S.M.J. Nazemosadat; L. Abbasi; S. Mehravar
Abstract
Introduction:Based on the research and assessment carried out during the Climate Change Enabling Activity Project under United Nations Framework Convention on Climate Change (UNFCCC) and using the scenarios proposed by IPCC, it is estimated that if the CO2 concentration doubles by the year 2100, ...
Read More
Introduction:Based on the research and assessment carried out during the Climate Change Enabling Activity Project under United Nations Framework Convention on Climate Change (UNFCCC) and using the scenarios proposed by IPCC, it is estimated that if the CO2 concentration doubles by the year 2100, the average temperature in Iran will increase by 1.5-4.5°C which will cause significant changes in water resources, energy demand, agricultural products and coastal zones. The present study is aimed to investigate the characteristics of climate change in Iran and some parts of the neighboring countries. Identifying the spatio-temporal changes in three atmospheric variables comprising perceptible water (PW), specific humidity (SH) and vector wind (VW, U and V components) over 1960-2017 was the main themes of the study. Materials and Methods: Monthly values of these variables during wintertime (January to March) were extracted from the CDC/ Reanalysis 2/ NOAA in 2.5 * 2.5 grids for the period of 1960-2017. The study area locates between 20o to 45o N and 30o to 70o E. After averaging monthly data into seasonal series, as first step, significant changes in the considered series were investigated between two equal periods having 29 years of data (1960-1988 and 1989-2017). In the second step, the 58 years of the study period were divided into five successive decades (1960-2009) and a period with eight years (2010-2017). The Kolmogorov-Smirnov (K-S) field significant test was used for assessing the spatio-temporal difference between the obtained maps associated with various decades. Results and Discussion: According to Figures 1 and 2, for both of the 29-year time-scales (1960-1988 and 1989-2017), PW was maximum (12 to 17 kg/m2) alongside the northern coasts of the Persian Gulf and the Oman Sea. After this, PW had the highest values over the southern coasts of the Caspian Sea (10 to 12 kg/m2). Oppose to these coastal areas, minimum values of this variable with about 6 to 10 kg/m2 were associated with the Zagros mountains. In general, PW exhibited an inverse relationship with elevation. In contrast to PW, SH maximized (4.2 to 5 g/kg) over the Zagros ranges and its relationship with elevation was generally positive. The lowest value of the SH data was about 3.5 g/kg suggesting relatively low variation in the SH data within the country. Compared to the 1960-1988 period, a significant decline was observed in the values of PW and SH in 1989-2017. Although this decline was obvious over all parts of the country, it was slightly significant for the southwestern (northwestern) districts. Compared to the first half of the study period (1960-1989), PW (or SH) decreased by about 2.5 kg/m2 (or 0.6 g/kg) in southwestern and 0.3 kg/m2 (or 0.15 g/kg) in northwestern parts of Iran for the recent half (1989-2017). Differences between wind data during these two time-periods were mostly either northerly or easterly suggesting a significant decrease in the rain-bearing southerly or westerly circulation over 1989-2017. Anomalies of the near-surface wintertime winds were mostly found to be southerly or westerly during 1960-1988 implicating the possibility of moisture transport from the Persian Gulf, the Oman Sea, the Mediterranean Sea, and the Red Sea into the most parts of Iran. Conversely, the anomalies were either northerly or easterly in1989-2017 suggesting less moisture transport into Iran for this recent period. In the decadal time-scale, maximum values of PW, SH, as well as southerly or westerly circulations, were observed during 1960-1969. The given results suggest that the enhanced (or suppressed) values of PW and SH are generally harmonized with the strengthened southerly and westerly (or northerly and easterly) wind anomalies. For this period, prevailing of southeasterly winds over the Caspian Sea enhanced or suppressed the measure of PW, SH over the western or eastern coasts of the Sea, respectively. Even though the mentioned atmospheric circulation patterns were generally similar for the 1960-1969 and 1970-1979 decades, positive anomalies of PW and SH, as well as the westerly and southerly airflows, were slightly suppressed for the second decade. The anomalies of westerly and southerly winds decreased by about one-fifth for 1980-1989 as compared with that in 1960-1969 resulting in a significant decrease in the PW and SH data for this decade. Although these anomalies were slightly positive over most parts of Iran, their weakness did not allow significant improvement in the PW and SH values. The period of 2000-2009 was evaluated as the driest decade of the study period for which the negative anomalies of PW and SH, as well as westerly and southerly circulations, were maximized (in absolute values). In spite of the fact that these undesirable conditions have recovered during the period of 2010-2017, PW and SH were still very low for this recent period. With the exception of the 1990-1999 decade, PW and SH have continuously decreased for the decades after 1970. The rain-bearing southerly and westerly winds have been gradually replaced with dry northerly or easterly wind during the recent periods. Conclusion: The findings showed that the PW and SH distribution patterns are close together in the 29-year periods, the measures were, however, significantly smaller in the second period than in the first. The wind anomalies, which were mostly southerly and westerly in 1960-1988, have been changed to northerly and easterly in 1989-2017. Since the southerly and westerly winds play an influential role in moisture transfer to Iran, their reduction in the second period is consistent with the observed decrease in PW and SH. Among the ten-year periods, the highest positive PW and SH abnormalities are associated with the 1960 and 1969 decade. This positive anomaly decreased over the time. Since a positive trend is observed for 2010-2017, it can be concluded that 2000-2010 is the driest decade of the study period. The positive anomalies of westerlies (easterlies) and southerlies (northerlies) increased (decreased) the magnitudes of PW and SH.
Nooshin Ahmadibaseri; A. Shirvani; mohammad jafar nazemosadat
Abstract
In this study, the artificial neural networks (ANNs) and regression models were used to downscale the simulated outputs of the general circulation models (GCMs). The simulated precipitation for 25.18 º N to 34.51 º N and 45 º E to 60 º E, geopotential height at 850 mb and zonal wind at 200 mb for ...
Read More
In this study, the artificial neural networks (ANNs) and regression models were used to downscale the simulated outputs of the general circulation models (GCMs). The simulated precipitation for 25.18 º N to 34.51 º N and 45 º E to 60 º E, geopotential height at 850 mb and zonal wind at 200 mb for 12.56° N to 43.25° N and 19.68° E to 61.87° E data sets as the predictors were extracted from ECHAM5 GCM for the period 1960-2005. The observed monthly precipitation data of Abadan, Abadeh, Ahwaz, Bandar Abbas, Bushehr, Shiraz and Fasa stations as the predictand were extracted for the period 1960-2005. The principal components (PCs) of the simulated data sets were extracted and then six PCs were considered as the input file of the ANN and multiple regression models. Also the combinations of the simulated data sets were used as the input file of these models. The periods 1960-2000 and 2001-2005 were considered as the train and test data in the ANN, respectively. The Pearson correlation coefficient and normalized root mean square error results indicated that ANN predicts precipitation more accurate than multiple regression. For the monthly time scale, the geopotential height is the best predictor and for the seasonal time scale (winter) the simulated precipitation is the best predictor in ANN based standardized precipitation principal components.
mohammad jafar nazemosadat; K. Shahgholian
Abstract
The aim of this study is to assess some synoptic characteristics of heavy precipitations in southwestern parts of Iran and evaluate the relationship between them with the Madden-Julian Oscillation (MJO). Research is conducted with regard to distribution of precipitation per month and identifying their ...
Read More
The aim of this study is to assess some synoptic characteristics of heavy precipitations in southwestern parts of Iran and evaluate the relationship between them with the Madden-Julian Oscillation (MJO). Research is conducted with regard to distribution of precipitation per month and identifying their steam sources. Daily records of the November-April precipitation data in Abadan, Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations for the 1975- 2011 period are collected as well as same panel data for Yasuj station from 1990 to 2011. Rainfall data are sorted in descending order and precipitation values that were fallen within the 5% and 10% of highest records are categorized as the heavy precipitation. The most frequent precipitations occurred in January, February and December. The most frequent heavy precipitations in Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations occurred in phase 8, while in Abadan station occurred in phases 7 and 8. Apparently, due to the short duration precipitations data at Yasuj station, the most frequent heavy precipitation observed in phase 2.Synoptic maps show that harmonized with eastward movement of convective precipitation in Indian or pacific oceans.Heavy precipitation forms in the west region of Iran and moves toward southwest and south Central of Iran and then appears to Afghanistan.Formation of a cyclonic circulation that encompasses the Mediterranean Sea, Red Sea and Persian Gulf plays an important role for moisture supplement of these storm activities. The synoptic maps have indicated that main sources of these heavy rainfalls are moisture produced at the Arab sea and western parts of the Indian Ocean.
