Climatology
abdolreza hosseini; sayed mohammad hosseini; Rahman Zandi; hasan hajimohammadi
Abstract
IntroductionSnow, as one of the important climatic-hydrological parameters, has a significant role in providing the world's water resources for industrial, agricultural and drinking purposes. At the same time, the dangerous consequences of heavy snowfall, avalanches, destruction of rural housing, disruption ...
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IntroductionSnow, as one of the important climatic-hydrological parameters, has a significant role in providing the world's water resources for industrial, agricultural and drinking purposes. At the same time, the dangerous consequences of heavy snowfall, avalanches, destruction of rural housing, disruption of road transport and communication and numerous other consequences that it has on the natural and human environment are significant for environmental scientists (Shakiba et al, 2015: 88). However, heavy snowfall, especially in the lowlands and lowlands of the middle latitudes, is unexpected and somewhat surprising. So that its continuation for a few days in these areas will have negative effects on practically all living standards of the residents of these areas (Hosseini, 2014: 101). In recent years, the use of satellite data in natural, hydrological and water resource management has grown significantly, and in this regard, MODIS sensor images due to acceptable spatial resolution and fast temporal retrieval power with a variety of bands. Spectral has put it in a good position. Also, due to the very high albedo of snow, it is possible to measure the level of snow cover using satellite data. MethodologyIn the present study, the environmental approach to circulation was used to investigate the relationship between circulation patterns and heavy snowfall. Thus; first, the days of heavy snowfall in the studied stations were identified and then the synoptic patterns and atmosphere of the representative days were analyzed. In this regard, after receiving snow altitude data from the Meteorological Organization, heavy and widespread rainfall events were identified in three western provinces of the country, including Hamadan, Kurdistan and Kermanshah in the form of 16 synoptic stations, during the years 2000 to 2019. In order to study and analyze the synoptic patterns of days with heavy snowfall, by referring to the website of the National Center for Environmental Forecasting / Atmospheric Sciences (NCEP / NCAR), daily data on Sea Level Pressure (SLP), High Geopotential (HGT), zonal wind (UWND) and meridianal wind (VWND), air temperature (Air) and instability index (Omega) were extracted at the intersection of 2.5 * 2.5 and the relevant maps were drawn using GRADS software. Also, the area covered by snow was obtained from MODIS satellite images. MODIS data are of level1b type, which was calculated based on the parameters in the header, radiance and reflectivity. Reflective and thermal parameters for bands 4 and 6 were also used to apply the NDSI (Normalized Difference Snow Index). Results and DiscussionAfter 20 years of study, 8 days were identified that heavy and heavy snow had fallen in the area. On February 4, 2011, in the middle of the atmosphere, a deep trough formed in the western Mediterranean and North Africa, with a strong positive vorticity. This situation has affected the study area.The location of this trough in the Mediterranean provides the moisture needed for snowfall from the Mediterranean Sea. ConclusionsThe results showed in the ground formed a powerful cyclone on Iraq and turbulent weather caused chaos for the region. This condition causes the air to cause accelerated the rise of the package and water vapor in the atmosphere with his quick ascent to the seed quickly convert hexagonal snow. Creates a pressure gradient that causes more than 12 HPa in the region was to create a strong front will be formed in the region. In the high latitudes of cold air and warm air in front of it is the lower latitude. Has caused more than 60 to 70 percent of the study area are covered by snow. A deep trough of cold air loss in middle levels at depths greater than 25 degrees latitude has been. With extreme vorticity and air along rapid ascent has been closed. NDSI index showed the results of actions by deploying the most weather systems has gone down snow-covered forests of western Iran.
Climatology
Mohammad Hossein Aalinejad; Saeed jahanbakhsh; Ali Mohammad Khorshiddoust
Abstract
Introduction
Determining the temporal change of snowmelt or agriculture water equivalent of snow, predicting flood, and managing the reservoirs of a region is of utmost importance. Some major parts of the western sections of the country are located in the mountainous region and most of the precipitations ...
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Introduction
Determining the temporal change of snowmelt or agriculture water equivalent of snow, predicting flood, and managing the reservoirs of a region is of utmost importance. Some major parts of the western sections of the country are located in the mountainous region and most of the precipitations of this region occur in the form of snow in winter. The runoff resulting from snowmelt has an important role in feeding the rivers of this region and it has a significant share in developing agriculture and the economy.
Scientific studies have shown that climate change phenomena have significant effects on precipitations, evaporation, perspiration, runoff, and finally water supply. As the demand increases, climate changes, greatness, frequency, and the damage resulting from extreme weather events, as well as the costs of having access to water increase, as well. Therefore, evaluating the runoff resulting from snowmelt and the effect of climate change seems necessary for managing water resources.
Methodology
Gamasiab basin is located in the northeast part of the Karkheh basin originating from the springs in the vicinity of Nahavand. Its basin has an area almost equal to 11040 square kilometers that have been located in the east part having 47 degrees and 7 minutes to 49 degrees and 10 minutes geographical longitude and from the north part, it has 33 degrees and 48 minutes to 34 degrees and 54 minutes geographical latitude. This basin has an altitude between 1275 to 3680 meters.
In this study, snow-related data required for simulation were derived from the daily images of the MODIS sensor. To this end, first, the snow-covered area of the Gamasiab basin was measured during the 2016-2017 water years using the process of satellite images obtained from the MODIS sensor in the google earth engine system. All geometric justifications and calibration processes of images were applied precisely in the mentioned system. In the next step, the output of the GCM model scenarios was utilized for calculating temperature and precipitation changes in future periods. These CMIP5 kind models were under the control of two RCP45 and RCP85 scenarios and were downscaled with LARS-WG statistical model.
Moreover, to investigate the uncertainty of models and scenarios, the best models and scenarios were selected for producing temperature and precipitation data of future periods; accordingly, the outputs of the models for future periods (2021-2040) having the basis period of (1980-2010) were compared using statistical indexes of coefficient of determination (R2) and Root Mean Square Error (RMSE). The results were entered into the SRM model as the inputs. In addition, temperature and precipitation data of meteorological station of the studied region as well as the daily discharge of the river flow of hydrometric station of Chehr Bridge (as located in the output part of Gamasiab basin) were used during the statistical period of October 2016 to May 2018.
Discussion
Using Digital Elevation Model (DEM) of the region and the appendage of Hec-GeoHMS in GIS software, firstly, flow direction map, flow accumulation map, and stream maps were drawn and the output point (hydrometric station of Chehr Bridge) was introduced to the border program of the identified basin and the basin was classified based on the three elevation regions.
Producing temperature and precipitation data of future periods requires a long-term statistical period; accordingly, the meteorological station of Kermanshahd was selected since it was in the vicinity of the studied region. To be confident in the ability of the model in producing data in future periods, the calculated data had to be compared with the observed model and data in the studied stations. The capabilities of the LARS-WG model in modeling the mentioned parameters of this station confirmed the observed data. Moreover, the ability of the model in modeling precipitation was very good and acceptable; however, the most modeling error was related to the precipitation in Mars.
In the next phase and compared to the basic periods, the mean of changes in average precipitation and temperature was measured in the studied stations during January and Juan of 2015 to 2017(for which simulation had occurred); as an index of changing the climate, this was entered into the SRM model under climate change conditions. During the simulation period (January to Juan), it had been predicted that the precipitation parameter would decrease and the temperature parameter would increase.
Conclusion
The results of this study indicated that using the MODIS sensor could provide an acceptable estimation of the snow cover level of the Gamasiab basin, which lacked snow gauge data. Moreover, the results of simulation with the SRM model showed that the model could simulate the snow runoff in the studied region. As the main purpose of the study, the effect of temperature and precipitation in future periods was well stated considering the uncertainty of CMP15 series models and scenarios. The results of temperature changes indicated an average increase of 1.8 C. the results of precipitation also indicated an average decrease of more than 5%. However, decreasing precipitation in the cold months of the years had been predicted severely so that the reduction of precipitation in February was of utmost importance for feeding the snow cover and rivers, which had been estimated to be 20%. This happened while increasing precipitation was mainly related to the hot months of the year whose amount was insignificant and didn`t have that much effect on the runoff. Accordingly, due to the increases in temperature and decreases in precipitation in cold seasons, the results of runoff simulation have indicated a 24% reduction for 2016-2017 and a 29% reduction for 2017-2018 water years.
