D., Hatzianastassiou, N., & Bartzokas, A. (2017). On the intra-annual variation of cloudiness over the Mediterranean region. Atmospheric Research, 208, 246- 256.
  12. Kavyani, M. R., & Alijani, B. (2000). The Foundation of Meteorology, Seventh Edition, Tehran: Samt Publications. [in Persian].
  13. Khoshhal Dastjerdi, J. (1997). Synoptic model of climatology for precipitation of more than one hundred millimeters on the southern shores of the Caspian Sea. Tarbiat Modares University. [in Persian].
  14. Menzel, P. W., Frey, R. A., & Baum, B. A. (2015). Cloud Top Properties and cloud phase algorithm Theoretical Basis Document, Version 11.
  15. Minnis, P., Smith, Jr., W.L., & Young, D.F. (2001). Cloud macro-and microphysical properties derived from GOES over the ARM SGP domain. Eleventh ARM Science Team Meeting Proceedings, Atlanta, Georgia, 19-23.
  16. Nazim Sadat, M. J. (2015). Fundamentals of Air and Climatology, Third Edition, University Publishing Center. [in Persian].
  17. Norris, J. (2005). Multidecadal changes in near-global cloud cover and estimated cloud cover radiative forcing, JOURNAL OF GEOPHYSICAL RESEARCH, 110(8), 1-17.
  18. Pirnia, A., Habibnejad Roshan, M., & Solaimani, K. (2015). Investigation of Precipitation and Temperature Changes in Caspian Sea Southern Coasts and Its Comparison with Changes in Northern Hemisphere and Global Scales. Journal of Watershed Management Research, 6(11), 90-100. [in Persian].
  19. Rasooli, A. A., Jahanbakhsh, S., & Ghasemi, A. R. (2013). Investigation of Spatial and Temporal Variations of Cloud Cover in Iran. GeoRes, 28(3), 87-104. [in Persian].
  20. Riihimaki, L.D., Sally, A., & Comstock, J. M. (2012). Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site, J. Climate, 25(19), 6538- 6850. [in Persian].
  21. Rostamzadeh, H., Rasuly, A.A., Wazifedoust, M., & maleki, N. (2020). Evaluation and analysis of the role of the physical properties of the cloud in the probable rainfall amount using satellite data MSG (Case study area: West of Iran). Journal Geography, 24(72), 225-245. [in Persian].
  22. Stordal, F., Myhre, G., Arlander, W., Svendby, T., Stordal, E. J. G., Rossow, W. B., & Lee, D. S. (2004). Is there a trend in cirrus cloud cover due to aircraft traffic? Atmos. Chem. Phys. 5(8), 473–6501.
  23. Stull, R. )2017.( Practical Meteorology: An Algebra-based Survey of Atmospheric Science, version 1.02b,  Univ of British Columbia, Vancouver, Canada.
  24. Wang, P. K. (2013). Physics and dynamics of clouds and precipitation, Cambridge University Press.
  25. Zhang, Y., Lu, H., Shen, S., & Cai, J. (2015). Comment on Do aerosols impact ground observation of total cloud cover over the North China Plain?. Global and Planetary Change, 133, 120-124.