Journal of Spatial Analysis

We can identify the flood not only considering circulation pattern in occurring day but also by studying circulation pattern a few days before fresh event. This subject has mutual approach. In one hand, it indicates  that circulation patterns which were before flood event have important role in determining the conditions and moisture content of studied area and playing the fundamental role in few coefficient of region because it determines the previous moisture. On the other hand, it indicates that we should tracking the rain-genesis synoptic systems from source to end place of their activity for studying floods and their meteorology factors which have created them. By this way, we can acquire more comprehensive recognition about the relationship between circulation pattern and floods. In the other words, the identification of synoptic patterns that have created the flood reveals not only the mechanism of their emergence but also is useful for prognosis and encountering with them. The extensive researches have been accomplished about Inundation in the world and Iran, but Iran haven’t much antiquity about synoptic researches. For foreign researches, we can name researchers such as Hireschboeck (1987), Kutiel et al(1996), Komusce and et al (1998), Krichak  and et al (2000), Rohli and et al (2001), Kahana (2002), Teruyuki Kato(2004), Ziv and et al (2005), Carlalima and et al (2009). The numerous researchers have studied the Inundation climatology in internal of country such as Bagheri (1373), Ghayour (1373), Kaviani and Hojatizadeh (1380), Moradi (1380), moradi (1383), Mofidy (1383), Masoodian (1384), Masoodian (1384), Hejazizadeh et al(1386), Parandeh Khozani and Lashkari (1389). In this research, we considered the heavy precipitation of Azar 1391 in southwestern of Iran that resulted in flood phenomenon in the cause and effect manner so that can do necessary prevention actions before occurring the flood for preventing the probable damages and optimal use of precipitations by forecasting the patterns that have created the flood.

In this synoptic study, we need to two database: one group is variables and atmospheric data consisting of geopotential height of 500 hpa level (in meter geopotential), zonal wind and meridional wind (in m/s) and special humidity (in gr/kg) during this times 00:00, 06:00, 12:00 and 18:00 Greenwich in 0-80° northern and 0-120° eastern with local resolution of 2.5*2.5 Arc that have been borrowed from database of (NCEP/NCAR) dependent to National Atmosphere and Oceanography Institute of USA, and other group is daily precipitation data of region rain gauge stations during 4-8^th Azar of 1391 (24^th November – 28^th November 2012). In continuation. By applying the environment- circulation approach, we took action to drawing circulation pattern maps of 500 hpa level, thickness of atmosphere patterns of 500-1000 hpa and moisture flux convergence function from 4-8^th Azar of 1391 (that for calendar, conform with 48 hours before beginning the showery precipitation until ending the storm activity) by using data which obtained from database of NCEP/NCAR and the synoptic conditions of above flood have been studied and interpreted in the region.

Flood is one of the most destructive natural hazards that have imposed and impose many damages to people during the history. Hence, the final aim of this research is to explain the key interactions between atmosphere and surface environment and in other words exploration of the relationship between circulation patterns leading to the flood generating precipitation in the southwestern of Iran for forecasting the time and intensity of showers occurrence that lead to flood. For this purpose, by applying environmental-circulation approach, the circulation patterns identified and studied which resulted in flood generating precipitation. The result of this research indicated that torrential precipitations in the region have formed the deep trough in days 4-8 of Azar on the east of Mediterranean and the studied region placed in the east half of this trough that is the location of atmosphere instability. At same time, thickness patterns, indicate the flux of cold air from northern Europe to lower latitudes and spreading the warm air of north of Africa to latitude 50° northern. As a result we expected the frontal discontinuity in the encountering place of these two air mass. Analysis of the moisture flux convergence patterns also indicated that torrential precipitations were the result of moisture flux from Mediterranean and Persian Gulf; and Red Sea and Arab Sea taken into account as reinforced sources.

Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small.  Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.

This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI.  Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions.  The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.

Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.