Frequency Distribution Patterns of Precipitable Water in Iran

Precipitable water (PW) is highly variable in space and time and is one of the most important abundant greenhouse gases that play crucial role in the study of climate change, hydrological cycle, energy budget and numerical weather prediction. The knowledge about the spatial and temporal variability of PW is important in understanding climatic processes and in order to monitor drought conditions and desertification processes (Kaufman & Gao,1992). It is therefore necessary to obtain the distribution condition of water vapor in the atmosphere and to understand the effects of spatial–temporal variation of PW on regional, meso-micro scales and on global climate change (Wang, 2013). PW has a very short life cycle in atmosphere and this rapid turnover, joined to temperature variations with altitude and geography, distance to sea, evapotranspiration and moisture advection causes an irregular PW distribution in atmosphere, both horizontally and vertically. The purpose of this study was to identify the distribution patterns of PW in Iran and relationship these patterns with elevation and distance to sea.

In the present research, MODIS Aqua data (MYD05_L2. A V06) were used. The data with spatial resolution of 1 km (Near Infrared) have been selected. The selected study period covers since 2002/07/04 to 2017/07/25 (5501 days) that was exploited from NASA web site. These data are errors in the range between 5% and 10% (Kaufman & Gao,2003). The spatial resolution of the PW data are 1 km and temporal resolution is twice per day. Then using functions, these data converted from Level_2(swath data) to Level_3(grid data) and PW values interpolated on sinusoidal grid in 1800×2700 matrix with 1 km spatial resolution and daily temporal resolution. These data have been extracted for pixels within the political boundary of Iran and obtained a matrix with 1884080 rows (locations) and 200 columns (PW classes). Then on the base this matrix, calculated frequency distribution in 1 mm intervals from 0-199 mm for each of pixels (1884040×200). Finally, Principal Component Analysis (PCA) performed and frequency distribution patterns in Iran identified. The effects of altitude and distance to sea on these patterns, analyzed. The special program was developed and employed in MATLAB software for analysis the data.

The spatial distribution of atmospheric humidity in Iran is controlled by the height above the sea level, distance to sea and moisture advection. Based on the results, the mean annual PW of the country is about 12 mm. PW is maximum near the southern and northern coasts of the country. The highest and lowest amount of PW near the Oman sea coast (31 mm) and the peak of Damavand (3 mm), respectively. The results of PCA showed that 95% of spatial variation of PW can be explained through 4 components. Based on the results, local factors like distance to sea and altitude are the most important in spatial distribution of PW. The study of the relationship between distance from the sea and frequency distribution patterns of PW shows the effect of distance and proximity to the sea in the frequency distribution patterns. This fact is more evident in the first and second components. Up to the distance of approximately 250 kilometers in the first component and 150 kilometers in the second component, as expected, the amount of PW will gradually decrease. From now on, the spatial pattern of PW is affected by altitude and morphology rather than by distance from sea and sealand breeze. In the third component, due to the formation of a moisture convergence belt at approximately 11 and 4 km, respectively, on the south and north coasts, the amount of atmospheric moisture is maximum. Then from 11 to 66 kilometers due to the Alborz Range, which is a short distance from the Caspian Sea, the amount of PW is minimal. Minimal atmospheric humidity on the southern coast occurs approximately at 250 kilometers away from the sea. In the South Coast, moisture penetrates the country further away from the coast, as it is smoother than the North Coast; so that sea moisture enters through the straits of Kahnouj area into the Jazmourian plain and distinguishes this area from its surrounding areas in terms of moisture. Moisture in the Caspian Sea enters the Tarom Valley through the Manjil Strait. The spatial distribution of moisture in the western, middle and eastern Persian Gulf coasts does not have a similar pattern; this difference is due to factors such as the dominance of the sea-land breeze in the eastern areas of Bushehr and the presence of small firth and bays in the area that increase the atmospheric moisture of these areas. than the environment around them. The amount of moisture in the coast of the Oman Sea is clearly different from PW of the Persian Gulf; PW MODIS is also overestimated in places such as near beaches with high temperatures and humidity.In addition to the height above the sea level and distance to sea, the role of moisture advection should not be ignored. In the coastal region the variability caused by the high temperature and moisture advection and in areas far from coastline, height above the sea level causes many spatial differences in moisture distribution.

Although Iran is bounded from the north and south to the sea, atmospheric moisture is very low in the country. Based on the result, minimum and maximum difference of PW is about 27 mm, so that, in the region with more than 3000 m elevation PW is less than 6 mm, and the coast of the Oman Sea 60% of the time is above 26 mm. This result means, in spite of the great source of water in south and north, atmosphere of Iran suffers from poor moisture. Topography is a barrier to the entry of moisture north and south seas to the inland. In the inland region, altitude and in the coastal region, moisture advection and temperature, play crucial role in frequency distribution of PW. In this way, moisture advection is the important factor that well justified spatiotemporal variations of PW in Iran and through this, affected on water budget.